POS0301 STRUCTURAL OUTCOMES IN THE SACROILIAC JOINT AFTER IXEKIZUMAB TREATMENT FOR 16 WEEKS IN PATIENTS WITH ACTIVE NON‑RADIOGRAPHIC AXIAL SPONDYLOARTHRITIS STRATIFIED BY GENDER, HLA-B27, AND BASELINE MRI INFLAMMATION

Background

Ixekizumab (IXE) has demonstrated clinical efficacy in patients with active non-radiographic axial spondyloarthritis (nr-axSpA) together with significant repair of structural lesions in the sacroiliac joint (SIJ) on MRI. There is, however, a paucity of data as to which patients may be most responsive.

Objectives

We aimed to evaluate whether patients’ gender, HLA-B27 status, and presence of MRI inflammation impacted the effect of treatment with IXE versus placebo (PBO) on MRI structural lesions in the SIJ in patients with nr-axSpA.

Methods

Patients with active nr-axSpA, biologic-naïve (COAST-X, NCT02757352) were randomized 1:1:1 to ixekizumab 80 mg every 4 (Q4W) or 2 weeks (Q2W) or PBO. Structural lesions on SIJ MRI were assessed by the Spondyloarthritis Research Consortium of Canada (SPARCC) MRI SIJ structural score (SSS). Treatment comparisons used analysis of covariance based on observed cases. SPARCC SSS subgroup analyses were performed according to baseline gender, HLA-B27 status, and SPARCC MRI SIJ bone marrow oedema (BME) <4 and ≥4 subgroups, which reflects a definite MRI for inflammation in the SIJ typical of axSpA.

Results

Of 303 randomized patients, 266 patients (Q4W: n=85, Q2W: n=91, PBO: n=90) had an MRI scan at baseline and week 16. At baseline, SPARCC scores were consistently higher in males, and mostly higher in HLA-B27 and BME≥4 positive subgroups. Significant differences between patients treated with IXE versus PBO were observed for male patients, HLA-B27 positives, and those with baseline SPARCC BME ≥4. Numerically similar changes were observed in female patients, patients with negative HLA-B27, and patients with SPARCC BME<4, though not statistically significant.

Conclusion

Effects of IXE on structural repair are most evident in males, HLA-B27 positives, and patients with definite MRI inflammation at baseline.

Table 1.

MRI SIJ Structural Lesion Outcomes.

LesionAnalysisPBOIXE Q4WIXE Q2WMale (n=39)Female (n=51)Male (n=44)Female (n=41)Male (n=43)Female (n=48)ErosionBL mean5·1671·9803·5452·8173·5232·594LS mean CFB (SE)0·51 (0·20)-0·11 (0·17)-0·63 (0·18)-0·11 (0·19)-0·51 (0·18)-0·32 (0·17)P value vs PBONANAp<0·001p>0·99p<0·001p=0·37FatBL mean2·0510·9122·0911·2931·4650·677LS mean CFB (SE)-0·02 (0·09)-0·03 (0·08)0·29 (0·08)0·03 (0·08)0·21 (0·08)0·04 (0·08)P value vs PBONANAp=0·01p=0·65p=0·062p=0·51BackfillBL mean1·1540·1670·6630·4150·7910·323LS mean CFB (SE)-0·20 (0·13)0·01 (0·11)0·39 (0·12)0·01 (0·12)0·34 (0·12)0·14 (0·11)P value vs PBONANAp<0·001p>0·99p=0·002p=0·38LesionAnalysisHLA-B27+HLA-B27-HLA-B27+HLA-B27-HLA-B27+HLA-B27-(n=64)(n=25)(n=61)(n=23)(n=65)(n=26)ErosionBL mean3·8202·1003·4672·5433·5151·827LS mean CFB (SE)0·27 (0·15)-0·10 (0·24)-0·49 (0·15)-0·01 (0·25)-0·50 (0·15)-0·17 (0·24)P value vs PBONANAp<0·001p=0·79p<0·001p=0·84FatBL mean1·5781·0201·3282·7831·2850·462LS mean CFB (SE)-0·06 (0·06)-0·06 (0·10)0·22 (0·06)0·01 (0·10)0·13 (0·06)0·10 (0·10)P value vs PBONANAp=0·002p=0·65p=0·027p=0·25BackfillBL mean0·7420·2400·5420·5650·7620LS mean CFB (SE)-0·12 (0·10)0·01 (0·16)0·28 (0·10)0 (0·17)0·27 (0·10)0·16 (0·16)P value vs PBONANAp=0·005p=0·96p=0·005p=0·52LesionAnalysisBME ≥4BME <4BME ≥4BME <4BME ≥4BME <4(n=40)(n=50)(n=27)(n=58)(n=38)(n=53)ErosionBL mean4·8632·1605·3522·1905·2761·425LS mean CFB (SE)0·42 (0·19)-0·06 (0·17)-0·70 (0·23)-0·23 (0·16)-0·71 (0·20)-0·19 (0·17)P value vs PBONANAp<0·001p=0·47p<0·001p=0·57FatBL mean0·7751·9101·9261·6031·6710·604LS mean CFB (SE)-0·02 (0·08)-0·02 (0·07)0·54 (0·10)-0·01 (0·07)0·28 (0·08)0·01 (0·07)P value vs PBONANAp<0·001p=0·90p=0·013p=0·74BackfillBL mean0·7500·4701·0190·3280·7630·387LS mean CFB (SE)-0·21 (0·12)0·01 (0·11)0·41 (0·15)0·11 (0·10)0·49 (0·13)0·05 (0·11)P value vs PBONANAp=0·002p=0·52p<0·001p=0·80

CFB=change from BL. BL=baseline, LS=least squares.

Acknowledgements

Study was sponsored by Eli Lilly and Company

Disclosure of Interests

Walter P Maksymowych Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly and Company, Galapagos, Janssen, Novartis, Pfizer, and UCB and is Chief Medical Officer of CARE Arthritis Ltd, Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Xenofon Baraliakos Grant/research support from: Abbvie, Amgen, BMS, Chugai, Galapagos, Gilead, Eli Lilly and Company, MSD, Novartis, Pfizer, Roche, Sandoz, and UCB, Robert G Lambert Consultant of: CARE Arthritis, Image Analysis Group, Parexel, and Pfizer, Robert B.M. Landewé Consultant of: AbbVie, Astra-Zeneca, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Gilead, Galapagos, Glaxo-Smith-Kline, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Novartis, Pfizer, and UCB; and is director of Imaging Rheumatology BV, which is a registered company under Dutch Law, David Sandoval Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Hilde Carlier Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Jeffrey Lisse Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Xiaoqi Li Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Maja Hojnik Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Mikkel Østergaard Speakers bureau: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli Lilly and Company, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Consultant of: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli Lilly and Company, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Grant/research support from: AbbVie, BMS, Merck, Celgene, and Novartis

LB0001 BIMEKIZUMAB IN BDMARD-NAIVE PATIENTS WITH PSORIATIC ARTHRITIS: 24-WEEK EFFICACY & SAFETY FROM BE OPTIMAL, A PHASE 3, MULTICENTRE, RANDOMISED, PLACEBO-CONTROLLED, ACTIVE REFERENCE STUDY

Background

Bimekizumab (BKZ) is a monoclonal IgG1 antibody that selectively inhibits IL-17F in addition to IL-17A.

Objectives

Assess BKZ efficacy and safety vs PBO in bDMARD-naïve pts with active PsA to Wk 24 of BE OPTIMAL.

Methods

BE OPTIMAL (NCT03895203) comprises 16 wks double-blind PBO-controlled and 36 wks treatment-blind. Pts were ≥18 yrs, bDMARD-naïve, with adult-onset, active PsA, ≥3 tender and ≥3 swollen joints. Pts randomised 3:2:1, subcutaneous BKZ 160 mg Q4W:PBO:adalimumab (ADA; reference arm) 40 mg Q2W. From Wk 16, PBO pts received BKZ 160 mg Q4W. Primary endpoint: ACR50 at Wk 16.

Results

821/852 (96.4%) pts completed Wk 16 and 806 (94.6%) Wk 24. Mean age 48.7 yrs, BMI 29.2 kg/m2; since diagnosis: 5.9 yrs; 46.8% male. BL characteristics comparable across arms. Primary endpoint met (Wk 16 ACR50: 43.9% BKZ vs 10.0% PBO, p<0.001; ADA: 45.7%; Figure 1). All ranked secondary endpoints met at Wk 16 (Table 1). As early as Wk 2, ACR20 was higher in BKZ vs PBO (27.1% vs 7.8%, nominal p<0.001; ADA: 33.6%). Outcomes continued to improve at Wk 24 (Table 1). To Wk 16, pts with ≥1 TEAE, BKZ: 59.9%; PBO: 49.5%; ADA: 59.3%. SAE rate low (1.6%; 1.1%; 1.4%). Most frequent (≥5%) AEs for all arms: nasopharyngitis (9.3%; 4.6%; 5.0%), URTI (4.9%; 6.4%; 2.1%), increased ALT (0.7%; 0.7%; 5.0%). Candida infections: 2.6%, 0.7%, 0%; no systemic candidiasis. 2 malignancies (BKZ: basal cell carcinoma; PBO: breast cancer stage 1); no MACE, uveitis, IBD or deaths.

Table 1.

Wk 16 and 24 efficacy

BLWk 16Wk 24PBO N=281BKZ 160 mg Q4W N=431ADA 40 mg Q2W N=140†PBO N=281BKZ 160 mg Q4W N=431ADA 40 mg Q2W N=140†p value (BKZ vs PBO)PBO→ BKZ 160 mg Q4WaN=281BKZ 160 mg Q4W N=431ADA 40 mg Q2W N=140†Ranked endpointsbACR50 [NRI],–––28189 (43.9)64<0.00110119666n (%)-10-45.7(35.9)(45.5)-47.1HAQ-DI CfB [MI],0.890.820.86−0.09 (0.03)−0.26 (0.02)−0.33<0.001c−0.28−0.30−0.34mean (SE)-0.04-0.03-0.05(0.04)(0.03)(0.02)(0.05)PASI90d [NRI],–––4133 (61.3)f28<0.00186 (61.4)e158 (72.8)f32n (%)(2.9)e(41.2)g(47.1)gSF-36 PCS CfB [MI],36.938.137.62.36.36.8<0.001c6.27.37.3mean (SE)-0.6-0.5-0.7-0.5-0.4-0.8-0.5-0.4-0.8MDA [NRI],51413719463<0.00110620967n (%)-1.8-3.2-0.7-13.2(45.0)-45(37.7)(48.5)-47.9vdHmTSS CfB (subgroup)h [MI], mean (SE)15.67 (1.80)i15.56 (1.69)j17.39 (2.89)k0.36 (0.10)i−0.01 (0.04)j−0.06 (0.08)k<0.001c–––vdHmTSS CfB [MI],mean (SE)13.31 (1.56)l13.44 (1.47)m14.55 (2.44)n0.31 (0.09)l0(0.04)m−0.03 (0.07)n0.001c–––Other endpointsACR20 [NRI],–––6726896<0.001o17528299n (%)-23.8(62.2)-68.6(62.3)(65.4)-70.7ACR70 [NRI],–––1210539<0.001o5312642n (%)-4.3(24.4)-27.9-18.9(29.2)-30PASI100d [NRI],–––3103f14<0.001o6012226n (%)(2.1)e(47.5)(20.6)g(42.9)e (56.2)f(38.2)gTJC CfB [MI],17.116.817.5−3.2−10.0−10.9<0.001o−9.4−11.5−11.8mean (SE)-0.7-0.6-1.1(0.7) (0.5)-1(0.7)(0.5)-0.9SJC CfB [MI],9.599.6−3.0 (0.5)−6.6 (0.3)−7.5<0.001o−6.8 (0.4)−7.2 (0.3)−7.9mean (SE)-0.4-0.3-0.6-0.6-0.6

Randomised set. Interim results.

†Reference arm; study not powered for statistical comparisons of ADA to BKZ or PBO.

aPBO→BKZ pts received PBO to Wk 16, switched to BKZ 160 mg Q4W through Wk 24 (8 wks BKZ);

bResolution of enthesitis/dactylitis in pts with LEI>0/LDI>0 at BL pooled with BE COMPLETE (Wk 16 LEI=0 BKZ: 124/249 [49.8%], PBO: 37/106 [34.9%], p=0.008; LDI=0 BKZ: 68/90 [75.6%], PBO: 24/47 [51.1%], p=0.002);

cContinuous outcome p values calculated with RBMI data;

dPts with PSO and ≥3% BSA at BL;

en=140;

fn=217;

gn=68;

hPts with hs-CRP ≥6 mg/L and/or bone erosion at BL;

in=221;

jn=357;

kn=108;

ln=261;

mn=416;

nn=131;

oNominal, not powered for multiplicity.

Conclusion

Dual inhibition of IL-17A and IL-17F with BKZ in bDMARD-naïve pts with active PsA resulted in rapid, clinically relevant improvements in musculoskeletal and skin outcomes vs PBO. No new safety signals observed.1,2

References

[1]Ritchlin CT Lancet 2020;395(10222):427–40; 2. Coates LC Ann Rheum Dis 2021;80:779–80(POS1022).

Disclosure of Interests

Iain McInnes Consultant of: AbbVie, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen, Novartis, and UCB Pharma, Grant/research support from: BMS, Boehringer Ingelheim, Celgene, Janssen, UCB Pharma, Laura Coates Consultant of: AbbVie, Amgen, Boehringer Ingelheim, BMS, Celgene, Domain, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer, and UCB Pharma, Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, and UCB Pharma, Robert B.M. Landewé Consultant of: Abbott, Ablynx, Amgen, AstraZeneca, BMS, Centocor, GSK, Novartis, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Speakers bureau: Abbott, Amgen, BMS, Centocor, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Grant/research support from: Abbott, Amgen, Centocor, Novartis, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Philip J Mease Consultant of: AbbVie, Amgen, BMS, Boehringer Ingelheim, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma, Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer and UCB Pharma, Grant/research support from: AbbVie, Amgen, BMS, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma, Christopher T. Ritchlin Consultant of: AbbVie, Amgen, Eli Lilly, Gilead, Janssen, Novartis, Pfizer and UCB Pharma, Grant/research support from: AbbVie, Amgen and UCB Pharma, Yoshiya Tanaka Consultant of: AbbVie, Ayumi, Daiichi-Sankyo, Eli Lilly, GSK, Sanofi, and Taisho, Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer-Ingelheim, Chugai, Eisai, Eli Lilly, Gilead, Mitsubishi-Tanabe, and YL Biologics, Grant/research support from: AbbVie, Asahi-Kasei, Boehringer-Ingelheim, Chugai, Corrona, Daiichi-Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda, Akihiko Asahina Grant/research support from: AbbVie, Amgen, Eisai, Eli Lilly, Janssen, Kyowa Kirin, LEO Pharma, Maruho, Mitsubishi Tanabe Pharma, Pfizer, Sun Pharma, Taiho Pharma, Torii Pharmaceutical, and UCB Pharma, Laure Gossec Consultant of: AbbVie, Amgen, BMS, Celltrion, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer and UCB Pharma, Grant/research support from: Amgen, Galapagos, Lilly, Pfizer, Sandoz and UCB Pharma, Alice B Gottlieb Consultant of: Amgen, AnaptsysBio, Avotres Therapeutics, Boehringer Ingelheim, BMS, Dermavant, Eli Lilly, Incyte, Janssen, Novartis, Pfizer, Sanofi, Sun Pharma, UCB Pharma, and XBiotech, Grant/research support from: Boehringer Ingelheim, Janssen, Novartis, Sun Pharma, UCB Pharma, and XBiotech: all funds go to Mount Sinai Medical School, Richard B. Warren Consultant of: AbbVie, Almirall, Amgen, Arena, Astellas, Avillion, Biogen, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, GSK, Janssen, LEO Pharma, Novartis, Pfizer, Sanofi, and UCB Pharma, Paid instructor for: Astellas, DiCE, GSK, and Union, Grant/research support from: AbbVie, Almirall, Janssen, LEO Pharma, Novartis, and UCB Pharma, Barbara Ink Shareholder of: GSK, UCB Pharma, Employee of: UCB Pharma, Deepak Assudani Shareholder of: UCB Pharma, Employee of: UCB Pharma, Jason Coarse Shareholder of: UCB Pharma, Employee of: UCB Pharma, Rajan Bajracharya Shareholder of: UCB Pharma, Employee of: UCB Pharma, Joseph F. Merola Consultant of: AbbVie, Amgen, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma, and UCB Pharma, Paid instructor for: Amgen, Abbvie, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma, and UCB Pharma

POS0125 EXTRA-ARTICULAR FINDINGS WITH FDG-PET/CT IN RHEUMATOID ARTHRITIS PATIENTS: MORE HARM THAN BENEFIT

Background

Whole-body Positron Emission Tomography with CT-scanning using fluorine-18 fluorodeoxyglucose (18F-FDG) is occasionally used in Rheumatoid Arthritis (RA) patients. Reasons to use FDG-PET/CT-scans are to diagnose arthritis or guide decisions on systemic therapy, as FDG uptake in affected joints may reflect disease activity [1]. FDG-PET/CT might also detect malignancies, but the frequency of incidental findings and the proportion of relevant malignant disease that could be missed are currently unknown.

Objectives

To study the malignancy screening performance of whole-body FDG-PET/CT in longstanding RA patients with low disease activity.

Methods

FDG-PET/CT-scanning was done in the intervention arm of the Dose REduction Strategy of Subcutaneous TNF-inhibitors (DRESS) study, a randomized controlled trial on dose-tapering of biological Disease Modifying Anti-Rheumatic Drugs (bDMARDs) [3]. Baseline and if applicable follow up whole-body FDG-PET/CT-scans were performed in consenting patients in the tapering arm to assess predictive value of subclinical PET-arthritis for risk of flaring [4]. The scans were also read by experienced nuclear medicine specialists immediately after they were performed for any unexpected extra-articular finding, conform routine clinical care.

The reference standard was clinical diagnosis of malignancy during the 3 year follow-up. Prevalence of extra-articular abnormalities, follow-up, and received treatments were summarized post-hoc.

Results

121 scans were made in 79 patients. Extra-articular abnormalities were found in 59/121 (48.8%) scans (Table 1) in 45/79 (57%) patients.

Table 1.

Abnormalities found on FDG-PET/CT scans

# abnormal results found on scans (%)No PET/CT result obtained3 (2.5)No abnormalities found on any scan59 (48.8)One or more abnormalities found per scan*59 (48.8)Total number of scans121 Inflammatory7 (5.7) Suspected malignancies9 (7.4) Cardiovascular2 (1.6) Pulmonary7 (5.8) Gastrointestinal10 (8.3) Muscles/tendons3 (2.5) Bone-related3 (2.5) Hypermetabolic lymph nodes (non-specific)16 (13.2) Thyroid4 (3.3)

* Fifteen of these abnormalities were found on the second PET/CT, the rest was found on the first scan. 11 abnormalities on the second PET/CT were the same as the one seen on the first scan, and 7 abnormalities resolved after the first scan. One scan can show multiple abnormalities, from different categories.

Follow-up action occurred in 21 (26.6%) patients, consisting of referral to a specialist or reassessing and/or scheduling diagnostics directly by the treating rheumatologist. In 5 (6.3%) patients, the rheumatologist followed-up. In 17 (21.5%) patients a consultation with a different specialist was scheduled. In five patients surgical/invasive intervention took place. In one patient a hemi-thyroidectomy was performed revealing a follicular adenoma. This resection was complicated by persistent recurrent laryngeal nerve paresis and hoarseness. In a second, an intra-uterine myomectomy took place. In a third, a colonoscopy was performe revealing two low-grade adenomas. In a fourth a benign cyst in the neck was extracted. A fifth patient underwent spinal marginal myotomy which turned out to be a benign schwannoma.

Nine patients (7.4%) were suspected of malignancy, none turned out to be malignant. Six clinical malignancies (bladder, penile, lymphoma, 2x melanoma and prostate) that developed during follow-up were all negative on baseline FDG-PET/CT. The malignancies were diagnosed after an interval of between 5 and 34 months (mean 13 months).

Conclusion

Whole-body FDG-PET/CT-scanning for arthritis imaging in RA patients results in frequent incidental extra-articular findings, while some who apparently had normal scans developed malignancies.

References

[1]Mandl P. et al. RMD open 2019;5:e000950.

[2]Van Herwaarden N. et al. BMJ 2015;350:1–8. doi:10.1136/bmj.h1389

[3]Bouman C.A.M et al. Rheumatology 2021.

Disclosure of Interests

None declared

POS0976 IMPACT OF PATIENT AND DISEASE CHARACTERISTICS ON GLOBAL FUNCTIONING AND HEALTH IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS: A BAYESIAN NETWORK ANALYSIS OF DATA FROM AN EARLY axSpA COHORT

Background

Current knowledge on the health status of patients (pts.) with axial spondyloarthritis (axSpA) mainly focusses on physical function and disease activity. Using a generic measure for physical- or mental health (SF36), a hierarchical relationship between disease activity, spinal damage, spinal mobility, physical function and overall health has been demonstrated in pts. with radiographic axSpA (r-axSpA) 1. Disease-specific global functioning and health can be assessed in pts. with axSpA using the ASAS Health Index (ASAS HI), which encompasses physical function, as well as aspects of emotional and social functioning and aspects of activity and participation.

Objectives

To build a structural model that visualizes interrelationships of different patient- and disease characteristics with global functioning and health in pts. with early axSpA.

Methods

Data of pts. with axSpA from the DESIR cohort was analyzed, which included information on socio-demographics (age, BMI), disease activity (ASDAS), physical function (BASFI), spinal mobility (BASMI), structural damage (mSASSS), disease-specific global functioning (ASAS HI), and comorbidity count. Information on patient- and disease characteristics was retrieved from the visit performed 72 months after inclusion, which was the first time point of ASAS HI collection. A Bayesian network (BN) was used to obtain insight of the underlying structural model. BNs are probabilistic graphical models consisting of “nodes” (representing specific variables) joined by “edges” (lines representing directions of effects). They are capable of capturing complex relationships between variables and allow the incorporation of existing (prior) knowledge from previous studies.

Results

The DESIR cohort contained data from 582 pts. at month 72, of whom 398 had data for ASAS HI. Descriptive information of these pts. is shown in Table 1. The mean ASAS HI was 5.7 (range: 0 - 16). Applying existing cut-offs for ASAS HI, 51% had ‘good’ global functioning (ASAS HI ≥5), 40% had ‘moderate’ global functioning (5< ASAS HI <12) and 9% had ‘bad’ global functioning (ASAS HI ≥12). The structural model that was constructed from combining data and prior expert knowledge is visualized in Figure 1. It suggests that ASDAS and BASFI have a direct impact on ASAS HI and that ASDAS has an indirect impact via BASFI. The model also suggests that ASDAS has an impact on the number of co-morbidities via BMI and that BASFI determines BASMI, which is in turn also influenced by age and mSASSS. In addition, it suggests a direct effect of age, BMI and ASAS HI on the comorbidity count. The model denies a relationship between BASMI or mSASSS and ASAS HI.

Table 1.

Patient and disease characteristics at month 72

N = 398Gender (male), N (%)181 (45%)Age (years)40.7 (8.7)Symptom duration (years)7.5 (0.9)BMI (kg/m2)25.0 (4.6)ASDAS2.0 (1.0)BASFI (0–10)2.3 (2.1)BASMI (0–10)2.5 (1.0)mSASSS (0-72)1.0 (3.6)ASAS HI (0-17)5.7 (3.9)good global functioning: ASAS HI ≤5, N (%)201 (51%)moderate global functioning: 5< ASAS HI <12, N (%)160 (40%)bad global functioning: ASAS HI ≥12, N (%)37 (9%)Comorbidity count1.4 (0.7)Figure 1.

Structural model on interrelationships of different patient- and disease characteristics with global functioning and health (ASAS HI) in patients with early axSpA

Conclusion

The BN-analysis approach, that combines prior knowledge and measured data, serves to better understand the construct of global functioning and health in pts. with early axSpA. Our model shows that global functioning (ASAS-HI) is determined both by patient-reported physical function (BASFI) and by disease activity (ASDAS), which confirms the hierarchical model once proposed by Machado et al. The observed directional relationship between ASAS HI and comorbidity count is counterintuitive and requires further investigation.

References

[1]Machado P, ARD 2011.

Disclosure of Interests

Imke Redeker: None declared, Robert B.M. Landewé Speakers bureau: AbbVie, BMS, GSK Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, UCB, Consultant of: AbbVie, BMS, GSK Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, UCB, Désirée van der Heijde Speakers bureau: AbbVie, Bayer, BMS, Cyxone, Eisai, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Lilly, Novartis, Pfizer, UCB Pharma, Consultant of: AbbVie, Bayer, BMS, Cyxone, Eisai, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Lilly, Novartis, Pfizer, UCB Pharma, Grant/research support from: AbbVie, Bayer, BMS, Cyxone, Eisai, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Lilly, Novartis, Pfizer, UCB Pharma, Sofia Ramiro Speakers bureau: Eli Lilly, MSD, Novartis, UCB, Consultant of: AbbVie, Eli Lilly, MSD, Novartis, UCB, Sanofi, Grant/research support from: AbbVie, Galapagos, Novartis, Pfizer, UCB, Annelies Boonen Speakers bureau: Abbvie / Galapagos, Consultant of: Galapagos, Grant/research support from: Abbvie, Maxime Dougados: None declared, Juergen Braun Speakers bureau: Abbvie, Amgen, Biogen, BMS, Boehringer, Celltrion, Chugai, Fresenius, Hexal, Janssen, Lilly, Medac, MSD, Mylan, Mundipharma, Novartis, Pfizer und UCB, Consultant of: Abbvie, Amgen, Biogen, BMS, Boehringer, Celltrion, Chugai, Fresenius, Hexal, Janssen, Lilly, Medac, MSD, Mylan, Mundipharma, Novartis, Pfizer und UCB, Grant/research support from: Abbvie, Amgen, Biogen, BMS, Boehringer, Celltrion, Chugai, Fresenius, Hexal, Janssen, Lilly, Medac, MSD, Mylan, Mundipharma, Novartis, Pfizer und UCB, Uta Kiltz Speakers bureau: AbbVie, Biocad, Biogen, Chugai, Eli Lilly, Hexal, Janssen, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: AbbVie, Biocad, Biogen, Chugai, Eli Lilly, Hexal, Janssen, MSD, Novartis, Pfizer, Roche, UCB, Grant/research support from: AbbVie, Biogen, Fresenius, Amgen, Hexal, Novartis, Pfizer

OP0155 DO FATTY LESIONS EXPLAIN THE ASSOCIATION BETWEEN INFLAMMATION AND NEW SYNDESMOPHYTES IN PATIENTS WITH RADIOGRAPHIC AXIAL SPONDYLOARTHRITIS?

Background

Presence of vertebral corner inflammation (VCI) increases the likelihood of a new syndesmophyte in the same vertebral corner (VC) in patients with r-axSpA. It was suggested that subsequent vertebral corner fat deposition (VCFD) partially explains this effect. However, this has not been formally tested.

Objectives

To determine how much of the effect of VCI on the development of new syndesmophytes is explained by new VCFD.

Methods

Two datasets (SIAS cohort, ASSERT clinical trial) were analyzed. Patients with r-axSpA were assessed at baseline (T0), an intermediate visit (T1) (SIAS: 1 year; ASSERT: 24 weeks) and the end of follow-up (T2) (SIAS: 2 years; ASSERT: 102 weeks). Syndesmophytes were assessed on whole spine low dose CT (SIAS) or spinal radiographs (ASSERT) at T0 and T2 and considered present if seen by 2 of 2 readers. VCI (T0) and VCFD (T0 and T1) on spinal MRI were present if seen by ≥2 of 3 readers (SIAS) or 2 of 2 readers (ASSERT). VCs with VCFD or a syndesmophyte at baseline were excluded. We used the counterfactual approach1 to decompose the total effect of VCI at T0 (binary exposure) on the formation of a new syndesmophyte in the same VC at T2 (binary outcome) into the effect that is explained (natural indirect effect, NIE) and the effect that is not explained (natural direct effect, NDE) by new VCFD (binary mediator) at T1. Because there was no interaction between the exposure and mediator (p=0.88 for SIAS; p=0.82 for ASSERT), the average NIE (aNIE) and average NDE (aNDE) are reported. The aNIE, aNDE and total effect, expressed as absolute increase in risk, were estimated in R using the ‘mediation’ package, which takes into account the 2-level structure of the data (VCs nested within patients).

Results

In total, 49 patients (2,667 corners) in SIAS and 168 patients (2,918 corners) in ASSERT were included. A new syndesmophyte occurred at T2 in 124/2,667 (5%) corners in SIAS and 91/2,918 (3%) corners in ASSERT (Table 1). New VCFD at T1 was also uncommon (SIAS: 4%; ASSERT: 2%), but occurred more often in corners with (SIAS: 12%; ASSERT: 18%) than without VCI at T0 (SIAS: 3%; ASSERT: 1%). Applying the mediation formula, in SIAS, the presence of VCI at T0 increased the probability of a new syndesmophyte in the same VC at T2 by 9.3% [total effect (95% CI)=9.3% (4.5; 15.0)]. There was only a 0.2% increase in this probability that was mediated by the formation of new VCFDs at T1 [aNIE=0.2% (-0.4; 1.0)]. In contrast, 9.1% of the increase in probability remained unexplained [aNDE=9.1 (4.3; 15.0)]. This means that only 2% (0.2/9.3) of the total effect of VCI on the formation of new syndesmophytes was explained by new VCFD [% mediated=2.0% (-4.1; 13)]. In ASSERT, the total effect was somewhat lower than in SIAS [total effect=7.3% (2.0; 16.0)], and again the aNIE was small [aNIE=0.8% (-0.2; 3.0)], and the aNDE composed most of the total effect [aNDE=6.5% (1.3; 14.0)]. The proportion of the total effect explained by VCFD (0.8/7.3=10% (-3.1;44)) was larger than in SIAS but still non-significant.

Table 1.

