POS0512 ANTI-CITRULLINATED PROTEIN ANTIBODY SEROSTATUS DETERMINES 2-YEAR RETENTION OF IV AND SC ABATACEPT IN PATIENTS WITH RA IN A REAL-WORLD SETTING

Background

A treat-to-target approach for RA management is recommended.1,2 However, up to half of patients discontinue DMARD treatment within 18 months.2 Predictive biomarkers, such as anti-citrullinated protein antibodies (ACPAs) and RF, may be useful to stratify patients to the most appropriate treatment. ACTION (AbataCepT In rOutiNe clinical practice; NCT02109666) and ASCORE (Abatacept SubCutaneOus in Routine Clinical PracticE; NCT02090556) were 2-year, international, observational, prospective, multicenter studies of IV and SC abatacept, respectively, for the treatment of RA in routine clinical practice.3,4 Higher retention has been previously reported in patients with double ACPA/RF seropositive RA compared with double ACPA/RF seronegative RA.3,4

Objectives

To assess the independent effect of ACPA or RF single seropositivity on abatacept retention in patients with RA receiving abatacept in a post hoc analysis of ACTION and ASCORE.

Methods

This post hoc analysis included patients aged ≥ 18 years, with active moderate-to-severe RA (ACR/EULAR 2010 criteria) who initiated IV (body weight–adjusted dosing) or SC (125 mg once weekly) abatacept.3,4 Patients were stratified by baseline ACPA/RF status: ACPA+/RF− (ACPA+ only), ACPA/RF double positive (+/+), ACPA−/RF+ (RF+ only), and ACPA/RF double negative (−/−). Abatacept retention rate at 2 years was estimated by Kaplan–Meier (KM) analysis.

Results

Patients with ACPA/RF serostatus data from the ACTION and ASCORE studies (N = 1679 and N = 1748, respectively) were evaluated. Baseline demographic and disease characteristics were similar across studies and serostatus groups (Table 1). In patients with ACPA+ only RA, abatacept retention rates were similar to the +/+ group and greater than the RF+ only and −/− groups (Figure 1). In ASCORE (Figure 1A), retention rates were significantly higher in ACPA+ only and +/+ groups when compared with the −/− group. In contrast, retention rates for patients with RF+ only RA were not significantly different vs −/− patients. Results were similar in ACTION, although the higher retention in the ACPA+ group did not reach statistical significance (Figure 1B).

Table 1.

Baseline demographics and disease characteristics by ACPA/RF status for the ASCORE and ACTION studies

ASCORE+/+RF+ onlyACPA+ only−/−(n = 1079)(n = 142)(n = 184)(n = 343)Age, years57.1 (12.8)58.2 (11.8)57.4 (13.5)57.8 (13.9)DAS28 (CRP)4.7 (1.2)4.6 (1.1)4.4 (1.0)4.8 (1.2)CDAI26.6 (12.5)25.8 (12.0)23.6 (10.9)28.2 (13.2)SDAI28.1 (13.0)27.2 (12.4)24.4 (10.8)29.7 (13.9)ACTION+/+RF+ onlyACPA+ only−/−(n = 1028)(n = 161)(n = 98)(n = 392)Age, years58.2 (12.0)58.4 (13.4)58.5 (14.0)57.0 (13.3)DAS28 (CRP)4.9 (1.1)5.0 (1.1)4.9 (1.0)5.0 (1.1)CDAI28.7 (12.2)29.2 (12.4)28.7 (11.5)30.1 (12.9)SDAI30.4 (13.1)31.2 (13.4)29.8 (11.5)31.7 (13.4)

Data are mean (SD). Patients with missing data for baseline ACPA/RF status are excluded.

Conclusion

In this post hoc analysis of the real-world ACTION and ASCORE studies, ACPA positivity was associated with an increased likelihood of retention over 2 years. Patients with ACPA+ only RA were equally as likely to be retained on abatacept as patients with ACPA/RF double positivity. In contrast, patients with RF+ only RA were less likely to be retained on abatacept over 2 years. These findings suggest that ACPA positivity played a more important role than RF positivity in abatacept retention. The higher retention seen in patients with ACPA+ only vs RF+ only disease demonstrates the key role of ACPA in RA and supports the importance of precision medicine in treating patients.

References

[1]Fraenkel L, et al. Arthritis Care Res (Hoboken) 2021;73:924–39.

[2]Smolen JS, et al. Ann Rheum Dis 2020;79:685–99.

[3]Alten R, et al. Clin Rheumatol 2019;38:1413–24.

[4]Alten R, et al. Ann Rheum Dis 2021;80(suppl 1):OP0180.

Acknowledgements

This study was sponsored by Bristol Myers Squibb. Medical writing and editorial assistance was provided by Fiona Boswell, PhD, of Caudex, and was funded by Bristol Myers Squibb. Study management provided by Syneos (CRO).

Disclosure of Interests

Rieke Alten Speakers bureau: AbbVie, Bristol Myers Squibb, Celltrion, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Paid instructor for: AbbVie, Bristol Myers Squibb, Celltrion, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Consultant of: AbbVie, Bristol Myers Squibb, Celltrion, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Grant/research support from: AbbVie, Bristol Myers Squibb, Celltrion, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Christiane Rauch Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Melanie Chartier Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, M.T. Nurmohamed Speakers bureau: AbbVie, Bristol Myers Squibb, Eli Lilly, Janssen, Pfizer, Consultant of: AbbVie, Bristol Myers Squibb, Eli Lilly, Janssen, Pfizer, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Janssen, MSD, Pfizer, Sean Connolly Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Galapagos, Gilead, Pfizer, Grant/research support from: Gilead, Pfizer, UCB, Peter Peichl Speakers bureau: GlaxoSmithKline, Janssen, Xavier Mariette Consultant of: Bristol Myers Squibb, Galapagos, GlaxoSmithKline, Janssen, Novartis, Pfizer, Sanofi, UCB, Yusuf Patel: None declared, Sara Marsal Speakers bureau: Bristol Myers Squibb, Lilly, MSD, Novartis - Sandoz, Pfizer, Roche, Consultant of: AbbVie, Galapagos, Pfizer, Sanofi; IMIDomics (executive role), Grant/research support from: AbbVie, Bristol Myers Squibb, Galapagos, Janssen, Lilly, MSD, Novartis - Sandoz, Pfizer, Roche, Sanofi, UCB, Roberto Caporali Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Fresenius-Kabi, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, Sandoz, UCB, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Sandoz, UCB, Hedley Griffiths Consultant of: Amgen, Raimón Sanmartí Speakers bureau: AbbVie, Bristol Myers Squibb, Lilly, MSD, Pfizer, Roche, Sanofi, Grant/research support from: AbbVie, Bristol Myers Squibb, MSD, Pfizer, Roche, Bettina Bannert Speakers bureau: Novartis Pharma Schweiz AG, Yedid Elbez Consultant of: Bristol Myers Squibb, Employee of: Signifience, Karissa Lozenski Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb.

POS0676 EFFICACY AND SAFETY OF FILGOTINIB IN PATIENTS AGED ≥75 YEARS: A POST HOC SUBGROUP ANALYSIS OF THE FINCH 4 LONG-TERM EXTENSION (LTE) STUDY

Background

Filgotinib (FIL) is a Janus kinase 1 preferential inhibitor for the treatment of moderate to severe rheumatoid arthritis (RA)1. The recommended dose for adults with RA is 200 mg (FIL200); however, a starting dose of 100 mg (FIL100) is recommended for those aged ≥75 years (y) in view of limited clinical experience1. An important consideration is the generally higher incidence of adverse events (AEs) in the elderly due to comorbidities.

Objectives

To evaluate the efficacy and safety of FIL100 and FIL200 in patients with RA aged ≥75 y.

Methods

FINCH 4 (NCT03025308) is an ongoing phase 3 open-label LTE study of FIL100 and FIL200 for RA. Eligible patients completed a prior phase 3 randomized double-blind study of FIL lasting 52 weeks (FINCH 1 or 3) or 24 weeks (FINCH 2). In this post hoc analysis, safety and efficacy were assessed in patients aged <75 and ≥75 y in FINCH 4. Efficacy measures were American College of Rheumatology (ACR)20/50/70 responses, clinical disease activity index (CDAI) ≤10/≤2.8, disease activity score (DAS)28 <2.6/≤3.2 and health assessment questionnaire-disability index (HAQ-DI).

Results

At LTE Week 48, 52% and 44% of patients aged <75 and ≥75 y, respectively, were on methotrexate. In both age groups, response rates for key efficacy measures at LTE Week 48 were generally maintained from LTE baseline (Figure 1) in patients with and without prior FIL exposure in FINCH 1–3, and were numerically higher with FIL200 vs FIL100. Mean change from baseline in HAQ-DI with FIL200 and FIL100 was 0.61 and 0.74 in those aged <75 y and 1.04 and 0.98 in those aged ≥75 y, respectively.

Figure 1.

The exposure-adjusted incidence rate (EAIR) of serious AEs and AEs of special interest (AESI) was generally higher in patients aged ≥75 y than <75 y. In those aged ≥75 y, the EAIR of AEs leading to premature study discontinuation, treatment-emergent AEs (TEAEs), and serious TEAEs was higher with FIL200 vs FIL100; the incidence of major adverse cardiovascular events, venous thrombotic and embolic events, serious infections, herpes zoster and malignancies was low in both dose groups (Table 1). Three patients died, all from the FIL200 group; each had a medical history relevant to the cause of death.

Table 1.

Exposure-adjusted incidence rate (95% CI) of AEs at Week 48 as events per 100 years of exposure

FIL200FIL100Age, years<75≥75<75≥75n=1469n=61n=1136n=63(PYE 2253.9)(PYE 92.2)(PYE 1753.7)(PYE 98.4)With prior FIL exposure, n (%)1142 (77.7)53 (86.9)830 (73.1)33 (52.4)TEAE48.3 (45.5, 51.3)55.3 (42.1, 72.8)48.7 (45.5, 52.1)42.7 (31.6, 57.8)Serious TEAE6.8 (5.8, 8.0)17.4 (10.6, 28.3)7.4 (6.2, 8.7)14.2 (8.4, 24.0)AE leading to premature study discontinuation2.9 (2.3, 3.7)9.8 (5.1, 18.8)3.9 (3.1, 5.0)4.1 (1.5, 10.8)AE leading to death0.5 (0.3, 0.9)3.3 (0.7, 9.5)*0.3 (0.2, 0.8)0.0 (0.0, 3.8)Infections28.8 (26.6, 31.1)29.3 (20.1, 42.7)27.4 (25.0, 29.9)26.4 (18.0, 38.8)Serious infections1.6 (1.2, 2.2)2.2 (0.5, 8.7)1.7 (1.1, 2.4)3.1 (1.0, 9.5)Herpes zoster1.6 (1.2, 2.3)2.2 (0.5, 8.7)1.0 (0.6, 1.6)3.1 (1.0, 9.5)Adjudicated major adverse cardiovascular event0.4 (0.2, 0.7)2.2 (0.5, 8.7)0.5 (0.2, 0.9)1.0 (0.1, 7.2)Venous thrombotic and embolic events0.3 (0.1, 0.6)2.2 (0.5, 8.7)0.2 (0.1, 0.5)1.0 (0.1, 7.2)Malignancy excluding NMSC0.7 (0.4, 1.2)4.3 (1.6, 11.6)0.7 (0.4, 1.2)3.1 (1.0, 9.5)NMSC0.4 (0.2, 0.8)1.1 (0.0, 6.0)0.2 (0.1, 0.6)0.0 (0.0, 3.8)

*Cause of death: esophageal carcinoma; cardiovascular; unknown. FIL(100/200), filgotinib (100/200 mg); NMSC, nonmelanoma skin cancer; PYE, patient years of exposure; (TE)AE, (treatment-emergent) adverse event

Conclusion

In the ≥75 y group, response rates for key efficacy measures remained stable to Week 48 and were generally higher with FIL200 vs FIL100. The incidence of serious AEs and AESI was higher in those aged ≥75 than <75 y. Patient numbers/exposure time may have been insufficient to show potential between-group differences in safety/efficacy outcomes.

References

[1]Filgotinib SmPC

Acknowledgements

The FINCH studies were funded by Gilead Sciences (Foster City, CA, United States). We thank the physicians and patients who participated in the studies. Medical writing support was provided by Debbie Sherwood, BSc (Aspire Scientific Ltd, Bollington, UK) and funded by Galapagos NV (Mechelen, Belgium).

Disclosure of Interests

Daniel Aletaha Speakers bureau: AbbVie, Amgen, Lilly, Janssen, Merck, Novartis, Pfizer, Roche, and Sandoz, Consultant of: AbbVie, Amgen, Lilly, Janssen, Merck, Novartis, Pfizer, Roche, and Sandoz, Grant/research support from: AbbVie, Amgen, Lilly, Novartis, Roche, SoBi, and Sanofi, Rene Westhovens Speakers bureau: Celltrion, Galapagos, and Gilead, Consultant of: Celltrion, Galapagos, and Gilead, Bernard Combe Speakers bureau: AbbVie, BMS, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, MSD, Novartis, Pfizer, and Roche-Chugai, Consultant of: AbbVie, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, and Roche-Chugai, Jacques-Eric Gottenberg Consultant of: AbbVie, BMS, Galapagos, Gilead, Lilly, and Pfizer, Grant/research support from: BMS and Pfizer, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Galapagos, Gilead, and Pfizer, Grant/research support from: Gilead and Pfizer, Roberto Caporali Speakers bureau: AbbVie, Amgen, BMS, Celltrion, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Sandoz, and UCB, Consultant of: AbbVie, Amgen, BMS, Celltrion, Fresenius-Kabi, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, Sandoz, and UCB, José A Gómez-Puerta Speakers bureau: AbbVie, BMS, Galapagos, GSK, Lilly, MSD, Novartis, Pfizer, Roche, and Sanofi, Consultant of: GSK, Roche, and Sanofi, Paul Van Hoek Employee of: Galapagos, Vijay Rajendran Employee of: Galapagos, Pieter-Jan Stiers Shareholder of: Galapagos, Employee of: Galapagos, Thijs Hendrikx Employee of: Galapagos, Gerd Rüdiger Burmester Consultant of: AbbVie, Amgen, BMS, Galapagos, Lilly, MSD, Pfizer, Roche, and Sanofi, Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, Astra-Zeneca, Boehringer-Ingelheim, BMS, 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: AbbVie, Asahi-Kasei, Boehringer-Ingelheim, Chugai, Corrona, Daiichi-Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda

POS0107 ACPA POSITIVITY DETERMINES REMISSION IN PATIENTS WITH RA TREATED WITH IV AND SC ABATACEPT: A POST HOC ANALYSIS OF THE REAL-WORLD OBSERVATIONAL ACTION AND ASCORE STUDIES

Background

The goal of treatment for RA is achieving low disease activity and/or remission1,2; however, disease course and management can be complicated by additional factors that may be influenced by serostatus. Anti-citrullinated protein antibodies (ACPAs) and RF contribute to a more severe RA disease pattern3 and may be useful in predicting response to treatment.4 ACTION (AbataCepT In rOutiNe clinical practice; NCT02109666) and ASCORE (Abatacept SubCutaneOus in Routine Clinical PracticE; NCT02090556) were 2-year, international, observational, prospective, multicenter studies of IV and SC abatacept, respectively, for the treatment of RA in routine clinical practice.4,5 Previous analyses have shown that ACPA/RF double-positive serostatus was associated with better treatment outcomes compared with ACPA/RF double-negative serostatus.4–6

Objectives

To assess the independent effect of ACPA or RF single seropositivity among patients with RA on achieving remission after treatment with abatacept for 2 years, and to compare outcomes among patients with single versus double serostatus.

Methods

This post hoc analysis included patients from ACTION and ASCORE who initiated IV (body weight–adjusted dosing) or SC abatacept (125 mg once weekly), respectively. Patients were stratified by baseline ACPA/RF status: ACPA+/RF− (ACPA+ only), ACPA/RF double positive (+/+), ACPA−/RF+ (RF+ only), and ACPA/RF double negative (−/−). DAS28 (CRP) and CDAI remission rates (defined as < 2.6 and 0–2.8, respectively) at 2 years for patients who were ACPA+ or RF+ only at baseline were assessed and compared with those who were +/+ and −/−. Patients with missing baseline ACPA/RF status were excluded. Last observation carried forward efficacy analyses were used to impute missing values.

Results

This analysis included 1679 patients from ACTION (ACPA+ only, n = 98; +/+, n = 1028; RF+ only, n = 161; and −/−, n = 392) and 1748 patients from ASCORE (ACPA+ only, n = 184; +/+, n = 1079; RF+ only, n = 142; and −/−, n = 343). Across studies and serogroups, baseline demographics and disease characteristics were similar (data not shown). In both ACTION and ASCORE, a higher proportion of patients who were only ACPA+ achieved DAS28 (CRP) and CDAI remission at 2 years compared with patients who were only RF+ (Figure 1). Additionally, a similar proportion of patients who were only ACPA+ achieved DAS28 (CRP) and CDAI remission at 2 years compared with patients who were +/+. In contrast, a lower proportion of patients who were only RF+ achieved DAS28 (CRP) and CDAI remission at 2 years compared with patients who were +/+.

Conclusion

In this post hoc analysis of real-world data from ACTION and ASCORE, ACPA positivity was associated with an increased likelihood of achieving DAS28 (CRP) and CDAI remission at 2 years. Patients who were ACPA+ only were as likely to achieve remission as +/+ patients, suggesting that RF serostatus had less influence than ACPA serostatus on remission status at 2 years. In line with this, patients who were RF+ only were less likely to achieve remission at 2 years. This is the first large, real-world study to show that ACPA positivity plays a more important role than RF positivity in achieving remission whilst on abatacept. These results highlight the importance of assessing baseline ACPA status when considering treatment options for patients with RA.

References

[1]Smolen JS, et al. Ann Rheum Dis 2020;79:685–99.

[2]Fraenkel L, et al. Arthritis Care Res (Hoboken) 2021;73:924–39.

[3]Katchamart, W, et al. Rheumatol Int 2015;35:1693–9.

[4]Alten R, et al. Ann Rheum Dis 2021;80(suppl 1):OP0180.

[5]Alten R, et al. Clin Rheumatol 2019;38:1413–24.

[6]Alten R, et al. RMD Open 2017;3:e000345.

Acknowledgements

This study was sponsored by Bristol Myers Squibb. Medical writing and editorial assistance was provided by Rachel Rankin, PhD, of Caudex, and was funded by Bristol Myers Squibb. Study management provided by Syneos (CRO).

Disclosure of Interests

Rieke Alten Speakers bureau: AbbVie, Bristol Myers Squibb, Celltrion, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Paid instructor for: AbbVie, Bristol Myers Squibb, Celltrion, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Consultant of: AbbVie, Bristol Myers Squibb, Celltrion, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Grant/research support from: AbbVie, Bristol Myers Squibb, Celltrion, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Roche, Christiane Rauch Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Melanie Chartier Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, M.T. Nurmohamed Speakers bureau: AbbVie, Bristol Myers Squibb, Eli Lilly, Janssen, Pfizer, Consultant of: AbbVie, Bristol Myers Squibb, Eli Lilly, Janssen, Pfizer, Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Eli Lilly, Galapagos, Janssen, MSD, Pfizer, Sean Connolly Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Galapagos, Gilead, Pfizer, Grant/research support from: Gilead, Pfizer, UCB, Peter Peichl Speakers bureau: Janssen, GlaxoSmithKline, Xavier Mariette Consultant of: Bristol Myers Squibb, Galapagos, GlaxoSmithKline, Janssen, Novartis, Pfizer, Sanofi, UCB, Yusuf Patel: None declared, Sara Marsal Speakers bureau: Bristol Myers Squibb, Lilly, MSD, Novartis - Sandoz, Pfizer, Roche, Consultant of: AbbVie, Galapagos, Pfizer, Sanofi; IMIDomics (executive role), Grant/research support from: AbbVie, Bristol Myers Squibb, Galapagos, Janssen, Lilly, MSD, Novartis - Sandoz, Pfizer, Roche, Sanofi, UCB, Roberto Caporali Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Fresenius-Kabi, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, Sandoz, UCB, Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Sandoz, UCB, Hedley Griffiths Consultant of: Amgen, Raimón Sanmartí Speakers bureau: AbbVie, Bristol Myers Squibb, Lilly, MSD, Pfizer, Roche, Sanofi, Grant/research support from: AbbVie, Bristol Myers Squibb, MSD, Pfizer, Roche, Bettina Bannert: None declared, Yedid Elbez Consultant of: Bristol Myers Squibb, Employee of: Signifience, Karissa Lozenski Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb

OP0082 DISCORDANCE BETWEEN DAS28ESR AND PRESENCE OF ULTRASOUND POWER DOPPLER DURING EARLY TREATMENT IS ASSOCIATED WITH DISTINCT CLINICAL AND IMAGING PHENOTYPES AT PRESENTATION

Background

Discordance between DAS28ESR and musculoskeletal ultrasound (MSUS) detected power Doppler synovitis (PDUS) is well-recognised and may lead to under/overtreatment. We hypothesize that clinical and imaging features at diagnosis associate with early discordance of DAS28-PDUS and change in DAS28-PDUS status following DMARD treatment.

Objectives

To identify pre-treatment clinical factors associated with discordance and change in DAS28-PDUS status during early treatment in an early RA trial cohort.

Methods

The ‘VEDERA’ trial1 randomised 120 treatment-naïve, new-onset RA patients to either first-line etanercept + methotrexate (ETN+MTX) or methotrexate treat-to-target (MTX-TT) regime with escalation to ETN+MTX if not in DAS28ESR remission at week 24. Clinical and MSUS assessments were completed at baseline, weeks 12, 24 and 48. DAS28ESR ≤ 2.6 and DAS28ESR > 2.6 categorised remission and active disease respectively. PDUS presence was defined as total PDUS score ≥ 1. Active concordance (AC) was defined as active disease with PDUS while active discordance (AD) was defined as active disease without PDUS. Remission concordance (RC) was defined as DAS28ESR remission without PDUS while remission discordance (RD) was defined as DAS28ESR remission with PDUS. Bayesian multinomial logistic regression (posterior estimate and 95% credible intervals reported) was used to address the study objectives with AC as the comparator group.

Results

At baseline all patients had active disease (moderate or high DAS28ESR) in line with trial eligibility - 68% (81/120) were AC and 32% (39/120) were AD. Compared to AD patients, AC patients were older (median age 53 vs 44), had higher DAS28ESR (5.90 vs 5.16) and CRP (11.6mg/L vs 3.6mg/L), as well as a higher presence of greyscale (GS - 100% vs 67%), power Doppler tenosynovitis (PDTS - 78% vs 49%) and erosions (20% vs 0) (p < 0.01). Figure 1 illustrates the pre-treatment proportions and change in group proportions at each timepoint, revealing an early shift of AC to AD (36% by week 12) or RC (22% by week 12) but persistence of those in AD from baseline at subsequent timepoints (64% at week 12). Baseline characteristics associated with each group compared to the comparator AC group (at weeks 12, 24 and 48) are reported in Table 1. For AD versus AC these were lower CRP at week 12 and female sex at week 24. For RC versus AC these were lower CRP and allocation to ETN+MTX at week 12, allocation to ETN+MTX and presence of PDTS at week 24 and younger age at week 48. For RD versus AC these were presence of PDTS at week 24 and male sex at week 48.

Table 1.

Baseline characteristics associated with longitudinal discordance vs concordance. AC is the comparator group. Results in posterior estimate with 95% credible intervals

Week 12Week 24Week 48AD vs ACFemale0.53 (-0.44 to 1.48)1.52 (0.51 to 2.59)0.17(-0.91 to 1.25)CRP-0.05 (-0.1 to -0.01)-0.01 (-0.04 to 0.05)0.01(-0.02 to 0.02)RC vs ACAge at diagnosis-0.04(-0.09 to 0.01)-0.02(-0.06 to 0.03)-0.08(-0.13 to -0.03)CRP-0.05 (-0.10 to -0.01)0.001(-0.04 to 0.03)0.01(-0.02 to 0.04)ETN+MTX1.57, (0.57 to 2.64)1.26, (0.29 to 2.33)0.91(-0.02 to 1.85)PDTS0.58 (-0.5 to 1.68)1.23(0.2 to 2.29)0.8 (-0.2 to 1.83)RD vs ACFemale0.23 (-1.26 to 1.72)0.9 (-0.41 to 2.26)-1.59(-2.9 to -0.35)PDTS1.00 (-0.55 to 2.69)1.79 (0.44 to 3.33)0.95(-0.29 to 2.27)

Conclusion

DAS28ESR and PDUS discordance and concordance have distinct clinical and imaging phenotypes at presentation. Baseline active concordance and discordance respond differently to treatment –a sizeable proportion of former transition into active discordance early on and the latter persist in the face of effective treatment. Understanding the basis for these phenotypes is essential to facilitate optimal aggressive treatment and/or alternative management strategies.

References

[1]Emery P, Horton S, Dumitru RB, et al. Pragmatic randomised controlled trial of very early etanercept and MTX versus MTX with delayed etanercept in RA: The VEDERA trial. Ann Rheum Dis. 2020;79(4):464–71.

Disclosure of Interests

None declared.

AB0394 CLINICAL OUTCOMES UP TO WEEK 48 OF ONGOING FILGOTINIB (FIL) RHEUMATOID ARTHRITIS (RA) LONG-TERM EXTENSION (LTE) TRIAL OF BIOLOGIC DISEASE-MODIFYING ANTIRHEUMATIC DRUG (bDMARD) INADEQUATE RESPONDERS (IR) INITIALLY ON FIL OR PLACEBO IN A PHASE 3 PARENT STUDY (PS)

Background

The preferential Janus kinase-1 inhibitor FIL is approved for treatment of moderate to severe active RA in Europe and Japan.

Objectives

Efficacy and safety of FIL were assessed in patients (pts) with IR to bDMARDs in a LTE trial (NCT03025308) enrolled from a Phase 3 PS (NCT02873936).1

Methods

bDMARD-IR pts received FIL 200 mg (FIL200), FIL 100 mg (FIL100), or placebo (PBO), all with stable conventional synthetic (cs)DMARDs up to 24 weeks (W). At W14 of the PS, pts with IR to FIL or PBO (<20% improvement in swollen [66] and tender [68] joint counts) switched to standard of care (SOC; investigator’s choice of treatment). Pts completing the PS on FIL, PBO, or SOC could enter the LTE. PS FIL pts were maintained, blinded, on their FIL dose; PS PBO and PS SOC pts were rerandomized, blinded, to FIL200 or FIL100. Efficacy data to LTE W48 and safety data to data cutoff (June 1, 2020) are reported.

Results

The PS included 147, 153, and 148 pts on FIL200, FIL100, and PBO. Pts continuing on LTE FIL200 and FIL100 at data cutoff: 80/121 (66%) and 76/110 (69%) from PS FIL200 and FIL100; 35/47 (75%) and 32/46 (70%) from PS PBO, and 13/23 (57%) and 13/22 (59%) from PS SOC. LTE baseline (BL) characteristics were similar in FIL200 and FIL100 pts. During LTE, PS FIL ACR20/50/70 response rates decreased modestly by W48 (Figure 1). Among PS PBO pts, response rates were lower at LTE BL, reaching similar levels to PS FIL pts by W48; rates increased to W48 in PS SOC pts on either FIL dose but not to levels of other groups. Percentages of pts attaining DAS28(CRP) ≤3.2, DAS28(CRP) <2.6, CDAI ≤10, and CDAI ≤2.8 were maintained up to W48 for FIL/FIL pts. PBO/FIL and SOC/FIL pts showed similar patterns to ACR responses (Figure 1). Exposure-adjusted incidence rates (EAIRs)/100 pt-years of exposure for treatment-emergent adverse events (TEAE), serious AEs, and serious infection were higher in SOC/FIL pts vs FIL/FIL or PBO/FIL pts, but samples were small and confidence intervals overlapped. There were 5 deaths (Table 1).

Table 1.

EAIRs of TEAEs in LTE, as of June 1, 2020

EAIR (95% CI)FIL200+csD → FIL200+csD n=121PYE 228.4PBO+csD → FIL200+csD n=47PYE 98.1SOC+csD → FIL200+csD n=23PYE 42.1FIL100+csD → FIL100+csD n=110PYE 223.3PBO+csD → FIL100+csD n=46PYE 91.1SOC+csD → FIL100+csD n=22PYE 38.2TEAE46.9 (38.8, 56.6)38.7 (28.2, 53.2)52.2 (34.4, 79.3)40.3 (32.8, 49.5)40.6 (29.4, 56.1)49.8 (31.8, 78.0)TEAE Grade ≥310.5 (7.0, 15.7)10.2 (5.5, 18.9)19.0 (9.5, 38.0)10.3 (6.8, 15.5)13.2 (7.5, 23.2)18.3 (8.7, 38.5)TE serious AE12.3 (8.5, 17.8)12.2 (6.9, 21.5)21.4 (11.1, 41.1)8.1 (5.1, 12.8)13.2 (7.5, 23.2)21.0 (10.5, 41.9)Death1.3 (0.4, 4.1)1.0 (0, 5.7)0 (0, 8.8)0.4 (0.1, 3.2)0 (0, 4.0)0 (0, 9.7)TE infections34.2 (27.4, 42.6)22.4 (14.8, 34.1)35.6 (21.5, 59.1)22.4 (17.0, 29.5)26.3 (17.7, 39.3)39.3 (23.7, 65.2)TE serious infections3.5 (1.8, 7.0)2.0 (0.5, 8.2)7.1 (2.3, 22.1)0.9 (0.2, 3.6)2.2 (0.5, 8.8)7.9 (2.5, 24.4)Opportunistic infections0 (0, 1.6)0 (0, 3.8)0 (0, 8.8)0 (0, 1.7)0 (0, 4.0)0 (0, 9.7)TE herpes zoster2.2 (0.7, 5.1)1.0 (0.1, 7.2)0 (0, 8.8)0 (0, 1.7)2.2 (0.5, 8.8)2.6 (0.1, 14.6)TE MACE (adjudicated)1.3 (0.4, 4.1)1.0 (0.1, 7.2)0 (0, 8.8)0.9 (0.2, 3.6)1.1 (0.2, 7.8)0 (0, 9.7)TE DVT/PE (adjudicated)0.9 (0.2, 3.5)0 (0, 3.8)2.4 (0.1, 13.2)0.4 (0.1, 3.2)0 (0, 4.0)0 (0, 9.7)Malignancies (excluding NMSC)1.3 (0.4, 4.1)3.1 (1.0, 9.5)4.7 (0.6, 17.2)1.8 (0.7, 4.8)3.3 (1.1, 10.2)0 (0, 9.7)NMSC0 (0, 1.6)0 (0, 3.8)4.7 (0.6, 17.2)0 (0, 1.7)0 (0, 4.0)0 (0, 9.7)

DVT, deep vein thrombosis; MACE, major adverse cardiovascular event; NMSC, nonmelanoma skin cancer; PE, pulmonary embolism; TE, treatment-emergent

Conclusion

Efficacy was mostly maintained in PS FIL pts up to W48. Response among PS PBO and SOC pts increased from BL to W48, but response in PS SOC pts continued to be lower than in other groups; these pts may represent a refractory population. FIL safety was largely consistent between PS and LTE.

References

[1]Genovese MC et al. JAMA 2019;322:315–25.

Acknowledgements

This study was funded by Gilead Sciences, Inc., Foster City, CA. Medical writing support was provided by Claudine Bitel, PhD, of AlphaScientia, LLC, San Francisco, CA; and funded by Gilead Sciences, Inc., Foster City, CA.

Disclosure of Interests

Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Galapagos, Gilead, and Pfizer, Grant/research support from: Gilead and Pfizer, Tsutomu Takeuchi Speakers bureau: AbbVie, AYUMI, Bristol Myers Squibb, Chugai, Daiichi Sankyo, Dainippon Sumitomo, Eisai, Eli Lilly Japan, Gilead Sciences, Mitsubishi-Tanabe, Novartis, Pfizer Japan, and Sanofi, 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, Vijay Rajendran Shareholder of: Galapagos, Employee of: Galapagos, Jacques-Eric Gottenberg Speakers bureau: AbbVie, Eli Lilly and Co., Galapagos, Gilead Sciences, Inc., Roche, Sanofi Genzyme, and UCB, Consultant of: Bristol Myers Squibb, Sanofi Genzyme, and UCB, Grant/research support from: Bristol Myers Squibb and Pfizer, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., YingMeei Tan Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Qi Gong Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Katrien Van Beneden Shareholder of: Galapagos, Employee of: Galapagos, Roberto Caporali Speakers bureau: AbbVie, Amgen, BMS, Celltrion, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Sandoz, and UCB, Consultant of: AbbVie, Amgen, BMS, Celltrion, Galapagos, Janssen, Lilly, Fresenius-Kabi, MSD, Novartis, Pfizer, Roche, Sandoz, and UCB

POS0633 HIGH SENSITIVITY TROPONIN I IS ASSOCIATED WITH FOCAL FIBROSIS AS DETECTED BY CARDIAC MR IN EARLY, TREATMENT-NAIVE RA

Background

RA individuals are known to have excess CVD risk, equivalent to that of type 2 diabetes mellitus1. We recently reported vascular and myocardial abnormalities on cardiac magnetic resonance imaging (CMR) in an early RA cohort compared with control subjects, and improvement with DMARD treatment2. Non-invasive assays for high-sensitivity troponin and NT-pro-BNP have been evaluated in RA cohorts. No study has investigated these in early, treatment-naïve RA and in association with subclinical CMR findings.