Marginal and conditional probabilities

SIASVCI T0New VCFD T1New SYND T2nP (SYND|VCI, VCFD)P(VCFD|VCI)0002302P (SYND|0,0) =90/2392= 0.038P(VCFD|0) = 74/2466=0.0300019001070P (SYND|0,1) =4/74 = 0.0540114100152P (SYND|1,0) = 25/177 = 0.141P(VCFD|1) = 24/201 =0.1191012511019P (SYND|1,1) = 5/24 = 0.2081115ASSERTVCI T0New VCFD T1New SYND T2nP (SYND|VCI, VCFD)P(VCFD|VCI)0002660P (SYND|0,0) = 76/2736= 0.028P(VCFD|0) = 35/2771 =0.0130017601034P (SYND|0,1) =1/35= 0.0290111100112P (SYND|1,0) = 9/121= 0.074P(VCFD|1) = 26/147 =0.177101911021P (SYND|1,1) = 5/26 = 0.1921115

VCI, vertebral corner inflammation; VCFD, vertebral corner fat deposition; Synd, syndesmophytes; T0, baseline; T1, intermediate visit; T2, end of follow-up; n, number of vertebral corners; P, probability

Conclusion

In these two datasets we see that VCI only infrequently leads to syndesmophyte formation via visible VCFD.

References

[1]Pearl, The mediation formula, 2011

Figure 1.

The pathways under study. VCI, vertebral corner inflammation; VCFD, vertebral corner fat deposition

Disclosure of Interests

Rosalinde Stal: None declared, Alexandre Sepriano Speakers bureau: Novartis, Consultant of: UCB, Sofia Ramiro Speakers bureau: Eli Lilly, MSD, Novartis, UCB, Consultant of: AbbVie, Eli Lilly, MSD, Novartis, Pfizer, UCB, Sanofi, Grant/research support from: AbbVi, Galapagos, MSD, Novartis, Pfizer, UCB, Floris A. van Gaalen Consultant of: Novartis, MSD, AbbVie, Bristol Myers Squibb, Eli Lilly, Grant/research support from: Stichting vrienden van Sole Mio, Stichting ASAS, Jacobus Stichting, Novartis, UCB, Pedro Machado Consultant of: Abbvie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Orphazyme, Pfizer, Roche and UCB, Xenofon Baraliakos: None declared, Rosaline van den Berg: None declared, Monique Reijnierse Grant/research support from: reader for ASAS CLASSIC study, Juergen Braun: None declared, Robert B.M. Landewé Consultant of: AbbVie, Amgen, BMS, GSK, Janssen, Eli Lilly, Novartis, Pfizer, UCB, Désirée van der Heijde Consultant of: AbbVie, Gilead, Glaxo-Smith-Kline, Lilly, Novartis, UCB Pharma, Grant/research support from: Dutch Rheumatism Association

AB0400 A SYSTEMATIC LITERATURE REVIEW AND META-ANALYSIS INTO THE SUCCESS RATE OF GLUCOCORTICOID DISCONTINUATION AFTER THEIR USE AS INITIAL BRIDGING THERAPY IN RHEUMATOID ARTHRITIS PATIENTS IN OBSERVATIONAL COHORTS AND CLINICAL TRIALS

Background

Glucocorticoids (GC) are widely used for the initial treatment of rheumatoid arthritis (RA), to induce rapid suppression of inflammation and clinical symptoms and thereby limit radiographic damage progression. There are concerns that GC use in the long term is associated with a dose and duration dependent risk of serious side effects. Therefore, international guidelines have recommended to start GC when initiating a csDMARD, but to discontinue GC as rapidly as clinically feasible, preferably within 3 months (bridging therapy). In contrast, due to the concerns of GC side effects, the ACR guidelines published in 2021 conditionally recommend to start csDMARD monotherapy without GC bridging therapy.

Objectives

We aim to evaluate the success rate of GC discontinuation after using temporary GC as part of initial therapy (‘bridging’) both in observational cohorts and clinical trials in newly diagnosed RA patients.

Methods

Systematic literature searches were conducted to identify observational cohorts (scoping search) and clinical trials (in-depth search) that included RA patients who were treated with initial GC bridging therapy. GC bridging was defined as oral or intramuscular GC treatment that was discontinued within one year, alongside conventional DMARD therapy. Patient percentages still or again using GC were considered to represent the reverse of successful discontinuation. Random-effects meta-analyses were performed stratified by time point.

Results

The literature search on observational cohort studies could not identify any study answering the research question, since it remained unclear which patients had received GC as part of the initial treatment. The literature search for clinical trials identified 7160 abstracts, resulting in 10 included studies, with varying type and dose of GC and varying tapering schedules (Table 1). Of these included studies, 4 reported sufficient data on GC discontinuation or GC use after the bridging phase. The pooled proportion of patients who were still using GC was 22% (95% Confidence Interval (CI) 8; 37, based on 4 trials) at 12 months and 10% at 24 months (95% CI -1; 22, based on 2 trials) (Figure 1). Thus, the vast majority had stopped GC. Heterogeneity was substantial (I2 ≥ 65%).

Table 1.

Overview of included clinical trials.

Study (publication year)Tapering schedule (mg/day)COBRA (1997)In 7 weeks to 7.5. Stop after 28 weeks.*BeSt (2005)In 7 weeks to 7.5. Stop in 8 weeks after week 28 if DAS persistently ≤2.4IDEA (2014)N.A.COBRA-light (2015)arm 1: in 7 weeks to 7.5 arm 2: in 9 weeks to 7.5 Stop after 32 weeks if DAS<1.6.IMPROVED (2014)In 7 weeks to 7.5. Stop after 20 weeks if DAS <1.6 at 4 months.ARCTIC (2016)In 7 weeks to 0 if DAS <1.6 and no swollen joints present.tREACH (2013)In 10 weeks to 0.*CareRA (2017)- in 7 weeks to 7.5, further tapered from week 28, stop after 34 weeks.- Classic- in 6 weeks to 5, further tapered from week 28, stop after 34 weeks.- Slim- in 6 weeks to 5, further tapered from week 28, stop after 34 weeks.- Avant gardeAll if DAS28(CRP) ≤3.2.Hua et al. (2020)Tapering after 4 months to 5, stop after 6 months.*NORD-STAR (2020) - arm 1A (oral prednisolone)In 9 weeks to 5. Stop after 9 months.*

DAS=disease activity score; mg=milligram; N.A.=not applicable.

*GC tapered and stopped according to protocol, not depending on disease activity score.

Conclusion

The success rate of GC discontinuation after bridging as part of initial treatment of RA has been described in a limited number of studies. Reports on observational cohorts did not answer the research question and in clinical trials reports, GC (dis)continuation data were also scarce. However, the available data show that GC can be discontinued successfully in a large majority of patients. The paucity of data also reveals that more efforts are needed to provide data towards identifying the optimal GC bridging and discontinuation strategy, combining Treatment to Target with Starting to Stop.

Acknowledgements

We would like to thank J.W. Schoones for his help and expertise in the systematic literature search.

Disclosure of Interests

Lotte van Ouwerkerk: None declared, Andriko Palmowski: None declared, Isabell Nevins: None declared, Frank Buttgereit Consultant of: Consultant of AstraZeneca, AbbVie, Grünenthal, Horizon Pharma, Pfizer, and Roche., Grant/research support from: Grant/research support from AbbVie, Horizon Pharma, Pfizer, and Roche., Patrick Verschueren Consultant of: Was consultant for ABBVIE, BMS, Celltrion, Eli Lilly, Galapagos, Gilead, Nordic Pharma, Pfizer and UCB., Employee of: Holds the Pfizer Chair Early Rheumatoid Arthritis Management at KU Leuven., Josef Smolen: None declared, Robert B.M. Landewé Shareholder of: Shareholder of: Director of Rheumatology Consultancy BV., Consultant of: Consultant of: Honoraria from AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Eli-Lilly, Novartis, Pfizer, UCB Pharma., Hans Bijlsma Consultant of: Consultant for Galapagos, Lilly and Sun., Grant/research support from: Received study grants from AbbVie and Roche., Andreas Kerschbaumer: None declared, Rene Westhovens Consultant of: Was consultant for Celltrion, Galapagos and Gilead., Thomas Huizinga: None declared, Cornelia Allaart Grant/research support from: Received study grants for BeSt and IMPROVED from Centocor Inc. (now Janssen) and AbbVie, respectively., Sytske Anne Bergstra Grant/research support from: Received an ASPIRE grant from Pfizer.

POS0963 HOW IS EARLY SPONDYLOARTHRITIS DEFINED IN THE LITERATURE? RESULTS FROM A SYSTEMATIC REVIEW

Background

The term “early spondyloarthritis (SpA)” has been frequently used to refer to the first phase of the disease, however, no standardized definition on “early” has been established. The ASAS-SPEAR (SPondyloarthritis EARly definition) project aims at developing a consensual definition on what is meant by “early SpA”. In order to inform the ASAS-SPEAR working group, it is highly relevant to assess the current meaning of “early SpA” in the literature.

Objectives

To identify all possible definitions of “early SpA” employed in the literature, including “early axial SpA (axSpA)” and “early peripheral SpA (pSpA)”.

Methods

A systematic literature review was conducted in Medline, EMBASE and the Cochrane Library (through April 28th, 2021). The eligibility criteria were studies with any design, in adults that included any mention of “early SpA” or its subtypes in the title or abstract. Two reviewers independently identified eligible studies and extracted data, including the literal definition of early SpA used in each of them. The proportion of studies reporting a definition was calculated, and the different definitions were assessed, including the core of the definition: whether they were based on symptom duration, disease duration, radiographic damage, a combination of them or any other aspects, and their boundaries.

Results

Out of 9,651 titles identified, 355 publications reporting data from 186 studies were included (291 full papers, 64 conference abstracts). Among them, 217 (61%) were cohort studies, 72 (20%) were reviews and 46 (13%) were clinical trials. Over time, an increasing number of publications on early SpA were identified: <2005 (n=34), 2005-2010 (n=48), 2011-2015 (n=109) and 2016-2020 (n=164). Overall, 63 studies (34%) included the term “early axSpA”, 60 (32%) “early ankylosing spondylitis (AS)”, 58 (31%) “early SpA”, 4 (2%) “early non-radiographic axSpA (nr-axSpA)” and 1 (1%) “early pSpA”. In total, 116 (62%) studies reported a specific definition: 40 (34%) based it on symptom duration, 35 (30%) on radiographic damage, 32 (28%) on disease duration, 6 (5%) on both symptom/disease duration and radiographic damage, and 3 (3%) on other aspects. Symptom duration was defined as the time since the onset of low back pain in 21/40 (53%) studies, whereas in 14/40 (35%) the symptom of onset was not specified. Thirty-five of 116 studies (30%) included a definition referred to “early SpA”, 38 (33%) to “early axSpA”, 38 (33%) to “early AS”, 4 (3%) to “early nr-axSpA”, and 1 (1%) to “early pSpA”. Figure 1 shows the 18 distinct definitions that were identified (after combining some similar categories). The three most used definitions per subtype of disease are shown in Table 1. Regarding the studies that referred to “early axSpA”, the most used definition was symptom/disease duration <5 years, whereas for “early AS” was symptom/disease duration <10 years. After 2010, the definition of “early axSpA” based on the absence of radiographic sacroiliitis was less used compared to before 2010 (5/30, 17% vs 3/8, 38%).

Table 1.

Top 3 candidate definitions for “early SpA” and subtypes

Core of the definitionNumber of studies, n (%)SpA (n= 35)nr-axSpA10 (29%)< 2 years duration10 (29%)< 1 year duration6 (17%)AxSpA (n=38)< 5 years duration12 (34%)< 3 years duration9 (24%)nr-axSpA duration8 (21%)AS/r-axSpA (n=38)<10 years duration9 (24%)nr-axSpA7 (18%)< 2 years duration6 (16%)nr-axSpA (n=4)nr-axSpA2 (50%)< 1 year & nr-axSpA1 (25%)< 5 years & nr-axSpA1 (25%)pSpA (n=1)< 12 weeks duration1 (100%)

“Duration” refers to symptom duration or disease duration.

Figure 1.

Number of studies stratified by the core of the definition.

Conclusion

Over time, the term “early SpA” and its subtypes are increasingly used. Despite addressing early SpA, more than one third of the studies did not include a clear definition of the term. The studies reporting a definition of early SpA showed a large heterogeneity, with two out of three of them based on the duration of symptoms or disease. These results emphasize the need for a standardised definition of early SpA.

Acknowledgements

The Assessment of Spondyloarthritis international Society (ASAS) supported Diego Benavent financially for this work.

Disclosure of Interests

Diego Benavent Speakers bureau: Jannsen, Roche, Grant/research support from: Novartis., Dafne Capelusnik Speakers bureau: Bristol Myers Squibb, Pfizer, Grant/research support from: Pfizer, Désirée van der Heijde Consultant of: AbbVie, Bayer, BMS, Cyxone, Eisai, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Lilly, Novartis, Pfizer, UCB Pharma., Employee of: Director of Imaging Rheumatology bv., Robert B.M. Landewé Consultant of: AbbVie, BMS, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer, UCB, Denis Poddubnyy Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Biocad, Eli Lilly, Gilead, GlaxoSmithKline, Janssen, MSD, Novartis, Pfizer, Samsung Bioepis, and UCB, Grant/research support from: AbbVie, Eli Lilly, MSD, Novartis, and Pfizer, Astrid van Tubergen Consultant of: Novartis, Galapagos, Grant/research support from: Pfizer, UCB, Novartis, Louise Falzon: None declared, Sofia Ramiro Speakers bureau: Eli Lilly, MSD, Novartis, UCB, Consultant of: AbbVie, Eli Lilly, MSD, Novartis, Pfizer, UCB, Sanofi, Grant/research support from: AbbVie, Galapagos, Novartis, Pfizer, UCB, Victoria Navarro-Compán Speakers bureau: AbbVie, Eli Lilly, Janssen, MSD, Novartis, Pfizer, UCB Pharma, Consultant of: AbbVie, Eli Lilly, MSD, Novartis, Pfizer, UCB Pharma, Grant/research support from: Abbvie and Novartis

POS0153 MRI SPINAL LESIONS IN PATIENTS WITHOUT MRI OR RADIOGRAPHIC LESIONS IN THE SACROILIAC JOINTS TYPICAL OF AXIAL SPONDYLOARTHRITIS

Background

There are limited data as to the frequency of spinal lesions on MRI in patients without MRI or radiographic features typical of sacroiliac joint (SIJ) disease and to what degree spine MRI might enhance diagnostic evaluation.

Objectives

To assess the frequency of MRI lesions of the spine in the ASAS-Classification Cohort according to the presence of MRI SIJ lesions typical of axSpA and/or radiographic sacroiliitis (mNY+).

Methods

MRI spine lesions were recorded by 9 central readers in an eCRF that captures global assessment of the spine (“Is the MRI consistent with axSpA: yes/no”) (yes=MRIglobal spine+) and detailed anatomical-based scoring of each discovertebral unit plus lateral and posterior structures. Independently, readers globally assessed SIJ scans for active and/or structural lesions typical of axSpA. We compared the frequency of MRIglobal spine+ and frequencies of different types of spinal lesions according to the presence/absence of axSpA on global evaluation of SIJ scans by ≥5 of 9 readers (MRIglobal SIJ+) and mNY+ sacroiliitis using Fisher’s exact test. Analysis was also stratified by rheumatologist diagnosis.

Results

Among 51 cases with SIJ as well as spine MRI scans and radiographs of the SIJ,19 (37.3%) had MRIglobal SIJ+, and 12 (23.5%) and 7 (13.7%) had MRIglobal spine+ by ≥2 and ≥5 reader agreement, respectively. MRIglobal spine+ occurred significantly more frequently in the presence of mNY+ sacroiliitis and MRIglobal SIJ+ but was also recorded in 4 of 32(12.5%) (≥2 readers) and 1 of 32(3.4%) (≥5 readers) cases that were MRIglobal SIJ- and x-ray negative, all 4 cases being diagnosed with axSpA. Moreover, vertebral corner BME lesions, but not spinal structural lesions, were significantly more frequent in MRIglobal SIJ- cases that had been clinically diagnosed as axSpA versus non-axSpA (Table 1).

Table 1.

Frequency of Spinal MRI lesions According to SIJ Imaging Positive for AxSpA

MRI Spinal Lesions, N (%)MRIglobalSIJ+ (n=19)MRIglobalSIJ- (n=32)P valueMRIglobal SIJ+ and/or mNY+ (n=22)MRIglobal SIJ- and mNY- (n=29)P valueMRIglobal SIJ- and SpA Diagnosis+(n=17)MRIglobal SIJ- and SpA Diagnosis- (n=15)P valueMRIglobal consistent with axSpA (≥2/9 readers agree)8 (42.1%)4 (12.5%)0.048(36.4%)4(13.8%)0.104 (23.5%)0 (0%)0.10MRIglobal consistent with axSpA (≥5/9 readers agree)6 (31.6%)1 (3.1%)0.016 (27.3%)1 (3.4%)0.031 (5.9%)0 (0%)1.0VC BME ≥19 (47.4%)15 (46.9%)46.9% RT 62.5% CT 29.4% GT1.010(45.5%)14(48.3%)1.011 (64.7%)4 (26.7%)0.04VC BME ≥26 (31.6%)10 (31.3%)31.2% RT 55.6% CT 19.6% GT1.06(27.3%)10(34.5%)0.769 (52.9%)1 (6.7%)0.007VC BME ≥36 (31.6%)7 (21.9%)21.9% RT 53.8% CT 13.7% GT0.526(27.3%)7(24.1%)1.07 (41.2%)0 (0%)0.008VC BME ≥45 (26.3%)5 (15.6%)0.475(22.7%)5(17.2%)0.735 (29.4%)0 (0%)0.046Vertebral Endplate BME ≥12 (10.5%)3 (9.4%)1.02(9.1%)3(10.3%)1.02 (11.8%)1 (6.7%)1.0Lateral vertebral BME3 (15.8%)3 (9.4%)0.663(13.6%)3(10.3%)1.03 (17.6%)0 (0%)0.23Facet BME ≥14 (21.1%)1 (3.1%)3.1% RT 20.0% CT 2.0% GT0.064(18.2%)1(3.4%)0.151 (5.9%)0 (0%)1.0Posterior BME ≥15 (26.3%)2 (6.3%)0.095(22.7%)2(6.9%)0.221 (5.9%)1 (6.7%)1.0VC Fat ≥18 (42.1%)42.1% RT 44.4% CT 15.7% GT10 (31.3%)31.2% RT 55.6% CT 19.6% GT0.558(36.4%)10(34.5%)1.05 (29.4%)5 (33.3%)1.0VC Fat ≥27 (36.8%)5 (15.6%)0.107(31.8%)5(17.2%)0.323 (17.6%)2 (13.3%)1.0VC Fat ≥36 (31.6%)31.6% RT 66.7% CT 11.8% GT3 (9.4%)0.066(27.3%)3(10.3%)0.151 (5.9%)2 (13.3%)0.59VC Fat ≥46 (31.6%)1 (3.1%)0.016(27.3%)1(3.4%)0.030 (0%)1 (6.7%)0.47Lateral Fat ≥16 (31.6%)2 (6.3%)0.046(27.3%)2(6.9%)0.060 (0%)2 (13.3%)0.21Erosion ≥13 (15.8%)2 (6.3%)0.353(13.6%)2(6.9%)0.641 (5.9%)1 (6.7%)1.0Bone Spur ≥14 (21.1%)5 (15.6%)0.714(18.2%)5(17.2%)1.04 (23.5%)1 (6.7%)0.34Ankylosis ≥12 (10.5%)0 (0%)0.132(9.1%)0(0%)0.180 (0%)0 (0%)-

Conclusion

Spinal lesions on MRI indicative of axSpA per majority read occurred in about 3% of patients without positive imaging in the SIJ. Frequency of spinal BME lesions was higher in cases with negative SIJ imaging but clinically diagnosed with axSpA.

Disclosure of Interests

None declared

POS0303 TREATMENT DECISIONS IN AXIAL SPONDYLOARTHRITIS ARE MORE THAN TREAT TO TARGET

Background

Several guidelines advise treating axial spondyloarthritis (axSpA) patients according to the ‘treat-to-target principles’ (T2T)1 although a clear target has not yet been defined. Disease activity measures, which are often used as targets, do not always reflect pure inflammatory disease activity. Currently is it not known if T2T is applied in axSpA clinical practice and what factors influence treatment decisions.

Objectives

To assess residual disease activity according to the physician’s opinion, patient’s opinion and disease activity measures and the subsequent treatment decisions made in axSpA patients.

Methods

This cross-sectional multicentre study included 249 patients with a clinical diagnosis of axSpA ≥ 6 months. Remission and low disease activity according to Bath Ankylosing Spondylitis Disease Activity Index (BASDAI <1.9 and <3.5 respectively), physician’s, and patient’s opinion was assessed. Questionnaires including patient reported outcomes (PROs) such as the Patient Global Assessment (PGA) of disease activity, Bath Ankylosing Spondylitis Functional Index (BASFI), ASAS-Health Index (ASAS-HI), central sensitization inventory (CSI), Brief Illness Perception Questionnaire (B-IPQ), and satisfaction with treatment; or questions regarding motivations for treatment decisions were filled in by patients and physicians respectively.

Results

In this cohort, 115/249 patients were in remission according to the physician. Of these 115 patients, 67% (n=80) indeed perceived their disease as being inactive, but only 37% (n=43) reached remission according to the BASDAI. This shows a significant level of discrepancy in comparison with the physician’s opinion. Of note, 30% (n=35) even reported a BASDAI >3.5. In 93% (n=107) treatment-intensity remained unchanged and in 6% (n=5) treatment was tapered. Physicians motivated that treatment was left unchanged in the majority of these patients because of remission (n=55, 48%), low disease activity (n=28, 24%), or complaints not related to axSpA (n=13, 12%). The latter two motives were most frequently mentioned for the patients with a BASDAI >3.5 (respectively n=13, 39% and n=9, 27%). Residual disease activity was present in 134/249 patients according to the physician’s opinion and 67% (n=90) of these patients also perceived their disease as active. In 89% (n=119) BASDAI score was >1.9 and in 62% (n=83) >3.5. In 61% (n=51) of these patients with residual disease and a BASDAI >3.5, treatment remained unchanged, as well as in 84% (n=43) of the patients with a BASDAI between 1.9 and 3.5. Physician’s most frequently mentioned motives for not changing treatment in the residual disease activity group were: low disease activity achieved (n=29, 25%), the need to await the effect of the current treatment (n= 23, 20%), or complaints that were not related to axSpA (n=9, 8%). The second (n=20, 39%) motive was most frequently mentioned for unchanged treatment in the BASAI >3.5 group and additionally, physicians mentioned that these patients had a preference to continue their current treatment despite high disease activity (n=5, 10%).

Analyses of PROs showed significantly higher scores for PGA of disease activity, several subdomains of the B-IPQ, general fatigue and morning stiffness in patients with remission according to the physician despite a BASDAI >3.5 compared to patients with residual disease according to the physician with a BASDAI <1.9.

Conclusion

This study shows that physicians in daily clinical practice do not always adjust treatment according to the T2T-principles in patients with residual disease activity when measured by BASDAI scores, either because low disease activity is achieved, because they classify the patient as being in remission, as having low disease activity, or because there was a need to await the efficacy of the current treatment. Further studies are needed to investigate if treatment choices made in clinical practice result in under-treatment of axSpA patients with worse outcome in comparison to the T2T approach.

References

[1]Van der Heijde et al. Ann Rheum Dis. 2017

Disclosure of Interests

J.W. Bolt: None declared, Caroline Aalbers Speakers bureau: I am paid by Novartis as a speaker, Laura H Walet: None declared, Leonieke van Mens: None declared, J.C. van Denderen: None declared, Irene van der Horst-Bruinsma Speakers bureau: Fees received for Lectures from BMS, AbbVie, Pfizer, MSD., Consultant of: Consultant for Abbvie, UCB, MSD, Novartis, Lilly., Grant/research support from: Unrestricted Grants received for investigator initiated studies from: MSD, Pfizer, AbbVie, UCB., Lisa van Baarsen: None declared, Robert B.M. Landewé Speakers bureau: AbbVie, Pfizer, UCB, Eli-Lilly, Novartis, Galapagos, Gilead. Honoraria paid to my small business (Rheumatology Consultancy BV)., Consultant of: AbbVie, Pfizer, UCB, Eli-Lilly, Novartis, Galapagos, Gilead. Consulting fees for participation in advisory boards, paid to my small business (Rheumatology Consultancy BV), Marleen G.H. van de Sande Speakers bureau: UCB., Consultant of: Advisory board: Abbvie, Eli Lily, Novartis, UCB, Grant/research support from: Novartis, Janssen, UCB, Eli Lilly

OP0148 THE ASAS CORE MEASUREMENT SET FOR AXIAL SPONDYLOARTHRITIS

Background

Recently, the core domains of the 20-years old core outcome set for ankylosing spondylitis were updated.1 The next step is to define the measurement core set, which includes at least one instrument for each domain.

Objectives

To define the instruments for the ASAS-OMERACT core outcome set for axial spondyloarthritis (axSpA).

Methods

The scientific committee invited an international working group representing all key stakeholders (patients, rheumatologists, health professionals and pharmaceutical industry). The instrument selection process is presented in Figure 1.

Figure 1.

Development process to determine the core measurement set

Results

The updated core measurement set for axSpA is shown in Table 1. This includes seven instruments for six domains that are mandatory for all trials: ASDAS and NRS patient global assessment for disease activity, NRS total back pain for pain, composite index for morning stiffness, NRS fatigue for fatigue, BASFI for physical function, and ASAS Health Index for overall functioning and health. There are 9 additional instruments for disease modifying drugs (DMARDs): two MRI activity scores (SPARCC SIJ and SPARCC spine) for disease activity, the three extra-musculoskeletal manifestations uveitis, IBD and psoriasis assessed as recommended by ASAS2, the three peripheral manifestations (44 swollen joint count, MASES and Dactylitis count2) and mSASSS for structural damage. The imaging outcomes are mandatory to be included at least in one trial for a drug that is considered to be a DMARD. The other instruments specific for DMARDs should be included in every trial. This core set is applicable to patients with radiographic and non-radiographic axSpA. Furthermore, 11 other instruments were also endorsed by ASAS and can additionally be used in axSpA trials: BASDAI, CRP, Berlin MRI-SIJ and MRI-spine activity scores for disease activity, NRS back pain at night for pain, severity (BASDAI Q5) and duration (BASDAI Q6) for morning stiffness, SF-36 for overall functioning and health, 66 swollen joint count and SPARCC enthesitis for peripheral manifestations and MRI-SIJ erosions scores (SPARCC SSS) for structural damage.

Table 1.

Updated core measurement set for axial spondyloarthritis.

Instruments mandatory for all trialsDomainInstrument Disease activityASDASPatient global assessment of disease activity (NRS) PainNRS total back pain (BASDAI Q2) Morning stiffnessSeverity and duration (BASDAI (Q5+Q6)/2)) FatigueNRS fatigue (BASDAI Q1) Physical functionBASFI Overall functioning & healthASAS Health IndexAdditional instruments mandatory for disease modifying drugs trials Disease activitySPARCC MRI-SIJ*SPARCC MRI-spine* Extra-musculoskeletal manifestationsuveitis (ASAS CRF)2psoriasis (ASAS CRF)2inflammatory bowel disease (ASAS CRF)2 Peripheral manifestations44 Swollen joint countMASESDactylitis count (ASAS CRF)2 Structural damagemSASSS*

*Needs to be assessed at least once in a disease modifying drug programme; 2Dougados M, et al. Ann Rheum Dis 2012;71(6):1103-04. ASDAS: Ankylosing Spondylitis Disease Activity Score; NRS: Numerical Rate Scale; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; Q: question; BASFI: Bath Ankylosing Spondylitis Functional Index; SPARCC: SpondyloArthritis Research Consortium of Canada Scoring System; MRI: Magnetic Resonance Imaging; SIJ: Sacroiliac Joint; CRF: Case Report Form; MASES: Maastricht Ankylosing Spondylitis Enthesitis Score; mSASSS: modified Stoke Ankylosing Spondylitis Spinal Score.

Conclusion

The previous core measurement set has been updated and endorsed by ASAS for the use in all axSpA trials.

References

[1]Navarro-Compán V, et al. Semin Arthritis Rheum 2021;51(6):1342-49.

[2]Dougados M, et al. Annals of the Rheumatic Diseases 2012;71(6):1103-04.

Acknowledgements

The ASAS axSpA core measurement set working group:

Désirée van der Heijde

Victoria Navarro Compán

Annelies Boonen

Philip Mease

Anne Boel

Uta Kiltz

Robert Landewé

Maxime Dougados

Xenofon Baraliakos

Wilson Bautista

Pravina Chiowchanwisawakit

Yu Heng Kwan

Lianne Gensler

Bassel El-Zorkany

Karl Gaffney

Nigel Haroon

Pedro Machado

Walter Maksymowych

Anna Molto

Denis Poddubnyy

Mikhail Protopopov

Sofia Ramiro

Salima van Weely

Marco Garrido Cumbrera

Natasha de Peyrecave

Lara Fallon

In-Ho Song

Hanne Dagfinrud

The Assessment of Spondyloarthritis international Society (ASAS) supported Anne Boel and Victoria Navarro-Compán financially to update the core outcome set.