Objectives

In a treatment-naïve, early RA trial cohort, we examined serum cardiac markers of ventricular stretch (NT-pro-BNP) and myocardial injury (high-sensitivity troponin-I (hs-Tn-I)) and change with treatment, and whether these associated with cardiac MRI abnormalities.

Methods

In CADERA (a unique early RA RCT derived study), out of a total of 120 patients randomised to either first-line TNFi+MTX (n=60) or MTX and conventional synthetic DMARDs (n=60), 81 subjects with no previous history of CVD or diabetes and with only a maximum of 1 other traditional risk factor, underwent baseline and year 1 CMR. Corresponding levels of NT-pro-BNP (pg/ml) and hs-Tn-I (ng/L) were measured at baseline and year 1. CADERA reported CMR measures of vascular stiffness [aortic stiffness index (AoSI), and aortic distensibility (AD)]; tissue oedema/fibrosis [native T1 values (T1), myocardial extracellular volume (ECV), and late gadolinium enhancement (LGE)] and ventricular function 2. Bayesian linear and logistic regression models with mixed effects for overall data were used to test association between serum cardiac markers and CMR parameters.

Results

CADERA trial already reported baseline demographics and comorbidity data of patients. The most common risk factor was smoking history (55%) followed by hypertension (7%) and family history of ischaemic heart disease (5%)2. 7 patients had abnormal findings on LGE imaging at baseline and 4 at year 1.2

From baseline to year 1, NT-pro-BNP remained within normal limits although a numerical improvement was noted at year 1(76.4 to 59.4, p = 0.038). Hs-Tn-I was within normal limits (<3ng/L) with no significant change noted (1.62 to 1.7).

At baseline, median hs-Tn-I was 2 (IQR 1.4 - 3.05) in patients with abnormal LGE findings compared to 1.60 (0.95 – 2.52) in those without (p = 0.3). At year 1, median hs-Tn-I was 2.70 (IQR 1.08 – 4.82) in patients with abnormal LGE findings versus 1.7 (IQR 1 – 2.5) in those without (p = 0.5). Table 1 outlines the association of serum cardiac markers with CMR parameters. At baseline, hs-Tn-I positively associated with LGE. This association was also demonstrated when considering overall data (baseline + week 48). Association of NT-pro-BNP with CMR was not significant.

Table 1.

Association of serum Hs-Tn-I with CMR parameters (posterior estimates with 95% credible intervals reported)

CMR parameterHs-Tn-IOverallBaselineYear 1Measures of myocardial tissue oedema/fibrosisLGE0.56(0.1 to 1.11)0.6(0.04 to 1.27)0.54(-0.13 to 1.17)T1-4.42(-10.5 to 1.5)-0.38(-6.7 to 6.2)-6.02(-14.9 to 3.15)ECV0.002(-0.04 to 0.080.001(-0.05 to 0.07)0.001(-0.04 to 0.04)Measures of vascular stiffnessAoSI0.01(-0.23 to 0.25)0.05(-0.22 to 0.33)0.05(-0.33 to 0.42)AD-0.05(-0.23 to 0.13)-0.02(-0.18 to 0.14)-0.06(-0.37 to 0.25)

Conclusion

Our data suggest hs-Tn-I is within normal limits in a treatment-naïve, RA cohort but with numerical differences that associated with presence of focal fibrosis on CMR. Modest numbers of those with focal fibrosis may account for normal range values for hs-Tn-I.

References

[1]Peters MJL, Van Halm VP, Voskuyl AE, et al. Does rheumatoid arthritis equal diabetes mellitus as an independent risk factor for cardiovascular disease? A prospective study. Arthritis Care Res. 2009;61(11).

[2]Plein S, Erhayiem B, Fent G, et al. Using cardiovascular magnetic resonance to define mechanisms of comorbidity and to measure the effect of biological therapy: the CADERA observational study. Effic Mech Eval. 2021;8(4):1–42.

Disclosure of Interests

None declared

POS0704 EFFICACY AND SAFETY OF FILGOTINIB IN PATIENTS WITH INADEQUATE RESPONSE TO METHOTREXATE, WITH 4 OR <4 POOR PROGNOSTIC FACTORS: A POST HOC ANALYSIS OF THE FINCH 1 STUDY

Background

Patients (pts) with rheumatoid arthritis (RA) and poor prognostic factors1 (PPF) are at risk for progression without adequate treatment. Filgotinib (FIL) is a once daily Janus kinase 1 preferential inhibitor. In FINCH 1 (NCT02889796), FIL 200 mg (FIL200) was effective vs placebo (PBO) and noninferior to adalimumab (ADA) in pts with RA and inadequate response to methotrexate (MTX-IR); FIL200 and FIL 100 mg (FIL100) were well tolerated.2

Objectives

This post hoc, exploratory analysis examined efficacy and safety of FIL in MTX-IR pts with 4 or <4 PPF.

Methods

The FINCH 1 52-week (W), double-blind trial randomised MTX-IR pts with moderate–severe RA to FIL200 or FIL100, ADA, or PBO; all received background MTX. PBO pts were rerandomised, blinded, at W24 to FIL200 or FIL100. We examined pts with 4 PPF at baseline (BL): erosions on X-ray, seropositivity for rheumatoid factor or anticyclic citrullinated peptide, high-sensitivity C-reactive protein (hsCRP) ≥6 mg/L, and disease activity score in 28 joints with CRP (DAS28[CRP]) >5.1, along with those with <4 PPF. Efficacy included DAS28(CRP) <2.6 and modified Total Sharp Score (mTSS) change from baseline (CFB). Fisher’s exact test was used for DAS28(CRP); the mixed-effects model was used to generate least squares mean mTSS CFB. P values were nominal, not adjusted for multiplicity.

Results

At BL, of 1755 randomized, treated pts, 687 had 4 PPF, and 1068 had <4 PPF. Among pts with <4PPF, 804 [75%] had erosions, 810 [76%] were seropositive, 377 [35%] had hsCRP ≥6 mg/L, 638 [60%] had DAS28[CRP] >5.1). Pts with 4 vs <4 PPF were aged 53 vs 52 years, had RA duration 8.3 vs 7.4 years, DAS28(CRP) 6.3 vs 5.4, and SDAI 45.6 vs 37.7. In pts with 4 or <4 PPF, higher proportions receiving FIL200 or FIL100 achieved DAS28(CRP) <2.6 at W12 vs PBO (nominal P <.001); proportions with DAS28(CRP) <2.6 increased with FIL200, FIL100, or ADA at W52 (Figure 1). DAS28(CRP) responses for FIL200 at W52 were similar in 4 vs <4 PPF pts; FIL100 and ADA responses were numerically higher in <4 vs 4 PPF pts. At W24, mTSS CFB in pts with 4 PPF was 0.21, 0.23, 0.30, and 0.66 for FIL200, FIL100, ADA, and PBO (P <.05 for FIL200 and FIL100 vs PBO); corresponding changes in <4 PPF pts were 0.08, 0.10, 0.11, and 0.24 (P >.05). At W52, mTSS CFB in 4 PPF pts was 0.29, 0.84, and 0.80 for FIL200, FIL100, and ADA, respectively, and 0.14, 0.25, and 0.53 in <4 PPF pts. Rates of adverse events (AEs), including AEs of interest, were comparable for pts with 4 PPF and <4 PPF for all treatment arms (Table 1).

Table 1.

AEs and AEs of interest in BL 4 PPF and <4 PPF subgroups

4 PPF<4 PPFFIL200FIL100ADAPBO beforeFIL200FIL100ADAPBO(n = 191)(n = 189)(n = 126)W24 switch (n = 181)(n = 284)(n = 291)(n = 199)before W24 switch (n = 294)All AEs146 (76.4)136 (72.0)85 (67.5)90 (49.7)206 (72.5)214 (73.5)154 (77.4)164 (55.8)AEs of interestSerious infectious AE5 (2.6)4 (2.1)6 (4.8)2 (1.1)8 (2.8)9 (3.1)4 (2.0)2 (0.7)Opportunistic infections001 (0.8)0001 (0.5)0Active tuberculosis0000001 (0.5)0Herpes zoster1 (0.5)1 (0.5)1 (0.8)05 (1.8)3 (1.0)1 (0.5)2 (0.7)Hepatitis B or C01 (0.5)001 (0.5)01 (0.5)0MACE01 (0.5)01 (0.6)01 (0.3)1 (0.5)1 (0.3)VTE001 (0.8)1 (0.6)1 (0.4)001 (0.3)DVT001 (0.8)1 (0.6)0001 (0.3)PE00001 (0.4)000Malignancy0003 (1.7)2 (0.7)2 (0.7)2 (1.0)0(non-NMSC)GI perforation00001 (0.4)000

Values are n (%). ADA, adalimumab; AE, adverse event; BL, baseline; DVT, deep vein thrombosis; FIL100, filgotinib 100 mg; FIL200; filgotinib 200 mg; GI, gastrointestinal; MACE, major adverse cardiac event; NMSC, nonmelanoma skin cancer; PBO, placebo; PE, pulmonary embolism; PPF, poor prognostic factor; VTE, venous thromboembolism; W, week.

Conclusion

In high-risk (4 PPF) pts with MTX-IR RA, FIL200 and FIL100 showed similar reductions in disease activity vs PBO at W12 as in pts with <4 PPF; mTSS in FIL200 pts changed little from W24 to W52. Tolerability was comparable across treatment arms, regardless of presence of 4 or <4 PPF.

References

[1]Smolen JS et al. Ann Rheum Dis. 2020;79:685–99.

[2]Combe B et al. Ann Rheum Dis. 2021;80:848–58.

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 was 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

Bernard Combe Speakers bureau: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and Roche-Chugai, Consultant of: AbbVie, Bristol-Myers Squibb, Celltrion, Eli Lilly, Gilead-Galapagos, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, and Roche-Chugai, Grant/research support from: Pfizer and Roche-Chugai, Yoshiya Tanaka Speakers bureau: AbbVie, Amgen, Astellas, AstraZeneca, Behringer-Ingelheim, Bristol-Myers, Chugai, Eisai, Eli Lilly, Gilead Sciences, Inc., Mitsubishi-Tanabe, and YL Biologics, Paid instructor for: AbbVie, Amgen, Astellas, AstraZeneca, Behringer-Ingelheim, Bristol-Myers, Chugai, Eisai, Eli Lilly, Gilead Sciences, Inc., Mitsubishi-Tanabe, and YL Biologics, Grant/research support from: AbbVie, Asahi-Kasei, Boehringer-Ingelheim, Chugai, Corrona, Daiichi-Sankyo, Eisai, Kowa, Mitsubishi-Tanabe, and Takeda, Maya H Buch Speakers bureau: AbbVie, Eli Lilly, Gilead Sciences, Inc., Merck-Serono, Pfizer, Roche, Sanofi, and UCB, Paid instructor for: AbbVie, Eli Lilly, Gilead Sciences, Inc., Merck-Serono, Pfizer, Roche, Sanofi, and UCB, Consultant of: AbbVie, Eli Lilly, Gilead Sciences, Inc., Merck-Serono, Pfizer, Roche, Sanofi, and UCB, Grant/research support from: AbbVie, Eli Lilly, Gilead Sciences, Inc., Merck-Serono, Pfizer, Roche, Sanofi, and UCB, Gerd Rüdiger Burmester Speakers bureau: AbbVie, Eli Lilly, Pfizer, and Gilead Sciences, Inc., Consultant of: AbbVie, Eli Lilly, Pfizer, and Gilead Sciences, Inc., Beatrix Bartok Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Alena Pechonkina 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., Thijs Hendrikx Employee of: Galapagos BV, Daniel Aletaha Speakers bureau: Bristol-Myers Squibb, Merck Sharp & Dohme, and UCB; AbbVie, Amgen, Celgene, Eli Lilly, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, and Sanofi/Genzyme., Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, and Sanofi/Genzyme; Janssen, Grant/research support from: from AbbVie, Merck Sharp & Dohme, Novartis, and Roche

POS0674 RISK FACTORS FOR MAJOR ADVERSE CARDIOVASCULAR EVENTS IN PATIENTS AGED ≥50 YEARS WITH RHEUMATOID ARTHRITIS AND ≥1 ADDITIONAL CARDIOVASCULAR RISK FACTOR: A POST HOC ANALYSIS OF ORAL SURVEILLANCE

Background

ORAL Surveillance (NCT02092467) was a post-approval safety study of tofacitinib vs TNF inhibitors (TNFi) in rheumatoid arthritis (RA) patients (pts) aged ≥50 yrs with ≥1 additional cardiovascular (CV) risk factor and an inadequate response to methotrexate (MTX).

Objectives

To identify independent risk factors for major adverse CV events (MACE) in ORAL Surveillance.

Methods

Pts on stable MTX were randomised 1:1:1 to receive tofacitinib 5 or 10 mg twice daily (BID) or a TNFi (adalimumab 40 mg every 2 weeks or etanercept 50 mg once weekly). Incidence rates (IRs; pts with first events/100 pt-yrs) and hazard ratios (HRs; tofacitinib vs TNFi) were assessed for adjudicated MACE (total/fatal/non-fatal), sudden cardiac death, and total/fatal/non-fatal myocardial infarction (MI) and stroke. Post hoc univariate Cox model analyses identified potentially independent baseline (BL) risk factors for MACE across treatments; those with p<0.10 were entered into a multivariate Cox model using backward selection (p<0.10 stay criteria). MACE HRs were produced for subgroups for BL risk factors with p<0.05 in the final multivariate Cox model.

Results

4362 pts were included (tofacitinib 5 mg BID, n=1455; tofacitinib 10 mg BID, n=1456; TNFi, n=1451). IRs for total/fatal/non-fatal MACE, sudden cardiac death, and total/non-fatal MI were higher with tofacitinib vs TNFi (Table 1). Fatal MI and stroke (including fatal/non-fatal events) IRs were similar across treatments (Table 1). Total MACE and MI IRs and risk were higher with tofacitinib vs TNFi (HRs >1) and higher for non-fatal MI for tofacitinib 5 mg BID (Table 1). Current smoking, aspirin use, history of chronic lung disease, history of diabetes, male sex and older age were BL risk factors for MACE. While MACE risk was generally higher with tofacitinib vs TNFi across all BL risk factors, increased risk was clearest in current/past smokers (vs never smoked) and aspirin users (vs non-users) (Figure 1). When age and smoking status were considered in combination, pts aged ≥65 yrs or who had ever smoked had a particularly elevated MACE risk vs never smokers aged ≥50–<65 yrs (Figure 1).

Table 1.

MACE, MI and stroke IRs (pts with first events/100 pt-yrs; 95% CI) and HRs (tofacitinib vs TNFi; 95% CI)

Tofacitinib 5 mg BID(N=1455)Tofacitinib 10 mg BID(N=1456)TNFi(N=1451)nIRHRnIRHRnIR(95% CI)(95% CI)(95% CI)(95% CI)(95% CI)MACE470.911.24511.051.43370.73(0.67, 1.21)(0.81, 1.91)(0.78, 1.38)(0.94, 2.18)(0.52, 1.01)Fatal MACE140.271.14190.391.63120.24(0.15, 0.45)(0.53, 2.47)(0.23, 0.60)(0.79, 3.36)(0.12, 0.41)Non-fatal MACE330.641.29320.661.33250.50(0.44, 0.90)(0.77, 2.17)(0.45, 0.93)(0.79, 2.24)(0.32, 0.73)Sudden cardiac death100.191.22130.261.6780.16(0.09, 0.35)(0.48, 3.10)(0.14, 0.45)(0.69, 4.04)(0.07, 0.31)MI190.371.69190.391.80110.22(0.22, 0.57)(0.80, 3.55)(0.23, 0.61)(0.85, 3.77)(0.11, 0.39)Fatal MI00NI30.061.0330.06(0.00, 0.07)(0.01, 0.18)(0.21, 5.11)(0.01, 0.17)Non-fatal MI190.372.32160.332.0880.16(0.22, 0.57)(1.02, 5.30)a(0.19, 0.53)(0.89, 4.86)(0.07, 0.31)Stroke180.351.03180.371.10170.34(0.21, 0.55)(0.53, 2.00)(0.22, 0.58)(0.57, 2.13)(0.20, 0.54)Fatal stroke40.08NI20.04NI00.00(0.02, 0.20)(0.00, 0.15)(0.00, 0.07)Non-fatal stroke140.270.80160.330.97170.34(0.15, 0.45)(0.40, 1.63)(0.19, 0.53)(0.49, 1.93)(0.20, 0.54)

aHR 95% CI excludes 1.