Disclosure of Interests

Victoria Navarro-Compán Speakers bureau: AbbVie, Eli Lilly, Janssen, MSD, Novartis, Pfizer, UCB Pharma, Consultant of: AbbVie, Eli Lilly, MSD, Novartis, Pfizer, UCB Pharma; Research grants from AbbVie and Novartis, Grant/research support from: AbbVie and Novartis, Anne Boel: None declared, Annelies Boonen Speakers bureau: Abbvie / Galapagos, Consultant of: Galapagos, Grant/research support from: AbbVie, Philip J Mease Speakers bureau: Abbvie, Janssen, Lilly, Novartis, Pfizer, UCB, Consultant of: Abbvie, Aclaris, Amgen, Bristol Myers, Boehringer-Ingelheim, Galapagos, Gilead, GlaxoSmithKline, Inmagene, Janssen, Lilly, Novartis, Pfizer, SUN Pharma, UCB, Grant/research support from: Abbvie, Bristol Myers, Gilead, Inmagene, Janssen, Lilly, Novartis, Pfizer, UCB, Maxime Dougados: None declared, Uta Kiltz Consultant of: AbbVie, Chugai, Eli Lilly, Fresenius, Hexal, Janssen, MSD, Novartis, onkowissen.de, Pfizer, Roche and UCB, Grant/research support from: Abbvie, Amgen, Biogen, Hexal, Novartis und Pfizer, Robert B.M. Landewé Consultant of: AbbVie, BMS, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer, UCB, Désirée van der Heijde Consultant of: AbbVie, Bayer, BMS, Cyxone, Eisai, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Lilly, Novartis, Pfizer, UCB Pharma, Employee of: Director of Imaging Rheumatology bv.

POS0111 MORE METICULOUSLY FOLLOWING TREAT-TO-TARGET IN RA DOES NOT LEAD TO LESS RADIOGRAPHIC PROGRESSION: A LONGITUDINAL ANALYSIS IN BIODAM

Background

A Treat-to-Target approach (T2T) is broadly considered to lead to better clinical outcomes and recommended in patients with RA. However, very few studies have analyzed the effect of T2T on radiographic progression, and any such studies have provided inconsistent results.

Objectives

To investigate whether meticulously following a treat-to-target (T2T)-strategy in daily clinical practice leads to lower radiographic progression in RA.

Methods

Patients from the multicenter RA-BIODAM cohort with ≥2 consecutive visits with radiographs available were included. In RA-BIODAM patients were enrolled as they were initiating a new csDMARD/bDMARD treatment were followed-up with the intention to benchmark and intensify treatment. The primary outcome of this analysis was the change in Sharp-van der Heijde score (SvdH, 0-448), assessed every 6 months, using average scores from 2 readers (scores with known chronological order). Following a DAS44-T2T remission strategy, which was defined at each 3-month visit, was the main variable of interest. Patients were categorized based on the proportion of visits in which T2T was followed according to our definition: very low (≤40% of the visits, low (>40%, <62.5%), high (≥62.5%, ≤75%) and very high (>75%). Radiographic progression at 2 years was visualized across groups by cumulative probability plots. Per 3-month interval T2T could be followed zero, one or two times (in a total of 2 visits). Associations between the number of visits with T2T in an interval and radiographic progression, both in the same and in the subsequent 6-month interval, were analysed by generalised estimating equations, adjusted for age, gender, disease duration and country.

Results

In total, 511 patients were included (mean (SD) age: 56 (13) years; 76% female). After 2 years, patients showed on average 2.2 (4.1) units progression (median:1 unit). Mean (SD) 2-year progression was not significantly different across categories of T2T: very low: 2.1 (2.7)-units; low: 2.8 (6.0); high: 2.4 (4.5), very high: 1.6 (2.2) (Figure 1). Meticulously following-up T2T in a 3-month interval neither reduced progression in the same 6-month interval (parameter estimates (for yes vs no): +0.15 units (95%CI: -0.04 to 0.33) for 2 vs 0 visits; and +0.08 units (-0.06;0.22) for 1 vs 0 visits) nor did it reduce progression in the subsequent 6-month interval (Table 1).

Table 1.

Effect of following DAS44-remission-T2T strategy on 6-month radiographic progression over 2 years

Change in radiographic damage(regression coefficient (95% CI))N=506T2T during 3 months on radiographic progression in the same 6-month period 2 visits vs 0 followed0.15 (-0.04; 0.33) 1 visit vs 0 followed0.08 (-0.06; 0.22)T2T during 3 months on radiographic progression in the subsequent 6-month period 2 visits vs 0 followed-0.09 (-0.28; 0.10) 1 visit vs 0 followed-0.10 (-0.24; 0.05)Figure 1.

Cumulative probability plot with 2-year radiographic progression according to the proportion of 3-monthly visits with T2T followed

Conclusion

In this daily practice cohort, more meticulously following T2T principles did not result in more reduction of radiographic progression than a somewhat more liberal attitude toward T2T. One possible interpretation of these results is that the intention to apply T2T already suffices and that a more stringent approach does not further improve outcome.

Acknowledgements

BIODAM was financially supported by an unrestricted grant from AbbVie

Disclosure of Interests

Sofia Ramiro Speakers bureau: Eli Lilly, MSD, Novartis, UCB, Consultant of: AbbVie, Eli Lilly, MSD, Novartis, Pfizer, UCB, Sanofi, Grant/research support from: AbbVie, Galapagos, Novartis, Pfizer, UCB, Robert B.M. Landewé Speakers bureau: AbbVie, BMS, Gilead, Galapagos, GSK,Janssen, Lilly, Novartis, Pfizer, UCB, Consultant of: AbbVie, BMS, Gilead, Galapagos, GSK,Janssen, Lilly, Novartis, Pfizer, UCB

Dr Landewé owns Rheumatology Consultancy BV, Désirée van der Heijde Consultant of: AbbVie, Bayer, BMS, Cyxone, Eisai, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Lilly, Novartis, Pfizer, UCB Pharma. Director of Imaging Rheumatology bv., Alexandre Sepriano Speakers bureau: Novartis, Consultant of: UCB, Oliver FitzGerald Speakers bureau: Biogen, Novartis, AbbVie, BMS, Pfizer, Grant/research support from: BMS, Novartis, UCB, Pfizer, Lilly, Janssen, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Celgene, Eli-Lilly, Galapagos, Gilead, Janssen, Merck, Novartis, Orion, Pfizer, Roche and UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Grant/research support from: Abbvie, Amgen, BMS, Merck, Celgene and Novartis, Joanne Homik: None declared, Ori Elkayam Speakers bureau: Pfizer, Lilly, Novartis, Abbvie, BI, Janssen, Consultant of: Pfizer, Lilly, Novartis, Abbvie, BI, Janssen, Grant/research support from: Pfizer, Abbvie, Janssen, Carter Thorne Consultant of: Abbvie, Organon, Pfizer, Sandoz, Maggie Larché Speakers bureau: AbbVie, Actelion, Amgen, BMS, Boehringer-Ingelheim, Fresenius-Kabi, Gilead, Janssen, Mallinckrodt, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, Sobi, UCB, Grant/research support from: Abbvie, BMS, Gianfranco Ferraccioli Speakers bureau: SOBI, Consultant of: Abbivie, Marina Backhaus: None declared, Gilles Boire Speakers bureau: Abbvie Canada, BMS Canada, Lilly Canada, Janssen Canada, Merck Canada, Pfizer Canada, Viatris, Consultant of: Abbvie Canada, Amgen Canada, BMS Canada, Celgene, GileadSciences, Janssen Canada, Lilly Canada, Merck Canada, Mylan Canada, Novartis Canada, Pfizer Canada, Roche Canada, Samsung Bioepis, Sanofi Canada, Teva, Grant/research support from: Lilly Canada, BMS Canada, Pfizer, Sandoz Canada, UCB Canada, Merck Canada, Novartis Canada, Roche Canada, Bernard Combe Speakers bureau: Abbvie, BMS,Celltrion,Galapgos-Gilead, Janssen, Lilly, MERCK, Pfizer,Roche-Chugai, Consultant of: Abbvie, Celltrion,Galapgos-Gilead, Janssen, Lilly, MERCK, Roche-Chugai, Grant/research support from: Pfizer, Roche-chugai, Thierry Schaeverbeke: None declared, Alain Saraux Speakers bureau: Abbvie, Lilly, Nordic, Novartis, Pfizer, Roche-Chugai, Sanofi, UCB, Consultant of: Abbvie, Lilly, Nordic, Novartis, Pfizer, Roche-Chugai, UCB, Grant/research support from: Novartis, Fresenius, Lilly, Maxime Dougados Consultant of: Pfizer, AbbVie, UCB, Merck, Lilly, Novartis, BMS, Galapagos, Biogen, Roche, Grant/research support from: Pfizer, AbbVie, UCB, Merck, Lilly, Novartis, BMS, Galapagos, Biogen, Roche, Maurizio Rossini Speakers bureau: Amgen, Abbvie, BMS, Eli-Lilly, Galapagos,MSD, Novartis, Pfizer, Sandoz, Theramex, UCB, Marcello Govoni Speakers bureau: Abbvie, Pfizer, Galapagos, BMS, Eli-Lilly, Paid instructor for: Pfizer, Consultant of: Abbvie, BMS, Novartis, Astrazeneca, Pfizer, Luigi Sinigaglia: None declared, Alain Cantagrel Speakers bureau: Abbvie, Amgen, Biogen, BMS, Janssen, Lilly France, Médac, MSD France, Nordic-Pharma, Novartis, Pfizer, Sanofi Aventis, UCB, Consultant of: BMS, Janssen, Lilly France, MSD France, Sandoz, Grant/research support from: MSD France, Novartis, Pfizer, Cornelia Allaart: None declared, Cheryl Barnabe Speakers bureau: Sanofi Genzyme, Pfizer, Fresenius Kabi, Janssen, Consultant of: Gilead, Celltrion Healthcare, Clifton Bingham Consultant of: AbbVie, BMS, Eli Lilly, Janssen, Moderna, Pfizer, Sanofi, Grant/research support from: BMS, Dirkjan van Schaardenburg: None declared, Hilde Berner Hammer Speakers bureau: AbbVie, Novartis, Lilly, Rana Dadashova: None declared, Edna Hutchings: None declared, Joel Paschke: None declared, Walter P Maksymowych Speakers bureau: Abbvie, Janssen, Novartis, Pfizer, UCB, Consultant of: Abbvie, Boehringer Ingelheim, Celgene, Eli-Lilly, Galapagos, Novartis, Pfizer, UCB, Grant/research support from: Abbvie, Novartis, Pfizer

POS0296 INTEGRATED SAFETY ANALYSIS OF TOFACITINIB IN ANKYLOSING SPONDYLITIS CLINICAL TRIALS

Background

Tofacitinib is an oral JAK inhibitor for the treatment of adults with ankylosing spondylitis (AS).

Objectives

To describe the tofacitinib safety profile from an integrated analysis of randomised controlled trials (RCTs) in patients (pts) with active AS.

Methods

Pooled data from Phase (P)2 (NCT01786668) and P3 (NCT03502616) RCTs in pts with AS were analysed in 3 cohorts (Table 1): the 16-Week (Wk) placebo (PBO)-controlled cohort (pts receiving tofacitinib 5 mg twice daily [BID] or PBO from Wks 0–12 [P2 RCT] or Wks 0–16 [P3 RCT]), the 48-Wk all tofacitinib 5 mg BID cohort and the 48-Wk all tofacitinib cohort (pts receiving ≥1 dose of tofacitinib 2, 5 or 10 mg BID), including pts receiving tofacitinib from Wks 0–12 (P2 RCT) or Wks 0–48 (P3 RCT). Pts receiving tofacitinib 5 mg BID were included in the 16-Wk PBO-controlled cohort and both 48-Wk tofacitinib cohorts. Adverse event (AE)/AEs of special interest incidence rates (IRs; pts with events/100 pt-yrs) were reported based on a 28-day risk period (time of first to last study drug dose +28 days). Baseline (BL) cardiovascular (CV) risk was calculated post hoc by the atherosclerotic CV disease (ASCVD)-pooled cohort equations calculator for pts without history of coronary artery disease (48-Wk tofacitinib cohorts).

Results

At BL, most pts (>76%) in the 48-Wk tofacitinib cohorts had <5% (low) 10-yr ASCVD risk (Figure 1). The most common treatment-emergent AEs were nasopharyngitis/upper respiratory tract infection. Serious AE IRs were higher with tofacitinib 5 mg BID vs PBO in the 16-Wk PBO-controlled cohort, and similar in the 48-Wk tofacitinib cohorts (Table 1). Discontinuation due to AEs was similar between groups in the 16-Wk PBO-controlled cohort and between the 48-Wk tofacitinib cohorts (Table 1). One pt receiving tofacitinib 5 mg BID (included in the 16-Wk PBO-controlled and both 48-Wk tofacitinib cohorts) had a serious infection (SI; meningitis; Table 1). No SIs with PBO. Herpes zoster (HZ; all non-serious) occurred in the 48-Wk all tofacitinib 5 mg BID (5 pts [1.6%]) and 48-Wk all tofacitinib cohorts (7 pts [1.7%]; Table 1) only. Most cases involved a single dermatome, but 1 pt (tofacitinib 10 mg BID) had HZ involving 2 adjacent dermatomes. Across cohorts, there were no deaths or adjudicated opportunistic infections (OIs), OIs excluding tuberculosis (TB), TB, malignancies excluding non-melanoma skin cancer (NMSC), NMSC, major adverse CV events, thromboembolic events, gastrointestinal perforation or interstitial lung disease. Uveitis was reported in 1 (0.5%), 3 (1.6%), 4 (1.3%) and 6 (1.4%) pts in the tofacitinib 5 mg BID, PBO, 48-Wk all tofacitinib 5 mg BID and 48-Wk all tofacitinib groups, respectively; all but 1 pt (tofacitinib 2 mg BID) had history of uveitis. Psoriasis occurred in 1 (0.5%) pt (PBO) with history of psoriasis. There were no AEs of inflammatory bowel disease.

Table 1.

AEs and AEs of special interest

16-Wk PBO-controlled cohort48-Wk tofacitinib cohortsTofacitinib 5 mg BID N=185PBO N=18748-Wk all tofacitinib 5 mg BID N=31648-Wk all tofacitinib N=420AE, n (%), IR [95% CI per 100 pt-yrs]Serious AE3 (1.6) 5.28 [0.00, 11.25]2 (1.1) 3.56 [0.00, 8.49]8 (2.5) 3.49 [1.51, 6.87]9 (2.1) 3.45 [1.58, 6.55]Discontinuation due to AEs4 (2.2) 7.04 [0.14, 13.94]4 (2.1) 7.10 [0.14, 14.05]11 (3.5) 4.77 [2.38, 8.54]12 (2.9) 4.58 [2.37, 8.00]SI1 (0.5) 1.77 [0.00, 5.89]0 0.00 [0.00, 3.31]1 (0.3) 0.43 [0.01, 2.41]1 (0.2) 0.38 [0.01, 2.12]HZ0 0.00 [0.00, 3.28]0 0.00 [0.00, 3.31]5 (1.6) 2.18 [0.71, 5.08]7 (1.7) 2.68 [1.08, 5.53]All-cause mortality0 0.00 [0.00, 3.28]0 0.00 [0.00, 3.31]0 0.00 [0.00, 1.59]0 0.00 [0.00, 1.40]Malignancies excluding NMSC0 0.00 [0.00, 3.28]0 0.00 [0.00, 3.31]0 0.00 [0.00, 1.59]0 0.00 [0.00, 1.40]Major adverse CV event0 0.00 [0.00, 3.28]0 0.00 [0.00, 3.31]0 0.00 [0.00, 1.59]0 0.00 [0.00, 1.40]Venous thromboembolism0 0.00 [0.00, 3.28]0 0.00 [0.00, 3.31]0 0.00 [0.00, 1.59]0 0.00 [0.00, 1.40]

CI, confidence interval; n, number of pts with event within 28-day risk period

Conclusion

Tofacitinib 5 mg BID was well tolerated over 48 Wks in pts with AS, and safety was consistent with the established safety profile of tofacitinib.

Acknowledgements

Study sponsored by Pfizer Inc. Medical writing support was provided by Jennifer Arnold, CMC Connect, and funded by Pfizer Inc.

Disclosure of Interests

Atul Deodhar Consultant of: AbbVie, Amgen, Aurinia, Boehringer Ingelheim, Bristol-Myers Squibb, Celegene, Eli Lilly, GlaxoSmithKline, Janssen, MoonLake, Novartis, Pfizer Inc and UCB, Grant/research support from: AbbVie, Eli Lilly, GlaxoSmithKline, Novartis, Pfizer Inc and UCB, Servet Akar Speakers bureau: AbbVie, Amgen, Eli Lilly, MSD, Novartis, Pfizer Inc and UCB, Consultant of: AbbVie, Amgen, Eli Lilly, MSD, Novartis, Pfizer Inc and UCB, Grant/research support from: Pfizer Inc, Jeffrey Curtis Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, CorEvitas, LLC (formerly Corrona, LLC), Eli Lilly, Janssen, Myriad, Pfizer Inc, Radius, Roche and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, CorEvitas, LLC (formerly Corrona, LLC), Eli Lilly, Janssen, Myriad, Pfizer Inc, Radius, Roche and UCB, Bassel Zorkany Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eva, Eli Lilly, Hekma, Janssen, MSD, New Bridge, Novartis, Pfizer Inc, Roche, Sanofi-Aventis and Servier, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Eva, Eli Lilly, Hekma, Janssen, MSD, New Bridge, Novartis, Pfizer Inc, Roche, Sanofi-Aventis and Servier, Marina Magrey Consultant of: AbbVie, Eli Lilly, Novartis, Pfizer Inc and UCB, Grant/research support from: AbbVie and UCB, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Joseph Wu Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Solomon B Makgoeng Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Ivana Vranic Shareholder of: Pfizer Inc, Employee of: Pfizer Ltd, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Dona Fleishaker Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Annette Diehl Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Lara Fallon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Arne Yndestad Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Robert B.M. Landewé Consultant of: AbbVie, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Galapagos NV, Novartis, Pfizer Inc and UCB

POS0664 RADIOGRAPHIC CHANGE IN PATIENTS WITH RHEUMATOID ARTHRITIS AND ESTIMATED BASELINE YEARLY PROGRESSION ≥5 OR <5: POST HOC ANALYSIS OF TWO PHASE 3 TRIALS OF FILGOTINIB

Background

In some patients (pts) with rheumatoid arthritis (RA), especially those with joint damage early in the disease, first-line methotrexate (MTX) treatment may not suffice to prevent further rapid radiographic progression (RRP).1 In FINCH 1 (NCT02889796), filgotinib 200 mg (FIL200) and 100 mg (FIL100) reduced change in modified total Sharp score (mTSS) vs placebo (PBO) in pts with RA and inadequate response to MTX (MTX-IR).2 In FINCH 3 (NCT02886728), FIL200 and FIL100 reduced change in mTSS vs MTX monotherapy (MTX mono) in MTX-naïve pts.3

Objectives

To evaluate, via post hoc analysis of 2 trials, filgotinib’s effects on radiographic progression vs MTX mono in pts with estimated baseline (BL) yearly progression ≥5 or <5 mTSS units/year.

Methods

The double-blind 52-week (W) FINCH 1 study randomised MTX-IR pts with moderate–severe active RA to FIL200 or FIL100, subcutaneous adalimumab (ADA) 40 mg, or PBO; at W24, PBO pts were rerandomised blinded to FIL200 or FIL100; all took stable background MTX.2 In FINCH 3, MTX-naïve pts were randomised, blinded, to FIL200 + MTX, FIL100 + MTX, FIL200 alone, or MTX mono for up to W52.3 This analysis examined subgroups by estimated BL yearly progression (BL mTSS/duration in years of RA diagnosis), based on ≥5 or <5 mTSS units/year,4 a threshold commonly used to define RRP. We assessed effects of filgotinib vs ADA or PBO in mTSS change from BL (CFB) at W24/W52 (using a mixed model for repeated measures) and percentages with no W24 progression (mTSS change ≤0, ≤0.5, ≤smallest detectable change [SDC], using Fisher’s exact test).

Results

At BL, 558/1755 MTX-IR and 787/1249 MTX-naïve pts had BL estimated yearly progression ≥5. Median mTSS in pts with BL yearly progression ≥5 and <5 was 53.25 vs 5.00 respectively in the MTX-IR trial and 6.00 vs 2.50 in the MTX-naïve trial. At W24, the mTSS CFB in pts with BL yearly progression ≥5 and <5 was 0.84 and 0.22 in MTX-IR pts taking PBO + MTX, and 0.67 and 0.25 in MTX-naïve pts taking MTX mono. At W52, in pts with BL yearly progression ≥5, FIL200 + MTX reduced mTSS change vs PBO + MTX in the MTX-IR trial and vs MTX mono in the MTX-naïve trial (Figure 1). At W24, among pts with estimated BL yearly progression ≥5, FIL200 + MTX increased odds of no progression (≤0.5 or ≤0) vs PBO + MTX in MTX-IR pts and vs MTX mono in MTX-naïve pts (Table 1).

Table 1.

Ratio of no radiographic progression at W24

FINCH 1: MTX-IRFIL200 + MTXFIL100 + MTXADA + MTXPBO + MTXBL yearly progression≥5(n = 138)<5(n = 267)≥5(n = 139)<5(n = 265)≥5(n = 91)<5(n = 180)≥5(n = 101)<5(n = 250)% with no progression (≤0.5)87.797.088.592.587.993.976.291.6OR2.22*2.97*2.40*1.12††††% with no progression (≤0)80.491.881.388.380.289.467.386.4OR2.00*1.752.11*1.19††††% with no progression (≤SDC [1.36])91.398.192.196.692.395.681.294.0OR2.43*3.35*2.70*1.82††††FINCH 3: MTX-naïveFIL200 + MTXFIL100 + MTXFIL200 monoMTXBL yearly progression≥5<5≥5<5≥5<5≥5<5(n = 221)(n = 134)(n = 121)(n = 63)(n = 115)(n = 58)(n = 224)(n = 132)% with no progression (≤0.5)86.994.083.593.789.689.778.687.9OR1.81*2.171.382.032.34*1.20††% with no progression (≤0)78.783.672.784.180.087.967.980.3OR1.75*1.251.261.31.89*1.79††% with no progression (≤SDC [1.53])93.797.891.796.895.796.689.395.5OR1.772.081.331.452.641.33††

MTX-IR ORs are FIL vs PBO + MTX; MTX-naïve are FIL vs MTX. *Nominal P<.05. †Not applicable.

ADA, adalimumab; FIL, filgotinib; IR, inadequate response; mTSS, modified total Sharp score; MTX, methotrexate; OR, odds ratio; SDC, smallest detectable change; W, week.

Conclusion

These data suggest filgotinib’s inhibition of radiographic progression was numerically greater than MTX monotherapy in RA pts with high estimated BL yearly progression. In those with a more moderate estimated rate of progression, filgotinib suppressed progression comparably to ADA and/or MTX.

References

[1]Smolen J et al. Ann Rheum Dis 2018;77:1566–1572.

[2]Combe B et al. Ann Rheum Dis 2021;80:848–858.

[3]Westhovens R et al. Ann Rheum Dis 2021;80:727–738.

[4]Vastesaeger N et al. Rheumatology. 2009;48:1114–1121.

Acknowledgements

This study was funded by Gilead Sciences, Inc., Foster City, CA. Medical writing support was provided by Rob Coover, MPH, of AlphaScientia, LLC, San Francisco, CA; and funded by Gilead Sciences, Inc., Foster City, CA. Funding for this analysis was provided by Gilead Sciences, Inc. The sponsors participated in the planning, execution, and interpretation of the research.

Disclosure of Interests

Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, Behringer-Ingelheim, Bristol-Myers Squibb, Chugai, Eisai, Eli Lilly, Gilead, Mitsubishi-Tanabe, and YL Biologics, Grant/research support from: AbbVie, Asahi-Kasei, Boehringer-Ingelheim, Chugai, Corrona, Daiichi Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda, Tatsuya Atsumi Paid instructor for: Gilead Sciences, Inc.; Mitsubishi Tanabe; Chugai; Astellas Pharma; Takeda; Pfizer; AbbVie: Eisai; Daiichi Sankyo; Bristol-Myers Squibb; UCB Japan Co. Ltd.; Eli Lilly Japan K.K., Otsuka Pharmaceutical Co., Ltd.; and Alexion Inc., Grant/research support from: Gilead Sciences, Inc.; Mitsubishi Tanabe; Chugai; Astellas Pharma; Takeda; Pfizer; AbbVie: Eisai; Daiichi Sankyo; Bristol-Myers Squibb; UCB Japan Co. Ltd.; Eli Lilly Japan K.K., Otsuka Pharmaceutical Co., Ltd.; and Alexion Inc., Daniel Aletaha Speakers bureau: AbbVie; Amgen; Celgene; Eli Lilly; Medac; Merck; Novartis; Pfizer; Roche; Sandoz; and Sanofi/Genzyme; Bristol-Myers Squibb, Merck Sharp & Dohme, and UCB, Consultant of: Janssen; AbbVie; Amgen; Celgene; Eli Lilly; Medac; Merck; Novartis; Pfizer; Roche; Sandoz; and Sanofi/Genzyme, Grant/research support from: AbbVie, Merck Sharp & Dohme, Novartis, and Roche, Robert B.M. Landewé Paid instructor for: AbbVie, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Galapagos NV, Novartis, Pfizer, and UCB, Consultant of: AbbVie, AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Galapagos NV, Novartis, Pfizer, and UCB, Beatrix Bartok Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Zhaoyu Yin Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Ling Han Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Kahaku Emoto Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences K.K., Shungo Kano Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences K.K., Vijay Rajendran Employee of: Galapagos BV, Tsutomu Takeuchi Speakers bureau: AbbVie, Ayumi Pharmaceutical Corporation, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Dainippon Sumitomo Eisai, Eli Lilly Japan, Mitsubishi-Tanabe, Novartis, Pfizer Japan, Sanofi, and Gilead Sciences, Inc., Consultant of: Astellas, Chugai, and Eli Lilly Japan, Grant/research support from: AbbVie, Asahi Kasei, Astellas, Chugai, Daiichi Sankyo, Eisai, Mitsubishi-Tanabe, Shionogi, Takeda, and UCB Japan

OP0255 BIMEKIZUMAB IN PATIENTS WITH ACTIVE PSORIATIC ARTHRITIS AND AN INADEQUATE RESPONSE TO TUMOUR NECROSIS FACTOR INHIBITORS: 16-WEEK EFFICACY & SAFETY FROM BE COMPLETE, A PHASE 3, MULTICENTRE, RANDOMISED PLACEBO-CONTROLLED STUDY

Background

Bimekizumab (BKZ) is a monoclonal IgG1 antibody that selectively inhibits IL-17F in addition to IL-17A. BKZ has shown sustained efficacy and tolerability up to 152 wks in a phase 2b study in patients (pts) with active psoriatic arthritis (PsA).1,2

Objectives

To assess efficacy and safety of BKZ vs placebo (PBO) in pts with active PsA and prior inadequate tumour necrosis factor inhibitor (TNFi) response in the 16-wk pivotal phase 3 study, BE COMPLETE.

Methods

BE COMPLETE (NCT03896581) comprises a 16-wk double-blind, PBO-controlled period. Pts were aged ≥18 yrs, had a diagnosis of adult-onset, active PsA with ≥3 tender joints and ≥3 swollen joints, and inadequate response or intolerance to treatment with 1 or 2 TNFi. Pts were randomised 2:1 to BKZ 160 mg Q4W or PBO. From Wk 16, pts were eligible to enter an open-label extension, receiving BKZ 160 mg Q4W. The primary endpoint was a ≥50% improvement in American College of Rheumatology response criteria (ACR50) at Wk 16. Primary and ranked secondary efficacy endpoints were assessed at Wk 16.

Results

Of 400 randomised pts (BKZ: 267; PBO: 133), 388 (97.0%) completed Wk 16 (BKZ: 263 [98.5%]; PBO: 125 [94.0%]). Baseline characteristics were comparable between groups: mean age 50.5 yrs, weight 86.0 kg, BMI 29.8 kg/m2, time since diagnosis 9.5 yrs; 47.5% pts were male.

At Wk 16, the primary endpoint (ACR50: 43.4% BKZ vs 6.8% PBO; p<0.001; Figure 1) and all ranked secondary endpoints (HAQ-DI CfB, PASI90, SF-36 PCS CfB and MDA response) were met (all p<0.001; Table 1). The ACR50 response was rapid with separation from PBO observed from Wk 4 (nominal p<0.001). Additional outcomes, including ACR20/70, TJC and SJC CfB, and PASI75/100, demonstrated numerical improvement with BKZ compared to PBO at Wk 16 (all nominal p<0.001; Table 1).

Table 1.

Disease characteristics at baseline and efficacy at Wk 16

PBO N=133BKZ 160 mg Q4W N=267p valueBaseline characteristicsTJCmean (SD)19.3 (14.2)18.4 (13.5)-SJCmean (SD)10.3 (8.2)9.7 (7.5)-PtGA-PsAmean (SD)63.0 (22.0)60.5 (22.5)-PtAAPmean (SD)61.7 (24.6)58.3 (24.2)-Psoriasis BSAn (%)<3%45 (33.8)91 (34.1)-≥3 to ≤10%63 (47.4)109 (40.8)->10%25 (18.8)67 (25.1)-PASIamean (SD)8.5 (6.6)b10.1 (9.1)c-Prior TNFin (%)Inadequate response to 1 TNFi103 (77.4)204 (76.4)-Inadequate response to 2 TNFi15 (11.3)29 (10.9)-Intolerance to TNFi15 (11.3)34 (12.7)-Current cDMARDsn (%)63 (47.4)139 (52.1)-Ranked endpoints in hierarchical orderACR50* [NRI] n (%)9 (6.8)116 (43.4)<0.001HAQ-DI CfB† [RBMI] mean (SE)–0.1 (0.0)–0.4 (0.0)<0.001PASI90†a [NRI]n (%)6 (6.8)b121 (68.8)c<0.001SF-36 PCS CfB† [RBMI]mean (SE)1.4 (0.7)7.3 (0.5)<0.001MDA Response† [NRI]n (%)8 (6.0)118 (44.2)<0.001Other endpointsACR20† [NRI]n (%)21 (15.8)179 (67.0)<0.001‡ACR70† [NRI] n (%)1 (0.8)71 (26.6)<0.001‡TJC CfB [MI] mean (SE)–2.4 (0.9)–10.9 (0.8)<0.001‡SJC CfB [MI] mean (SE)–2.0 (0.5)–7.0 (0.4)<0.001‡PASI75a [NRI]n (%)9 (10.2)b145 (82.4)c<0.001‡PASI100a [NRI]n (%)4 (4.5)b103 (58.5)c<0.001‡

Randomised set (N=400). *Primary endpoint; †Secondary endpoint; ‡Nominal p value. aIn patients with ≥3% BSA with PSO at BL; bn=88; cn=176.