Data collected after pts who were randomised to tofacitinib 10 mg BID had their dose reduced to 5 mg. BID were included in the tofacitinib 10 mg BID group

. HRs (95% CI) were not informative when one of the treatments in the comparison had 0 events.

Risk period was defined as time from first dose to last dose +60 days or to the last contact date, whichever was earlier.

CI, confidence interval; NI, non-informative

Conclusion

MACE IRs and risk were higher with tofacitinib vs TNFi in ORAL Surveillance. BL risk factor findings could aid identification of RA pts with potentially highest risk for MACE, with a view to informing treatment decisions.

Acknowledgements

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

Disclosure of Interests

Christina Charles-Schoeman Consultant of: AbbVie, Gilead Sciences, Pfizer Inc and Sanofi-Regeneron, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead Sciences, MSD, Pfizer Inc and Roche, Grant/research support from: Pfizer Inc, Roche and UCB, Maxime Dougados Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Deepak L Bhatt Grant/research support from: Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, Chiesi, CSL Behring, Eli Lilly, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Medtronic, MyoKardia, Novo Nordisk, Owkin, Pfizer Inc, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic and The Medicines Company, Jon T Giles Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genentech, Gilead Sciences and UCB, Grant/research support from: Pfizer Inc, Steven R. Ytterberg Consultant of: Corbus Pharmaceuticals, Kezar Life Sciences and Pfizer Inc, Gary G Koch Shareholder of: IQVIA, Grant/research support from: AbbVie, Acceleron, Amgen, Arena, AstraZeneca, Cytokinetics, Eli Lilly, Gilead, GSK, Huya Bioscience International, Johnson & Johnson, Landos Biopharma, Merck, Momentum, Novartis, Otsuka, Pfizer Inc, Sanofi and vTv Therapeutics, Employee of: University of North Carolina at Chapel Hill, Ivana Vranic Shareholder of: Pfizer Inc, Employee of: Pfizer Ltd, Joseph Wu Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jose L. Rivas Shareholder of: Pfizer Inc, Employee of: Pfizer SLU, Arne Yndestad Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Carol A. Connell Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi

OP0264 IMPACT OF BASELINE CARDIOVASCULAR RISK ON THE INCIDENCE OF MAJOR ADVERSE CARDIOVASCULAR EVENTS IN THE TOFACITINIB RHEUMATOID ARTHRITIS CLINICAL PROGRAMME

Background

Results from ORAL Surveillance, a post-authorisation safety study, indicated that patients (pts) with rheumatoid arthritis (RA) aged ≥50 yrs with ≥1 additional cardiovascular (CV) risk factor have an increased risk of major adverse CV events (MACE) with tofacitinib vs tumour necrosis factor inhibitors.1

Objectives

To evaluate the impact of baseline (BL) CV risk on MACE in the wider tofacitinib RA clinical programme.

Methods

Data for pts who received ≥1 tofacitinib dose in 21 Phase 1–3b/4 (excluding ORAL Surveillance) and 2 long-term extension tofacitinib RA studies were pooled and analysed post hoc as two cohorts: (1) overall cohort and (2) CV risk-enriched cohort (pts aged ≥50 yrs with ≥1 additional CV risk factor [current smoker, hypertension, HDL-cholesterol <40 mg/dL, diabetes mellitus, history of myocardial infarction (MI) or coronary heart disease (CHD)]). Data were summarised by average tofacitinib 5 or 10 mg twice daily (BID; average total daily dose of <15 or ≥15 mg, respectively). Incidence rates (IRs; pts with first events/100 pt-yrs) for adjudicated MACE were calculated. MACE IRs were stratified by pts’ BL CV risk profile: pts were first categorised by history of coronary artery disease (HxCAD), then pts without a HxCAD were categorised by 10-yr risk of MACE, per the ASCVD-PCE risk calculator2 with a 1.5 multiplier applied.3

Results

The overall cohort included 7964 pts (average tofacitinib 5 mg BID, n=3969; average tofacitinib 10 mg BID, n=3995); of these, 3125 (39.2%) pts were included in the CV risk-enriched cohort (average tofacitinib 5 mg BID, n=1614; average tofacitinib 10 mg BID, n=1511). In both treatment arms, as expected, higher proportions of pts in the CV risk-enriched cohort had a HxCAD or a high or intermediate 10-yr predicted risk of MACE at BL vs the overall cohort (Table 1). MACE IRs (95% CIs) were lower in the overall cohort (0.38 [0.26, 0.54] and 0.37 [0.27, 0.48] for average tofacitinib 5 and 10 mg BID, respectively) vs the CV risk-enriched cohort (0.72 [0.46, 1.09] and 0.67 [0.46, 0.93], respectively), and were similar between treatment arms. MACE IRs were lower than reported in ORAL Surveillance.1 In the overall cohort, adjudicated MACE most commonly occurred in pts with a HxCAD (IR [95% CI] 0.98 [0.02, 5.47] and 1.05 [0.13, 3.78] for average tofacitinib 5 and 10 mg BID, respectively), or in pts with a high 10-yr risk of MACE at BL (Figure 1). A lower predicted 10-yr MACE risk was associated with lower MACE IRs (Figure 1); trends were similar for the CV risk-enriched cohort (data not shown).

Table 1.

Proportions of pts with a HxCAD and pts without a HxCAD categorised by 10-yr risk of MACE, per ASCVD-PCE risk calculator2 with a 1.5 multiplier applied3

Average tofacitinib 5 mg BIDAverage tofacitinib 10 mg BIDOverall cohort(N=3969)CV risk-enriched cohort(N=1614)Overall cohort(N=3995)CV risk-enriched cohort(N=1511)HxCAD, n (%)61 (1.5)61 (3.8)65 (1.6)60 (4.0)No HxCAD: 10-yr risk of MACE, n (%)High (≥20%)440 (11.1)365 (22.6)337 (8.4)276 (18.3)Intermediate (≥7.5–<20%)853 (21.5)593 (36.7)788 (19.7)530 (35.1)Borderline (≥5–<7.5%)435 (11.0)234 (14.5)404 (10.1)195 (12.9)Low (<5%)2133 (53.7)342 (21.2)2058 (51.5)307 (20.3)Missing data47 (1.2)19 (1.2)343 (8.6)143 (9.5)

CAD is defined as any of MI or CHD.

n, number of pts with specified characteristic; N, number of evaluable pts

Conclusion

In the tofacitinib RA clinical programme, MACE were largely associated with BL CV risk in the overall cohort, consistent with results of ORAL Surveillance, although results should be interpreted with caution due to low pt-yrs of exposure in some pt groups. Noting this limitation, these findings emphasise the importance of assessing and addressing BL CV risk when treating pts with RA.

References

[1]Ytterberg et al. New Engl J Med 2022; 386: 316-326.

[2]American College of Cardiology, American Heart Association. ASCVD risk estimator. https://tools.acc.org/ldl/ascvd_risk_estimator/index.html#!/calulate/estimator/.

[3]Agca et al. Ann Rheum Dis 2017; 76: 17-28.

Acknowledgements

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

Disclosure of Interests

Maxime Dougados Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Christina Charles-Schoeman Consultant of: AbbVie, Gilead Sciences, Pfizer Inc and Sanofi-Regeneron, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Grant/research support from: Pfizer Inc, Jon T Giles Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genentech, Gilead Sciences and UCB, Grant/research support from: Pfizer Inc, Steven R. Ytterberg Consultant of: Corbus Pharmaceuticals, Kezar Life Sciences and Pfizer Inc, Deepak L Bhatt Grant/research support from: Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, Chiesi, CSL Behring, Eisai, Eli Lilly, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Medtronic, MyoKardia, Novo Nordisk, Owkin, Pfizer Inc, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic and The Medicines Company, Gary G Koch Grant/research support from: AbbVie, Acceleron, Amgen, Arena, AstraZeneca, Cytokinetics, Eli Lilly, Gilead Sciences, GSK, Huya Bioscience International, Johnson & Johnson, Landos Biopharma, Merck, Momentum, Novartis, Otsuka, Pfizer Inc, Sanofi and vTv Therapeutics, Employee of: University of North Carolina at Chapel Hill, Ivana Vranic Shareholder of: Pfizer Inc, Employee of: Pfizer Ltd, Joseph Wu Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Kenneth Kwok Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Carol A. Connell Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Arne Yndestad Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jose L. Rivas Shareholder of: Pfizer Inc, Employee of: Pfizer SLU, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead Sciences, MSD, Pfizer Inc and Roche, Grant/research support from: Pfizer Inc, Roche and UCB

POS0520 ASSOCIATION BETWEEN BASELINE STATIN TREATMENT AND MAJOR ADVERSE CARDIOVASCULAR EVENTS IN PATIENTS WITH RHEUMATOID ARTHRITIS: A POST HOC ANALYSIS OF ORAL SURVEILLANCE

Background

ORAL Surveillance (NCT02092467) was a post-authorisation safety study of tofacitinib vs tumour necrosis factor inhibitors (TNFi) in patients (pts) with rheumatoid arthritis (RA) aged ≥50 years (yrs) with ≥1 additional cardiovascular (CV) risk factor and an inadequate response to methotrexate (MTX). Statins are used to treat coronary artery disease (CAD) and are recommended by the American College of Cardiology/American Heart Association (ACC/AHA) for the management of pts at risk of atherosclerotic CV disease (ASCVD),1 such as those with ≥7.5% 10-yr risk of major adverse CV events (MACE) or diabetes mellitus.

Objectives

To examine the association between baseline (BL) statin use and MACE in ORAL Surveillance.

Methods

Pts with RA on stable MTX were randomised 1:1:1 to receive tofacitinib 5 or 10 mg twice daily (BID) or TNFi (adalimumab 40 mg every 2 weeks or etanercept 50 mg once weekly). Pts were stratified post hoc by BL statin use (yes/no). Pts were further categorised by history of CAD (HxCAD), BL CV risk score per ACC/AHA guidelines1 (for pts without HxCAD; 10-yr risk of MACE per the ASCVD-pooled cohort equations risk calculator2 with a 1.5 multiplier applied3), and separately by BL diabetes status. CV risk score/BL diabetes status categories were: high (≥20%)/HxCAD (yes), intermediate (≥7.5–<20%) or low-borderline (<7.5%), and diabetes status (yes). For the overall population and each treatment group, risk of MACE was compared between BL statin use (yes vs no) via Cox analyses for each CV risk category and diabetes status (yes). Incidence rates (IRs; pts with first events/100 pt-yrs) and hazard ratios (HRs; BL statin use: yes vs no) were evaluated for adjudicated MACE.

Results

Of 4362 pts (tofacitinib 5 mg BID, n=1455; tofacitinib 10 mg BID, n=1456; TNFi, n=1451), 497 had a HxCAD, and 3813 without a HxCAD had CV risk scores determined; 789 had BL diabetes. Overall, 1020 (23.4%) pts reported BL statin use. Across CV risk score categories for all treatment groups, <50% of pts received statins at BL, with statin use highest in the high/HxCAD category pts (35.7–40.6%) and pts with diabetes (35.7–44.2%) (Table 1). Across categories, no interpretable associations between BL statin use and MACE were found. However, in the overall population, MACE IRs were lower in pts with vs without BL statin use in the high/HxCAD category, and in pts with diabetes (Figure 1). In pts receiving tofacitinib 5 mg BID and TNFi, MACE IRs were lower in pts with vs without BL statin use across all categories (Figure 1).

Table 1.

Proportion of pts receiving statins at BL, by CV risk category and presence of diabetes

n/N (%)OverallTofacitinibTofacitinibTNFi5 mg BID10 mg BIDHigh (≥20%)/HxCAD525/1370 (38.3)168/435 (38.6)193/475 (40.6)164/460 (35.7)Intermediate (≥7.5–<20%)302/1511 (20.0)110/490 (22.4)94/516 (18.2)98/505 (19.4)Low-borderline (<7.5%)178/1429 (12.5)66/513 (12.9)57/446 (12.8)55/470 (11.7)Diabetes (yes)320/789 (40.6)111/251 (44.2)114/272 (41.9)95/266 (35.7)

N, number of pts in each category; n, number of pts receiving BL statins

Conclusion

In this post hoc analysis of data from ORAL Surveillance, most pts did not receive BL statin treatment. This suggests suboptimal CV risk management, particularly in pts at high risk of CV events. There was no interpretable association between BL statin use and MACE. However, pts in the higher risk categories, particularly those receiving tofacitinib 5 mg BID, had lower MACE IRs with vs without BL statin use. This analysis did not take into account initiation or dose adjustment of statin treatment during the study, and had low yrs of exposure in some categories.

References

[1]Arnett et al. J Am Coll Cardiol 2019; 74: e177-232.

[2]American College of Cardiology, American Heart Association. ASCVD risk estimator. https://tools.acc.org/ldl/ascvd_risk_estimator/index.html#!/calulate/estimator/.

[3]Agca et al. Ann Rheum Dis 2017; 76: 17-28.

Acknowledgements

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

Disclosure of Interests

Jon T Giles Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genentech, Gilead Sciences and UCB, Grant/research support from: Pfizer Inc, Christina Charles-Schoeman Consultant of: AbbVie, Gilead Sciences, Pfizer Inc and Sanofi-Regeneron, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead Sciences, MSD, Pfizer Inc and Roche, Grant/research support from: Pfizer Inc, Roche and UCB, Maxime Dougados Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly, Merck, Novartis, Pfizer Inc, Roche and UCB, Zoltán Szekanecz Speakers bureau: AbbVie, Eli Lilly, Novartis, Pfizer Inc, Roche and Sanofi, Paid instructor for: AbbVie, Eli Lilly, Gedeon Richter, Novartis, Pfizer Inc and Roche, Consultant of: AbbVie, Eli Lily, Novartis, Pfizer Inc, Roche and Sanofi, Steven R. Ytterberg Consultant of: Corbus Pharmaceuticals, Kezar Life Sciences and Pfizer Inc, Gary G Koch Shareholder of: IQVIA, Grant/research support from: AbbVie, Acceleron, Amgen, Arena, AstraZeneca, Cytokinetics, Eli Lilly, Gilead Scienes, GlaxoSmithKline, Huya Bioscience International, Johnson & Johnson, Landos Biopharma, Merck, Momentum, Novartis, Otsuka, Pfizer Inc, Sanofi and vTv Therapeutics, Employee of: University of North Carolina at Chapel Hill, Joseph Wu Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Cunshan Wang Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Kenneth Kwok Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Sujatha Menon Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Yan Chen Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Teoman Yusuf Cesur Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jose L. Rivas Shareholder of: Pfizer Inc, Employee of: Pfizer SLU, Arne Yndestad Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Annette Diehl Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Deepak L Bhatt Grant/research support from: Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, Chiesi, CSL Behring, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Lilly, Medtronic, MyoKardia, Novo Nordisk, Owkin, Pfizer Inc, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic and The Medicines Company.

POS0213 EFFECT OF EARLY ETANERCEPT TREATMENT ON CIRCULATING LIPOPROTEINS DIFFERS TO TREATMENT WITH METHOTREXATE AND IS MODULATED BY CLINICAL DISEASE ACTIVITY

Background

A reduction in serum lipids such as total cholesterol (TC) and low-density lipoprotein (LDL) has been associated with increased risk of cardiovascular events in active RA, paradoxical to the general population1. The effect of DMARDs and active inflammation on lipid profiles has been investigated in RA but detailed lipid profiling has been lacking in very early disease and across the spectrum of disease activity.

Objectives

In a treatment naïve early RA trial cohort, we sought to compare circulating lipid profiles between patients treated with first line etanercept + methotrexate (ETN+MTX) versus methotrexate treat-to-target (MTX-TT) regime and between clinical remission and high disease activity.

Methods

VEDERA trial (Very early Etanercept and Methotrexate versus Methotrexate with/without Delayed Etanercept in RA) randomised 120 treatment-naïve RA patients to either first-line ETN+MTX or MTX-TT regime with escalation to ETN+MTX if not in DAS28ESR remission at week 242. TC, triglycerides (TG), high density lipoprotein (HDL) and LDL were measured; apolipoproteins and atherogenic indices such as TC/HDL, atherogenic index of plasma (AIP) and apolipoprotein B/A-i ratio (aporatio) were calculated at baseline, weeks 12, 24 and 48. Linear mixed effects regression was used to test the effect of treatment on lipids and atherogenic indices in states of remission (DAS28-ESR ≤ 2.6) and high disease activity (DAS28-ESR > 5.1).

Results

Baseline clinical characteristics of individuals1 and lipid profiles including atherogenic indices were comparable between the two treatment groups (Table 1).