Over 16 wks, 107/267 (40.1%) pts on BKZ had ≥1 TEAE vs 44/132 (33.3%) pts on PBO; the three most frequent TEAEs on BKZ were nasopharyngitis (BKZ: 3.7%; PBO: 0.8%), oral candidiasis (BKZ: 2.6%; PBO: 0%) and upper respiratory tract infection (BKZ: 2.2%; PBO: 1.5%). Incidence of SAEs was low (BKZ: 1.9%; PBO: 0%); none led to discontinuation. 2 pts on BKZ discontinued due to a TEAE (BKZ: 0.7%; PBO: 0%). No systemic candidiasis, cases of IBD, MACE, uveitis, VTE or deaths were reported.

Conclusion

Dual inhibition of IL-17A and IL-17F with BKZ in pts with active PsA and prior inadequate TNFi response resulted in rapid, clinically relevant and statistically significant improvements in efficacy outcomes vs PBO. No new safety signals were observed.1,2

References

[1]Ritchlin C.T. Lancet 2020;395(10222):427–40; 2. Coates L.C. Ann Rheum Dis 2021;80:779–80(POS1022).

Acknowledgements

This study was funded by UCB Pharma. Editorial services were provided by Costello Medical.

Disclosure of Interests

Joseph F. Merola Paid instructor for: Amgen, Abbvie, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma and UCB Pharma, Consultant of: Amgen, Abbvie, Biogen, BMS, Dermavant, Eli Lilly, Janssen, Leo Pharma, Novartis, Pfizer, Regeneron, Sanofi, Sun Pharma and UCB Pharma, Iain McInnes Consultant of: AbbVie, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, Janssen, Novartis, and UCB Pharma, Grant/research support from: BMS, Boehringer Ingelheim, Celgene, Janssen, UCB Pharma, Christopher T. Ritchlin Consultant of: Amgen, AbbVie, Eli Lilly, Gilead, Janssen, Novartis, Pfizer and UCB Pharma, Grant/research support from: AbbVie, Amgen and UCB Pharma, Philip J Mease Speakers bureau: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer and UCB Pharma, Consultant of: AbbVie, Amgen, BMS, Boehringer Ingelheim, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma, Grant/research support from: AbbVie, Amgen, BMS, Eli Lilly, Gilead, Janssen, Novartis, Pfizer, Sun Pharma and UCB Pharma, Robert B.M. Landewé Speakers bureau: Abbott, Amgen, BMS, Centocor, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Consultant of: Abbott, Ablynx, Amgen, AstraZeneca, BMS, Centocor, GSK, Novartis, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Grant/research support from: Abbott, Amgen, Centocor, Novartis, Pfizer, Roche, Schering-Plough, UCB Pharma, and Wyeth, Akihiko Asahina Grant/research support from: AbbVie, Amgen, Eisai, Eli Lilly, Janssen, Kyowa Kirin, LEO Pharma, Maruho, Mitsubishi Tanabe Pharma, Pfizer, Sun Pharma, Taiho Pharma, Torii Pharmaceutical, and UCB Pharma, Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer-Ingelheim, Chugai, Eisai, Eli Lilly, Gilead, Mitsubishi-Tanabe, and YL Biologics, Consultant of: AbbVie, Ayumi, Daiichi-Sankyo, Eli Lilly, GSK, Sanofi, and Taisho, Grant/research support from: Asahi-Kasei, AbbVie, Boehringer-Ingelheim, Chugai, Corrona, Daiichi-Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda, Richard B. Warren Paid instructor for: Astellas, DiCE, GSK, and Union, Consultant of: AbbVie, Almirall, Amgen, Arena, Astellas, Avillion, Biogen, BMS, Boehringer Ingelheim, Celgene, Eli Lilly, GSK, Janssen, LEO Pharma, Novartis, Pfizer, Sanofi, and UCB Pharma, Grant/research support from: AbbVie, Almirall, Janssen, LEO Pharma, Novartis, and UCB Pharma, Laure Gossec Consultant of: AbbVie, Amgen, BMS, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, and UCB Pharma, Grant/research support from: Amgen, Galapagos, Lilly, Pfizer, and Sandoz, Dafna D Gladman Consultant of: AbbVie, Amgen, BMS, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, and UCB Pharma, Frank Behrens Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Chugai, Eli Lilly, Genzyme, Janssen, MSD, Novartis, Pfizer, Roche, and Sanofi, Barbara Ink Shareholder of: GSK, UCB Pharma, Employee of: UCB Pharma, Deepak Assudani Shareholder of: UCB Pharma, Employee of: UCB Pharma, Rajan Bajracharya Shareholder of: UCB Pharma, Employee of: UCB Pharma, Jason Coarse Shareholder of: UCB Pharma, Employee of: UCB Pharma, Laura Coates Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer, and UCB Pharma, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, BMS, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer, and UCB Pharma, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, and UCB Pharma

OP0017 RECAPTURE RATES WITH IXEKIZUMAB AFTER WITHDRAWAL OF THERAPY IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS: RESULTS AT WEEK 104 FROM A RANDOMIZED PLACEBO-CONTROLLED WITHDRAWAL STUDY

Background

COAST-Y is the first study to evaluate the effect of continuing vs withdrawing an IL-17A antagonist, Ixekizumab (IXE) on the maintenance of disease control in patients (pts) with ankylosing spondylitis and non-radiographic axial spondyloarthritis through 104 Weeks (wks).

Objectives

Here, we describe the final results of pts re-randomized to either placebo (PBO; IXE Withdrawal) or IXE, who experienced flare, and recaptured response before or after open label retreatment during COAST-Y.

Methods

COAST-Y (NCT03129100) is a Phase 3, long-term extension study that included a double-blind, PBO-controlled, randomized withdrawal-retreatment period (RWP). Eligible pts who completed an originating study (COAST-V, -W, or -X) entered a 24-Week (Wk) lead-in period and received 80 mg IXE every 2 (Q2W) or 4 wks (Q4W) (the treatment regimen at the end of the originating study); pts receiving PBO at the end of COAST-X were assigned to IXE Q4W in COAST-Y. Pts who achieved remission (Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3 (inactive disease; ID) at least once at Wk 16 or 20, and <2.1 (low disease activity; LDA) at both visits) were randomized 2:1 at Wk 24 to continue IXE (as per lead-in period) or withdrawn to PBO. Pts who subsequently experienced flare (ASDAS ≥2.1 at 2 consecutive visits or ASDAS >3.5 at any visit) were switched to open label IXE Q2W or Q4W at the next visit (same as lead-in period). Time to first flare was analyzed using the Kaplan-Meier method with treatment comparison performed using log-rank test. The observed proportion of pts who recaptured ASDAS LDA and ID were summarized for pts who experienced flare and were retreated with open label IXE.

Results

A total of 155 pts met the criteria for remission and entered the RWP (PBO [IXE withdrawal], N=53; IXE Q4W, N=48; IXE Q2W, N=54) and 138 completed Wk 104. At Wk 104, significantly more pts in the combined IXE group (75.5%, p<0.001, IXE Q4W: 75.0%, p<0.001; IXE Q2W: 75.9%, p<0.001) remained flare free through Wk 104 vs PBO (Figure 1). Notably, 35.8% of pts on PBO (IXE Withdrawal) never experienced flare. Of the PBO pts who experienced flare and were retreated during Wk 24-104 (N=28), 4 recaptured LDA before switching to open label IXE retreatment, while 23 recaptured LDA and 19 met ID after switching (Table 1). Of the continuously treated IXE pts (N=13), 7 recaptured LDA before switching to open label IXE retreatment, while 5 recaptured LDA and 4 met ID after.

Figure 1.

The proportion (%) of patients who remained flare free through 104 weeks. ‡p<0.001, †p<0.01, *p<0.05 vs PBO (IXE Withdrawal).

Table 1.

Recapture of first treatment response before or after switching to open label IXE through 104 weeks among placebo (ixekizumab withdrawal)-treated patients who experienced a flare and retreated

Total patients who flared and were switched to open-label ixekizumab retreatmentPlacebo (ixekizumab withdrawal)(N=28)ASDAS disease activity statusLDAIDRecaptured response before open label ixekizumab retreatment41Recaptured response with open label ixekizumab retreatment (≤16 weeks)2314Recaptured response with open label ixekizumab retreatment (>16 weeks)05Total patients who recaptured response at week 10427/28 (96%)20/28 (71%)

Data are presented as n, (%) for the total row and n only for all other rows. In each column, the denominator is 28. ASDAS, Ankylosing Spondylitis Disease Activity Score; ID, inactive disease; LDA, low disease activity including ID; N, number of patients in the analysis population.

Conclusion

Pts continuously treated with IXE were less likely to experience flare vs pts on PBO (IXE withdrawal). The vast majority of pts withdrawn from IXE to PBO recaptured at least LDA and over half met ID with IXE retreatment. This may provide support for pts who require interruption in therapy.

Acknowledgements

This study was sponsored by Eli Lilly and Company. Medical writing services were provided by Edel Hughes, PhD and Sumeet Sood, PhD of Eli Lilly and Company, and was funded by Eli Lilly and Company.

Disclosure of Interests

Robert B.M. Landewé Consultant of: Rheumatology Consultancy BV, AbbVie, UCB, Pfizer, Eli Lilly and Company, Novartis, and Celgene, Denis Poddubnyy Speakers bureau: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, and UCB Pharma, Consultant of: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, and UCB Pharma, Grant/research support from: AbbVie, Eli Lilly and Company, Merck Sharp & Dohme, Novartis, and Pfizer, Proton Rahman Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, and UCB, Rebecca Bolce Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Soyi Liu Leage Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Jeffrey Lisse Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Ann Leung: None declared, So Young Park Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Lianne S. Gensler Consultant of: AbbVie, Eli Lilly and Company, Grant/research support from: Novartis, Pfizer, and UCB.

OP0035 WHAT EXPLAINS THE WORLDWIDE GRADIENT OF AGE AT ONSET OF RHEUMATOID ARTHRITIS ALONG LATITUDE? A MULTILEVEL ANALYSIS IN THE METEOR REGISTRY

Background

It has been suggested that rheumatoid arthritis (RA) starts at a younger age in cities with a lower latitude (closer to both sides of the equator). This consistent finding still remains to be explained. It has been hypothesized that latitude is a proxy for presence of genetic (eg. ACPA) and environmental risk factors (eg. smoking) for RA onset.

Objectives

To study how age at RA onset varies with latitude worldwide and to what extent patient and country level factors explain this variability.

Methods

RA patients from the worldwide METEOR registry were included. Age at diagnosis as a proxy for age at RA onset, measured at the patient level, was the main outcome. The explanatory variable was the absolute value of latitude, measured as the latitude of the hospital (hospital level). Patient factors considered potentially relevant were gender, RF and ACPA positivity, smoking status, symptom duration (months), year of first visit and BMI (all patient level). Country level factors were socioeconomic indicators (physician density, health expenditure, life expectancy, GDP per capita and gross enrolment in secondary school), derived from country statistics. We hypothesized that both patient and country level factors explain (ie. mediate) a relationship between latitude and age at diagnosis (Figure 1).

We applied Bayesian multilevel linear structural equations models, which not only quantify effects at multiple levels but also disentangle at which level the effects take place. For example, they can differentiate whether hospital or country latitude affects age at diagnosis.

We examined: 1. the total effect of latitude on age at diagnosis at hospital and country level (Main model); 2. the amount of the total effect that is mediated by patient factors at the patient and hospital level (Model A); and 3. the amount of the total effect that is mediated by country factors at the country level (Model B). In each model we disentangle the effect in different measurement levels. For example, a patient level variable can vary at the patient, hospital and country level.

Results

We included 39 782 patients nested in 94 hospitals nested in 17 countries. The mean age at diagnosis per country ranged from 39 to 55 years. The study spanned a range of latitude between 9.9 and 55.8 degrees (ie. from Nigeria to the United Kingdom). In the main model, we confirmed the association between latitude and age at diagnosis and found that it only occurred at the country level (not at the hospital level). Per degree increase in country latitude, the average age at diagnosis per country increased by 0.23 years (95% credibility interval 0.07; 0.40). At the hospital level however, this effect was negligible: β= 0.040 (-0.16; 0.31). Associations between latitude and several patient factors were found at the country level, but these patient factors only associated with age at diagnosis at the patient level, not at the country (or hospital) level (Model A). This means patient-factors did not explain the association between latitude and age at diagnosis at the country level (main effect changed from 0.23 before to 0.37 after inclusion of patient factors). In model B latitude associated with most country factors (except GDP per capita). Even though none of these variables separately were significantly associated with age at diagnosis, inclusion of the set of country level factors reduced the country level effect of latitude on age at diagnosis from 0.23 to almost zero: β=-0.033 (-0.51; 0.37). Sensitivity analyses with age at symptom onset as outcome provided similar results.

Conclusion

Patients living close at the equator indeed get RA far earlier than those living closer to the poles. We here suggest that, rather than due to variation in patients’ characteristics, this latitude gradient is a country level phenomenon explained by indicators of countries’ socioeconomic status, and not by patient specific genetic or environmental factors. This big data analysis in a worldwide prevalence cohort provides a direct link between countries’ levels of welfare and the onset of RA.

Disclosure of Interests

Sytske Anne Bergstra Grant/research support from: Pfizer, Alexandre Sepriano Speakers bureau: Novartis, Consultant of: UCB, Arvind Chopra: None declared, Lai-Ling Winchow: None declared, David Vega-Morales: None declared, Karen Solomon-Escoto: None declared, Xanthe Matthijssen: None declared, Robert B.M. Landewé Shareholder of: Director of Rheumatology Consultancy BV, Consultant of: Honoraria from AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Eli-Lilly, Novartis, Pfizer, UCB Pharma.

Disease activity scores in non-radiographic axial spondyloarthritis

We would like to thank our colleagues for their comments on our paper "Is treatment with suspected non-radiographic axial spondyloarthritis effective? Six-month results of a placebo-controlled trial with etanercept".

POS0032 SCORING MRI STRUCTURAL LESIONS IN SACROILIAC JOINTS OF PATIENTS WITH AXIAL SPONDYLOARTHRITIS: HOW MANY SLICES ARE OPTIMAL?

Background:

There is no international consensus on the optimal number of slices for evaluation of MRI structural lesions in the SIJ. An “all slice” method evaluates lesions from the most anterior slice, defined as the first slice with vertical height of ≥1cm of the SIJ joint cavity, up to the most posterior slice, defined as the most posterior slice where ≥1cm vertical height of the cartilaginous portion is still visible. The SPARCC method scores the transitional slice between cartilaginous and ligamentous compartments as the first slice and then an additional 4 slices anterior to the transitional slice.

Objectives:

We aimed to investigate inter-reader reliability, the extent of detection of lesions, and frequency of cases with a positive MRI for structural lesions when using an “all slice” approach versus the SPARCC scoring of 5 central slices.

Methods:

MRI T1W images with DICOM series were available from 148 cases who had MRI performed in the ASAS-Classification Cohort. Seven central readers recorded MRI lesions in an eCRF that recorded global assessments of presence/absence of changes suggestive of axSpA and structural lesions typical of axSpA. Structural lesions per the ASAS definitions were also recorded in consecutive semicoronal slices using the “all slice” approach, but also recording the transitional slice, according to their presence/absence in SIJ quadrants (erosion, fat lesion, sclerosis) or halves (backfill, ankylosis). Structural lesion frequencies were assessed descriptively according to majority agreement (≥4/7) of central readers and also any 2 central readers. Reliability for detection of MRI lesions was compared between central and local readers using the ICC.

Results:

The mean (SD) (range) number of anterior and posterior slices peripheral to the 5 central slices was 1.0 (1.0) (0-4) and 2.2 (1.8) (0-6) per case, respectively. There were 2 cases (1.4%) where ≥2 readers scored structural lesions in peripheral slices but not in the 5 central slices. The mean percentage of the total structural lesion score that was captured by the 5 central slices was >75% for all types of lesions except ankylosis (59%) (Table 1). Inter-reader reliability was greater for all lesions when assessing the 5 central slices and especially for erosion and backfill (Table 1).

Conclusion:

The major component of structural lesion data is captured by assessment of 5 slices, which includes the transitional slice and the subsequent 4 anterior slices. Moreover, reliability for detection of structural lesions is substantially worse in peripheral slices.

MRI Lesion“All slice”Central 5 slicesPeripheral slicesP value central vs peripheral slicesP value“all slice” vs central slicesMean (SD) Lesion Score Per CaseErosion2.4 (4.5) (0-22.9)1.8(3.4) (0-17.1)0.6 (1.4) (0-10.1)<0.001< 0.001Fat lesion2.5 (5.9) (0-34.0)1.8 (4.5) (0-25.1)0.7 (1.8) (0-9.9)< 0.001<0.001Sclerosis2.0 (4.9) (0-39.0)1.5 (3.6) (0-26.1)0.5 (1.5) (0-12.9)< 0.001<0.001Backfill0.5 (1.5) (0-12)0.4 (1.2) (0.0-9.3)0.1 (0.4) (0-2.7)< 0.0010.84Ankylosis0.5 (3.4) (0-30.7)0.3 (2.3) (0-20.0)0.2 (1.2) (0-11.3)0.100.18Mean (SD) (Range) % of Total Lesion Score in Central vs Peripheral slicesErosion100%76.4% (28.9%) (0-100%)23.6% (28.9%) (0-100%)<0.001NAFat lesion100%75.4% (26.5%) (0-100%)24.6% (26.5%) (0-100%)<0.001NASclerosis100%79.5% (22.9%) (0-100%)20.5% (22.9%) (0-100%)<0.001NABackfill100%86.0% (20.2%) (0-100%)14.0% (20.2%)(0-100%)<0.001NAAnkylosis100%59.0% (36.4%) (0-100%)41.0% (36.4%) (0-100%)0.56NAICC of 7 readers (Mean (SD) (Range))MRI lesionAll slicesCentral 5 slicesPeripheral slicesErosion0.54 (0.15) (0.28-0.84)0.58 (0.13) (0.34-0.85)0.40 (0.17) (0.10-0.66)Fat lesion0.61 (0.18) (0.30-0.89)0.63 (0.16) (0.35-0.88)0.52 (0.20) (0.19-0.82)Sclerosis0.73 (0.18) (0.36-0.94)0.73 (0.16) (0.36-0.91)0.67 (0.19) (0.27-0.94)Backfill0.37 (0.21) (0.10-0.85)0.39 (0.19) (0.14-0.83)0.18 (0.23) (0.0-0.80)Ankylosis0.97 (0.02) (0.91-0.99)0.99 (0.01) (0.97-1.0)0.85 (0.10) (0.62-0.98)

Disclosure of Interests:

None declared.

OP0141 EFFECTS OF FILGOTINIB ON SPINAL LESIONS IN ANKYLOSING SPONDYLITIS: MAGNETIC RESONANCE IMAGING DATA FROM THE TORTUGA TRIAL

Background:

The oral Janus kinase 1 preferential inhibitor filgotinib (FIL) significantly improved Spondyloarthritis Research Consortium of Canada (SPARCC) magnetic resonance imaging (MRI) inflammation scores (bone marrow oedema) in the spine and sacroiliac joints vs placebo (PBO) in the Phase 2 TORTUGA trial (NCT03117270) in patients with active ankylosing spondylitis (AS).1

Objectives:

This post-hoc analysis evaluated the effects of FIL on Canada-Denmark (CANDEN) MRI measures of spinal inflammation and structural lesions in patients from the TORTUGA trial.

Methods:

TORTUGA was a PBO-controlled, multicentre, double-blind, randomised trial. Patients with active AS (as per modified New York classification criteria, with sacroiliitis confirmed by central reading) were treated with FIL 200 mg (n=58) or PBO (n=58) once daily for 12 weeks. MRI of the total spine was conducted at baseline and at treatment end. Scans were re-evaluated post-hoc by 2 independent experts (blinded to time point and assigned treatment) using the CANDEN method;2 inter-reader discrepancies were resolved by an independent adjudicator. Observed changes from baseline were evaluated using analysis of covariance, with factors for treatment, baseline value, and randomisation stratification by prior tumour necrosis factor inhibitor use. Least-squares (LS) mean changes from baseline and between-group differences with 95% confidence intervals (CI) were calculated; P values are nominal.

Results:

MRI scans from 88 patients (47 FIL, 41 PBO) with an evaluable scan at baseline and Week 12 (or early termination) were re-evaluated. Baseline characteristics were generally similar between patients with/without an MRI scan. Of those with MRI scans, mean total spine inflammation score (which ranges from 0–614) was higher, and mean ankylosis score (which ranges from 0–460) was lower, in the FIL vs PBO group at baseline. Total spine inflammation scores decreased from baseline with FIL but not with PBO (Figure and Table; P=0.0003 for between-group difference). Cumulative probability plots favoured FIL over PBO for change from baseline in subregion inflammation scores, including posterolateral elements (i.e. sum of lesions in ribs, transverse processes, spinous processes, soft tissue inflammation, and postero-lateral vertebral body), facet joint, and vertebral body. Total spine fat lesion scores numerically increased from baseline in the FIL but not PBO group (P=0.0878 for between-group difference; Table). There were no significant differences between groups for changes in erosion (P=0.1956) or ankylosis (P=0.3888) scores (Table).

Table 1.

Change from baseline at Week 12 in CANDEN total spine inflammation, total spine fat, total spine bone erosion, and ankylosis scores

Treatment groupnSample mean (SE)LS mean (SE)95% CI of treatment meanLS mean of group difference (SE)95% CI of group differenceBetween-group P valueTotal spine inflammation scoreFilgotinib47–4.98 (0.96)–4.40 (1.13)–6.65, –2.15–4.49 (1.21)–6.85, –2.120.0003Placebo410.29 (0.78)0.09 (1.13)–2.17, 2.34Total spine fat scoreFilgotinib471.01 (0.62)1.09 (0.66)–0.22, 2.401.18 (0.69)–0.18, 2.550.0878Placebo41–0.25 (0.19)–0.09 (0.66)–1.40, 1.21Total spine bone erosion scoreFilgotinib470.01 (0.02)0.07 (0.03)0.00, 0.140.05 (0.04)–0.02, 0.120.1956Placebo41–0.02 (0.03)0.02 (0.03)–0.04, 0.09Total ankylosis scoreFilgotinib470.30 (0.29)0.23 (0.31)–0.40, 0.850.28 (0.34)–0.37, 0.940.3888Placebo41–0.01 (0.08)–0.06 (0.31)–0.68, 0.56

SE, standard error

Conclusion:

This is the first PBO-controlled trial to demonstrate a decrease in inflammatory activity with FIL, not only in the spinal vertebrae but also in the postero-lateral elements of the spine and facet joints. As expected in a 12-week study period, no changes in erosion or ankylosis were seen, while fat lesions showed a tendency to increase with FIL. Larger trials are needed to confirm these results.

References:

[1]van der Heijde D, et al. Lancet 2018;392:2378–87.

[2]Krabbe S, et al. RMD Open 2019;5:e001057.

Acknowledgements:

The TORTUGA trial was sponsored by Galapagos NV (Mechelen, Belgium) and co-funded by Galapagos NV and Gilead Sciences, Inc. (Foster City, CA, USA). Medical writing support was provided by Debbie Sherwood BSc, CMPP (Aspire Scientific Ltd, Bollington, UK), and funded by Galapagos NV.

Disclosure of Interests:

Xenofon Baraliakos Consultant of: AbbVie, Bristol Myers Squibb, Celgene, Chugai, Eli Lilly, Galapagos, Hexal, Janssen, MSD, Novartis, Pfizer, Sandoz and UCB, Grant/research support from: AbbVie, Celgene, Novartis and UCB, Mikkel Østergaard Speakers bureau: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Orion, Pfizer, Roche, Sandoz, Sanofi and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Merck and Novartis, Robert B.M. Landewé Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Janssen (formerly Centocor), Merck, Pfizer, Roche, Schering and UCB, Consultant of: AbbVie, Ablynx, Amgen, AstraZeneca, Bristol Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, GlaxoSmithKline, Janssen, Merck, Novartis, Novo Nordisk, Pfizer, Roche, Schering, TiGenix and UCB, Grant/research support from: AbbVie, Amgen, Janssen (formerly Centocor), Novartis, Pfizer, Roche, Schering and UCB, Employee of: Director of Rheumatology Consultancy BV, William Barchuk Shareholder of: Gilead Sciences, Inc., Employee of: Currently employee of Gilead Sciences, Inc.; and former employee of AbbVie, Eli Lilly and Johnson & Johnson, Ke Liu Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Chantal Tasset Shareholder of: Galapagos, Employee of: Galapagos, Leen Gilles Employee of: Galapagos, Thijs Hendrikx Shareholder of: Galapagos, Employee of: Galapagos, Robin Besuyen Shareholder of: Galapagos, Employee of: Galapagos, Walter P Maksymowych Speakers bureau: AbbVie, Janssen, Novartis, Pfizer and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer and UCB, Grant/research support from: AbbVie, Novartis, Pfizer and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited

POS0033 IN RADIOGRAPHIC AXIAL SPONDYLOARTHRITIS, BRIDGING SYNDESMOPHYTES INCREASE RISK OF FACET JOINT ANKYLOSIS ON THE SAME VERTEBRAL LEVEL WHILE FACET JOINT ANKYLOSIS DOES NOT INCREASE RISK OF SAME LEVEL SYNDESMOPHYTES

Background:

In radiographic axial spondyloarthritis (r-axSpA), spinal damage manifests as syndesmophytes and facet joint ankylosis (FJA).

Objectives:

Explore whether syndesmophytes and FJA seem to have a preferential order of development.

Methods:

Data were used from the Sensitive Imaging in Ankylosing Spondylitis cohort from Leiden and Herne. Patients underwent low-dose Computed Tomography (ldCT) at baseline and two-years. LdCT images were scored independently by two trained readers. Vertebrae were scored according to the Computed Tomography Syndesmophyte Score (CTSS) for presence and size of syndesmophytes; facet joints were scored as not-ankylosed and ankylosed. Analyses were performed on the vertebral unit (VU) level and using individual-reader data (Figure 1). Two hypotheses were tested: 1) presence of bridging syndesmophyte(s) is associated with FJA on the same VU two years later, and 2) presence of FJA is associated with syndesmophyte(s) on the same VU two years later. Generalized Estimating Equations (GEE) models were used to take into account the correlations between VUs from the same patient and adjusting for reader to account for individual reader scores. Two models were tested per hypothesis using different outcomes. Model 1 uses the presence of syndesmophytes or FJA as outcome adjusting for the outcome at baseline. Model 2 uses development of new syndesmophytes or FJA at two years plus an increase in the number of syndesmophytes or FJA.

Results:

In total, 50 patients were included (mean age 49, 84% male, 82% HLA-B27+). At baseline, there was a higher percentage of bridging syndesmophytes (range: 10-60%) than FJA (range: 8-36%) considering all VUs and both readers (Figure 1). In both models, presence of bridging syndesmophytes was associated with development of FJA two years later (OR (95%CI) Model 1: 3.35 (2.18-5.14); Model 2: 2.23 (1.19-4.16)) while presence of FJA at baseline did not have a statistically significant association with development of syndesmophytes two years later (Table 1).

Conclusion:

The data showed a higher occurrence of bridging syndesmophytes than FJA at baseline and showed significantly increased odds to develop FJA when bridging syndesmophyte(s) are present on the same VU two years prior. This mechanism did not hold true for the other direction. These results cautiously imply that bridging syndesmophytes precede FJA, rather than FJA preceding syndesmophytes.

Figure 1.

Percentage of occurrence of syndesmophytes and facet joint ankylosis per vertebral unit and per reader at baseline.

Figure 1 displaying percentages of patients with a bridging syndesmophyte and with facet joint ankylosis at baseline, per reader. The image on the left illustrates the vertebral unit level (VU) at which analyses were performed. Seven VUs are illustrated in dashed boxes as example. Synd, syndesmophyte; FJA, facet joint ankylosis; BL, baseline.

Table 1.

Associations between facet joint ankylosis and syndesmophytes

Model 1: development of new FJA/syndesmophytes at FUOR (95% CI)Model 2: development and/or increase FJA/syndesmophytes at FUOR (95% CI)Hypothesis 1Presence bridging syndesmophytes at BL on development of FJA at FU3.35 (2.18-5.14)2.23 (1.19-4.16)Hypothesis 2Presence FJA at BL on development of syndesmophytes at FU1.60 (0.88-2.91)1.12 (0.76-1.66)

Disclosure of Interests:

None declared.

OP0251 DATA-DRIVEN DEFINITIONS BASED ON INFLAMMATORY LESIONS FOR A POSITIVE MRI OF THE SPINE CONSISTENT WITH AXIAL SPONDYLOARTHRITIS

Background:

The ASAS definition of a positive MRI for inflammation in the spine (ASAS-MRIspine+) is intended for classification of patients as having axSpA but is often misused for diagnostic purposes. This is problematic because bone marrow edema (BME) in the spine may occur in 20-40% of those with mechanical back disorders. The ASAS MRI group has generated updated consensus lesion definitions which have been validated on MRI spine images from the ASAS Classification Cohort.

Objectives:

We aimed to identify quantitative cut-offs based on numbers of vertebral corners that define ASAS-MRIspine+, there being two gold standards: A. majority central reader decision as to the presence of spine MRI findings consistent with axSpA B. rheumatologist expert opinion diagnosis of axSpA.

Methods:

Eight ASAS-MRI readers recorded MRI lesions in the spine according to recently updated ASAS definitions from 62 cases in an eCRF that comprises global assessment (MRI consistent with axSpA? (yes/no)), and detailed scoring of lesions for all sites in the spine. We calculated sensitivity and specificity for numbers of vertebral corners with BME where a majority of readers (≥5/8) agreed as to the presence of MRI findings consistent with axSpA. We selected cut-offs with ≥95% specificity. These cut-offs were analyzed for their predictive utility for rheumatologist diagnosis of axSpA by calculating positive and negative predictive values (PPV, NPV) and selecting cut-offs with PPV ≥95%. Both criteria were considered requirements for designation of MRI cut-offs defining ASAS-MRIspine+.

Results:

MRI findings consistent with axSpA were observed by majority read in 8 (20%) of 40 cases diagnosed with axSpA, and 0 (0%) of 19 cases without axSpA. Cut-offs achieving specificity of ≥95% for MRI findings consistent with axSpA were 4 vertebral corners (sensitivity 75%) for all cases, 3 vertebral corners (sensitivity 37.5%) for cases with ≥1 additional location with inflammation, 1 vertebral corner (sensitivity 62.5%) in cases with ≥2 vertebral corner fat lesions (Table 1). All of the above cut-offs also had very high PPV (≥95%) for diagnosis of axSpA in cases diagnosed by the rheumatologist (Table 2).

Table 1.

Majority readers agree MRI findings consistent with axSpA are present is the gold-standard external reference

MRI cut-offsSensitivity (95%CI)Specificity (95%CI)BME in ≥2 vertebral corners87.5 (47.3 - 99.7)87.0 (75.1 - 94.6)BME in ≥ 3 vertebral corners87.5 (47.3 - 99.7)94.4 (84.6 - 98.8)BME in ≥4 vertebral corners75.0 (34.9 - 96.8)98.2 (90.1 - 100.0)Cases with ≥1 additional non-corner site inflammatory lesionBME in ≥2 vertebral corners37.5 (8.5 - 75.5)94.4 (84.6 - 98.8)BME in ≥3 vertebral corners37.5 (8.5 - 75.5)98.2 (90.1-100.0)Cases with ≥2 vertebral corner fat lesionsBME in ≥1 vertebral corner62.5 (24.5 - 91.5)100.0 (93.4-100.0)BME in ≥2 vertebral corners62.5 (24.5 - 91.5)100.0 (93.4-100.0)Table 2.

Predictive values of cut-offs for number of vertebral corners with BME according to the diagnostic ascertainment of the rheumatologist

MRI cut-offsSensitivity (95%CI)Specificity (95%CI)PPVNPVMRI findings consistent with axSpA ≥any 2 readers52.5 (36.1 - 68.5)94.7 (74.0 - 99.9)95.5 (75.3 - 99.3)48.6 (40.2 - 57.2)MRI findings consistent with axSpA ≥majority read20.0 (9.1 - 35.6)100.0 (82.4 - 100.0)100.037.3 (33.7 - 40.9)BME in ≥ 4 vertebral corners17.5 (7.3 - 32.8100.0 (82.4 - 100.0)100.036.5 (33.3 - 39.9)Cases with ≥1 additional inflammatory lesionBME in ≥ 3 vertebral corners10.00 (2.8 - 23.7)100.00 (82.4 - 100.0)100.034.5 (32.2 - 36.9)Cases with ≥2 vertebral corner fat lesionsBME in ≥1 vertebral corner12.50 (4.2 - 26.8)100.00 (82.4 - 100.0)100.035.2 (32.6 - 37.9)

Conclusion:

A cut-off of BME in ≥4 vertebral corners, or ≥3 corners in the setting of additional inflammatory lesions at other locations or corner fat, are primary candidates for defining ASAS-MRIspine+. These cut-offs apply to typical patients referred to a rheumatologist with a high index of suspicion of axSpA and may not be appropriate in other populations.

Disclosure of Interests:

None declared

OP0250 MRI VERTEBRAL CORNER INFLAMMATION AND FAT DEPOSITION ARE ASSOCIATED WITH WHOLE SPINE LOW DOSE CT DETECTED SYNDESMOPHYTES: A MULTILEVEL ANALYSIS

Background:

A few studies have shown an association between vertebral corner inflammation (VCI) and vertebral corner fat deposition (VCFD) on MRI and syndesmophyte formation on cervical and lumbar conventional radiography.

Objectives:

To investigate whether magnetic resonance imaging (MRI) patterns of VCI, VCFD and a combination of both are associated with the development of new or grown syndesmophytes as detected by whole spine low dose computed tomography (ldCT), thereby studying these associations also in the thoracic spine.

Methods:

Patients in the Sensitive Imaging in Ankylosing Spondylitis cohort underwent MRI at baseline, 1 year and 2 years, and ldCT at baseline and 2 years. MRI lesions were scored by 3 central readers, using the SPARCC method for VCI and the CanDen method for VCFD, and coded as absent or present per timepoint and per reader. MRI patterns over time (Table) were based on patterns studied by Machado et al.1 and deemed present if seen by ≥2 out of 3 readers. The patterns reflect hypothetical associations between presence and absence of VCI and VCFD, independently and combined, on ldCT detected new or grown syndesmophytes. Individual reader change scores were used for ldCT images, scored by 2 central readers with the Computed Tomography Syndesmophyte Score. New (CTSS 0 to 1, 2 or 3) and grown (CTSS 1 to 2 or 3; 2 to 3) syndesmophytes were grouped together to represent bone formation. Corners not at risk for the outcome due to presence of a bridged syndesmophyte at baseline were excluded. Multilevel generalized estimated equations were used, with separate models per MRI pattern, accounting for correlations within patients and between ldCT readers.

Table 1.

Effect of vertebral corner inflammation and vertebral corner fat deposition on syndesmophyte formation

Patterns of lesions over time on MRICorners with VCI/VCFD patternN(%)OR (95% CI)1. VCI at any TP, irrespective of VCFD691 (15.0%)2.37 (1.49-3.78)2. VCFD at any TP, irrespective of VCI1080 (23.5%)2.58 (1.97-3.39)3. VCI on ≥1 TP and absence of VCFD on all TPs372 (8.1%)1.90 (1.15-3.13)4. VCFD on ≥1 TP and absence of VCI on all TPs754 (16.4%)1.87 (1.41-2.48)5. VCI precedes VCFD43 (0.9%)2.20 (0.83-5.86)6. VCI precedes or coincides with VCFD. VCFD does not precede VCI198 (4.3%)2.33 (1.47-3.69)7. Absence of VCI and VCFD on all TPs3108 (67.6%)0.35 (0.25-0.49)

VCI, vertebral corner inflammation; VCFD, vertebral corner fat deposition; TP, timepoint.

Results:

50 patients were included, contributing a total of 4600 vertebral corners. Their mean age was 49.3 years (SD 9.8), 86% were male and 78% were HLA-B27+. Presence of VCI and VCFD patterns ranged from 43 (0.9%) to 3108 (67.6%) corners (Table), with the lowest frequency being for VCI preceding VCFD. Protection against syndesmophyte development was seen in case of absence of both VCI and VCFD (OR 0.35) and positive associations with ORs ranging from 1.87-2.58 were observed for various VCI/VCFD patterns. Nevertheless, out of all corners with a new or grown syndesmophyte, 47.3% of corners according to reader 1 and 43.9% according to reader 2 had neither VCI nor VCFD preceding the bone formation.

Conclusion:

Presence of VCI or VCFD and combinations of the two, measured yearly on MRI, increased odds of bone formation 2 years later, whereas absence of both VCI and VCFD decreased the odds, showing that VCI and VCFD have some role in the development of syndesmophytes. However, almost half of all bone formation occurred in corners without VCI or VCFD, suggesting the presence of these lesions in yearly MRIs does not fully explain the development of syndesmophytes. This study confirmed that there is an association between VCI and VCFD and bone formation also for the thoracic spine and on ldCT compared to conventional radiography.

References:

[1]Machado et al ARD 2016

Disclosure of Interests:

Rosalinde Stal: None declared, Xenofon Baraliakos: None declared, Alexandre Sepriano: None declared, Floris A. van Gaalen Grant/research support from: Novartis, Sofia Ramiro: None declared, Rosaline van den Berg: None declared, Monique Reijnierse: None declared, Juergen Braun: None declared, Robert B.M. Landewé: None declared, Désirée van der Heijde: None declared

POS0971 HOW DO CLINICAL AND SOCIOECONOMIC FACTORS IMPACT ON WORK DISABILITY IN EARLY AXIAL SPONDYLOARTHRITIS? FIVE-YEAR DATA FROM THE DESIR COHORT

Background:

There remains substantial unmet need to study work disability (WD) in early axSpA. Previous studies suggest that treatment interventions alone do not improve work outcomes and that socioeconomic (SE) as well as clinical factors may play an important role.

Objectives:

To investigate the occurrence of WD and the impact of clinical and SE factors on WD in early axial spondyloarthritis (axSpA).

Methods:

Patients with a clinical diagnosis of axSpA from the DESIR cohort up to 5 years of follow-up (6-month visits in the first 2 years, followed by annual visits) were studied. Time to WD and potential baseline and time-varying predictors were explored, with a focus on SE variables: age, gender, smoking status since last visit, ethnicity (Caucasian vs other), job type based on ‘collar’ (blue vs white), educational status (low vs high -university), marital status (married vs not) and parental status (number of children); and clinical factors: disease activity (ASDAS/BASDAI), function (BASFI), mobility (BASMI), at each time point. The incidence of WD was calculated as the number of WD events over the total number of person-days under observation. Univariable analyses, followed by collinearity and interaction tests, guided subsequent multivariable Cox survival analyses.

Results:

A total of 704 axSpA patients with work-related data, mean (SD) age 33.8 (8.6), were studied. The estimated incidence of WD amongst those at risk and across the five years of DESIR, was 0.05 (95% CI 0.03, 0.06) per 1000 days (total person-days of observation of 999,999). Mean (SD) time to WD was 976 days (SD 476), (min 163, max 2021 days). In people who developed WD, 25% did so at 595 days; 50% and 75% at 1050 and 1433 days, respectively. Significant differences in age, level of education, marital and parental status as well as disease activity, function and mobility, all at baseline, were seen between those developing WD vs those who never did. In multivariable models (Table 1), older age, higher ASDAS and BASFI all strongly predicted more WD (p<0.005). In separate models adjusted for age, gender and education, BASFI and BASMI both predicted WD. SE factors, including education attained, were not associated with a risk for WD. There were no relevant interactions between clinical variables and SE factors.

Table 1.

Univariable and multivariable model analyses with WD as outcome.

Type of analysisUnivariableMultivariable modelFocus on ASDASMultivariable modelFocus on BASFI/BASMIHR (95% CI)HR (95% CI)(N=653)HR (95% CI)(N=639)Explanatory variablesAge1.07 (1.04, 1.11)1.06 (1.02, 1.10)1.03 (0.99, 1.08)Male gender0.68 (0.37, 1.23)1.10 (0.58, 2.08)1.00 (0.50, 2.02)High education0.25 (0.14, 0.48)0.57 (0.29, 1.11)0.42 (0.19, 0.90)Parental status1.36 (1.09, 1.70)NSNSASDAS (CRP)2.40 (1.77, 3.26)1.79 (1.27, 2.54)Not testedBASFI, 0-101.54 (1.36, 1.75)1.42 (1.22, 1.65)1.53 (1.29, 1.81)BASMI, 0-102.13 (1.65, 2.75)NS1.49 (1.10, 2.00)Symptom duration0.79 (0.56, 1.12)NSNSHLA B27 positive0.64 (0.36, 1.13)NSNSHip involvement (baseline) vs not1.98 (1.02, 3.82)NSNSComorbidity count2.33 (1.68, 3.21)NSNSNSAID use last 6m (vs no use)1.01 (1.00, 1.02)NSNSOral Corticosteroid use (vs no)2.72 (1.27, 5.83)NSNScsDMARD use last 6m (vs no)2.20 (0.90, 5.41)NSNSTNFi use2.15 (1.19, 3.87)NSNS

NS=Not significant

Conclusion:

In this early axSpA cohort, WD was an infrequent event. Nevertheless, clinical factors are amongst the strongest predictors of WD, over SE factors, with worse disease activity, function and mobility all independently implicated with more WD in early axSpA. Disease severity remains a strong predictor of adverse work outcome, despite substantial advances in therapeutic strategies in axSpA.

Disclosure of Interests:

None declared.

POS0238 SICK LEAVE AND ITS PREDICTORS IN EARLY AXIAL SPONDYLOARTHRITIS: THE ROLE OF CLINICAL AND SOCIOECONOMIC FACTORS. FIVE-YEAR DATA FROM THE DESIR COHORT

Background:

Sick leave (SL) represents an often poorly studied adverse work outcome especially in early axSpA, with speculation around the potential role of clinical and socioeconomic (SE) factors.

Objectives:

To investigate the occurrence of SL and the impact of clinical and SE factors on SL in early axSpA.

Methods:

Patients with a clinical diagnosis of axSpA from the DESIR cohort up to 5 years of follow-up (6-month visits in the first 2 years, followed by annual visits) were studied. Time to SL and potential baseline and time-varying predictors were explored, with a focus on SE variables: age, gender, smoking status since last visit, ethnicity (Caucasian vs other), job type based on ‘collar’ (blue vs white), educational status (low vs high -university), marital status (married vs not) and parental status (number of children); and clinical factors including disease activity (ASDAS/BASDAI), function (BASFI), mobility (BASMI), at each time point. The incidence of SL was calculated as the number of SL events over the total number of person-days under observation. Univariable analyses, followed by collinearity and interaction tests, guided subsequent multivariable Cox survival model building.

Results:

In total, 704 axSpA patients with work-related data were included in this study: mean (SD) age 33.8 (8.6); 46% male. At baseline, 80% of patients were employed; of these, 5.7% reported being on SL, with people shifting in and out of different work states over time. The distribution of first and recurrent SL episodes over time is shown in the figure 1. The incidence of SL amongst those at risk (n=620, 88%) and across the five years of DESIR was 0.05 (95% CI 0.03, 0.06) per 1000 days calculated in a total of 913,559 observed person-days. In survival analyses, 7% (n=43) of those at risk developed SL at some point. Mean (SD) time to SL was 806 (595) days (min 175, max 2021 days). In people who developed SL, 25% did so at 364 days; 50% and 75% at 545 and 1172 days, respectively. Significant differences were seen between baseline socio-demographic, clinical variables and treatment in patients who developed SL at any point, compared to those who did not. In multivariable models (Table 1) older age, higher disease activity, smoking and use of TNFi, the latter likely a proxy to worse disease, were all significantly associated with more SL. Male gender and higher education were associated with less SL. There were no relevant interactions between SE factors and clinical variables.

Table 1.

Univariable and multivariable model analyses with Sick Leave as outcome.

Type of analysisUnivariable analysisMultivariable modelHR (95% CI)HR (95% CI) (N = 614)Explanatory variablesAge1.04 (1.01, 1.08)1.05 (1.01, 1.09)Male gender0.37 (0.19, 0.74)0.41 (0.20, 0.86)High education0.33 (0.17, 0.61)0.48 (0.24, 0.95)Marital status2.44 (1.12, 5.27)NSASDAS (CRP)1.83 (1.34, 2.50)1.49 (1.04, 2.13)BASFI, 0-101.24 (1.09, 1.40)*BASMI, 0-101.76 (1.31, 2.38)*Comorbidity count1.77 (1.22, 2.57)NSHLA-B27 positive0.51 (0.28, 0.93)NSSmoking (current vs not)2.40 (1.31, 4.37)2.55 (1.32, 4.91)NSAID score last week, 0-4001.01 (1.00, 1.01)NSOral Corticosteroid use (vs no)3.90 (1.80, 8.46)NSTNF use2.86 (1.55, 5.28)2.41 (1.27, 4.58)

*Variables tested in models separate from ASDAS. NS=Not significant in multivariable model.

Figure 1.

Distribution of first and recurrent sick leave episodes over time in the study population at risk.

Conclusion:

In this early axSpA cohort of young, working-age individuals, older age and worse disease activity were associated with more SL, whereas male gender and higher education were associated with less SL. The findings suggest a role of SE factors such as gender and level of education in adverse work outcomes, alongside active disease.

Disclosure of Interests:

None declared

POS0229 DISEASE ACTIVITY AND INFLAMMATION FOLLOWING WITHDRAWAL OF CERTOLIZUMAB PEGOL TREATMENT IN AXIAL SPONDYLOARTHRITIS PATIENTS WHO DID NOT EXPERIENCE FLARES DURING THE C-OPTIMISE STUDY

Background:

C-OPTIMISE was a phase 3b clinical trial investigating certolizumab pegol (CZP) maintenance dose continuation, reduction or withdrawal following achievement of sustained remission in patients with axial spondyloarthritis (axSpA). During the C-OPTIMISE maintenance period, the majority of patients randomised to CZP, either the full or reduced maintenance dose, did not experience disease flares. Conversely, in those who had CZP withdrawn, only a minority of patients remained flare-free.1

Objectives:

This post-hoc analysis evaluates disease activity and clinical markers of inflammation in patients who did not experience a disease flare following randomisation to CZP full maintenance dose, CZP reduced maintenance dose or placebo (PBO) during the maintenance period (Weeks 48–96) of C-OPTIMISE.

Methods:

C-OPTIMISE (NCT02505542) was a multicentre, double-blind, parallel-group, randomised phase 3b study with a 48-week open-label run-in period.1 Adult patients with early (<5 years’ symptom duration) active axSpA received open-label CZP 200 mg every 2 weeks (Q2W) for the first 48 weeks; from Week 48, patients who achieved sustained remission (Ankylosing Spondylitis Disease Activity Score [ASDAS] <1.3 at Week 32 or 36 and Week 48) were randomised 1:1:1 to double-blind CZP 200 mg Q2W (full maintenance dose), CZP 200 mg Q4W (reduced maintenance dose) or PBO for a further 48 weeks (maintenance period). A flare was defined as ASDAS ≥2.1 at two consecutive visits or ASDAS >3.5 at any visit. We report ASDAS, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and C-reactive protein (CRP) and fecal calprotectin levels during Weeks 48–96 in CZP- and PBO-randomised patients who did not experience a flare (i.e. completed Week 96 on randomised treatment). Missing data were imputed using last observation carried forward.

Results:

Of 313 patients entering the maintenance period at Week 48, 197 (62.9%) completed Week 96 on randomised treatment without experiencing a flare; of these, 89 (85.6%) and 84 (80.0%) patients were in the CZP 200 mg Q2W and CZP 200 mg Q4W arm, respectively, with only 24 (23.1%) patients randomised to PBO not experiencing a flare. Baseline characteristics of these patients are shown in the Table 1. During Weeks 48–96, disease activity (ASDAS, BASDAI) and CRP levels were comparable between the CZP full and reduced maintenance dose group, and lower in both CZP arms than in PBO (Figure 1 A–C). From Week 60 up to Week 96, PBO patients who did not flare had consistently higher mean ASDAS, BASDAI and CRP levels compared with CZP-randomised patients (Figure 1 A–C). Similarly, there was a greater increase in fecal calprotectin levels between Weeks 48 and 96 in the PBO arm compared with both CZP arms (Figure 1 D).

Table 1.

Baseline (Week 0) characteristics of patients who did not experience flares during the C-OPTIMISE maintenance period

Placebo (n=24)CZP 200 mg Q4W (n=84)CZP 200 mg Q2W (n=89)Age (years), mean (SD)29.8 (7.4)32.9 (6.7)32.4 (7.2)Male, n (%)19 (79.2)69 (82.1)69 (77.5)Time since diagnosis (years)Mean (SD)2.0 (1.8)2.0 (1.7)2.5 (1.6)Median1.21.22.7Symptom duration (years)Mean (SD)2.7 (1.7)3.4 (1.9)3.9 (2.9)Median2.83.53.9ASDAS, mean (SD)3.4 (0.8)3.7 (0.8)3.7 (0.7)BASDAI, mean (SD)6.3 (1.1)6.6 (1.5)6.4 (1.4)CRP (mg/L), geometric mean6.287.887.35Fecal calprotectin (µg/g), mean (SD)71.8 (111.4)87.1 (110.5)81.0 (120.0)

SD: standard deviation.

Conclusion:

Despite not meeting the threshold for a flare, consistently higher disease activity and increases in serologic and inflammatory biomarkers were observed in PBO-randomised patients who did not experience a flare during the C-OPTIMISE study compared to those who remained on CZP. These findings confirm that patients with axSpA who achieve sustained remission benefit from continued CZP treatment, either with the full or reduced maintenance dose, over treatment withdrawal.

References:

[1]Landewé R. Ann Rheum Dis 2020;79:920–8.

Acknowledgements:

This study was funded by UCB Pharma. Editorial services were provided by Costello Medical.

Disclosure of Interests:

Lianne S. Gensler Consultant of: AbbVie, Eli Lilly, Gilead, GSK, Novartis, Pfizer, UCB Pharma, Grant/research support from: Pfizer, Xenofon Baraliakos Speakers bureau: AbbVie, BMS, Chugai, Eli Lilly, Galapagos, Gilead, Novartis, Merck, Pfizer, UCB Pharma, Paid instructor for: AbbVie, BMS, Chugai, Eli Lilly, Galapagos, Gilead, Novartis, Merck, Pfizer, UCB Pharma, Consultant of: AbbVie, BMS, Chugai, Eli Lilly, Galapagos, Gilead, Novartis, Merck, Pfizer, UCB Pharma, Grant/research support from: AbbVie, Merck, Novartis, Lars Bauer Shareholder of: UCB Pharma, Employee of: UCB Pharma, Bengt Hoepken Shareholder of: UCB Pharma, Employee of: UCB Pharma, Thomas Kumke Shareholder of: UCB Pharma, Employee of: UCB Pharma, Mindy Kim Shareholder of: UCB Pharma, Employee of: UCB Pharma, Robert B.M. Landewé Speakers bureau: Abbott, Amgen, BMS, Centocor, Merck, Pfizer, Roche, Schering-Plough, UCB Pharma, Wyeth, Consultant of: Abbott, Ablynx, Amgen, AstraZeneca, BMS, Centocor, GSK, Merck, Novartis, Pfizer, Roche, Schering-Plough, UCB Pharma, Wyeth, Grant/research support from: Abbott, Amgen, Centocor, Novartis, Pfizer, Roche, Schering-Plough, UCB Pharma, Wyeth

POS1256 SINGLE DOSE TOCILIZUMAB PHARMACOKINETICS IN GLUCOCORTICOID PRE-TREATED COVID-19 PATIENTS DURING CYTOKINE STORM SYNDROME HYPERINFLAMMATORY EPISODE: LESS IS MORE

Background:

The cytokine storm syndrome (CSS) associated with COVID-19 pneumonia occurs in up to 20% of the admitted patients causing high morbidity and mortality [1]. In the COVID High-intensity Immunosuppression in Cytokine storm syndrome (CHIC) study [1] we reported that CSS patients, who despite high-dose methylprednisolone (MP) treatment still showed severe respiratory deterioration, received subsequent single dose tocilizumab (TCZ) treatment. Our clinical experience with TCZ, every 4 weeks in RA, where a pre-dose serum concentration of > 1 µg/ml is sufficient to block all interleukin (IL)-6 receptors and thereby induce and maintain clinical remission, prompted further investigation of TCZ pharmacokinetics in patients with COVID-19 CSS [1,2].

Objectives:

In this pharmacokinetic study we investigated the clinical-pharmacokinetic rationale for a single TCZ dose in a subset of COVID19 induced CSS patients.

Methods:

Patients with COVID-19-associated CSS, defined as rapid respiratory deterioration plus at least two biomarker elevations (C-reactive protein (CRP) >100 mg/L; ferritin >900 μg/L; D-dimers >1500 μg/L), received per protocol high-dose intravenous MP for 5 consecutive days. If the respiratory condition had not improved sufficiently, TCZ (8 mg/kg, max. 800 mg) single infusion was added on or after day 2[1]. TCZ serum samples were drawn at TCZ day 1, 3 and 10 to assess TCZ serum concentrations with a validated ELISA-method. A nonlinear-mixed effects model was developed based on all concentration time data to characterise TCZ pharmacokinetics (NONMEM). Subsequently individual pharmacokinetic parameters (AUC0-inf, Cmax, time above 1 µg/ml) were estimated and TCZ concentration-time observations were plotted against the individual predicted concentrations to visualize the complete TCZ concentration-time curve.

Results:

In total, 34 patients with COVID19 induced CSS still showing clinical deterioration upon MP treatment received TCZ per protocol [mean (SD) age: 62 (12) years, 22% female, baseline mean (SD) bodyweight: 87 (17) kg, CRP: 108 (833) mmol/L, ferritin: 1653 (911) µg/L, D-dimers 4462 (7272) µg/L]. TCZ clearance was described by a homogeneous population-kinetics model yielding 87 serum samples. TCZ serum concentrations followed a biphasic course [Distribution volume 5.0 L (3.3-7.3), Area Under the Curve0-∞1st dose (682 (397-913) mg/L*days), Cmax 137 mg/L (88 – 199), half-life (linear) 3.5 days (2.3-4.1)]. In all patients, TCZ serum concentrations remained above the theoretical maximum IL-6 receptor occupancy concentration of 1 µg/ml for at least 12 days, depicted in Figure 1.

Figure 1.

Predicted concentration-time profiles after single dose tocilizumab in 34 methylpred-nisolone pretreated patients with COVID-19 induced cytokine storm syndrome. Dashed line: maximum IL-6 receptor occupancy concentration 1 µg/ml

Conclusion:

Based on our study results on the pharmacokinetics of TCZ in patients with severe COVID-19 induced CSS we conclude that the clearance of TCZ is faster compared to RA-patients at steady state. However, our observations indicate that a single dose of tocilizumab in CSS-patients is enough to cover IL-6 mediated hyperinflammation. Restricting TCZ to a single dosage can prevent overtreatment, drug shortage and saves costs, while still maintaining efficacy, as most patients will have overcome their hyperinflammatory period of the CSS after 10-14 days.

References:

[1]Ramiro S. Mostard R.L.M. et al. Historically controlled comparison of glucocorticoids with or without tocilizumab versus supportive care only in patients with COVID-19-associated cytokine storm syndrome: results of the CHIC study. Ann Rheum Dis 2020;79(9):1143-1151.

[2]Nishimoto N, Terao K et al. Mechanisms and pathologic significances in increase in serum interleukin-6 (IL-6) and soluble IL-6 receptor after administration of an anti IL-6 receptor antibody, tocilizumab, in patients with rheumatoid arthritis and Castleman disease. Blood. 2008;112:3959-3964.

Acknowledgements:

The authors are grateful to all patients, nurses and physicians who participated in this study.

Disclosure of Interests:

None declared

POS0609 A TOCILIZUMAB DOSING STRATEGY IN RHEUMATOID ARTHRITIS PATIENTS WITH STABLE DISEASE AIMING TO PREVENT OVERTREATMENT AND UNNECESSARY COSTS

Background:

Tocilizumab (TCZ) is a humanized interleukin 6 (IL-6) antibody that competitively inhibits IL-6 signalling by binding both membrane-bound and soluble IL-6 receptors. The EULAR recommends the use of TCZ, as a biological disease-modifying antirheumatic drug (DMARD), as second line therapy in rheumatoid arthritis (RA) when conventional DMARDs have failed achieving treatment target. The labelled dosing regimen for TCZ in RA is 8mg/kg (maximum 800mg) every 4 weeks. A TCZ predose serum concentration (TCZpsc) >1mg/L normalizes C-reactive protein, while clinical trials found mean TCZpsc of 19.9 ±17.0 mg/L in patients receiving the standard regimen. On the basis of these data, it can be hypothesized that cost-effectiveness of therapy can be improved.

Objectives:

In this study we evaluated TCZpsc in stable RA-patients to determine whether the TCZ 8mg/kg dose could be lowered while meeting the minimal required concentration for effective blockage of the IL-6 inflammatory cascade.

Methods:

Adult RA patients with stable disease (i.e. at least 3 months without treatment change) treated with intravenous TCZ were investigated in a prospective cohort study. TCZpsc before two different TCZ infusions over time was assessed. A validated ELISA was used to measure TCZpscs, immunogenicity was measured by quantifying human antibodies using antigen-binding tests (radioimmunoassay).

A population pharmacokinetic (PK) model was constructed using maximum a posteriori Bayesian estimation applied on the available PK data in the literature combined with the collected data on dosing and predose concentrations in the study patients. Body surface area, creatinine clearance and gender were included as covariates in the model. A patient individual dose tapering strategy was predicted based on the derived model.

The target TCZpsc was set on 8-10mg/L taking the measurement error of 15%, the use of the entire content of the vials and intra-individual variation into consideration.

Results:

A total of 44 patients were included [median (IQR) age: 63 (58-72), 75% female, mean (SD) DAS28-ESR: 1.5 (0.8)]. Half of the patients received TCZ in combination with a conventional DMARD, 32% used methotrexate (MTX). Patients received 7.7 ±0.8mg/kg (range 5.7-9.7) TCZ. Mean TCZpsc was 27.6 ±12.6mg/L. The intra-individual variance of TCZpsc was low; mean difference in individual TCZpscs was 0.56 (5.2)mg/L. Higher dosages (in mg/kg) were significantly associated with higher TCZpsc (regression coefficient 7.32 95%CI 2.73;11.9), suggesting overtreatment. No drug-neutralizing auto-antibodies were measured. Co-treatment with MTX did not influence the median TCZpsc (21.0mg/L versus 26.5mg/L without MTX, p=0.84).

According to the measured TCZpsc, TCZ dosage could be lowered in 36 patients (92%). In a 28-days regimen, target-TCZpsc would be reached with a 0.4-4.6mg/kg dose-reduction (Figure 1). Extending the interval between two administrations would lead to low TCZpsc (<1mg/L).

Figure 1.

Intended dose reduction related to the measured tocilizumab predose serum concentration

Considering the aimed average dose-reduction of 2.1 mg/kg per administration, efficacy would be expected to maintain (TCZpsc >1 mg/L) while reducing yearly costs with ±€3.900,- per patient. On average patients were started on TCZ treatment 63 months (SD26) earlier. As maximum efficacy of TCZ treatment can be achieved after 3 months, TCZpsc-guided dose reduction 3 months after start could have resulted in a total drug cost reduction of ±€750.000,- in our study population (±€19.500,- per patient).

Conclusion:

Measured TCZpsc under standard TCZ therapy was much higher than the minimal required concentration. These results suggest that the labelled TCZ dose leads to overtreatment and unnecessary costs in patients with stable RA. The TCZpsc seems supportive as an instrument for dose reduction strategies. Future prospective studies should assess its use in TCZ dose adjustment and confirm whether treatment efficacy is maintained.