Table 1.

Baseline lipids (mmol/L) and atherogenic indices in VEDERA. Median with interquartile range and n/N (%) reported.

Total, N = 120MTX_TT, N = 60ETN+MTX, N = 60TC4.69 (4.03,5.25)4.70 (4.04,5.42)4.69 (4.01,5.18)TG1.15 (0.90,1.41)1.18 (0.92,1.32)1.10 (0.89,1.55)HDL1.28 (1.04,1.53)1.29 (1.04,1.57)1.27 (1.05,1.48)LDL2.87 (2.22,3.27)2.87 (2.27,3.19)2.84 (2.01,3.29)TC/HDL3.53 (3.01,4.16)3.53 (3.00,4.14)3.58 (3.08,4.17)AIP-0.06 (-0.20,0.09)-0.06 (-0.22,0.08)-0.06 (-0.17,0.13)Aporatio0.63 (0.54,0.74)0.62 (0.54,0.74)0.64 (0.55,0.74)

In clinical remission, a lowering of atherogenic indices and TC, TG, LDL levels as well as a rise in predicted HDL levels were observed. In high disease activity, both HDL and LDL were increased along with the atherogenic indices TC/HDL-C, AIP and aporatio. However, the predicted values at different weeks did not reach statistical significance (not shown).

Treatment with MTX-TT and ETN+MTX had opposing effects on predicted HDL levels in remission and high-disease activity (Figure 1). In remission, MTX-TT treatment resulted in a predicted rise in HDL whilst with ETN+MTX a small reduction was observed (estimate 0.004, p 0.02). Similar trends were observed for HDL in high disease activity (p 0.5). In remission, both treatments resulted in a reduction in LDL (p 0.5), whilst in high disease activity ETN+MTX treatment resulted in a modest rise in LDL compared to MTX-TT (p 0.06). At weeks 24 and 48, significant differences were observed in LDL values between treatment groups in high disease activity (estimate 0.57, p 0.05 and estimate 1.13, p 0.04 respectively).

Conclusion

Effect of early ETN treatment on HDL, and to a lesser extent LDL, differs from MTX and is modulated by clinical disease activity. Further investigation is needed to understand the basis for these findings and the clinical implication of observed differences in LDL and HDL. These data may indicate direct effect of therapies on the qualitative and functional components of metabolic lipid pathway.

References

[1]Robertson J, Peters MJ, McInnes IB, et al. Changes in lipid levels with inflammation and therapy in RA: A maturing paradigm. Nat Rev Rheumatol. 2013;9(9):513–23.

[2]Emery P, Horton S, Dumitru RB, et al. Pragmatic randomised controlled trial of very early etanercept and MTX versus MTX with delayed etanercept in RA: The VEDERA trial. Ann Rheum Dis. 2020;79(4):464–71.

Disclosure of Interests

None declared

POS0513 SAFETY OF FILGOTINIB IN PATIENTS WITH RHEUMATOID ARTHRITIS: ANALYSIS OF LYMPHOCYTES IN THE LONG-TERM EXTENSION FINCH 4 STUDY

Background

Filgotinib (FIL) is a Janus kinase 1 preferential inhibitor approved for the treatment of moderate to severe rheumatoid arthritis (RA) in patients (pts) with an inadequate response to disease-modifying antirheumatic drugs.1 In a pooled analysis of Phase 3 FINCH 1–3 studies of FIL in RA, median lymphocyte levels were relatively stable over 1 year with lymphocyte decreases observed in individual FIL-treated pts. Lymphocyte levels should be monitored.1

Objectives

To assess the effect of FIL on lymphocyte levels and lymphopenia in the FINCH 4 long-term extension (LTE) study in RA.

Methods

Safety data of FIL 100 mg (FIL100) and 200 mg (FIL200) from LTE baseline to data cut off (01 June 2020) are reported overall and by prior FIL exposure for pts who received ≥1 FIL dose in FINCH 4 (NCT03025308; adults with RA who had completed FINCH 1/2/3). Adverse events (AEs) of lymphopenia were graded based on clinical severity; laboratory abnormalities (decreased lymphocytes) were graded per Common Terminology Criteria for Adverse Events v4.03 (CTCAE). Frequencies of both measures and exposure-adjusted incidence rates (EAIRs) of AEs are reported. Median lymphocyte levels are reported to LTE Week 48.

Results

The safety analysis set included 2729 pts (FIL200: n=1530; FIL100: n=1199). Of these, 75.4% (n=2058) had prior FIL exposure in FINCH 1/2/3. Median FIL exposure to LTE Week 48 was 600 (FIL200: 696; FIL100: 533) days.

In both treatment groups, median laboratory lymphocyte levels remained relatively stable to LTE Week 48 for pts with prior FIL exposure. Pts without prior exposure had numerically higher median lymphocyte levels at LTE baseline vs pts with prior exposure (Figure 1). These decreased over time, but medians remained within normal range. The frequency and EAIR of graded decreases in laboratory lymphocyte levels were higher with FIL200 vs FIL100 (Table 1); incidence was slightly higher in pts with vs without prior FIL exposure, with the difference most apparent for Grade 2 decreases.

Table 1.

Frequencies of treatment-emergent laboratory decreases in lymphocytes

Prior FIL exposureNo prior FIL exposureOverallTotalFIL200FIL100FIL200FIL100FIL200FIL100(N=2729)(n=1195)(n=863)(n=335)(n=336)(n=1530)(n=1199)Decreased lymphocytes228 (19.1)125 (14.5)41 (12.3)40 (12.0)269 (17.6)165 (13.8)434 (16.0)(any grade), n (%)Grade 148 (4.0)35 (4.1)14 (4.2)7 (2.1)62 (4.1)42 (3.5)104 (3.8)Grade 2159 (13.3)82 (9.5)21 (6.3)26 (7.8)180 (11.8)108 (9.1)288 (10.6)Grade 321 (1.8)8 (0.9)6 (1.8)7 (2.1)27 (1.8)15 (1.3)42 (1.5)Grade 40000000

A treatment-emergent laboratory decrease in lymphocytes was defined as an increase of ≥1 toxicity grade from baseline at any time post-baseline up to and including the date of last study drug dose + 30 days. Severity grades were defined per CTCAE (lower limit of normal: <0.8 × 109/L [Grade 1]; <0.8–0.5 × 109/L [2]; <0.5–0.2 × 109/L [3]; <0.2 × 109/L [4]).

Figure 1.

Of all pts receiving FIL, 43 (1.6%) reported a lymphopenia AE; frequencies and EAIRs of lymphopenia AEs were slightly higher with FIL200 (1.9%; EAIR [95% CI]: 1.2 [0.9–1.8]) vs FIL100 (1.2%; 0.8 [0.4–1.3]). Most were Grade 1 or 2 in severity. Grade 3 lymphopenia AEs occurred in 4 (0.3%) vs 1 (<0.1%) pts receiving FIL200 vs FIL100. There were no Grade 4 AEs in either group.

No serious AEs of lymphopenia or treatment discontinuations due to lymphopenia were reported. In total, 8 (0.3%) pts interrupted study treatment due to lymphopenia. Infection rates, but not serious infections, were slightly higher for pts with lymphopenia, however no relationship between lymphopenia severity and infection AE grade was seen.

Conclusion

In FINCH 4, lymphopenia AEs were infrequent but numerically greater with FIL200 vs FIL100, suggesting a dose–response relationship. While exposure at either dose may be associated with decreased lymphocytes, median lymphocyte levels were comparable in both groups and all remained within normal range at LTE Week 48, similar to observations in FINCH 1–3.

References

[1]Filgotinib SmPC and Jyseleca EPAR, 2020. Available at: https://www.ema.europa.eu/en

Acknowledgements

The authors would like to acknowledge Nadia Verbruggen and Pieter-Jan Stiers for providing statistical analysis support. This study was co-funded by Galapagos NV (Mechelen, Belgium) and Gilead Sciences, Inc. (Foster City, CA, USA). Medical writing support was provided by Kristian Clausen, MPH, CMPP (Aspire Scientific Ltd, Bollington, UK), and funded by Galapagos NV.

Disclosure of Interests

Jacques-Eric Gottenberg Consultant of: AbbVie, Bristol Myers Squibb, Galapagos, Gilead, Lilly, and Pfizer, Grant/research support from: Bristol Myers Squibb, and Pfizer, Gerd Rüdiger Burmester Consultant of: AbbVie, Amgen, Bristol Myers Squibb, Galapagos, Lilly, MSD, Pfizer, Roche, and Sanofi, Katrien Van Beneden Shareholder of: Galapagos NV, Employee of: Galapagos NV, Chris Watson Shareholder of: Galapagos Biotech Ltd, Employee of: Galapagos Biotech Ltd, Ineke Seghers Employee of: Galapagos NV, Vijay Rajendran Employee of: Galapagos NV, Lorenzo Dagna Consultant of: AbbVie, Amgen, AstraZeneca, Biogen, Boehringer-Ingelheim, Bristol Myers Squibb, Celltrion, Eli Lilly and Company, Galapagos, GlaxoSmithKline, Janssen, Kiniksa Pharmaceuticals, Novartis, Pfizer, Roche, Sanofi-Genzyme, and Swedish Orphan Biovitrium (SOBI), Grant/research support from: Bristol Myers Squibb, Celltrion, Kiniksa Pharmaceuticals, Pfizer, and Swedish Orphan Biovitrium (SOBI), Maya H Buch Speakers bureau: Speaker fees paid to host institution by AbbVie, Consultant of: Consultant honoraria paid to host institution by AbbVie, Galapagos, Gilead, and Pfizer, Grant/research support from: Gilead and Pfizer.

POS0643 SUSTAINABILITY OF RESPONSE BETWEEN UPADACITINIB AND ADALIMUMAB IN PATIENTS WITH RHEUMATOID ARTHRITIS: RESULTS THROUGH 3 YEARS FROM THE SELECT-COMPARE TRIAL

Background

The primary treatment target for patients with active rheumatoid arthritis (RA) is sustained clinical remission (REM) or low disease activity (LDA).1,2 A greater proportion of patients with RA and inadequate response to methotrexate (MTX) receiving the JAK inhibitor, upadacitinib (UPA), achieved REM/LDA compared with adalimumab (ADA), both with background MTX, through 26 weeks in the phase 3, SELECT-COMPARE trial.3

Objectives

We assessed sustainability of response over 3 years in UPA-treated patients with RA.

Methods

SELECT-COMPARE included a 26-week, double-blind, placebo (PBO)-controlled period, a 48-week, double-blind active comparator-controlled period, and an ongoing long-term extension for up to 10 years. Patients on background MTX received UPA 15 mg once daily, PBO, or ADA 40 mg every other week. Patients who did not achieve at least 20% improvements in tender and swollen joint counts (Weeks 14-22) or LDA (CDAI ≤10 at Week 26) were rescued from UPA to ADA or PBO/ADA to UPA. This post hoc analysis evaluated clinical REM (CDAI ≤2.8; SDAI ≤3.3), LDA (CDAI ≤10; SDAI ≤11), and DAS28(CRP) <2.6/≤3.2 at first occurrence (prior to treatment switch [rescue]), as well as over 3 years following initial response in patients randomized to UPA or ADA. For those patients who achieved REM/LDA, Kaplan-Meier was used to define the time from when the response was first achieved to the earliest date at which the response was lost at two consecutive visits, discontinuation of study drug, or losing response at the time of rescue. The predictive ability of time to CDAI REM/LDA was assessed using Harrell’s concordance (c)-index (range: 0 [all predictions wrong] to 1.0 [perfect predictive ability]. Non-responder imputation was used for missing data.

Results

Through 3 years, a significantly higher proportion of patients receiving UPA + MTX vs ADA + MTX achieved CDAI REM (47% vs 35%, P = 0.001) as well as CDAI LDA (70% vs 60%, P = 0.001). At 30 months after first occurrence of response, CDAI REM/LDA was sustained in 19%/42% of patients randomized to UPA and 10%/30% of patients randomized to ADA (Figure 1). Time to initial clinical response did not appear to be predictive of sustained disease control. The c-index for CDAI REM/LDA was 0.50/0.60 on UPA vs 0.49/0.56 on ADA. Through the last follow-up visit, 37%/58% of patients receiving UPA and 27%/48% on ADA remained in CDAI REM/LDA, respectively (Figure 2). Of patients who lost CDAI REM, 68% on UPA and 55% on ADA remained in LDA. Additionally, roughly similar proportions on UPA and ADA recaptured CDAI REM/LDA (UPA, 40%/17%; ADA, 48%/19%). Similar results were observed for REM/LDA based on SDAI and for DAS28(CRP) <2.6/≤3.2.

Conclusion

Among patients with inadequate response to MTX, a higher proportion receiving UPA + MTX achieved remission or LDA across disease activity measures vs ADA + MTX. UPA-treated patients demonstrated a consistently higher sustained response rate over 3 years compared to those receiving ADA. Furthermore, significant proportions of patients who lost response on either UPA or ADA were able to recapture remission or LDA.

References

[1]Smolen et al. Ann Rheum Dis 2020;79:685–99.

[2]Singh et al. Arthritis Rheumatol 2016;68:1–26.

[3]Fleischmann et al. Arthritis Rheumatol 2019;71:1788–1800.

Acknowledgements

AbbVie funded these studies and participated in the study design, research, analysis, data collection, interpretation of data, reviewing, and approval of the publication. No honoraria or payments were made for authorship. Medical writing support was provided by Matthew Eckwahl, PhD, of AbbVie.

Disclosure of Interests

Peter Nash Speakers bureau: AbbVie, BMS, Pfizer, Gilead/Galapagos, Sanofi, Celgene, Novartis, Lilly, Janssen, UCB, Samsung, MSD, Roche, Consultant of: AbbVie, BMS, Pfizer, Gilead/Galapagos, Sanofi, Celgene, Novartis, Lilly, Janssen, UCB, Samsung, MSD, Roche, Grant/research support from: AbbVie, BMS, Pfizer, Gilead/Galapagos, Sanofi, Celgene, Novartis, Lilly, Janssen, UCB, Samsung, MSD, Roche, Arthur Kavanaugh Consultant of: AbbVie Inc., Amgen, Astra-Zeneca, BMS, Celgene, Centocor-Janssen, Pfizer, Roche, and UCB, Grant/research support from: AbbVie Inc., Amgen, Astra-Zeneca, BMS, Celgene, Centocor-Janssen, Pfizer, Roche, and UCB, Maya H Buch Speakers bureau: AbbVie, Boehringer Ingleheim, Eli Lilly, Merck-Serono, and Sanofi, Consultant of: AbbVie, Boehringer Ingleheim, Eli Lilly, Merck-Serono, and Sanofi, Grant/research support from: Pfizer, Gilead, and UCB, Bernard Combe Consultant of: AbbVie, BMS, Celltrion, Gilead, Galapagos, Janssen, Eli Lilly, MSD, Pfizer, Roche Chugai, Louis Bessette Speakers bureau: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Sandoz, Gilead, Fresenius Kabi, and Teva, Consultant of: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Sandoz, Gilead, Fresenius Kabi, and Teva, Grant/research support from: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Sandoz, Gilead, Fresenius Kabi, and Teva, In-Ho Song Shareholder of: AbbVie Inc., Employee of: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Eli Lilly, Novartis, Sandoz, Gilead, Fresenius Kabi, and Teva, Tim Shaw Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Yanna Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Jessica Suboticki Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Roy M. Fleischmann Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Eli Lilly, GSK, Janssen, Novartis, Pfizer Inc, Sanofi-Aventis, and UCB, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Genentech, Janssen, Novartis, Pfizer Inc, Regeneron, Roche, Sanofi-Aventis and UCB

POS0607 IMPROVING TREAT-TO-TARGET IMPLEMENTATION IN RHEUMATOID ARTHRITIS: A SYSTEMATIC LITERATURE REVIEW OF BARRIERS, FACILITATORS, AND INTERVENTIONS

Background

Treat-to-target (T2T) is integral to international recommendations for managing patients with rheumatoid arthritis (RA),1,2 but its implementation in clinical practice is suboptimal.3 Understanding T2T barriers and facilitators may inform strategies for improving T2T implementation in RA.

Objectives

To review published evidence on barriers to and facilitators of T2T implementation in RA, and interventions designed to improve T2T implementation.

Methods

Two systematic literature searches were conducted to identify barriers to or facilitators of, and interventions designed to improve, T2T implementation in RA (Jan 1, 2015–Mar 1, 2021 and Jan 1, 2010–Jul 1, 2021, respectively). The quality of each study was assessed using the appropriate Critical Appraisal Skills Programme (CASP) checklist.4 Barriers/facilitators and interventions were grouped into categories and summarized descriptively.