Disclosure of Interests:

None declared

OP0047 IDENTIFICATION OF CLINICAL PHENOTYPES IN PATIENTS WITH AXIAL SPONDYLOARTHRITIS, PERIPHERAL SPONDYLOARTHRITIS AND PSORIATIC ARTHRITIS ACCORDING TO PERIPHERAL MUSCULOSKELETAL MANIFESTATIONS: A CLUSTER ANALYSIS IN THE INTERNATIONAL ASAS-PERSPA STUDY

Background:

Patients with a diagnosis of Spondyloarthritis (SpA) and Psoriatic Arthritis (PsA) may have predominant axial or peripheral symptoms, and the frequency and distribution of these symptoms may determine the clinical diagnosis by the rheumatologist (“clinical clusters”). Clustering analysis represents an unsupervised exploratory analysis which tries to identify homogeneous groups of cases (“statistical clusters”) without prior information about the membership for any of the cases.

Objectives:

To identify “statistical clusters” of peripheral involvement according to the specific location of these symptoms in the whole spectrum of SpA and PsA (without prior information about the diagnosis of the patients), and to evaluate whether these “statistical clusters” are in agreement with the “clinical clusters”.

Methods:

Cross-sectional and multicentre study with 24 participating countries. Consecutive patients considered by their treating rheumatologist as suffering from either PsA, axial SpA (axSpA) or peripheral SpA (pSpA) were enrolled. Four different cluster analyses were conducted: the first one using information about the specific location from all the peripheral musculoskeletal manifestations (i.e., peripheral arthritis, enthesitis and dactylitis), and thereafter a cluster analysis for each peripheral manifestation individually. Multiple correspondence analyses and k-means clustering methods were used. Distribution of peripheral manifestations and clinical characteristics were compared across the different clusters.

Results:

4465 patients were included in the analysis. Two clusters were found with regard to the location of all the peripheral manifestations (Fig. 1). Cluster 1 showed a low prevalence of peripheral manifestations in comparison with cluster 2; however, when peripheral involvement appeared in cluster 1, this was mostly represented by arthritis of hip, knee and ankle, as well as enthesitis of the heel. Patients from cluster 1 showed a higher prevalence of males (63% vs 44%), HLA-B27 positivity (69% vs 38%) and axial involvement (80% vs 52%), as well as more frequent diagnosis of axSpA (66% vs 21%) and more frequently fulfilling the ASAS axSpA criteria (69% vs. 41%). Patients from cluster 2 showed a higher prevalence of psoriasis (63% vs 25%), a more frequent diagnosis of PsA (61% vs 19%), and they fulfilled more frequently the peripheral ASAS (26% vs 11%) and the CASPAR criteria (57% vs 19%).

Figure 1.

Distribution of the peripheral involvement across clusters

Three clusters were found with regard to the location of the peripheral arthritis. Clusters 2 and 3 showed a high prevalence of peripheral joint disease, although this was located more predominantly in the lower limbs in cluster 2, and in the upper limbs in cluster 3. Cluster 1 showed a higher prevalence of males, HLA-B27 positivity, axial involvement, a lower presence of psoriasis, a more frequent diagnosis of axSpA and fulfilling the ASAS axSpA criteria in comparison with clusters 2 and 3, respectively. Clusters 2 and 3 showed a higher prevalence of enthesitis and dactylitis in comparison with cluster 1, a more frequent diagnosis of PsA and fulfillment of the CASPAR criteria.

Information about the location of enthesitis exhibited three groups: cluster 1 showed a very low prevalence of enthesitis, while cluster 2 and 3 showed a high prevalence of enthesitis, with a predominant involvement of axial enthesis in cluster 2 and peripheral enthesitis in cluster 3.

Finally, the analysis of dactylitis also exhibited three clusters that showed a very low prevalence of dactylitis, predominantly toes and predominantly fingers involvement, respectively.

Conclusion:

These results suggest the presence of heterogeneous patterns of peripheral involvement in SpA and PsA patients without clearly defined groups, confirming the clear overlap of these peripheral manifestations across the different underlying diagnoses.

Acknowledgements:

This study was conducted under the umbrella of ASAS with unrestricted grant of Abbvie, Pfizer, Lilly, Novartis, UCB, Janssen and Merck.

Disclosure of Interests:

None declared

THU0377 IMPACT OF FILGOTINIB ON STRUCTURAL LESIONS IN THE SACROILIAC JOINTS AT 12 WEEKS IN PATIENTS WITH ACTIVE AXIAL SPONDYLOARTHRITIS: MAGNETIC RESONANCE IMAGING DATA FROM THE DOUBLE-BLIND, RANDOMIZED TORTUGA TRIAL

Background:

Filgotinib, an oral selective Janus kinase (JAK) 1 inhibitor, reduced disease activity and improved symptoms and inflammation of the sacroiliac joint (SIJ) and spine in patients with active axial ankylosing spondylitis (AxSpA) in the Phase 2 TORTUGA trial (NCT03117270).1The effects of JAK inhibitors on structural lesions in active AxSpA are unknown and optimal methods for image analysis of structural disease progression are not established.

Objectives:

The aim of this post hoc analysis was to evaluate the effects of filgotinib on magnetic resonance imaging (MRI) measures of structural changes in the SIJ in patients from the TORTUGA trial, as assessed by Spondyloarthritis Research Consortium of Canada (SPARCC) SIJ Structural Scores (SSS).

Methods:

TORTUGA was a multicenter, double-blind, randomized trial of 116 patients with active AxSpA treated with filgotinib 200 mg (n=58) or placebo (n=58) once daily for 12 weeks. MRI was conducted at baseline and Week 12 (or early discontinuation visit). MRIs were re-evaluated post hoc by two independent experts (blinded to time point and assigned treatment) to determine SPARCC SSS; inter-reader discrepancies were resolved by an independent adjudicator. Observed changes from baseline were evaluated using analysis of covariance with factors for treatment, baseline value, and randomization stratification. Least-squares mean changes from baseline and between-group differences with 95% confidence intervals were calculated.

Results:

MRI scans from 87 patients with an evaluable MRI at baseline and Week 12 (or early termination visit) were re-evaluated (48 filgotinib, 39 placebo). Erosion scores decreased in the filgotinib group and increased in the placebo group (p=0.02 for between-group difference; Table 1; Figure 1a). Backfill scores increased in the filgotinib group but not in the placebo group (p=0.005; Table 1; Figure 1b). There was no statistically significant between-group difference in SSS total ankylosis (p=0.46) or fat lesion (p=0.17) changes from baseline (Table 1).

Table 1.

Summary of Spondyloarthritis Research Consortium of Canada Sacroiliac Joint Structural Scores.

ScoreMean (SD) BL scoreLSM change from BL (95% CI) at Week 12LSM group difference at Week 12 (95% CI)Erosion FIL 200 mg3.38 (5.34)–0.46 (–1.31, 0.40)–1.01 (–1.87, –0.16) PBO2.62 (3.76)0.56 (–0.31, 1.42)[p=0.02]Backfill FIL 200 mg1.02 (1.99)0.76 (0.07, 1.45)1.02 (0.32, 1.72) PBO1.35 (2.59)–0.26 (–0.97, 0.45)[p=0.005]Fat metaplasia FIL 200 mg4.19 (6.06)0.37 (–0.23, 0.97)0.43 (–0.18, 1.03) PBO4.35 (5.44)–0.06 (–0.67, 0.56)[p=0.17]Ankylosis FIL 200 mg9.58 (8.15)0.14 (–0.02, 0.30)0.06 (–0.10, 0.22) PBO9.83 (8.45)0.08 (–0.08, 0.25)[p=0.46]

BL, baseline; CI, confidence interval; FIL, filgotinib; LSM, least-squares mean; PBO, placebo; SD, standard deviation

Conclusion:

In addition to previously reported decreases in SPARCC inflammation, filgotinib was associated with significant reduction in SIJ erosion scores and increase in backfill scores at Week 12 of the TORTUGA trial, versus placebo. Long-term effects are to be determined.

References:

[1]van der Heijde D, et al. Lancet 2018;392:2378–87.

Acknowledgments:

We thank Robert Lambert for his review of the MRI scans in the role of adjudicator. The TORTUGA trial was sponsored by Galapagos NV and co-funded by Galapagos NV and Gilead Sciences. Medical writing support was provided by Hannah Mace MPharmacol, CMPP (Aspire Scientific Ltd, Bollington, UK) and funded by Galapagos NV (Mechelen, Belgium).

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, William Barchuk Shareholder of: Gilead Sciences Inc and Eli Lilly, Employee of: Current employee of Gilead Sciences Inc and a former employee of AbbVie, Eli Lilly, and Johnson & Johnson, Ke Liu Shareholder of: Gilead Sciences Inc (stockholder), Employee of: Gilead Sciences Inc, Chantal Tasset Shareholder of: Galapagos (share/warrant holder), Employee of: Galapagos, Leen Gilles Consultant of: Galapagos, Thijs Hendrikx Shareholder of: Galapagos (share/warrant holder), Employee of: Galapagos, Robin Besuyen Shareholder of: Galapagos, Employee of: Galapagos, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen

THU0198 EFFICACY AND SAFETY OF FILGOTINIB FOR PATIENTS WITH RHEUMATOID ARTHRITIS WITH INADEQUATE RESPONSE TO METHOTREXATE: FINCH 1 52-WEEK RESULTS

Background:

Filgotinib (FIL) is an oral, potent, selective JAK1 inhibitor. FINCH 1 (NCT02889796) assessed FIL efficacy and safety in patients (pts) with rheumatoid arthritis (RA) with inadequate response to methotrexate (MTX-IR); primary outcome results at week (W)12 and W24 were previously reported.1

Objectives:

To present FINCH 1 W52 results.

Methods:

This global, phase 3, double-blind, active- and placebo (PBO)-controlled study randomised MTX-IR pts with active RA on a background of stable MTX 3:3:2:3 to oral FIL 200 mg or FIL 100 mg once daily, subcutaneous adalimumab (ADA) 40 mg every 2W, or PBO up to W52; pts receiving PBO at W24 were rerandomised to FIL 100 or 200 mg. Efficacy was assessed from clinical, radiographic, and pt-reported outcomes; W52 comparisons were not adjusted for multiplicity. Safety endpoints included adverse events (AEs) and laboratory abnormalities.

Results:

Of 1755 treated pts, 1417 received study drug through W52. The majority (81.8%) were female, mean (standard deviation [SD]) RA duration was 7.8 (7.6) years, and baseline mean (SD) DAS28(CRP) was 5.7 (0.9). FIL efficacy was sustained through W52; 54%, 43%, and 46% of pts receiving FIL 200 and 100 mg and ADA, respectively, had W52 DAS28(CRP) <2.6 (nominal p for FIL 200 vs ADA = 0.024) (Figures 1–2, Table 1). FIL safety profile through W52 was consistent with W24 data. AEs of interest were infrequent and balanced among treatments (Table 2); 82 pts (4.7%) discontinued treatment due to AEs.

Table 1.

Efficacy outcomes at week 52

FIL 200 mg(n = 475)FIL 100 mg(n = 480)ADA(n = 325)ACR20/50/70, %78/62/4476/59/3874/59/39DAS28(CRP) ≤3.2, %66+5959mTSSa0.18+++0.450.61HAQ-DIb−0.93+−0.85−0.85SF-36 PCSb12.011.512.4FACIT-Fb11.912.211.7

aLeast squares mean change from baseline.

bMean change from baseline.

+p <0.05,+++p <0.001 vs ADA; not adjusted for multiplicity.

ADA, adalimumab; FIL, filgotinib; mTSS, modified van der Heijde TSS.

Table 2.

Treatment-emergent AEs through week 52

Event, n (%)FIL 200(n = 475)FIL 100 mg(n = 480)ADA(n = 325)All AEs352 (74.1)350 (72.9)239 (73.5)Serious AEs35 (7.4)40 (8.3)22 (6.8)Infection206 (43.4)194 (40.4)129 (39.7)Serious infection13 (2.7)13 (2.7)10 (3.1)Herpes zoster6 (1.3)4 (0.8)2 (0.6)VTE1 (0.2)01 (0.3)MACE (adjudicated)02 (0.4)1 (0.3)Malignancy (excluding NMSC)2 (0.4)2 (0.4)2 (0.6)NMSC1 (0.2)1 (0.2)0Death3 (0.6)1 (0.2)1 (0.3)

Data omitted for patients rerandomised from placebo to FIL.

ADA, adalimumab; AE, adverse event; FIL, filgotinib; MACE, major adverse cardiovascular event; NMSC, nonmelanoma skin cancer; VTE, venous thromboembolism.

Conclusion:

Through W52, both FIL 200 and 100 mg showed sustained efficacy based on clinical and pt-reported outcomes and radiographic progression and were well tolerated in MTX-IR pts with RA, with faster onset and numerically greater efficacy for FIL 200 vs 100 mg.

References:

[1]Combe et al.,Ann Rheum Dis.2019; 78 (Suppl 2):77–8.

Disclosure of Interests:

Bernard Combe Grant/research support from: Novartis, Pfizer, Roche-Chugai, Consultant of: AbbVie; Gilead Sciences, Inc.; Janssen; Eli Lilly and Company; Pfizer; Roche-Chugai; Sanofi, Speakers bureau: Bristol-Myers Squibb; Gilead Sciences, Inc.; Eli Lilly and Company; Merck Sharp & Dohme; Pfizer; Roche-Chugai; UCB, Alan Kivitz Shareholder of: AbbVie, Amgen, Gilead, GSK, Pfizer Inc, Sanofi, Consultant of: AbbVie, Boehringer Ingelheim,,Flexion, Genzyme, Gilead, Janssen, Novartis, Pfizer Inc, Regeneron, Sanofi, SUN Pharma Advanced Research, UCB, Paid instructor for: Celgene, Genzyme, Horizon, Merck, Novartis, Pfizer, Regeneron, Sanofi, Speakers bureau: AbbVie, Celgene, Flexion, Genzyme, Horizon, Merck, Novartis, Pfizer Inc, Regeneron, Sanofi, Yoshiya Tanaka Grant/research support from: Asahi-kasei, Astellas, Mitsubishi-Tanabe, Chugai, Takeda, Sanofi, Bristol-Myers, UCB, Daiichi-Sankyo, Eisai, Pfizer, and Ono, Consultant of: Abbvie, Astellas, Bristol-Myers Squibb, Eli Lilly, Pfizer, Speakers bureau: Daiichi-Sankyo, Astellas, Chugai, Eli Lilly, Pfizer, AbbVie, YL Biologics, Bristol-Myers, Takeda, Mitsubishi-Tanabe, Novartis, Eisai, Janssen, Sanofi, UCB, and Teijin, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, J-Abraham Simon-Campos: None declared, Herbert S.B. Baraf Grant/research support from: Horizon; Gilead Sciences, Inc.; Pfizer; Janssen; AbbVie, Consultant of: Horizon; Gilead Sciences, Inc.; Merck; AbbVie, Speakers bureau: Horizon, Uma Kumar: None declared, Franziska Matzkies Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Beatrix Bartok Shareholder of: Gilead Sciences Inc., Employee of: Gilead Sciences Inc., Lei Ye Shareholder of: Gilead Sciences Inc., Employee of: Gilead Sciences Inc., Ying Guo Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Chantal Tasset Shareholder of: Galapagos (share/warrant holder), Employee of: Galapagos, John Sundy Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Angelika Jahreis Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Neelufar Mozaffarian Shareholder of: Gilead, Employee of: Gilead, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Sang-Cheol Bae: None declared, Edward Keystone Grant/research support from: AbbVie; Amgen; Gilead Sciences, Inc; Lilly Pharmaceuticals; Merck; Pfizer Pharmaceuticals; PuraPharm; Sanofi, Consultant of: AbbVie; Amgen; AstraZeneca Pharma; Bristol-Myers Squibb Company; Celltrion; F. Hoffman-La Roche Ltd.; Genentech, Inc; Gilead Sciences, Inc.; Janssen, Inc; Lilly Pharmaceuticals; Merck; Myriad Autoimmune; Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis., Speakers bureau: AbbVie; Amgen; Bristol-Myers Squibb; Celltrion; F. Hoffman-La Roche Ltd, Janssen, Inc; Merck; Pfizer Pharmaceuticals; Sanofi-Genzyme; UCB, Peter Nash Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, MSD, Novartis, Pfizer Inc, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, MSD, Novartis, Pfizer Inc, Roche, Sanofi, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Gilead, Janssen, MSD, Novartis, Pfizer Inc, Roche, Sanofi, UCB

OP0008 DEVELOPMENT AND VALIDATION OF AN ALTERNATIVE ANKYLOSING SPONDYLITIS DISEASE ACTIVITY SCORE WHEN PATIENT GLOBAL ASSESSMENT IS UNAVAILABLE

Background:

Ankylosing Spondylitis Disease Activity Score (ASDAS) is a composite index measuring disease activity in axial spondyloarthritis (axSpA). It includes questions from the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Patient Global Assessment (PGA), and inflammation biomarkers. However, ASDAS calculation is not always possible because PGA is sometimes not collected.

Objectives:

To develop an alternative ASDAS to be used in research settings when PGA is unavailable.

Methods:

Longitudinal data from 4 axSpA cohorts and 2 RCTs were combined. Observations were randomly split in a development (N=1026) and a validation cohort (N=1059). Substitutes of PGA by BASDAI total score, single or combined individual BASDAI questions, and a constant value, were considered. In the development cohort, conversion factors for each substitute were defined by Generalized Estimating Equations. Validation was performed in the validation cohort according to the OMERACT filter, taking into consideration: 1) Truth (agreement with original-ASDAS in the continuous score, by intraclass correlation coefficient -ICC- and in disease activity states, by weighted kappa) 2) Discrimination (standardized mean difference –SMD- of ASDAS scores between high/low disease activity states defined by external anchors e.g Patient Acceptable Symptom State –PASS-; agreement -kappa- in the % of patients reaching ASDAS improvement criteria according to alternative vs. original formulae) 3) Feasibility.

Results:

Taking all psychometric properties into account and comparing the different formulae (Table), alternative-ASDAS using BASDAI total as PGA replacement proved to be: 1) truthful (agreement with original-ASDAS: ICC=0.98, kappa=0.90); 2) discriminative: it could discriminate between high/low disease activity states (e.g. scores between PASS no/yes: SMD=1.37 versus original-ASDAS SMD=1.43) and was sensitive to change (agreement with original-ASDAS in major improvement/clinically important improvement criteria: kappa=0.93/0.88; 3) feasible (BASDAI total often available; conversion coefficient≈1).

Table.

Psychometric properties of alternative ASDAS formulae

Conclusion:

Alternative-ASDAS using BASDAI total score as PGA replacement is the most truthful, discriminative and feasible instrument. This index enables ASDAS calculation in existing cohorts without PGA.

Disclosure of Interests:

Augusta Ortolan: None declared, Sofia Ramiro: None declared, Floris A. van Gaalen: None declared, Tore K. Kvien Grant/research support from: Received grants from Abbvie, Hospira/Pfizer, MSD and Roche (not relevant for this abstract)., Consultant of: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Paid instructor for: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Speakers bureau: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Adeline Ruyssen-Witrand Grant/research support from: Abbvie, Pfizer, Consultant of: Abbvie, BMS, Lilly, Mylan, Novartis, Pfizer, Sandoz, Sanofi-Genzyme, Astrid van Tubergen Consultant of: Novartis, Caroline Bastiaenen: None declared, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV

OP0077 DETERMINANTS OF THE PHYSICIAN’S GLOBAL ASSESSMENT AND INFLUENCE OF CONTEXTUAL FACTORS IN EARLY AXIAL SPONDYLOARTHRITIS

Background:

In RMDs, the physician’s global assessment (PhGA) is a major factor of treatment decision. It is not well-known which disease manifestations contribute to PhGA in early axSpA and if contextual factors have an impact.

Objectives:

To investigate determinants of PhGA and the influence of contextual factors on this relationship in patients with early axSpA.

Methods:

Five-year data from DESIR, a cohort of early axSpA, were analysed. Clinical data were collected every 6 months up to 2 years and annually thereafter. The primary analysis included all patients, and the subgroup analysis patients with follow-up MRI at 2 and/or 5 years. PhGA over 5 years was the outcome of interest. Univariable generalized estimating equation (GEE) models were used to investigate relationships between potential determinants and PhGA. Longitudinal relationships were investigated in autoregressive models. Effect modification by contextual factors (educational level, gender and age) was tested and, if significant, models were stratified. Univariable analyses were chosen to better assess the contributory explanatory effects of each of the determinants in each of the strata.

Results:

A total of 708 patients were included, mean age 33.7 (SD 8.6) years, 46% male, 41% lower educated. The subgroup consisted of 220 patients with similar characteristics. Higher BASDAI questions 1-6, SJC28, TJC53, Maastricht Ankylosing Spondylitis Enthesitis Score (MASES), CRP and BASMI were associated with a higher PhGA (Table 1). Gender and age were effect modifiers of SJC28; the effect was largest in the younger male stratum (β [95% CI]; 1.07 [0.71, 1.43]), and smallest in the older female stratum (0.13 [0.04, 0.22]) (Figure 1). Autoregressive GEE models revealed the same determinants of PhGA and the same pattern of effect modification by gender and age.

Table 1.

Factors associated with PhGA over time in gender/age-stratified groups in univariable analysis

Female/Older(n=200)Female/Younger(n=181)Male/Older(n=154)Male/Younger(n=173)Coefficient (95% CI)BASDAI Q1 (fatigue, 0-10)0.39 (0.34, 0.44)0.39 (0.34, 0.44)0.41 (0.35, 0.46)0.46 (0.41, 0.51)BASDAI Q2 (back pain, 0-10)0.49 (0.45, 0.54)0.53 (0.49, 0.57)0.48 (0.43, 0.53)0.58 (0.54, 0.63)BASDAI Q3 (peripheral joint pain, 0-10)0.31 (0.27, 0.36)0.36 (0.31, 0.41)0.32 (0.27, 0.37)0.43 (0.37, 0.48)BASDAI Q4 (enthesitis, 0-10)0.37 (0.33, 0.41)0.42 (0.37, 0.46)0.36 (0.31, 0.41)0.52 (0.47, 0.56)BASDAI Q5 (severity of morning stiffness, 0-10)0.42 (0.37, 0.46)0.45 (0.40, 0.49)0.44 (0.40, 0.49)0.58 (0.54, 0.63)BASDAI Q6 (duration of morning stiffness, 0-10)0.30 (0.25, 0.35)0.35 (0.30, 0.39)0.36 (0.31, 0.41)0.50 (0.45, 0.56)BASMI linear (0-10)0.61 (0.45, 0.78)0.67 (0.48, 0.86)0.49 (0.30, 0.68)0.95 (0.75, 1.15)SJC28 (0-28)0.13 (0.04, 0.22)0.52 (0.31, 0.73)0.58 (0.40, 0.76)1.07 (0.71, 1.43)TJC53 (0-159) ¶0.05 (0.04, 0.06)0.13 (0.11, 0.16)0.13 (0.11, 0.16)0.15 (0.13, 0.18)MASES (0-39)0.10 (0.08, 0.12)0.15 (0.12, 0.17)0.18 (0.14, 0.23)0.30 (0.25, 0.35)CRP (mg/L)0.02 (0.01, 0.04)0.03 (0.01, 0.05)0.06 (0.04, 0.07)0.04 (0.03, 0.05)Any EAM (presence vs absence)-0.13 (-0.49, 0.23)-0.20 (-0.58, 0.19)-0.26 (-0.68, 0.17)-0.28 (-0.69, 0.14)SPARCC-spine (0-414) §0.06 (-0.11, 0.22)0.05 (-0.11, 0.20)0.02 (-0.03, 0.06)0.05 (-0.04, 0.14)SPARCC-SIJ (0-72) §-0.02 (-0.13, 0.09)0.01 (-0.08, 0.10)0.05 (-0.01, 0.11)0.01 (-0.04, 0.06)

¶ Each joint graded 0-3

§ Coefficients were estimated in the subgroup

Conclusion:

Patient’s subjective symptoms, peripheral arthritis, enthesitis, higher CRP and impaired spinal mobility contribute to explain PhGA in patients with early axSpA irrespective of gender and age. But physicians consider the presence of swollen joints as more important in males than in females.

Disclosure of Interests:

Fumio Hirano Paid instructor for: Ono pharmaceuticals, Astellas Pharma Inc, Sumitomo Dainippon Pharma, Chugai Pharmaceutical Co., Ltd., Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Floris A. van Gaalen: None declared, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Cecile Gaujoux-Viala: None declared, Sofia Ramiro Grant/research support from: MSD, Consultant of: Abbvie, Lilly, Novartis, Sanofi Genzyme, Speakers bureau: Lilly, MSD, Novartis

FRI0563 COMPARISON OF TWO DIFFERENT APPROACHES TO INVOLVE PARTICIPANTS IN CONSECUTIVE ROUNDS OF A DELPHI CONSENSUS TECHNIQUE

Background:

There is no guidance on which participants to invite to consecutive rounds of a Delphi exercise. There are two options: 1) Invite only participants that have completed the previous round for the consecutive round; 2) Invite every participant for all consecutive rounds irrespective of whether they have responded. It is unknown whether different invitation-procedures provide similar results.

Objectives:

To investigate the effect of two different approaches to involve participants in consecutive rounds of a Delphi exercise on response rate and final outcome.

Methods:

Patients with and experts in spondyloarthritis were invited to partake in a 3-round Delphi exercise to update a core outcome set. A randomised controlled study with 1:1 allocation to two experimental groups was built in, to compare two approaches of invitation. The ‘all-rounds group’ includes patients invited for each round independent of response to the previous round; the ‘respondents group’ includes patients invited for the next round only if they responded to the previous round. A 9-point Likert scale (1=not important; 9=critical) was used to score the importance of domains. Additionally, participants provided their six most important domains.

Results:

The overall response rate after 3 rounds was lower in the ‘respondents’ compared to the ‘all-rounds group’ (46% vs. 61%) (table 1).

Table 1.

Response rates per group per round of the Delphi exercise

‘Respondents group’ (N=187)‘All-rounds group’ (N=189)Round 1Invited: 187Completed: 122Response rate: 65%Invited: 189Completed: 110Response rate: 58%Round 2Invited: 122Completed: 95 [response rate (78%)]Overall response rate: 51%Invited: 189Completed: 105Response rate: 56%Round 3Invited: 95Completed: 86 [response rate (91%)]Overall response rate: 46%Invited: 189Completed: 116Response rate: 61%

There was no difference in mean (standard deviation) scores between the ‘respondents’ and ‘all-rounds’ groups for any domain (figure 1).

After the final round, the 4 outcomes with the highest percentage of votes were identical between experimental groups, with only small differences in percentages between groups (table 2). The only difference in the 6 most important domains was selection of disease activity by the ‘respondents group’, whereas the ‘all-rounds group’ selected overall functioning & health, while these domains were ranked as the 7thdomain in the other group.

Table 2.

Most important domains afterround 3for the ‘respondents’ and ‘all-rounds’ groups ranked in descending order, based on selection by the ‘respondents’ and matched in the ‘all-rounds group’; and the difference in percentage of votes between groups. Domains initalicandboldrepresent the top 6 in each experimental group.

‘Respondents group’ N=86‘All-rounds group’ N=116Difference between groupsPain95%Pain91%Pain4%Stiffness62%Stiffness62%Stiffness0%Physical functioning62%Physical functioning61%Physical functioning1%Mobility59%Mobility54%Mobility5%Disease activity55%Disease activity49%Disease activity6%Fatigue50%Fatigue55%Fatigue-5%Overall functioning & health47%Overall functioning & health57%Overall functioning & health-10%Extra-musculoskeletal manifestations44%Extra-musculoskeletal manifestations45%Extra-musculoskeletal manifestations-1%Peripheral manifestations34%Peripheral manifestations44%Peripheral manifestations-10%Sleep30%Sleep26%Sleep4%Work & Employment21%Work & Employment23%Work & Employment-2%Emotional functioning16%Emotional functioning18%Emotional functioning-2%

Conclusion:

Inviting persons for all rounds irrespective of a response to the previous round increases the generalisability, while the content of the outcome of a Delphi procedure is similar to using data of those persons who participate in all rounds only.

Disclosure of Interests:

Anne Boel: None declared, Victoria Navarro-Compán Consultant of: Abbvie, Lilly, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, MSD, Lilly, Novartis, Pfizer, UCB, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV

OP0075 SPINAL RADIOGRAPHIC PROGRESSION IN AXIAL SPONDYLOARTHRITIS AND THE IMPACT OF CLASSIFICATION AS NONRADIOGRAPHIC VERSUS RADIOGRAPHIC DISEASE

Background:

Data on spinal radiographic progression is more limited in nonradiographic axial spondyloarthritis (nr-axSpA) than in the radiographic disease state (r-axSpA). It remains unclear, whether radiographic sacroiliitis is by itself associated with progression of spinal structural damage.

Objectives:

To investigate whether spinal radiographic progression relates to structural damage at the sacroiliac level in axSpA by means of statistical mediation analyses in a large prospective real-life cohort of patients with axSpA.

Methods:

Patients from the Swiss Clinical Quality Management cohort were included if they fulfilled the ASAS classification criteria and could be classified as nr-axSpA or r-axSpA after central scoring of pelvis radiographs. Spinal radiographs performed every 2 years were scored according to the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS). The relationship between classification status and spinal progression over 2 years was investigated using binomial generalized estimating equations models with adjustment for sex, ankylosing spondylitis disease activity score (ASDAS) and tumor necrosis factor inhibitor treatment. Baseline spinal damage was considered an intermediate variable and included in sensitivity analyses, as were additional variables potentially influencing radiographic progression.

Results:

In total, 88 nr-axSpA and 418 r-axSpA patients contributed to data for 725 radiographic intervals (Table 1). Mean (SD) mSASSS change over 2 years was 0.16 (0.62) units in nr-axSpA and 0.92 (2.78) units in r-axSpA, p=0.01. Nr-axSpA was associated with a significantly lower progression over 2 years (defined as an increase in ≥2 mSASSS units) in adjusted analyses (OR 0.33, 95%CI 0.13; 0.83), confirmed with progression defined as the formation of ≥1 syndesmophyte. Mediation analyses revealed that sacroiliitis exerted its effect on spinal progression indirectly by being associated with the appearance of a first syndesmophyte (OR 0.09, 95%CI 0.02; 0.36 for nr-axSpA vs r-axSpA) (Fig. 1 and 2). Baseline syndesmophytes were predictors of further progression.

Table 1.

Baseline characteristics at first radiograph.

ParameterN506nr-axSpAN = 88r-axSpAN = 418PFemale sex, %50654.533.7<0.001Age, y50639.5±11.140.4±11.00.52Symptom duration, y49810.0±9.914.0±9.8<0.001HLA-B27 positive, %45271.680.70.09BASDAI4274.6±2.04.2±2.30.26ASDAS4082.8±0.92.8±1.10.74Elevated CRP, %42230.640.60.14BASFI4332.8±2.23.1±2.50.71BASMI4351.1±1.42.2±2.0<0.001mSASSS5060.9±1.56.8±12.7<0.001Syndesmophytes, %5069.135.2<0.001On TNFi, %50619.336.40.002Fig. 1.

Modified Stoke Ankylosing Spondylitis Spine Score (mSASSS) for individual patients plotted as a function of duration since symptom onset.

Fig. 2.

Two-year mSASSS progression depicted in a cumulative probability plot. Progression was defined as an increase in mSASSS of at least 2 units (dotted line) in 2 years.

Conclusion:

Spinal structural damage is mainly restricted to patients with r-axSpA, leading to relevant prognostic and therapeutic implications.

Disclosure of Interests:

Monika Hebeisen: None declared, Raphael Micheroli: None declared, Almut Scherer: None declared, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Manouk de Hooge: None declared, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Kristina Buerki: None declared, Michael Nissen Grant/research support from: Abbvie, Consultant of: Novartis, Lilly, Abbvie, Celgene and Pfizer, Speakers bureau: Novartis, Lilly, Abbvie, Celgene and Pfizer, Burkhard Moeller: None declared, Pascal Zufferey: None declared, Pascale Exer: None declared, Adrian Ciurea Consultant of: Consulting and/or speaking fees from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Merck Sharp & Dohme, Novartis and Pfizer.

FRI0302 WHAT IS THE IMPACT OF DISCREPANCY BETWEEN CENTRAL AND LOCAL READERS IN EVALUATION OF MRI SCANS ON THE CLASSIFICATION OF AXIAL SPONDYLOARTHRITIS? DATA FROM THE ASAS CLASSIFICATION COHORT STUDY

Background:

Active MRI lesions typical of axial spondyloarthritis (axSpA) were reported in 61.6% and 2.2% of axSpA and not-axSpA patients, respectively, from the ASAS classification cohort (ASAS-CC)1. Discrepancy between local and central reader evaluation of MRI scans could result in differences in numbers of patients fulfilling the imaging arm of the ASAS classification criteria. But final classification may not be impacted if discrepant patients still fulfill the clinical arm.

Objectives:

We aimed to assess the impact of reader discrepancy in detection of active MRI lesions on the number of patients classified as having axSpA in patients recruited to the ASAS-CC.

Methods:

MRI images of the sacroiliac joints (SIJs) were available from 252 cases in the ASAS-CC, and these also had clinical and radiographic data. Seven central readers from the ASAS-MRI group recorded MRI lesions in an eCRF that included active lesions typical of axSpA in the SIJ (MRI-active) that was worded exactly the same as in the original ASAS-CC eCRF permitting comparisons between central and local site readers. Active lesions were deemed to be present according to majority agreement (≥4/7) of central readers and also any 2 central readers. We calculated the number of patients that were classified differently after central evaluation for overall fulfilment of the ASAS criteria and for the imaging arm.

Results:

Discordance between central and local readers for detection of MRI-active was recorded in 45(17.8%) and 47(18.2%) of cases according to 2-reader and majority (≥4/7) central reader data, respectively (kappa (95%CI) of 0.64 (0.54-0.73) and 0.62 (0.53-0.72). With central reading as external standard the false-positive rate for active lesions was 26.9%% and 32.2% (‘local overcall’) for 2-reader and majority reader data, respectively. There were 159(63.1%) patients who fulfilled the ASAS axSpA criteria based on local-reading, and 148(58.7%) and 143(56.7%) patients based on 2-reader and majority central-reading, respectively (Table). When fulfillment of the imaging arm was the primary consideration (irrespective of the clinical arm), 126 (50%) patients fulfilled the criteria based on local-reading, and 111 (44%) and 102 (40.5%) patients based on 2-reader and majority central-reading, respectively.

Conclusion:

Despite substantial overcall for positive MRI SIJ inflammation by local readers, the number of patients classified as having axSpA did not change substantially. This is due to the alternate mechanism for classification through the clinical arm.

References:

[1]Rudwaleit et al. Ann Rheum Dis 2009;68: 777-83

Impact of Central Vs. Local Reader SIJ MRI Inflammation Assessment on SpA Classification in cases with all clinical, radiographic, and central and local MRI inflammation data available (n=252)MRI assessment usedSpA Classification = Yes N(%)SpA Classification = No N(%)Imaging Arm SpA Classification = Yes N(%)Imaging Arm SpA Classification = No N(%)Local Reader MRI positive159 (63.1%)93 (36.9%)126 (50%)126 (50%)>2 Central Reader MRI positive148 (58.7%)104 (41.3%)111 (44.0%)141 (56.0%)Majority Central Reader (≥4/7) MRI positive143 (56.7%)109 (43.2%)102 (40.5%)150 (59.5%)

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Susanne Juhl Pedersen Grant/research support from: Novartis, Ulrich Weber: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Joachim Sieper Consultant of: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Speakers bureau: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Stephanie Wichuk: None declared, Denis Poddubnyy Grant/research support from: AbbVie, MSD, Novartis, and Pfizer, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Martin Rudwaleit Consultant of: AbbVie, BMS, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Joel Paschke: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Robert G Lambert: None declared

OP0199 POINTS TO CONSIDER WHEN ANALYSING AND REPORTING COMPARATIVE EFFECTIVENESS RESEARCH WITH OBSERVATIONAL DATA IN RHEUMATOLOGY

Background:

Comparing drug effectiveness in observational settings is hampered by several major threats, among them confounding and attrition bias bias (patients who stop treatment no longer contribute information, which may overestimate true drug effectiveness).

Objectives:

To present points to consider (PtC) when analysing and reporting comparative effectiveness with observational data in rheumatology (EULAR-funded taskforce).

Methods:

The task force comprises 18 experts: epidemiologists, statisticians, rheumatologists, patients, and health professionals.

Results:

A systematic literature review of methods currently used for comparative effectiveness research in rheumatology and a statistical simulation study were used to inform the PtC (table). Overarching principles focused on defining treatment effectiveness and promoting robust and transparent epidemiological and statistical methods increase the trustworthiness of the results.

Points to consider

Reporting of comparative effectiveness observational studies must follow the STROBE guidelinesAuthors should prepare a statistical analysis plan in advanceTo provide a more complete picture of effectiveness, several outcomes across multiple health domains should be comparedLost to follow-up from the study sample must be reported by the exposure of interestThe proportion of patients who stop and/or change therapy over time, as well as the reasons for treatment discontinuation must be reportedCovariates should be chosen based on subject matter knowledge and model selection should be justifiedThe study baseline should be at treatment initiation and a description of how covariate measurements relate to baseline should be includedThe analysis should be based on all patients starting a treatment and not limited to patients remaining on treatment at a certain time pointWhen treatment discontinuation occurs before the time of outcome assessment, this attrition should be taken into account in the analysis.Sensitivity analyses should be undertaken to explore the influence of assumptions related to missingness, particularly in case of attrition

Conclusion:

The increased use of real-world comparative effectiveness studies makes it imperative to reduce divergent or contradictory results due to biases. Having clear recommendations for the analysis and reporting of these studies should promote agreement of observational studies, and improve studies’ trustworthiness, which may also facilitate meta-analysis of observational data.

Disclosure of Interests:

Delphine Courvoisier: None declared, Kim Lauper: None declared, Sytske Anne Bergstra: None declared, Maarten de Wit Grant/research support from: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Consultant of: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Speakers bureau: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Bruno Fautrel Grant/research support from: AbbVie, Lilly, MSD, Pfizer, Consultant of: AbbVie, Biogen, BMS, Boehringer Ingelheim, Celgene, Lilly, Janssen, Medac MSD France, Nordic Pharma, Novartis, Pfizer, Roche, Sanofi Aventis, SOBI and UCB, Thomas Frisell: None declared, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Joanna KEDRA: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Tanja Stamm Grant/research support from: AbbVie, Roche, Consultant of: AbbVie, Sanofi Genzyme, Speakers bureau: AbbVie, Roche, Sanofi, Simon Stones Consultant of: I have been a paid consultant for Envision Pharma Group and Parexel. This does not relate to this abstract., Speakers bureau: I have been a paid speaker for Actelion and Janssen. These do not relate to this abstract., Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific

FRI0044 ROBUST ANALYSES FOR RADIOGRAPHIC PROGRESSION IN RHEUMATOID ARTHRITIS

Background:

Reducing structural damage is an important treatment goal for rheumatoid arthritis (RA). Demonstrating a clinically meaningful, statistically significant difference in radiographic progression (assessed by van der Heijde modified total Sharp score, mTSS) is a common objective in trials for RA treatments.

Complete collection of radiographic data is challenging, especially in long term follow-up and pediatric studies. Therefore, scores for individual joints or entire patients are regularly missing. A frequently used analysis method for mTSS is the analysis of covariance model, in which missing data are imputed using linear extrapolation (ANCOVA+LE). However, other ways to deal with missing information have also been proposed.

Objectives:

To evaluate robust analysis methods for mTSS data.

Methods:

Simulated data were used to compare a random coefficient model (RC) without imputation, ANCOVA+LE and ANCOVA with last observation carry forward imputation (LOCF).

A log-normal distribution was used to generate baseline patient level data to simulate a 2-arm clinical trial using baseline mTSS and rate of change in mTSS from recently completed trials. Changes in mTSS (12, 28 and 44 week timepoints) were generated under linear, concave quadratic (fast progression then slow progression), and convex quadratic (slow progression then fast progression) assumptions, with the proportion of change forced to be 0 (a proportion of simulated patients do not have progression). A monotone missing pattern was assumed to generate a data set with missing data (the ‘observed’ dataset).

ANCOVA analyses were performed using baseline and treatment as predictors. The RC model was applied using baseline, treatment, time, and time-by-treatment interactions as fixed effect and time as a random effect. Bias (difference between average of simulation sample mean and true value, the smaller the better), root mean square error (RMSE, a measure of variation among simulation samples, the smaller the better), power and type I error rate were compared between methods.

Results:

The random coefficient model provided better or at least similar results in bias, RMSE, power and type I error rate as ANCOVA+LE under evaluated scenarios (Table 1).

Progression assumptionSimulation parameters(Number of simulations = 500; common sample size=300, baseline mTSS=~11.7)ModelBiasPowerRMSELinearppbo= 0.6, rpbo= 0.065ptrt= 0.68 rpbo= 0.046Δwk44= −0.49ANCOVA + Full0.0020.9240.140ANCOVA + LE0.0030.8660.155ANCOVA+LOCF0.1540.8440.190RC + FULL0.0010.920.139RC + OBS−0.0020.8720.156Concaveppbo= 0.6, rpbo= −0.0009, qpbo= 0.11ptrt= 0.68, rtrt= −0.0011, qtrt= 0.093Δwk44= −0.611ANCOVA + Full0.0020.9820.141ANCOVA + LE−0.0020.9260.180ANCOVA+LOCF0.1880.940.222RC + FULL0.0020.9780.141RC + OBS−0.0050.9240.174Convexppbo=0.6, rpbo= 0.0037, qpbo=−0.09ptrt= 0.68, rtrt= 0.003, qtrt= −0.1Δwk44= −0.83ANCOVA + Full0.00310.139ANCOVA + LE0.3430.9480.368ANCOVA+LOCF0.3910.9740.405RC + FULL−0.00410.140RC + OBS0.1990.9880.249

Abbreviations: FULL = complete dataset with no missing values trt = active treatment, OBS = the ‘observed’ dataset, pbo = placebo, p= proportion of patients with no progression, r = linear progression rate (mTSS units per week), q = quadratic term coefficient. Δ = active treatment progression – placebo r

Conclusion:

RC is a robust analysis method for mTSS. We recommend its use in primary analyses, especially for long-term extension and pediatric studies with a higher likelihood of missing data. This method can also provide reference for time points when no data are collected via estimated slope. ANCOVA+LE can be used for sensitivity analysis.

References:

None.

Disclosure of Interests:

Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Luna Sun Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Yun-Fei Chen Shareholder of: Own shares in Eli Lilly and Company., Employee of: Employee of Eli Lilly and Company, Douglas Schlichting Shareholder of: Eli Lilly and Company, Employee of: Eli Lilly and Company, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV

OP0079 PRELIMINARY DEFINITION OF A POSITIVE MRI FOR STRUCTURAL LESIONS IN THE SACROILIAC JOINTS IN AXIAL SPONDYLOARTHRITIS

Background:

There is lack of international consensus as to what defines a structural lesion on MRI of the sacroiliac joints (SIJ) typical of axial spondyloarthritis (axSpA). The ASAS MRI group has generated updated consensus lesion definitions that describe each of the MRI lesions in the SIJ1. These definitions have been evaluated by 7 readers from the ASAS-MRI group on MRI images from the ASAS Classification Cohort.

Objectives:

We aimed to identify quantitative cut-offs based on numbers of slices and SIJ quadrants that define a positive MRI for structural lesions typical of axSpA, the gold standard being majority central reader decision as to the presence of a structural lesion typical of axSpA with high confidence.

Methods:

MRI structural lesions meeting ASAS definitions were recorded in an eCRF that comprises global assessment (structural lesion typical of axSpA present/absent and degree of confidence (-4 (absent) to +4 (present)), and detailed scoring of lesions per SIJ quadrant. Detailed scoring was based only on assessment of DICOM images (n =148). We calculated sensitivity and specificity for numbers of SIJ quadrants and consecutive slices with erosion, sclerosis, and fat lesions where a majority of readers (≥4/7) agreed as to the presence of a structural lesion typical of axSpA with high confidence (≥ +3). We tested candidate lesion definitions for predictive diagnostic utility in cases assessed after 4.4 years of follow up by the local rheumatologist.

Results:

Structural lesions typical of axSpA were observed by majority read in 33 (32.4%) of 102 cases diagnosed with axSpA, and 3 (6.8%) of 44 cases without axSpA and 29 cases were assigned a high degree of confidence (≥ +3) by a majority of readers. Cut-offs achieving specificity of 95% were erosion in ≥2 consecutive slices (sensitivity 83%), erosion ≥3 SIJ quadrants (sensitivity 90%), and fat lesion (≥1cm horizontal depth) in ≥1 SIJ quadrant (sensitivity 59%) (Table). These had very high positive predictive values (>95%) for diagnosis of axSpA in cases diagnosed by the rheumatologist after 4.4 years follow up.

Conclusion:

ASAS-defined erosion in ≥2 consecutive slices or in ≥3 SIJ quadrants and ASAS-defined fat lesion with depth >1cm in ≥1 SIJ quadrant are high priority candidates for defining an MRI structural lesion typical of axSpA. This will require similar assessment in additional axSpA cohorts.

References:

[1]Maksymowych et al. Ann Rheum Dis 2019; 78:1550-8.

Table 1.

Majority readers agree structural lesion indicative of axSpA is present with confidence ≥3/4 is the gold-standard external reference

SensitivitySpecificityErosion Score ≥1 SIJ qdr93.1 (77.2-99.2)80.6 (72.4-87.3)Erosion Score ≥2 SIJ qdr93.1 (77.2-99.2)90.8 (84.1-95.3)Erosion Score ≥3 SIJ qdr89.7 (72.6-97.8)95.8 (90.5-98.6)Erosion in 2 consecutive slices82.8 (64.2-94.2)95.0 (89.3-98.1)Fat lesion ≥1 SIJ qdr82.8 (64.2-94.2)81.5 (73.4-88.0)Fat lesion ≥2 SIJ qdr69.0 (49.2-84.7)86.6 (79.1-92.1)Fat lesion ≥3 SIJ qdr62.1 (42.3-79.3)91.6 (85.1-95.9)Fat lesion in 2 consecutive slices55.2 (35.7-73.6)93.3 (87.2-97.1)Fat lesion (>1cm depth) ≥158.6 (38.9-76.5)95.0 (89.3-98.1)Fat lesion (>1cm depth) ≥255.2 (35.7-73.6)95.8 (90.5-98.6)Fat lesion (>1cm depth) ≥351.7 (32.5-70.6)97.5 (92.8-99.5)Fat lesion (>1cm depth) in 2 consecutive slices48.3 (29.4-67.5)97.5 (92.8-99.5)

Table. SIJ qdr: sacroiliac joint quadrant

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Xenofon Baraliakos: None declared, Ulrich Weber: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Susanne Juhl Pedersen Grant/research support from: Novartis, Joachim Sieper Consultant of: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Speakers bureau: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Stephanie Wichuk: None declared, Denis Poddubnyy Grant/research support from: AbbVie, MSD, Novartis, and Pfizer, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Martin Rudwaleit Consultant of: AbbVie, BMS, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Joel Paschke: None declared, Robert G Lambert: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB

SAT0384 REPLACEMENT OF RADIOGRAPHIC SACROILITIS BY MRI STRUCTURAL LESIONS: WHAT IS THE IMPACT ON CLASSIFICATION OF AXIAL SPONDYLOARTHRITIS IN THE ASAS CLASSIFICATION COHORT?

Background:

Classification of axial spondyloarthritis (axSpA) is based on either an imaging or clinical arm. Radiographic or MRI evidence of sacroiliitis can be applied for the imaging arm. However, it is well-established that reliability and sensitivity of radiographic sacroiliitis is inadequate.

Objectives:

To assess the impact of replacing radiographic sacroiliitis with MRI structural lesions (MRI-S) typical of axSpA on the number of patients classified as having axSpA in patients with undiagnosed back pain recruited to the ASAS Classification Cohort (ASAS-CC).

Methods:

MRI images of the sacroiliac joint (SIJ) were available from 217 cases in the ASAS-CC, which also had clinical, laboratory, and radiographic data. Seven central readers from the ASAS-MRI group recorded MRI lesions in an eCRF that included active (MRI-A) and structural (MRI-S) lesions typical of axSpA. MRI-A was deemed to be present according to majority agreement (≥4/7) of central readers. MRI-S was deemed to be present according to the majority (majority reader MRI-S) and also according to at least 2 central readers (≥2-reader MRI-S). We calculated the number of patients that were classified differently after replacement of radiographs by MRI-S for overall fulfillment of the ASAS criteria and for the imaging arm.

Results:

In total, 119 (54.8%) cases fulfilled the axSpA criteria based on local reading of radiographic sacroiliitis and central reading of active inflammation on MRI. This changed to 125 (57.6%) and 118 (54.4%) of cases after replacement of radiographic sacroiliitis by ≥2-reader and majority reader MRI-S, respectively (Table). A total of 13 (6.0%) and 7 (3.2%) cases who were classified as not having axSpA were re-classified as having axSpA after replacing radiographic sacroiliitis with ≥2-reader and majority reader MRI-S, respectively. Conversely, 7 (3.2%) and 8 (3.7%) cases were re-classified as not having axSpA after substitution by ≥2-reader and majority reader MRI-S, respectively. When fulfillment of the imaging arm was the primary consideration (irrespective of the clinical arm), the number of patients reclassified from not axSpA to axSpA was 25 (11.5%) by ≥2-reader and 13 (6.0%) by majority reader MRI-S, while 8 (3.7%) and 11 (5.1%) were reclassified from axSpA to not axSpA.

Conclusion:

The number of patients classified as having axSpA does not change substantially when MRI-S replaces radiographic sacroiliitis. However, it remains possible that MRI structural lesions can influence the final diagnosis, the gold standard for assessment of the performance of the ASAS criteria.

Impact of Replacement of Radiographic Sacroilitis by MRI Structural Lesions on SpA Classification in cases with all clinical, radiographic, and central and local MRI inflammation data available (n=217)

MRI assessment usedSpA Classification=Yes N(%)SpA Classification=No N(%)Imaging Arm SpA Classification=Yes N(%)Imaging Arm SpA Classification=No N(%)Radiographic Sacroiliitis + Majority Central Reader MRI Inflammation Positive119 (54.8%)97 (44.7%)83(38.2%)134 (61.8%)Replace Radiographic Sacroiliitis with ≥2 Central Reader MRI Structural Positive125 (57.6%)92 (42.4%)100 (46.1%)117 (53.9%)Replace Radiographic Sacroiliitis with Majority Central Reader MRI Structural Positive118 (54.4%)99 (45.6%)85 (39.2%)132 (60.8%)

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Robert G Lambert: None declared, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Joachim Sieper Consultant of: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Speakers bureau: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Stephanie Wichuk: None declared, Denis Poddubnyy Grant/research support from: AbbVie, MSD, Novartis, and Pfizer, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Martin Rudwaleit Consultant of: AbbVie, BMS, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Joel Paschke: None declared, Susanne Juhl Pedersen Grant/research support from: Novartis, Ulrich Weber: None declared

OP0110 IS VERY EARLY TREATMENT EFFECTIVE? SIX MONTHS RESULTS OF THE PREVAS STUDY, A PLACEBO-CONTROLLED TRIAL WITH ETANERCEPT IN PATIENTS SUSPECTED OF NON-RADIOGRAPHIC AXIAL SPONDYLOARTHRITIS

Background:

Despite the new classification criteria for non-radiographic axial spondyloarthritis (nr-axSpA) patients according to the Assessment of Spondyloarthritis International Society (ASAS), there are limited data on disease progression in nr-axSpA patients.

Objectives:

First to assess the improvement in disease activity in patients suspected of nr-axSpA after 16 weeks treatment with Etanercept (ETN) or Placebo (PBO). Second, to assess the changes of active inflammation on MRI of the SI-joints (SIJ) between the ETN and PBO group after 16 and 24 weeks without study medication.

Methods:

The PrevAS study is a randomized, double blind, placebo-controlled trial with ETN performed in the VU University medical center (VUmc) (EudraCT number 2009-015515-40), with a screening period from 2009 until 2014. Patients suspected of nr-axSpA were included if they had chronic back pain for ≥ 3 months, were ≥ 18 years, fulfilled the Calin criteria of inflammatory back pain and had to be either HLA-B27 positive with at least ≥ 1 Spondyloarthritis (SpA)-feature (as defined by the European Spondyloarthropathy Study Group (ESSG), or HLA-B27 negative with at least ≥ 2 SpA-features and had a high disease activity score (Bath Ankylosing Spondylitis Disease Activity Index ≥ 4) plus insufficient response to at least two NSAIDs. Excluded were patients who fulfilled the modified New York criteria for ankylosing spondylitis, or in case of previous biological use. Included patients were randomly assigned (1:1) for 16 weeks treatment with ETN (N=40) or PBO (N=40) and followed after the treatment period for 24 weeks. The primary endpoint was the number of patients achieving the ASAS20 response at week 16. MRI was performed at baseline, 16 and 24 weeks and scored using the Spondyloarthritis Research Consortium of Canada (SPARCC) index for number of active inflammatory lesions.

Results:

The majority of included patients was female (63.8%). Patient characteristics, like the presence of the HLA-B27 antigen and number of SpA-features at baseline, were comparable between the ETN and PBO group. Mean compliance to the study medication at sixteen weeks was 72.1%. Longitudinal regression analysis over the first 16 weeks showed a trend towards a three times higher chance to achieve the ASAS20 response in the ETN compared to the PBO group (OR = 3.2, 95% CI [0.6;16.7]p=0.18) (Figure 1). No differences were observed in ASAS20 response at 24 weeks. A positive SPARCC score (SPARCC ≥ 2.5) of the SIJ was observed in the ETN and PBO group in 33.3% (13/39 patients) vs. 30.8% (12/39 patients) at baseline, 16.7% (6/36 patients) vs. 17.5% (7/40 patients) at 16 weeks and 21.9% (7/32 patients) vs. 20.0% (7/35 patients) at 24 weeks, respectively. Increased CRP-levels (CRP_UL ≥ 10.0mg/L) nor a positive SPARCC score at baseline, had significant influence on the ASAS20 response at 16 weeks follow-up. The safety profile was consistent with what is known for ETN in AS.

Conclusion:

Patients suspected of nr-axSpA with high disease activity showed a trend towards a three times higher chance to achieve the ASAS20 response in the ETN group, compared to the PBO group at 16 weeks, regardless of a raised CRP level or positive MRI-SIJ at baseline.

Figure:

Acknowledgments:

We thank Pfizer for financial support of this investigator initiated study. In addition we want to thank H. Hofman and W.A. ter Wee for practical study support.

Disclosure of Interests:

Tamara Rusman: None declared, Mignon A.C. van der Weijden: None declared, Michael T Nurmohamed Grant/research support from: Abbvie, Bristol-Myers Squibb, Celltrion, GlaxoSmithKline, Jansen, Eli Lilly, Menarini, Merck Sharp & Dohme, Mundipharma, Pfizer, Roche, Sanofi, USB, Consultant of: Abbvie, Bristol-Myers Squibb, Celltrion, GlaxoSmithKline, Jansen, Eli Lilly, Menarini, Merck Sharp & Dohme, Mundipharma, Pfizer, Roche, Sanofi, USB, Speakers bureau: Abbvie, Bristol-Myers Squibb, Celltrion, GlaxoSmithKline, Jansen, Eli Lilly, Menarini, Merck Sharp & Dohme, Mundipharma, Pfizer, Roche, Sanofi, USB, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Janneke J. de Winter: None declared, B.J.H. Boden: None declared, Pierre M. Bet: None declared, Camile M.A. van der Bijl: None declared, Conny J. van der Laken: None declared, Irene van der Horst-Bruinsma Grant/research support from: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Consultant of: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma

OP0103 DOES GENDER, AGE OR SUBPOPULATION INFLUENCE THE MAINTENANCE OF CLINICAL REMISSION IN AXIAL SPONDYLOARTHRITIS FOLLOWING CERTOLIZUMAB PEGOL DOSE REDUCTION?

Background:

Previous studies have shown that withdrawing tumour necrosis factor inhibitors (TNFi) in patients (pts) with axial spondyloarthritis (axSpA) who have achieved sustained remission often leads to relapse.1However, none have formally tested TNFi dose reduction strategies in a broad axSpA population or evaluated whether relapse following TNFi dose reduction and withdrawal is associated with a specific demographic subgroup.

Objectives:

C-OPTIMISE evaluated the percentage of pts without flare after TNFi dose continuation, reduction or withdrawal in adults with early axSpA treated with the Fc-free, PEGylated TNFi certolizumab pegol (CZP). Here, we analyse whether responses to reduced maintenance dose were comparable in pts stratified by axSpA subpopulation, gender and age.

Methods:

C-OPTIMISE (NCT02505542) was a multicentre, two-part phase 3b study in adults with early (<5 years’ symptom duration) active axSpA (stratified for radiographic [r]- and non-radiographic [nr]- axSpA). Pts received CZP 200 mg every 2 weeks (wks) (Q2W; 400 mg loading dose at Wks 0, 2 and 4) during the open-label induction period. At Wk 48, pts in sustained remission (Ankylosing Spondylitis Disease Activity Score [ASDAS] <1.3 at Wk 32 or 36 [if ASDAS <1.3 at Wk 32, it must be <2.1 at Wk 36, or vice versa] and at Wk 48) were randomised to double-blind full maintenance dose (CZP 200 mg Q2W); reduced maintenance dose (CZP 200 mg every 4 wks [Q4W]) or placebo (PBO) for a further 48 wks (maintenance period). The primary endpoint was the percentage of pts not experiencing a flare (ASDAS ≥2.1 at two consecutive visits or ASDAS >3.5 at any timepoint) during Wks 48–96. Analyses were conducted on subgroups according to axSpA subpopulation, gender and age ≤/> the median age of the randomised set (32 years).

Results:

During the 48-wk induction period, 43.9% of patients (323/736) achieved sustained remission and 313 pts entered the 48-wk maintenance period (r/nr-axSpA: 168/145 pts; males/females: 247/66 pts; age ≤32/>32: 165/148 pts). During the maintenance period, responses in r- and nr-axSpA pts were comparable across all three randomised arms. 83.9% r-axSpA and 83.3% nr-axSpA pts receiving the full CZP maintenance dose did not experience a flare, and in the reduced maintenance dose arm 82.1% r-axSpA and 75.5% nr-axSpA pts did not experience a flare. In the PBO group this was reduced to 17.9% and 22.9%, respectively. Similar responses were seen in pts stratified by gender or age, with substantially higher percentages of pts randomised to CZP full or reduced maintenance dose remaining free of flares compared to PBO in all subgroups (Figure).

Conclusion:

The results of C-OPTIMISE indicate that a reduced maintenance dose is suitable for pts with axSpA who achieve sustained remission following 1 year of CZP treatment, regardless of axSpA subpopulation, gender or age. Complete treatment withdrawal is not recommended due to the high risk of flare.

References:

[1]Landewe R. Lancet 2018;392:134–44.

Acknowledgments:

This study was funded by UCB Pharma. Editorial services were provided by Costello Medical

Disclosure of Interests:

Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Maxime Dougados Grant/research support from: AbbVie, Eli Lilly, Merck, Novartis, Pfizer and UCB Pharma, Consultant of: AbbVie, Eli Lilly, Merck, Novartis, Pfizer and UCB Pharma, Speakers bureau: AbbVie, Eli Lilly, Merck, Novartis, Pfizer and UCB Pharma, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Filip van den Bosch Consultant of: AbbVie, Celgene Corporation, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Speakers bureau: AbbVie, Celgene Corporation, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Karl Gaffney Grant/research support from: AbbVie, Celgene, MSD, Novartis, Pfizer, and UCB Pharma, Consultant of: AbbVie, Celgene, MSD, Novartis, Pfizer, and UCB Pharma, Speakers bureau: AbbVie, Celgene, MSD, Novartis, Pfizer, and UCB Pharma, Lars Bauer Employee of: UCB Pharma, Bengt Hoepken Employee of: UCB Pharma, Natasha de Peyrecave Employee of: UCB Pharma, Karen Thomas Employee of: UCB Pharma, Lianne S. Gensler Grant/research support from: Pfizer, Novartis, UCB, Consultant of: AbbVie, Eli Lilly, GSK, Novartis, UCB

OP0315 WHICH RESPONSE OR STATUS CRITERION DISCRIMINATES BEST IN AXSPA?