Results

The barriers/facilitators literature search retrieved 235 articles. Seventy-seven of these, which described primary studies mentioning a total of 331 T2T barriers/facilitators in RA, were included in the analysis. The interventions literature search identified 451 articles, including 70 primary studies reporting a total of 56 unique interventions to improve T2T implementation in RA. The quality of the studies varied; however, most addressed at least half of the information evaluated in the CASP checklists. Barriers/facilitators were categorized into 18 key target areas for patients (n=7), healthcare professionals (HCPs; n=6), or patients and HCPs (n=5). These related to: HCPs’ or patients’ knowledge or perceptions; patients’ clinical or social conditions; patient–HCP communication or alignment; and time or resources (Figure 1). The 56 interventions were grouped into 18 types (Table 1). More than half of the interventions (n=30; 53.6%) were designed to improve or streamline disease activity or patient-reported outcome assessments or increase patient–HCP alignment on disease activity. Interventions designed to improve shared decision-making were also common (n=23; 41.1%); these included patient and HCP education (n=15), decision aids (n=7), and shared decision-making prompts (n=3). Of the 56 interventions, 20 (35.7%) reported improvements in T2T implementation and/or patient outcomes in RA. However, as most interventions were evaluated in single centers, their effectiveness, feasibility, and generalizability across other regions or healthcare settings were unclear.

Table 1.

Interventions for improving T2T implementation in RA, by type

Type of interventionNumber of unique interventions (n=56)aElectronic disease assessment recording11Disease assessment process/quality improvement initiative8Allied HCP-supported T2T strategy8Patient educational tools7Patient decision aid7HCP performance feedback7Integrated PRO assessment6Ultrasound assessment5HCP learning collaborative (structured learning sessions + performance feedback)4Patient PRO dashboard/visual feedback tool4Telehealth monitoring3HCP T2T/shared decision-making prompt3Nurse-led patient education3Multidisciplinary team program3HCP training2Patient telehealth education2HCP decision-making tool1Patient group sessions1

aInterventions may be assigned to more than one category

PRO, patient-reported outcome

Conclusion

While practical methods designed to improve T2T implementation in RA are available, their effectiveness and feasibility will likely vary by region and healthcare setting. More primary research is required to identify the most relevant barriers/facilitators and prioritize the most appropriate interventions to optimize T2T implementation both globally and locally.

References

[1]Smolen JS, et al. Ann Rheum Dis 2020;79:685–99

[2]Smolen JS, et al. Ann Rheum Dis 2016;75:3–15

[3]Yu Z, et al. Arthritis Care Res 2018;70:801–6

[4]Critical Appraisal Skills Programme 2019. https://casp-uk.net/casp-tools-checklists/ (Last accessed November 2021)

Acknowledgements

AbbVie funded the evidence synthesis and had the opportunity to review and comment on the publication prior to submission. However, decisions regarding the final publication content were made solely by the authors. Medical writing support was provided by Hilary Wong, PhD, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.

Disclosure of Interests

Laure Gossec Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Galapagos, Gilead, GSK, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, and UCB, Grant/research support from: Amgen, Galapagos, Lilly, Pfizer, and Sandoz, Louis Bessette Consultant of: AbbVie, Celgene, Fresenius Kabi, Gilead, Lilly, Novartis, Pfizer, Sandoz, and UCB, Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB, Ricardo Xavier Speakers bureau: AbbVie, Janssen, Lilly, Novartis, Pfizer, and Roche, Consultant of: AbbVie, Janssen, Lilly, Novartis, Pfizer, and Roche, Grant/research support from: AbbVie, Janssen, Lilly, and Pfizer, Ennio Giulio Favalli Speakers bureau: AbbVie, Bristol-Myers Squibb, Celltrion, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Sanofi-Genzyme, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celltrion, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Sanofi-Genzyme, and UCB, Andrew Ostor Consultant of: AbbVie, Bristol-Myers Squibb, Gilead, Janssen, Lilly, Novartis, Paradigm, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Gilead, Janssen, Lilly, Novartis, Paradigm, Pfizer, Roche, and UCB, Maya H Buch Consultant of: AbbVie, Boehringer Ingelheim, Galapagos, Gilead, Lilly, and Pfizer (consulting fees paid to the host institution and travel honoraria), Grant/research support from: Pfizer and UCB

OP0190 COMPREHENSIVE GENETIC AND FUNCTIONAL ANALYSES OF Fc GAMMA RECEPTORS EXPLAIN RESPONSE TO RITUXIMAB THERAPY FOR AUTOIMMUNE RHEUMATIC DISEASES

Background

Rituximab is widely used to treat rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) but clinical response varies. Efficacy is determined by the efficiency of depletion, which may depend on a variety of Fc gamma receptor (FcγR)-dependent mechanisms. Previous research was limited by complexity of the FCGR locus, not integrating copy number variation with functional SNP, and small sample size.

Objectives

The study objectives were to assess the effect of the full range of FcγRs variants on depletion, clinical response and functional effect on NK-cell-mediated killing in two rheumatic diseases with a view to personalised B-cell depleting therapies.

Methods

A prospective longitudinal cohort study was conducted in 873 patients [RA=611; SLE=262] from four cohorts (BSRBR-RA and BILAG-BR registries, Leeds RA and Leeds SLE Biologics). For RA, the outcome measures were 3C-DAS28CRP and 2C-DAS28CRP at 6 (+/-3) months post-rituximab (adjusted for baseline DAS28). For SLE, major clinical response (MCR) was defined as improvement of active BILAG-2004 domains to grade C/better at 6 months. B-cell depletion was evaluated by highly-sensitive flow cytometry. Qualitative and quantitative polymorphisms for five major FcγRs were measured using a commercial multiplex ligation-dependent probe amplification. Median NK cell FcγRIIIa expression (CD3-CD56+CD16+) and NK-cell degranulation (CD107a) in the presence of rituximab-coated Daudi/Raji B-cell lines were assessed using flow cytometry.

Results

In RA, for FCGR3A, carriage of V allele (coefficient -0.25 (SE 0.11); p=0.02) and increased copies of V allele (-0.20 (0.09); p=0.02) were associated with greater 2C-DAS28 response. Irrespective of FCGR3A genotype, increased gene copies were associated with a better response. In SLE, 177/262 (67.6%) achieved BILAG response [MCR=34.4%; Partial=33.2%]. MCR was associated with increased copies of FCGR3A-158V allele, OR 1.64 (95% CI 1.12-2.41) and FCGR2C-ORF allele 1.93 (1.09-3.40). Of patients with B-cells data in the combined cohort, 236/413 (57%) achieved complete depletion post-rituximab. Only homozygosity for FCGR3A-158V and increased FCGR3A-158V copy number were associated with increased odds of complete depletion. Patients with complete depletion had higher NK cell FcγRIIIa expression at rituximab initiation than those with incomplete depletion (p=0.04) and this higher expression was associated with improved EULAR response in RA. Moreover, for FCGR3A, degranulation activity was increased in V allele carriers vs FF genotype in the combined cohort; p=0.02.

Conclusion

FcγRIIIa is the major low affinity FcγR and increased copies of the FCGR3A-158V allele, encoding the allotype with a higher affinity for IgG1, was associated with clinical and biological responses to rituximab in two autoimmune diseases. This was supported by functional data on NK cell-mediated cytotoxicity. In SLE, increased copies of the FCGR2C-ORF allele was also associated with improved response. Our findings indicate that enhancing FcγR-effector functions could improve the next generation of CD20-depleting therapies and genotyping could stratify patients for optimal treatment protocols.

References

None

Acknowledgements

This research was funded/supported by the joint funding from the Medical Research Council (MRC) and Versus Arthritis of MATURA (grant codes 36661 and MR/K015346/1). MASTERPLANS was funded by the MRC (grant code MR/M01665X/1). The Leeds Biologics Cohort was part funded by programme grants from Versus Arthritis (grant codes 18475 and 18387), the National Institute for Health Research (NIHR) Leeds Biomedical Research Centre (BRC) and Diagnostic Evaluation Co-operative and the Ann Wilks Charitable Foundation. The BILAG-BR has received funding support from Lupus UK, and unrestricted grants from Roche and GSK.

The functional studies were in part supported through a NIHR/HEFCE Clinical Senior Lectureship and a Versus Arthritis Foundation Fellowship (grant code 19764) to AWM, the Wellcome Trust Institutional Strategic Support Fund to JIR and MYMY (204825/Z/16/Z), NIHR Doctoral Research Fellowship to MYMY (DRF-2014-07-155) and NIHR Clinician Scientist to EMV (CS-2013-13-032). . AWM, INB, JDI and PE were supported by NIHR Senior Investigator awards. Work in JDI’s laboratory is supported by the NIHR Newcastle BRC, the Research Into Inflammatory Arthritis Centre Versus Arthritis, and Rheuma Tolerance for Cure (European Union Innovative Medicines Initiative 2, grant number 777357). INB is funded by the NIHR Manchester BRC.

This article/paper/report presents independent research funded/supported by the NIHR Leeds BRC and the NIHR Guy’s and St Thomas’ BRC. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

Disclosure of Interests

Md Yuzaiful Md Yusof: None declared, James Robinson: None declared, Vinny Davies: None declared, Dawn Wild: None declared, Michael Morgan: None declared, John Taylor: None declared, Yasser El-Sherbiny: None declared, David Morris: None declared, Lu Liu: None declared, Andrew Rawstron: None declared, Maya H Buch: None declared, Darren Plant: None declared, Heather Cordell: None declared, John Isaacs: None declared, Ian N. Bruce: None declared, Paul Emery Speakers bureau: Roche, Consultant of: Roche, Grant/research support from: Roche, Anne Barton: None declared, Timothy Vyse: None declared, Jennifer Barrett: None declared, Edward Vital Consultant of: Roche, Grant/research support from: Roche, Ann Morgan Speakers bureau: Roche/Chugai, Consultant of: GSK, Roche, Chugai, AstraZeneka, Regeneron, Sanofi, Vifor, Grant/research support from: Roche, Kiniksa Pharmaceuticals

POS0670 ROUTINE ASSESSMENT OF PATIENT INDEX DATA 3 (RAPID3) IN PATIENTS WITH RHEUMATOID ARTHRITIS TREATED WITH LONG-TERM UPADACITINIB THERAPY

Background:

Routine Assessment of Patient Index Data 3 (RAPID3) is a pooled index of 3 patient-reported measures: patient global assessment, pain, and physical function. RAPID3 was shown to correlate with other composite measures of disease activity1 and is recommended by the American College of Rheumatology for use in clinical practice.2

Objectives:

To evaluate the impact of upadacitinib (UPA) versus comparators on RAPID3 over 60 weeks, as well as the correlation of RAPID3 scores with other disease measures in the UPA phase 3 SELECT clinical program.

Methods:

This post hoc analysis included placebo-controlled (SELECT-NEXT, -BEYOND, and -COMPARE) and active comparator-controlled (SELECT-EARLY, -MONOTHERAPY, and -COMPARE) trials. Patients received UPA as monotherapy or in combination with conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). Mean change from baseline in RAPID3 and the proportion of patients reporting RAPID3 remission (≤3), low (LDA, >3 to ≤6), moderate (MDA, >6 to ≤12), and high disease activity (HDA, >12) were assessed. Correlations between absolute scores for RAPID3 and Clinical Disease Activity Index (CDAI), Simplified Disease Activity Index (SDAI), and 28-joint Disease Activity Score with C-reactive protein (DAS28[CRP]) were assessed using Spearman correlation coefficients. All data are as observed.

Results:

A total of 661, 498, 648, 1629, and 945 patients were included from SELECT-NEXT, -BEYOND, -MONOTHERAPY, -COMPARE, and -EARLY. At baseline, the majority of patients across all studies were in RAPID3 HDA (mean baseline RAPID3 [across all studies], 17.2–19.2) (Table 1 and Figure 1). Improvements from baseline in RAPID3 were observed with UPA 15 mg and 30 mg through Week 60, with numerically greater improvements observed with UPA compared with active comparators (Table 1). Across studies, mean improvements in RAPID3 exceeded the minimal clinically important difference (MCID) with UPA and adalimumab (ADA) treatment (MCID=3.83). By Week 60, approximately one-half of UPA-treated patients were in RAPID3 remission or LDA, with only 10–25% remaining in HDA, except for the more refractory population in SELECT-BEYOND, in which ~38% of patients remained in HDA (Figure 1). RAPID3 scores moderately to strongly correlated with CDAI (ρ=0.69–0.83), SDAI (ρ=0.69–0.82), and DAS28(CRP) (ρ=0.58–0.77), across all studies, at Week 60 (all p<0.001).

Conclusion:

UPA, as monotherapy or in combination with csDMARDs, was associated with improvements in patient-reported disease activity, pain, and physical function, as assessed by RAPID3 over 60 weeks in the phase 3 SELECT clinical program. RAPID3 continues to be an important tool in clinical practice to assess disease activity, as it was shown to correlate to other disease activity measures and allows for rapid scoring.

References:

[1]Pincus T, et al. Arthritis Care Res (Hoboken) 2010;62:181–9.

[2]England BR, et al. Arthritis Care Res (Hoboken) 2019;71:1540–55.

[3]Ward MM, et al. J Rheumatol 2019;46:27–30.

Table 1.

Change from BL in RAPID3 at Week 60 (as observed)

Phase 3 studyGroupnaMean (SD) BL scoreMean (SD) change from BLbSELECT-EARLYc(MTX-naïve)MTX23618.5 (5.6)−9.6 (7.5)UPA 15 mg QD26918.9 (5.6)−12.0 (7.6)UPA 30 mg QD25318.2 (5.6)−13.4 (7.2)SELECT-NEXT(csDMARD-IR)UPA 15 mg QD17217.7 (5.1)−11.1 (7.3)UPA 30 mg QD17217.6 (5.3)−10.4 (6.8)SELECT-MONOTHERAPY(MTX-IR)UPA 15 mg QD17217.4 (5.8)−9.6 (7.4)UPA 30 mg QD18017.2 (5.9)−10.6 (7.2)SELECT-COMPAREc(MTX-IR)UPA 15 mg QD55218.5 (5.5)−10.2 (7.1)ADA 40 mg EOW26418.7 (5.4)−8.8 (6.7)SELECT-BEYOND(bDMARD-IR)UPA 15 mg QD13319.2 (5.1)−8.6 (6.8)UPA 30 mg QD11818.5 (5.3)−9.3 (7.3)

b, biologic; BL, baseline; EOW, every other week; IR, inadequate response; MTX, methotrexate; QD, once daily; SD, standard deviation

aNumber of patients with RAPID3 values at both BL and Week 60. bNegative values indicate improvement from BL. cObserved data include patients rescued to UPA and/or ADA; treatment effect may include both the randomized and switch treatments in these patients

Acknowledgements:

AbbVie funded this study; contributed to its design; participated in data collection, analysis, and interpretation of the data; and participated in the writing, review, and approval of the abstract. No honoraria or payments were made for authorship. Medical writing support was provided by Grant Kirkpatrick, MSc, of 2 the Nth (Cheshire, UK), and was funded by AbbVie.

Disclosure of Interests:

Martin Bergman Shareholder of: Johnson & Johnson, Speakers bureau: AbbVie, Celgene, GSK, MSD, Novartis, Pfizer, and Sanofi/Regeneron, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Genentech/Roche, Gilead, Horizon, Janssen, MSD, Novartis, Pfizer, Sandoz, Sanofi/Regeneron, and Scipher, Maya H Buch Consultant of: AbbVie, Eli Lilly, Merck-Serono, Pfizer, Sandoz, and Sanofi, Grant/research support from: Pfizer, Roche, and UCB, Yoshiya Tanaka Speakers bureau: AbbVie, Asahi Kasei, Astellas, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Eli Lilly, GSK, Janssen, Mitsubishi Tanabe, Novartis, Pfizer, Sanofi, Takeda, UCB, and YL Biologics, Grant/research support from: AbbVie, Astellas, Bristol-Myers Squibb, Chugai, Daiichi Sankyo, Eisai, Mitsubishi Tanabe, MSD, Ono, Taisho Toyama, and Takeda, Gustavo Citera Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Genzyme, Pfizer, and Roche, Sami Bahlas: None declared, Ernest Wong Consultant of: AbbVie, Chugai, Eli Lilly, MSD, Novartis, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, Chugai, Novartis, and UCB, Yanna Song Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Namita Tundia Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Jessica Suboticki Shareholder of: May own stock or options in AbbVie, Employee of: AbbVie, Vibeke Strand Consultant of: AbbVie, Amgen, Arena, AstraZeneca, Bayer, Bristol-Myers Squibb, Boehringer Ingelheim, Celltrion, Eli Lilly, Gilead, Ichnos, Inmedix, Janssen, Kiniksa, MSD, Myriad Genetics, Novartis, Pfizer, Regeneron, Samsung, Sandoz, Sanofi, Scipher, Setpoint, and UCB.

OP0126 INFECTIONS AND SERIOUS INFECTIONS IN THE FILGOTINIB RHEUMATOID ARTHRITIS PROGRAM

Background:

The Janus kinase (JAK)-1 preferential inhibitor filgotinib (FIL) improved rheumatoid arthritis (RA) signs and symptoms in 3 phase (P)3 trials.1–3 Like other RA therapies, JAK inhibition is associated with increased infection rates.4

Objectives:

To assess long-term safety across the FIL program regarding infections, including serious infections (SI).

Methods:

Patients (pts) meeting 2010 ACR/EULAR RA criteria in pooled analysis of P2 DARWIN 1–2 (D1–2), P3 FINCH 1–3 (F1–3), and long-term extension studies (DARWIN 3, FINCH 4) were included. The placebo (PBO)-controlled as-randomised data set included pts receiving FIL 100 mg (FIL100), FIL 200 mg (FIL200), or PBO up to week (W)12 (D1–2, F1–2). The active-controlled as-randomised data set included pts receiving FIL100, FIL200, adalimumab (ADA), or methotrexate (MTX) up to W52 (F1, F3). The long-term as-treated data set included pts in all 7 studies receiving FIL100 or FIL200; data after rerandomisation were included and contributed to treatment received.

Exposure-adjusted incidence rates (EAIRs) per 100 patient-years exposure (PYE) and differences with 95% confidence intervals (CIs) were calculated using Poisson regression; EAIRs for tuberculosis (TB) in active controlled sets were calculated using an Exact Poisson method. Kaplan-Meier (KM) event probabilities with 95% CIs were provided for SI. If pts had multiple events within the same treatment period, only the first event was counted in EAIR calculation; PYE were calculated up to the last follow-up time or day before next treatment, including after first event. For KM analysis, time to event was calculated until the first event.

Results:

Of 2267/1647 pts in as-treated set receiving FIL200/FIL100, 1697 had treatment-emergent infection; 118 were SI. Baseline potential risk factors for pts with SI are in Table.

Table 1.

Baseline characteristics of pts with/without treatment emergent SIa

Parameter, n (%)SIN = 92No SIN = 2491Medical history Chronic lung disease13 (14.1)125 (5.0) Chronic renal disease3 (3.3)23 (0.9) Infections and infestations29 (31.5)499 (20.0)Baseline body mass index, kg/m2 <3064 (69.6)1749 (70.2) ≥3028 (30.4)742 (29.8)Age, years <6567 (72.8)2006 (80.5) ≥6525 (27.2)485 (19.5)Former/current smoker30 (32.6)677 (27.2)Oral corticosteroids, mg <7.528 (56.0)731 (66.1) ≥7.522 (44.0)375 (33.9) Missing data421385

aPhase 3 (FINCH 1-4) studies, as randomised.

SI, serious infection.

In 12W PBO-controlled period, infection rates were 17.9%/15.6%/13.3% for FIL200/FIL100/PBO. In 52W ADA-controlled period, infection EAIRs (95% CIs)/100 PYE were 46.9 (40.9, 53.7)/43.7 (38.0, 50.4)/43.4 (36.5, 51.5), FIL200/FIL100/ADA; and 38.5 (33.8, 43.9)/39.0 (31.1, 48.8)/42.2 (36.1, 49.3), FIL200/FIL100/MTX in 52W MTX-controlled period; 24.8 (23.1, 26.5)/34.4 (30.4, 38.8), FIL200/FIL100 in long-term analysis. In 12W PBO-controlled period, there was no active TB for FIL200/FIL100/PBO. In 52W ADA-controlled period, active TB EAIRs (95% CIs)/100 PYE were: 0 (0.0, 0.8)/0 (0.0, 0.8)/0.3 (0.0, 1.9), FIL200/FIL100/ADA and 0 (0.0, 0.6)/0 (0.0, 1.9)/0 (0.0, 1.0), FIL200/FIL100/MTX in 52W MTX-controlled period; 0/0.1 (0.0, 0.5), FIL200/FIL100 in long-term analysis.

SI rate or EAIRs are in Figure. Most common infections were upper respiratory tract infection and nasopharyngitis; majority were low grade. Pneumonia was most common SI (<1%). In long-term population, event probability (95% CI) of SI was 2.2% (1.6, 2.9)/2.5% (1.8, 3.4) for FIL200/FIL100 at 52W. In F1–3 (excluding data after rerandomisation), there were no significant changes in mean neutrophil and lymphocyte counts; values remained within normal limits up to W52 for all arms.

Conclusion:

EAIRs of infections and SI for FIL were similar to PBO, ADA, and MTX. At 52W, incidence rates of SI were comparable for FIL100 and FIL200. Long-term SI EAIR for FIL100 was slightly higher than for FIL200.

References:

[1]Genovese et al. JAMA. 2019;322:315–25.

[2]Westhovens et al. Ann Rheum Dis. 2021; online first.

[3]Combe et al. Ann Rheum Dis. 2021; online first.

[4]Strand et al. Arthritis Res Ther. 2015;17:362.

Disclosure of Interests:

James Galloway Speakers bureau: Pfizer, Bristol-Myers Squibb, UCB and Celgene, Maya H Buch Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Grant/research support from: Pfizer, Roche, and UCB, Kunihiro Yamaoka Speakers bureau: AbbVie, Actelion Pharmaceuticals Japan, Asahikasei Pharma Corp, Astellas Pharma, AYUMI Pharma Co, Boehringer Ingelheim Japan, Bristol-Myers Squibb, Chugai Pharma, Daiichi Sankyo, Eisai Pharma, Eli Lilly, GlaxoSmithKline, Gilead G.K., Hisamitsu Pharma Co., Janssen Pharma, Mitsubishi-Tanabe Pharma, MSD, Nippon Kayaku, Nippon Shinyaku, Ono Pharma, Otsuka Pharma, Pfizer, Sanofi, and Takeda Industrial Pharma, Consultant of: Asahikasei Pharma Corp., AbbVie, Gilead G.K., Pfizer, Astellas Pharma Inc, Eli Lilly Japan K.K., and Japan Tobacco Inc., Grant/research support from: Takeda Industrial Pharma, Pfizer, Astellas Pharma, Daiichi Sankyo, Eli Lilly, Eisai Pharma, Teijin Pharma, MSD, Shionogi, Chugai Pharma, Nippon Kayaku, Mitsubishi-Tanabe Pharma, and AbbVie, Cianna Leatherwood Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Iyabode Tiamiyu Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Deyuan Jiang Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Lei Ye Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Robin Besuyen Shareholder of: Galapagos BV, Employee of: Galapagos BV, Daniel Aletaha Speakers bureau: AbbVie, Celgene, Lilly, Merck, Novartis, Pfizer, Sanofi Genzyme, UCB, Consultant of: AbbVie, Amgen, Celgene, Lilly, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi Genzyme, Grant/research support from: AbbVie, Novartis, Roche, Kevin Winthrop Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly and Co., Galapagos NV, Gilead Sciences, GlaxoSmithKline, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, and Pfizer

POS0086 ANALYSIS OF DISEASE ACTIVITY MEASURES IN THE CONTEXT OF A METHOTREXATE WITHDRAWAL STUDY AMONG PATIENTS WITH RHEUMATOID ARTHRITIS TREATED WITH TOFACITINIB 11 MG ONCE DAILY + METHOTREXATE: POST HOC ANALYSIS OF DATA FROM ORAL SHIFT

Background:

The Phase 3b/4 study ORAL Shift demonstrated sustained efficacy and safety of tofacitinib modified-release (MR) 11 mg once daily (QD) following methotrexate (MTX) withdrawal that was non-inferior to continued tofacitinib + MTX use (per DAS28-4[ESR]), in patients (pts) with rheumatoid arthritis (RA) who achieved CDAI-defined low disease activity (LDA) with tofacitinib + MTX at Week (W)24.1

Objectives:

To assess the performance of alternative disease activity measures at W24 (randomisation) and W48 (study endpoint) in ORAL Shift.

Methods:

ORAL Shift (NCT02831855) enrolled pts aged ≥18 years with moderate to severe RA and an inadequate response to MTX. Pts received open-label tofacitinib MR 11 mg QD + MTX for 24 weeks. Achievement of CDAI LDA (≤10) at W24 was set as the criteria for entry to the 24-week double-blind MTX withdrawal phase, with pts randomised 1:1 to receive tofacitinib MR 11 mg QD + placebo (PBO) (ie blinded MTX withdrawal) or continue tofacitinib + MTX. In this post hoc analysis, efficacy analyses were performed in 8 subgroups defined by achievement of various disease activity criteria at W24: DAS28-4(ESR) remission (<2.6) or LDA (≤3.2); DAS28-4(CRP) <2.6 or ≤3.2; RAPID3 remission (≤3) or LDA (≤6); CDAI remission (≤2.8); and SDAI remission (≤3.3). For each subgroup, the proportion of pts who achieved the corresponding disease activity criterion at W48 was calculated, with a 95% confidence interval (CI) estimated using the normal approximation to the binomial distribution. The change (Δ) from W24 to W48 in least squares (LS) mean DAS28-4(ESR) and DAS28-4(CRP) was also calculated in each subgroup, with a 95% CI for the difference between treatment groups estimated using a mixed model with repeated measures. Nominal p values were calculated and are presented with no formal statistical hypothesis testing formulated.

Results:

Overall, 694 pts entered the open-label phase of ORAL Shift, and 530 were randomised and received treatment in the double-blind phase; 264 and 266 pts received tofacitinib + PBO and tofacitinib + MTX, respectively (Figure 1a). Considering those pts who were randomised and treated, the proportion of pts achieving each disease activity criterion at W24 varied, but was similar between treatments within each subgroup (Figure 1a). Among pts who met each disease activity criterion at W24, generally the majority of pts in both treatment groups also met the same criterion at W48 (Figure 1b). Numerically more pts receiving tofacitinib + MTX vs tofacitinib + PBO continued to meet the corresponding criterion at W48. Regardless of the disease activity criterion met at W24, differences between treatment groups in LS mean ΔDAS28-4(ESR) (Figure 1c) and ΔDAS28-4(CRP) (data not shown) from W24 to W48 favoured tofacitinib + MTX vs tofacitinib + PBO.

Conclusion:

This post hoc analysis of data from pts randomised and treated in ORAL Shift demonstrated that, regardless of the disease activity state criterion met at W24, generally a majority of pts receiving tofacitinib maintained achievement of the corresponding disease activity criterion at W48, with or without continued MTX. Differences between treatment groups in LS mean ΔDAS28-4(ESR) from W24 to W48, as defined by achievement of LDA or remission with a variety of disease activity measures, were less than a change of 1.2, which is considered to be the threshold for a minimal clinically important improvement.2

References:

[1]Cohen et al. Lancet Rheumatol 2019; 1: E23-34.

[2]Ward et al. Ann Rheum Dis 2015; 74: 1691-1696.

Acknowledgements:

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

Disclosure of Interests:

Roy Fleischmann Speakers bureau: Pfizer Inc, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celltrion, Eli Lilly, GlaxoSmithKline, Janssen, Novartis, Pfizer Inc, Sanofi-Aventis, UCB, Grant/research support from: AbbVie, Amgen, AstraZeneca, Bristol-Myers Squibb, Celltrion, Eli Lilly, Genentech, GlaxoSmithKline, Janssen, Novartis, Pfizer Inc, Samumed, Sanofi-Aventis, UCB, VORSO, Boulos Haraoui Speakers bureau: Amgen, Pfizer Inc, UCB, Consultant of: AbbVie, Amgen, Eli Lilly, Merck, Pfizer Inc, UCB, Grant/research support from: AbbVie, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead, MSD, Pfizer Inc, Roche, Sanofi, Grant/research support from: Pfizer Inc, Roche, UCB, David Gold Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Gosford Sawyerr Consultant of: Pfizer Inc, Employee of: Syneos Health Inc, Harry Shi Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Annette Diehl Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Kristen Lee Shareholder of: Pfizer Inc, Employee of: Pfizer Inc.

POS0447 PHYSICAL FUNCTION IN PATIENTS WITH RA, STRATIFIED BY SEROSTATUS AND TREATMENT LINE, FOLLOWING SC ABATACEPT: POST HOC ANALYSIS OF AN OBSERVATIONAL, 2-YEAR STUDY CONDUCTED IN ROUTINE CLINICAL PRACTICE (ASCORE)

Background:

RA is characterised by the production of autoantibodies, including RF and anti-citrullinated protein antibodies (ACPAs).1 Seropositive disease is associated with poorer prognosis in patients with RA,2 and response to different treatments has been shown to vary based on ACPA status.3 ASCORE (Abatacept SubCutaneOus in Routine Clinical PracticE; NCT02090556) was a 2-year, observational, prospective, multicentre study of SC abatacept for the treatment of RA.4

Objectives:

This post hoc analysis of the ASCORE study evaluated patient-reported outcomes, assessed using HAQ-DI, by RF/ACPA serostatus and treatment line over 24 months of treatment with abatacept.

Methods:

Eligible patients, aged ≥18 years, with active moderate-to-severe RA (ACR/EULAR 2010 criteria) who were IV abatacept-naive and initiated SC abatacept 125 mg once weekly, were enrolled into two cohorts: biologic (b)DMARD-naive patients and those with ≥1 prior bDMARD treatment failure. This post hoc analysis assessed mean change from baseline in HAQ-DI score at 6, 12, 18 and 24 months in response to treatment with abatacept stratified by baseline serostatus (RF/ACPA double positive [+/+]; RF/ACPA single positive [+/−; RF+/ACPA– or RF–/ACPA+] or RF/ACPA double negative [–/–]) and by line of therapy (all patients, patients receiving abatacept as a first-line bDMARD or as a ≥ second-line bDMARD [data not shown], and those receiving abatacept following 1 [data not shown] or ≥2 prior bDMARDs). Estimates of mean difference with 95% CIs between patients with different serostatus were calculated using a t-test for all patients and within different lines of therapy.

Results:

Among 2892 eligible patients in ASCORE, 1748 patients with RF/ACPA status available at baseline were included in this analysis (1079 +/+, 326 +/– and 343 –/–). Of these, 791 patients received abatacept as a first-line bDMARD therapy and 957 as a ≥ second-line bDMARD therapy (505 patients had received ≥2 prior bDMARDs). Among all patients, mean change from baseline in HAQ-DI score at 6 months was greater for patients with +/+ RA (mean difference [95% CI]: –0.2 [–0.3, –0.0]; p=0.0068) or +/– RA (mean difference [95% CI]: –0.2 [–0.3, –0.0]; p=0.0315) versus those with –/– RA at baseline (Figure 1). Similarly, mean change (95% CI) in HAQ-DI score at 6 months was greater for patients with +/+ RA versus –/– RA among those receiving abatacept as first-line therapy (–0.2 [–0.4, –0.0]; p=0.0407) or following treatment with ≥2 bDMARDs (–0.3 [–0.5, –0.0]; p=0.0265) (Figure 1). Among patients treated with abatacept following ≥2 prior bDMARDs, mean change in HAQ-DI score was higher among patients with +/– RA versus –/– RA at 18 months (data not shown) and 24 months (Figure 1). No other significant differences were observed by serostatus or line of therapy at any other time points.

Conclusion:

Patients with RA who were RF+/ACPA+ at baseline showed an enhanced initial response to abatacept compared with those who were RF–/ACPA–. Over 24 months of treatment in this real-world setting, abatacept was equally effective as a first- or ≥ second-line therapy.

References:

[1]Scott DL, et al. Lancet 2010;376:1094–1108.

[2]Hecht C, et al. Ann Rheum Dis 2015;74:2151–2156.

[3]Harrold LR, et al. J Rheumatol 2018;45:32–39.

[4]Alten R, et al. Ann Rheum Dis 2019;78(suppl 2):A1639.

Acknowledgements:

Professional medical writing and editorial assistance was provided by Fiona Boswell, PhD, at Caudex and was funded by Bristol Myers Squibb. This study was funded by Bristol Myers Squibb.