Background:

Response criteria and disease activity status used to assess treatment efficacy in axial spondyloarthritis (axSpA) are: the ASAS response criteria (ASAS20; 40; 5/6 and partial remission - PR), BASDAI50 and ASDAS-based criteria (clinically important/major improvement –CII/MI; low disease activity/inactive disease –LDA/ID). These outcomes are variably used in RCTs testing biological (b) and targeted-synthetic (ts)DMARDs. However, it remains unknown which are the most discriminative.

Objectives:

To compare the ability of different criteria to discriminate between the response to active treatment and placebo in axSpA.

Methods:

A systematic literature review was performed in Medline and Embase to identify RCTs of b- and tsDMARDs. Placebo-controlled RCTs meeting the primary endpoint were included provided they reported ≥2 response/status criteria. Outcomes were collected at the timepoint of primary endpoint assessment (PEA). Risk of bias was evaluated by The Cochrane tool. Meta-analysis with the Mantel-Haenszel method was conducted to calculate the Chi-square (Χ2) between percentages of patients fulfilling each criterion in the treatment arm versus the placebo arm (higherΧ2, better discrimination). Comparisons among criteria were conducted evaluating their performances across RCTs reporting the exact same outcomes at the PEA. Different sets of RCTs were used for the comparisons depending on the available outcomes (Table).

Results:

29 RCTs fulfilled inclusion criteria. In total, 23/29 RCTs with PEA at 12, 14 or 16 weeks, all at a low risk of bias, could be considered for meta-analysis. Other 6 RCTs had later (e.g 24 weeks) or earlier (e.g. 6 weeks) PEA. Out of the 23 RCTs, only 16 reported at least a minimum set of ASAS20,-40, -PR and BASDAI50 (Table, Set 1): discriminative performances for ASAS40 were >ASAS20>BASDAI50>ASAS-PR. In 11/16 RCTs ASAS5/6 was also included (Table, Set 2): this criterion showed the best performances among ASAS-based response criteria. 8/16 RCTs additionally included some ASDAS-based criteria (Table, Set 3): ASDAS-CII and -MI showed a much higher discrimination compared to the ASAS-based criteria. In only 3 trials could all criteria be compared, with the ASDAS-CII and -MI appearing as the most discriminative criteria, followed by ASAS 5/6 (Table, Set 4).

Conclusion:

Response criteria are more discriminative than status criteria. ASDAS-CII and ASDAS-MI showed the best discrimination between treatment/placebo arms. Using the ASDAS-CII as primary outcome in future RCTs can reduce the number of patients needed to be included while keeping the same statistical power.

Table.

Discriminative performances of response and status criteria in RCTs of biological and targeted synthetic DMARDs in axial spondyloarthritis

Minimum set of outcomesSet 1:ASAS20,-40,-PR, BASDAI50Set 2:ASAS20,-40,-5/6, -PRBASDAI50Set 3:ASAS20,-40, -5/6, -PR BASDAI50ASDAS-CII, -MI, -IDSet 4:AllN° of RCTsTotal=16*161183Descending Χ2orderΧ2Χ2Χ2Χ2 1ASAS40339ASAS5/6334ASDAS-CII309ASDAS-CII124 2ASAS20316ASAS40266ASDAS-MI253ASDAS-MI65 3BASDAI50297ASAS20254ASAS40169ASAS5/648 4ASAS-PR146BASDAI50248BASDAI50163BASDAI5039 5-ASAS-PR119ASDAS-ID117ASAS4034 6--ASAS2098ASDAS-LDA27 7--ASAS-PR80ASAS-PR22 8---ASAS2021 9---ASDAS-ID7

Legend.*total of 16 RCTs analysed, with different sets of RCTs within the 16 analysed based on the availability of response criteria; Χ2=Chi-square; RCTs=randomized controlled trials; BASDAI= Bath Ankylosing Spondylitis Disease Activity Index; ASAS= Assessment in SpondyloArthritis International Society; PR= partial remission; CII= clinically important improvement; MI= major improvement; LDA= low disease activity; ID= inactive disease

Disclosure of Interests:

Augusta Ortolan: None declared, Sofia Ramiro: None declared, Alexandre Sepriano: None declared, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Victoria Navarro-Compán Consultant of: Abbvie, Lilly, Novartis, Pfizer, UCB, Speakers bureau: AbbVie, MSD, Lilly, Novartis, Pfizer, UCB

FRI0317 CONSENSUS DEFINITIONS FOR MRI LESIONS IN THE SPINE OF PATIENTS WITH AXIAL SPONDYLOARTHRITIS: FIRST ANALYSIS FROM THE ASSESSMENTS IN SPONDYLOARTHRITIS INTERNATIONAL SOCIETY CLASSIFICATION COHORT

Background:

A recent consensus from the ASAS MRI group has culminated in updated spine lesion definitions for axial spondyloarthritis (ASAS_MRI_defn)1. There has been no central reader evaluation of MRI scans from the ASAS Classification Cohort (ASAS-CC)2to determine the spectrum of MRI lesions in the spine in this cohort.

Objectives:

To determine the spectrum of active and structural lesions on MRI images of the spine from the ASAS-CC according to the consensus ASAS_MRI_defnupdate.

Methods:

ASAS_MRI_defnwere recorded by 9 central readers in an eCRF for global assessment and detailed scoring of each discovertebral unit and postero-lateral structures. Vertebral corner bone marrow edema (VCBME) and corner fat (VCFAT) lesions were recorded if present on 2 slices; facet joint, lateral, and posterior inflammatory lesions were recorded if present on a single slice. Vertebral corner erosion, bone spurs, and ankylosis were each scored on a single slice. Comparison of active and structural lesion frequencies by local rheumatologist diagnosis of axSpA was assessed descriptively according to ≥2 and majority reader (≥5/9) concordant data.

Results:

MRI scans of the spine were available from 69 cases with axSpA diagnosed in 44/64 (68.8%). VCBME was most frequent with ≥1 lesion in 32(46.4%) and 19 (27.5%) by ≥2 and ≥5/9 readers, respectively. VCFAT was the most frequent structural lesion with ≥1 lesion in 24 (34.8%) and 14 (20.3%) by ≥2 and ≥5/9 readers, respectively. There were significantly more VCBME lesions in axSpA patients than non-axSpA (mean(SD):1.8(2.7) vs 0.3 (0.5)) (p<0.001) while differences in VCFAT were not significant (Table). The presence of ≥2 VCBME had 90-95% specificity for axSpA. Significantly more VCBME and VCFAT were observed in the setting of radiographic sacroiliitis (modified New York criteria (mNY)).

Conclusion:

Spine lesions on MRI are relatively frequent in patients with undiagnosed back pain presenting to the rheumatologist. The presence of ≥2 VCBME, but not VCFAT, may have some diagnostic utility.

References:

[1]Maksymowych WP, et al. Arthritis Rheumatol 70 (suppl 10): 654, 2018

[2]Rudwaleit et al. Ann Rheum Dis 2009;68: 777-83

Vertebral Corner MRI lesionsmajority of readers (>=5)≥2 readersaxSpA=Yes (n=44)axSpA=No (n=20)p-valueaxSpA=Yes (n=44)axSpA=No (n=20)p-valueCorner Fat ≥112 (27.3%)2 (10%)0.1917 (38.6%)7 (35%)0.78Corner Fat ≥210 (22.7%)2 (10%)0.3113 (29.5%)4 (20%)0.64Corner Fat ≥38 (18.2%)1 (5%)0.2510 (22.7%)3 (15%)0.74Corner Fat ≥47 (15.9%)1 (5%)0.429 (20.5%)2 (10%)0.48Corner BME ≥117 (38.6%)1 (5%)0.00625 (54.5%)6 (30%)0.047Corner BME ≥215 (34.1%)1 (5%)0.01319 (43.2%)2 (10%)0.009Corner BME ≥311 (25%)0 (0%)0.01316 (36.4%)1 (5%)0.008Corner BME ≥48 (18.2%)0 (0%)0.09412 (27.3%)1 (5%)0.048mNY=Yes (n=10)mNY=No (n=49)p-valuemNY=Yes (n=10)mNY=No (n=49)p-valueCorner Fat ≥15 (50%)9 (18.4%)0.0475 (50%)17 (34.7%)0.48Corner Fat ≥25 (50%)7 (14.3%)0.0225 (50%)11 (22.4%)0.12Corner Fat ≥34 (40%)5 (10.2%)0.0364 (40%)9 (18.4%)0.20Corner Fat ≥44 (40%)4 (8.2%)0.0224 (40%)7 (14.3%)0.079Corner BME ≥15 (50%)11 (22.4%)0.1167 (70%)22 (44.9%)0.18Corner BME ≥25 (50%)9 (18.4%)0.0475 (50%)14 (28.6%)0.27Corner BME ≥35 (50%)6 (12.2%)0.0145 (50%)11 (22.4%)0.12Corner BME ≥45 (50%)3 (6.1%)0.0025 (50%)7 (14.3%)0.022

Disclosure of Interests:

Walter P. Maksymowych Grant/research support from: AbbVie, Novartis, Pfizer, and UCB, Consultant of: AbbVie, Boehringer Ingelheim, Celgene, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, and UCB, Employee of: Chief Medical Officer of CARE Arthritis Limited, Speakers bureau: AbbVie, Janssen, Novartis, Pfizer, and UCB, Iris Eshed: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Susanne Juhl Pedersen Grant/research support from: Novartis, Ulrich Weber: None declared, Manouk de Hooge: None declared, Joachim Sieper Consultant of: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Speakers bureau: AbbVie, Boehringer Ingelheim, Eli Lilly and Company, Janssen, Merck, Novartis, Pfizer, Roche, and UCB Pharma, Stephanie Wichuk: None declared, Denis Poddubnyy Grant/research support from: AbbVie, MSD, Novartis, and Pfizer, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB, Martin Rudwaleit Consultant of: AbbVie, BMS, Celgene, Janssen, Eli Lilly, MSD, Novartis, Pfizer, Roche, UCB Pharma, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Robert G Lambert: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Xenofon Baraliakos Grant/research support from: Grant/research support from: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Consultant of: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen, Speakers bureau: AbbVie, BMS, Celgene, Chugai, Merck, Novartis, Pfizer, UCB and Werfen

OP0198 A SYSTEMATIC REVIEW TO INFORM THE EULAR POINTS TO CONSIDER WHEN ANALYSING AND REPORTING COMPARATIVE EFFECTIVENESS RESEARCH WITH OBSERVATIONAL DATA IN RHEUMATOLOGY

Background:

Comparative effectiveness studies using observational data are increasingly used. Despite their high potential for bias, there are no detailed recommendations on how these studies should best be analysed and reported in rheumatology.

Objectives:

To conduct a systematic literature review of comparative effectiveness research in rheumatology to inform the EULAR task force developing points to consider when analysing and reporting comparative effectiveness research with observational data.

Methods:

All original articles comparing drug effectiveness in longitudinal observational studies of ≥100 patients published in key rheumatology journals (Scientific Citation Index > 2) between 1.01.2008 and 25.03.2019 available in Ovid MEDLINE® were included. Titles and abstracts were screened by two reviewers for the first 1000 abstracts and independently checked to ensure sufficient agreement has been reached. The main information extracted included the types of outcomes used to assess effectiveness, and the types of analyses performed, focusing particularly on confounding and attrition.

Results:

9969 abstracts were screened, with 218 articles proceeding to full-text extraction (Figure 1), representing a number of rheumatic and musculoskeletal diseases. Agreement between the two reviewers for the first 1000 abstracts was 92.7% with a kappa of 0.6. The majority of the studies used several outcomes to evaluate effectiveness (Figure 2A). Most of the studies did not explain how they addressed missing data on the covariates (70%) (Figure 2B). When addressed (30%), 44% used complete case analysis and 10% last observation carried forward (LOCF). 25% of studies did not adjust for confounding factors and there was no clear correlation between the number of factors used to adjust and the number of participants in the studies. An important number of studies selected covariates using bivariate screening and/or stepwise selection. 86% of the studies did not acknowledge attrition (Figure 2C). When trying to correct for attrition (14%), 38% used non-responder (NR) imputation, 24% used LUNDEX1, a form of NR imputation, and 21% LOCF.

Conclusion:

Most of studies used multiple outcomes. However, the vast majority did not acknowledge missing data and attrition, and a quarter did not adjust for any confounding factors. Moreover, when attempting to account for attrition, several studies used methods which potentially increase bias (LOCF, complete case analysis, bivariate screening…). This systematic review confirms the need for the development of recommendations for the assessment and reporting of comparative drug effectiveness in observational data in rheumatology.

References:

[1]Kristensen et al. A&R. 2006 Feb;54(2):600-6.

Acknowledgments:

Support of the Standing Committee on Epidemiology and Health Services Research

Disclosure of Interests:

Kim Lauper: None declared, Joanna KEDRA: None declared, Maarten de Wit Grant/research support from: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Consultant of: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Speakers bureau: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Bruno Fautrel Grant/research support from: AbbVie, Lilly, MSD, Pfizer, Consultant of: AbbVie, Biogen, BMS, Boehringer Ingelheim, Celgene, Lilly, Janssen, Medac MSD France, Nordic Pharma, Novartis, Pfizer, Roche, Sanofi Aventis, SOBI and UCB, Thomas Frisell: None declared, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Tanja Stamm Grant/research support from: AbbVie, Roche, Consultant of: AbbVie, Sanofi Genzyme, Speakers bureau: AbbVie, Roche, Sanofi, Simon Stones Consultant of: I have been a paid consultant for Envision Pharma Group and Parexel. This does not relate to this abstract., Speakers bureau: I have been a paid speaker for Actelion and Janssen. These do not relate to this abstract., Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific, Sytske Anne Bergstra: None declared, Delphine Courvoisier: None declared

SAT0158 EFFICACY AND SAFETY OF FILGOTINIB IN METHOTREXATE-NAÏVE PATIENTS WITH RHEUMATOID ARTHRITIS: FINCH 3 52-WEEK RESULTS

Background:

Filgotinib (FIL) is a potent, selective JAK 1 inhibitor. FINCH 3 assessed FIL efficacy and safety in methotrexate (MTX)-naïve patients (pts) with rheumatoid arthritis (RA); week (W)24 primary outcome results were previously presented.1

Objectives:

To report FINCH 3 (NCT02886728) results through W52.

Methods:

This global, phase 3, double-blind, active-controlled study randomised MTX-naïve pts with moderately to severely active RA 2:1:1:2 to oral FIL 200 mg once daily + MTX ≤20 mg weekly, FIL 100 mg + MTX, FIL 200 mg monotherapy (mono) + placebo (PBO), or PBO + MTX up to W52. Comparisons at W52 were not adjusted for multiplicity. Safety was assessed from adverse events and laboratory abnormalities.

Results:

Of 1249 treated pts, 975 received study drug through W52. FIL efficacy was sustained up to W52. Treatment with FIL + MTX or FIL mono increased proportions of pts achieving ACR20/50/70 and clinical disease remission by DAS28(CRP) <2.6 (FIL 200 mg + MTX, 53%; FIL mono, 46%), CDAI, SDAI, and Boolean criteria; improved HAQ-DI; and halted radiographic progression vs MTX alone (Table 1 andFigure). Safety was consistent with W24 data (Table 2).

Table 1.

Efficacy outcomes at week 52

FIL 200 mg + MTX (n = 416)FIL 100 mg + MTX (n = 207)FIL 200 mg(n = 210)MTX(n = 416)ACR20, %75.0***73.4**74.8***61.8ACR50, %62.3***59.4**61.4**48.3ACR70, %47.8***40.1*45.2***29.8mTSSa0.21***0.27*0.23**0.74HAQ-DIb−1.00***−0.97−0.95*−0.88

aLeast-squares mean change from baseline.

bMean change from baseline.

*, p <0.05;**, p <0.01;***, p <0.001 vs MTX alone; not adjusted for multiplicity.

FIL, filgotinib; mTSS, van der Heijde modified total Sharp score; MTX, methotrexate.

Table 2.

Safety outcomes through week 52

Event, n (%)FIL 200 mg + MTX(n = 416)FIL 100 mg + MTX(n = 207)FIL 200 mg(n = 210)MTX(n = 416)All AEs318 (76.4)164 (79.2)143 (68.1)305 (73.3)Serious AEs26 (6.3)13 (6.3)17 (8.1)28 (6.7)Infection148 (35.6)76 (36.7)75 (35.7)157 (37.7)Serious infection5 (1.2)3 (1.4)5 (2.4)8 (1.9)Herpes zoster6 (1.4)3 (1.4)4 (1.9)4 (1.0)VTE0004 (1.0)MACE (adjudicated)4 (1.0)1 (0.5)2 (1.0)2 (0.5)Malignancya1 (0.2)004 (1.0)NMSC2 (0.5)001 (0.2)Death3 (0.7)b1 (0.5)c00

aExcluding NMSC.

b1 lupus cardiomyopathy, 1 atypical interstitial pneumonia, 1 non–treatment-emergent cardiovascular death.

cDissecting cerebral and vertebral aneurysm.

AE, adverse event; FIL, filgotinib; MACE, major adverse cardiovascular event; MTX, methotrexate; NMSC, nonmelanoma skin cancer; VTE, venous thromboembolism.

Conclusion:

Efficacy of FIL 200 mg + MTX, FIL 100 mg + MTX, and FIL 200 mg mono was sustained through W52, with faster onset1and consistently numerically greater efficacy for FIL 200 vs 100 mg. No new safety signals were observed.

References:

[1]Westhovens, et al.Ann Rheum Dis.2019;78(Suppl2):259–60.

Disclosure of Interests:

Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, William Rigby Consultant of: Gilead Sciences, Inc., Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Daniel Ching Grant/research support from: AbbVie, Gilead Sciences, Inc., Pfizer, Sanofi, Consultant of: AbbVie, Pfizer, Speakers bureau: AbbVie, William Stohl Grant/research support from: GlaxoSmithKline, Consultant of: Janssen Research & Development, Jonathan Kay Grant/research support from: Gilead Sciences, Inc., Pfizer, Novartis Pharmaceuticals Corporation, Consultant of: Alvotech Suisse AG; Arena Pharmaceuticals, Inc.; Boehringer Ingelheim GmbH; Celltrion Healthcare Co. Ltd.; Merck Sharp & Dohme Corp.; Mylan Inc.; Novartis AG; Samsung Bioepis; Sandoz, Inc; UCB, Inc., Arvind Chopra Grant/research support from: Zydus Pharamceutical Ltd India, Beatrix Bartok Shareholder of: Gilead Sciences Inc., Employee of: Gilead Sciences Inc., Franziska Matzkies Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Zhaoyu Yin Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Ying Guo Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Chantal Tasset Shareholder of: Galapagos (share/warrant holder), Employee of: Galapagos, John Sundy Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Angelika Jahreis Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Neelufar Mozaffarian Shareholder of: Gilead, Employee of: Gilead, Osvaldo Messina Speakers bureau: Amgen; Americas Health Foundation; Pfizer, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Tatsuya Atsumi Grant/research support from: Eli Lily Japan K.K., Alexion Pharmaceuticals, Inc., Bristol-Myers Squibb Co., AbbVie Inc., Daiichi Sankyo Co., Ltd., Pfizer Inc., Chugai Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Co., Astellas Pharma Inc., Consultant of: Gilead Sciences, Inc., Eli Lilly Japan K.K., UCB Japan Co. Ltd., AbbVie Inc., Daiichi Sankyo Co., Ltd., Pfizer Inc., Chugai Pharmaceutical Co., Ltd., Speakers bureau: Eli Lilly Japan K.K., UCB Japan Co. Ltd., Bristol-Myers Squibb Co., AbbVie Inc., Eisai Co. Ltd., Otsuka Pharmaceutical Co., Ltd., Daiichi Sankyo Co., Ltd., Pfizer Inc., Chugai Pharmaceutical Co., Ltd., Mitsubishi Tanabe Pharma Co., Takeda Pharmaceutical Co., Ltd., Astellas Pharma Inc., Gerd Rüdiger Burmester Consultant of: AbbVie Inc, Eli Lilly, Gilead, Janssen, Merck, Roche, Pfizer, and UCB Pharma, Speakers bureau: AbbVie Inc, Eli Lilly, Gilead, Janssen, Merck, Roche, Pfizer, and UCB Pharma

SAT0375 DETERMINANTS OF PATIENT’S GLOBAL ASSESSMENT OF WELL-BEING IN EARLY AXIAL SPONDYLOARTHRITIS; 5-YEAR LONGITUDINAL DATA FROM THE DESIR COHORT

Background:

A framework has been proposed to explain which disease outcomes impact quality of life or well-being in patients with axSpA; this was based on cross-sectional data and patients with radiographic axSpA.1

Objectives:

To investigate the determinants of patient’s well-being over time, and the influence of contextual factors on these relationships in patients with early axSpA.

Methods:

Five-year data from DESIR, a cohort of early axSpA, were analysed. Clinical data were collected every 6 months up to 2 years and annually thereafter. X-rays and MRI of the spine and SIJ were performed at baseline, 2, and 5 years. The outcome was BAS-G, the patient’s global assessment of the disease impact on well-being. Generalized estimating equations (GEE) were used to test the relationship between potential explanatory variables from 5 domains (disease activity, physical function, spinal mobility, structural damage, spinal and SIJ inflammation) and BAS-G over 5 years. Longitudinal relationships were analysed using an autoregressive GEE model. Contextual factors (patient’s educational level, gender and age) were tested as potential effect modifiers or confounders.

Results:

A total of 708 patients were included, mean age 33.7 (SD 8.6) years, 46% male, 41% lower educated. Higher scores of the individual questions of BASDAI on fatigue (Q1) (β [95% CI]: 0.17 [0.13-0.22]), back pain (Q2) (0.51 [0.46-0.56]), peripheral joint pain (Q3) (0.08 [0.04-0.12]) and severity of morning stiffness (Q5) (0.08 [0.03-0.13]), and BASFI (0.14 [0.08-0.19]) were independently associated with a higher BAS-G over time (Table 1). In the autoregressive GEE model, all variables except for the BASDAI Q5 showed true longitudinal associations with BAS-G. Age, gender and educational level were neither effect modifiers nor confounders.

Table 1.

Factors associated with BAS-G over time.

Multivariable GEE modelMultivariable autoregressive GEE model §Coefficient (95% CI)Coefficient (95% CI)BASDAI Q1 (fatigue, 0-10)0.17 (0.13 to 0.22)*0.15 (0.10 to 0.20)*BASDAI Q2 (back pain, 0-10)0.51 (0.46 to 0.56)*0.54 (0.47 to 0.60)*BASDAI Q3 (peripheral joint pain, 0-10)0.08 (0.04 to 0.12)*0.13 (0.08 to 0.19)*BASDAI Q4 (enthesitis, 0-10)0.03 (-0.01 to 0.07)0.02 (-0.04 to 0.08)BASDAI Q5 (severity of morning stiffness, 0-10)0.08 (0.03 to 0.13)*0.06 (-0.01 to 0.13)BASDAI Q6 (duration of morning stiffness, 0-10)0.03 (-0.01 to 0.07)0.05 (-0.01 to 0.11)SJC28 (0-28)0.01 (-0.11 to 0.13)0.10 (-0.11 to 0.31)TJC53 (0-159) ¶-0.01 (-0.02 to 0.01)-0.01 (-0.03 to 0.01)MASES (0-39)0.00 (-0.02 to 0.02)-0.00 (-0.03 to 0.02)CRP (mg/L)0.01 (-0.00 to 0.01)0.00 (-0.01 to 0.01)Any EAM (presence vs absence)-0.05 (-0.21 to 0.11)-0.09 (-0.28 to 0.10)BASFI (0-10)0.14 (0.08 to 0.19)*0.08 (0.00 to 0.16)*BASMI linear (0-10)-0.07 (-0.16 to 0.02)-0.10 (-0.22 to 0.02)mNY grading (0-8)0.01 (-0.03 to 0.06)0.06 (0.01 to 0.12)*mSASSS (0-72)-0.01 (-0.04 to 0.02)0.00 (-0.03 to 0.04)

* p-value < 0.05

¶ Each joint graded 0-3

§Adjusted for the outcome (i.e. BAS-G) one year before, in order to disentangle the cross-sectional and longitudinal relationships between outcomes and allow the interpretation of a longitudinal relationship

Conclusion:

A higher level of back pain was associated with a worsening of the patient’s well-being in early axSpA, as were, though to a lesser extent, higher levels of fatigue, morning stiffness, peripheral joint pain and physical disability. Contextual factors like age, gender and educational level did not have an impact on these relationships. Thus, the previously proposed framework of disease outcomes also applies to patients with early axSpA and to outcomes over time.

References:

[1]Machado, P. ARD 2011.

Disclosure of Interests:

Fumio Hirano Paid instructor for: Ono pharmaceuticals, Astellas Pharma Inc, Sumitomo Dainippon Pharma, Chugai Pharmaceutical Co., Ltd., Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Floris A. van Gaalen: None declared, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Cecile Gaujoux-Viala: None declared, Sofia Ramiro Grant/research support from: MSD, Consultant of: Abbvie, Lilly, Novartis, Sanofi Genzyme, Speakers bureau: Lilly, MSD, Novartis

The nocebo effect challenges the non-medical infliximab switch in practice

Background

In clinical practice, non-medical switching of biological medication may provoke nocebo effects due to unexplained deterioration of therapeutic benefits. Indication extrapolation, idiosyncratic reactions, and interchangeability remain challenged in clinical practice after biosimilar approval by the European Medicines Agency. The principle of “first do no harm” may be challenged in a patient when switching from originator to biosimilar biological.

Aim

To describe the 1-year results of a pragmatic study on infliximab biosimilar implementation in immune-mediated inflammatory disease patients on the basis of shared decision-making under effectiveness and safety monitoring.

Methods

Inflammatory bowel disease and rheumatology patients on infliximab originator were converted to infliximab biosimilar after providing informed consent. Nocebo response patients were monitored after switch back to originator. Linear mixed models were used to analyze continuous endpoints on effectiveness and laboratory outcomes to determine significance (P ≤ 0.05) of change over time after switching.

Results

After inviting 146 patients, a group of 125 patients enrolled in the project over time, respectively, 73 Crohn’s disease, 28 ulcerative colitis, nine rheumatoid arthritis, ten psoriatic arthritis, and five ankylosing spondylitis patients. No statistically significant changes in effectiveness and safety were observed in any of the indications after a median of 4 infusions in 9 months of study. An overall nocebo response of 12.8% was found among the patients during a minimal observation period of 6 months after the transition to biosimilar infliximab. The overall nocebo response rate did not differ between the studied indications.

Conclusions

In inflammatory bowel disease and rheumatological patients, similar effectiveness and safety were demonstrated on the transition into infliximab biosimilar. In our series, patient empowerment and registration of treatment outcomes delineated biosimilar transition, an approach that hypothetically could reduce nocebo response rates which are relevant to account for regarding biosimilar implementation.

Electronic supplementary material

The online version of this article (10.1007/s00228-018-2418-4) contains supplementary material, which is available to authorized users.

Meta-Regression of a Dose-Response Relationship of Methotrexate in Mono- and Combination Therapy in Disease-Modifying Antirheumatic Drug-Naive Early Rheumatoid Arthritis Patients

OBJECTIVE

To investigate a possible short-term dose-response relationship of initial treatment with methotrexate (MTX) in monotherapy and combination therapy in recent-onset rheumatoid arthritis (RA) patients.

METHODS

A systematic literature search was performed on trials and cohorts, including early, disease-modifying antirheumatic drug (DMARD)-naive RA patients treated with MTX, with data on clinical results within 6 months from treatment start. Cohen's effect sizes were calculated for the Health Assessment Questionnaire (HAQ), erythrocyte sedimentation rate (ESR)/C-reactive protein (CRP) level, and/or Disease Activity Score (DAS)/in 28 joints (DAS28) in 4 treatment groups: MTX monotherapy, or MTX in combination with synthetic (cs) DMARDs, biologic (b) DMARDs, or glucocorticoids. Random-effects meta-regression analyses were performed for each outcome, with treatment group as the predictor corrected for baseline HAQ or disease activity and assessment point.

RESULTS

Thirty-one studies including 5,589 patients were included. The meta-regression did not support higher effectiveness of increasing MTX dose in monotherapy. The number of treatment groups using combination therapy with csDMARDs was too small to perform meta-regression analyses. In combination therapy with glucocorticoids, a higher MTX dose was associated with higher (worse) outcome HAQ, but not with DAS/DAS28 or ESR/CRP level. In combination therapy with bDMARDs, a higher MTX dose was associated with higher outcome HAQ and DAS/DAS28, but not with ESR/CRP level. All effect sizes were small.

CONCLUSION

In DMARD-naive, early RA patients who start MTX, either as monotherapy or in combination with bDMARDs or glucocorticoids, a higher initial dose of MTX was not associated with better clinical outcomes. This finding suggests that there is little short-term gain from starting with high compared to low MTX doses.

Optimisation of rheumatic disease assessments in clinical trials, clinical care, and long-term databases

The assessment of disease in rheumatological diseases is rather complicated, because it may involve different contexts (clinical practice, clinical trials, observational studies, registries, etc.) as well as different domains (disease activity, physical function, radiographic damage, quality of life, etc.). Furthermore, available tools can be comprehensive but also rather condense, may be patient-oriented or rather physician-oriented, and so on. In this article all these levels that may matter in case of a choice of disease assessment tool are discussed, arriving at a conclusion that choosing the appropriate tool for the assessment of disease is not 'cookbook medicine'.