Disclosure of Interests:

Rieke Alten Speakers bureau: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Consultant of: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Grant/research support from: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Xavier Mariette Consultant of: Bristol Myers Squibb, Galapagos, Gilead, GlaxoSmithKline, Janssen, Pfizer, UCB, Rene-Marc Flipo Speakers bureau: AbbVie, Bristol Myers Squibb, Janssen, Lilly, Medac, Merck Sharp & Dohme, Novartis, Pfizer, Roche-Chugai, Grant/research support from: Amgen, Janssen, Novartis, Pfizer, Roberto Caporali Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Fresenius Kabi, Galapagos, Gilead, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Samsung Bioepis, Sanofi, UCB, Consultant of: Galapagos, Gilead, Janssen, Lilly, Merck Sharp & Dohme, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead, Merck Serono, Pfizer, Roche, Sanofi, Grant/research support from: Gilead, Pfizer, Roche, UCB, Yusuf Patel: None declared, Sara Marsal Speakers bureau: Bristol Myers Squibb, Celgene, Pfizer, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol Myers Squibb, Celgene, Galapagos, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, UCB, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Sanofi, UCB, M.T. Nurmohamed Speakers bureau: AbbVie, Bristol Myers Squibb, Eli Lilly, Roche, Sanofi, Consultant of: AbbVie, Celgene, Celltrion, Eli Lilly, Janssen, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Mundipharma, Novartis, Pfizer, Roche, Sanofi, Hedley Griffiths Consultant of: AbbVie, Gilead, Janssen, Novartis, Peter Peichl: None declared, Bettina Bannert: None declared, Adrian Forster: None declared, Melanie Chartier Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Yedid Elbez Consultant of: Bristol Myers Squibb, Christiane Rauch Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Karissa Lozenski Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Vadim Khaychuk Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb

OP0180 IMPACT OF RF AND ANTI-CITRULLINATED PROTEIN ANTIBODY SEROSTATUS ON 2-YEAR RETENTION OF ABATACEPT IN PATIENTS WITH RA

Background:

Up to 50% of patients with RA discontinue DMARD treatment within 18 months.1 However, up to 20% of patients who fail multiple treatments may have a good treatment response to another therapy.1 Predictive biomarkers, such as RF and anti-citrullinated protein antibodies (ACPAs), may be useful to stratify patients with RA to the most appropriate treatment.1 ASCORE (Abatacept SubCutaneOus in Routine Clinical PracticE; NCT02090556) was a 2-year, observational, prospective, multicentre study of SC abatacept for the treatment of RA in routine clinical practice.2

Objectives:

To determine if RF/ACPA serostatus and treatment line impact abatacept retention in patients with RA in a post hoc analysis of ASCORE.

Methods:

Eligible patients, aged ≥18 years, with active moderate-to-severe RA (ACR/EULAR 2010 criteria) who were IV abatacept-naive and initiated SC abatacept 125 mg once weekly, were enrolled into two cohorts: biologic (b)DMARD-naive patients and those with ≥1 prior bDMARD treatment failure. This post hoc analysis assessed abatacept retention rate at 2 years in a subset of patients with RF/ACPA serostatus data (n=1748) from the ASCORE study (N=2892; as observed). Baseline (BL) serostatus groups examined by treatment line were: RF/ACPA double positive (+/+) RA, RF/ACPA single positive (RF+/ACPA– or RF–/ACPA+) RA (data not shown) and RF/ACPA double negative (–/–) RA. Last observation carried forward (LOCF) analyses were used to assess change from BL and measures of disease remission (DAS28 [CRP] <2.6, CDAI ≤2.8, and SDAI ≤3.3) in patients with +/+ RA versus –/– RA.

Results:

BL demographic and disease characteristics were similar across serostatus groups and treatment lines (Table 1). Mean age was 57.1 and 57.8 years for +/+ RA and –/– RA, respectively. Mean DAS28 (CRP) was 4.7 and 4.8 for +/+ RA and –/– RA, respectively. In patients with +/+ RA, abatacept retention was greater when given as first-line treatment (57% vs 48% when given as ≥ second-line) (Figure 1). Retention was similar in patients with –/– RA regardless of treatment line. After 2 years, mean (SE) change from BL (LOCF) in DAS28 (CRP) was –1.41 (0.06) and –0.97 (0.09) for patients with +/+ and –/– RA, respectively. For patients with +/+ RA, mean (SE) change from BL in DAS28 (CRP) was –1.62 (0.08) for those in whom abatacept was first-line and –1.19 (0.08) for those in whom abatacept was ≥ second-line. For patients with –/– RA, mean (SE) change from BL in DAS28 (CRP) was –1.03 (0.13) for those in whom abatacept was first-line and –0.93 (0.12) for those in whom abatacept was ≥ second-line. Remission rates (LOCF) were significantly (p<0.0001) higher in patients with +/+ RA vs –/– RA respectively: DAS28 (CRP) 38.4% (n=393) versus 19.3% (n=62); CDAI 50.6% (n=513) versus 33.0% (n=107); and SDAI 49.5% (n=497) versus 32.5% (n=102).

Table 1.

BL demographics and disease characteristics by RF/ACPA status

+/+ RA(n=1079)–/– RA(n=343)First-line (n=511)≥ second-line (n=568)First-line(n=140)≥ second-line(n=203)Age57.1 (13.4)57.1 (12.2)59.5 (14.7)56.6 (13.2)DAS28 (CRP)4.7 (1.2)4.7 (1.2)4.8 (1.1)4.8 (1.2)CDAI26.6 (12.5)26.6 (12.4)27.7 (12.5)28.6 (13.8)SDAI28.1 (13.1)28.1 (12.9)29.1 (12.9)30.2 (14.7)

Data are mean (SD). Patients with missing data for BL RF/ACPA status are excluded.

ACPA=anti-citrullinated protein antibody; BL=baseline.

Conclusion:

In this real-world analysis, patients with +/+ RA treated with first-line abatacept had higher retention than patients receiving abatacept as a ≥ second-line therapy. Remission rates on abatacept were higher in patients with +/+ RA versus –/– RA. These results support early treatment with abatacept and highlight the importance of further evaluating precision medicine approaches in RA.

References:

[1]Smolen JS, et al. Ann Rheum Dis 2020;79:685–699.

[2]Alten R, et al. Ann Rheum Dis 2019;78(suppl 2):A1639.

Acknowledgements:

Professional medical writing and editorial assistance was provided by Lindsay Craik at Caudex and was funded by Bristol Myers Squibb. This study was funded by Bristol Myers Squibb.

Disclosure of Interests:

Rieke Alten Speakers bureau: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Consultant of: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Grant/research support from: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Xavier Mariette Consultant of: Bristol Myers Squibb, Galapagos, Gilead, GlaxoSmithKline, Janssen, Pfizer, UCB, Rene-Marc Flipo Speakers bureau: AbbVie, Bristol Myers Squibb, Janssen, Lilly, Medac, Merck Sharp & Dohme, Novartis, Pfizer, Roche-Chugai, Grant/research support from: Amgen, Janssen, Novartis, Pfizer, Roberto Caporali Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Fresenius Kabi, Galapagos, Gilead, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Samsung Bioepis, Sanofi, UCB, Consultant of: Galapagos, Gilead, Janssen, Lilly, Merck Sharp & Dohme, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead, Merck Serono, Pfizer, Roche, Sanofi, Grant/research support from: Gilead, Pfizer, Roche, UCB, Yusuf Patel: None declared, Raimón Sanmartí Speakers bureau: AbbVie, Bristol Myers Squibb, Gebro, Janssen, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, Consultant of: AbbVie, Bristol Myers Squibb, Gebro, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, Grant/research support from: Bristol Myers Squibb, Merck Sharp & Dohme, Pfizer, Sara Marsal Speakers bureau: Bristol Myers Squibb, Celgene, Pfizer, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol Myers Squibb, Celgene, Galapagos, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, UCB, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Sanofi, UCB, M.T. Nurmohamed Speakers bureau: AbbVie, Bristol Myers Squibb, Eli Lilly, Roche, Sanofi, Consultant of: AbbVie, Celgene, Celltrion, Eli Lilly, Janssen, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Mundipharma, Novartis, Pfizer, Roche, Sanofi, Hedley Griffiths Consultant of: AbbVie, Gilead, Janssen, Novartis, Peter Peichl: None declared, Bettina Bannert: None declared, Adrian Forster: None declared, Melanie Chartier Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Sean Connolly Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Yedid Elbez Consultant of: Bristol Myers Squibb, Christiane Rauch Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Vadim Khaychuk Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Karissa Lozenski Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb

POS0657 GEOGRAPHIC VARIATION OF SAFETY IN THE FILGOTINIB RHEUMATOID ARTHRITIS PROGRAM

Background:

The Janus kinase-1 preferential inhibitor filgotinib (FIL) improved signs and symptoms of rheumatoid arthritis (RA) in the FIL clinical program.1–3

Objectives:

To assess FIL safety across regions.

Methods:

This was an analysis of patients (pts) meeting 2010 ACR/EULAR RA criteria in pooled phase (P)2 DARWIN 1–2 (D1–2), P3 FINCH 1–3 (F1–3), and long-term extension studies (DARWIN 3, FINCH 4). Data were analyzed by region: North America, South and Central America, Western Europe, Eastern Europe, Asia, South East (SE) Asia, and Other. Week (W)12 placebo (PBO)-controlled analysis included data from pts receiving once-daily FIL 100 mg (FIL100), FIL 200 mg (FIL200), or PBO for ≤12W (D1–2, F1–2); long-term as-treated data included pts from all 7 studies receiving FIL100 or FIL200; data after rerandomization were included and contributed to treatment received. Data presented as exposure-adjusted incidence rates (EAIRs)/100 patient-years of exposure (PYE) of treatment-emergent (TE) adverse events (TEAEs).

Results:

Table 1 shows EAIRs of TEAEs in PBO-controlled analysis. EAIRs/100 PYE of all TEAEs in Western Europe, Asia, and Other were higher than in remaining regions and for PBO vs FIL arms; EAIRs for FIL200/FIL100 in North America and SE Asia were higher vs PBO. EAIRs/100 PYE of TE serious AEs were higher in SE Asia for FIL100 and for FIL200/FIL100 in Other, with high PBO EAIRs in Western Europe. EAIRs/100 PYE of TEAEs leading to study discontinuation were higher in FIL arms vs PBO in Western Europe and Other (FIL200); in Asia and SE Asia, EAIRs were higher for PBO vs FIL200/FIL100.

Table 1.

EAIR of TEAEs (placebo-controlled)

North AmericaN = 481South and Central AmericaN = 350Western EuropeN = 141Eastern EuropeN = 933AsiaN = 236South East AsiaN= 135OtherN = 70TEAEFIL200a216.9 (162.5, 289.5)205.6 (155.1, 272.6)285.0 (188.6, 430.8)150.3 (119.3, 189.4)248.9 (180.6, 343.1)165.1 (104.0, 262.1)298.4 (150.3, 592.5)FIL100b182.2 (136.8, 242.7)159.2 (117.3, 216.1)285.7 (183.7, 444.3)146.4 (115.9, 185.0)246.9 (180.3, 338.1)153.7 (94.2, 251.0)263.5 (113.9, 609.2)PBOC174.5 (130.3, 233.7)162.1 (118.8, 221.2)314.9 (200.7, 493.9)148.4 (117.6, 187.4)259.0 (188.0, 356.8)81.6 (40.8, 163.3)306.0 (142.8, 655.7)TE serious AEFIL200a14.3 (6.0, 34.4)11.4 (3.7, 35.5)8.3 (1.2, 59.0)12.2 (5.2, 28.7)5.5 (0.8, 38.9)0.0 (0.0, ∞)49.6 (10.2, 144.9)FIL100b10.6 (4.0, 28.3)7.2 (1.8, 28.7)19.9 (5.0, 79.7)15.1 (6.8, 33.7)16.2 (5.2, 50.2)28.8 (9.3, 89.4)20.5 (0.5, 114.0)PBOC16.1 (7.2, 35.9)7.5 (1.9, 30.0)29.6 (9.5, 91.7)4.6 (1.3, 15.8)11.4 (2.8, 45.5)10.2 (1.4, 72.4)0.0 (0.0, 69.2)TEAE leading to discontinuationFIL200a8.6 (2.8, 26.6)3.8 (0.1, 21.2)16.6 (4.2, 66.5)12.9 (5.5, 30.5)0.0 (0.0, 20.2)9.2 (1.3, 65.1)16.5 (0.4, 92.1)FIL100b10.6 (4.0, 28.3)7.2 (0.9, 26.0)19.9 (5.0, 79.7)1.9 (0.2, 13.8)5.4 (0.1, 30.1)9.6 (1.4, 68.2)0.0 (0.0, 75.5)PBOC5.4 (1.3, 21.5)0.0 (0.0, 13.8)9.9 (1.4, 70.0)12.9 (5.4, 30.7)17.1 (3.5, 49.9)20.4 (5.1, 81.6)0.0 (0.0, 69.2)

Data presented as EAIR (95% CI)/100 patient-years

aN = 777, 179.8 PYE bN = 788, 181.6 PYE cN = 781, 178.4 PYE

A subject may contribute to more than one treatment group if they received more than one treatment of interest.

EAIR and corresponding 95% CI were estimated using Poisson regression model by treatment, including study and treatment with an offset of natural log of exposure time, except when 0 events occurred; Poisson model was not adjusted by study.

AE, adverse event; CI, confidence interval; EAIR, exposure-adjusted incidence rate; FIL, filgotinib; PBO, placebo; PYE, patient-years of exposure; TE, treatment-emergent

Figure shows serious infections (SI), venous thromboembolism (VTE) and herpes zoster (HZ) EAIRs.

EAIRs for SI were highest in Other for FIL200 and SE Asia for FIL100. While VTE EAIRs were low, pts in 5/7 regions had VTE. HZ EAIRs were highest in Asia.

Conclusion:

Although EAIR of TEAEs varied between regions, no consistent trend was reflected in any particular region.

References:

[1]Genovese et al. JAMA. 2019;322:315–25.

[2]Westhovens et al. Ann Rheum Dis. 2021; online first.

[3]Combe et al. Ann Rheum Dis. 2021; online first.

Disclosure of Interests:

Bernard Combe Speakers bureau: BMS; Eli Lilly & Co.; Gilead Sciences, Inc.; MSD; Pfizer; Roche-Chugai; and UCB, Consultant of: AbbVie; Eli Lilly & Co.; Gilead Sciences, Inc.; Janssen; Pfizer; Roche-Chugai; and Sanofi, Grant/research support from: Novartis, Pfizer, and Roche-Chugai, Tsukasa Matsubara Speakers bureau: Pfizer Japan, Nichi-Iko, Astellas, Meiji Seika, Bristol-Myers Squibb, AbbVie GK, Janssen, Chugai, Eisai, AYUMI, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., YingMeei Tan Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Zhaoyu Yin Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Jaehyung Hong Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Robin Besuyen Shareholder of: Galapagos, BV, Employee of: Galapagos, BV, Antonio Gomez-Centeno Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly & Co., Gebro, Janssen, Menarini, Merck Sharp & Dohme, Pfizer, Roche, Rubio, Sanofi, and UC, Consultant of: AbbVie, Biogen, Bristol-Myers Squibb, Celgene, Eli Lilly & Co., Gebro, Gilead Sciences, Inc., Hospira, Merck Sharp & Dohme, Pfizer, Roche, Rubio, Sandoz, Sanofi, Grant/research support from: Boehringer Ingelheim, Celltrion, Eli Lilly & Co., Galapagos NV, Gilead Sciences, Inc., Novartis, Pfizer, Roche, Sanofi, UCB, YL Biologics, Maya H Buch Speakers bureau: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB, Consultant of: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB, Grant/research support from: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB

POS0599 DISEASE ACTIVITY IN PATIENTS WITH RA BY SEROSTATUS AND TREATMENT LINE, FOLLOWING TREATMENT WITH ABATACEPT: RESULTS FROM AN INTERNATIONAL OBSERVATIONAL STUDY

Background:

RF and anti-citrullinated protein antibodies (ACPAs) are associated with a severe and aggressive disease course in patients with RA.1 Abatacept is a selective co-stimulation modulator for the treatment of RA.2 ASCORE (Abatacept SubCutaneOus in Routine Clinical PracticE; NCT02090556) was a 2-year, observational, prospective, multicentre study of SC abatacept for the treatment of RA in routine clinical practice.3

Objectives:

To determine if serostatus and treatment line impacted disease activity in patients enrolled in the ASCORE study.

Methods:

Eligible patients, aged ≥18 years, with active moderate-to-severe RA (ACR/EULAR 2010 criteria) who were IV abatacept-naive and initiated SC abatacept 125 mg once weekly, were enrolled into two cohorts: biologic (b)DMARD-naive patients and those with ≥1 prior bDMARD treatment failure. This post hoc analysis assessed the mean change in disease activity (CDAI, SDAI and DAS28 [ESR]) from baseline (BL) at 6, 12, 18 and 24 months in response to treatment with abatacept. Patients were stratified by BL serostatus (all patients, RF/ACPA double positive [+/+] RA; RF/ACPA single positive [+/–; RF+/ACPA– or RF–/ACPA+] RA and RF/ACPA double negative [–/–] RA) and by line of therapy (all patients, patients receiving abatacept as a first-line or ≥ second-line therapy and those receiving abatacept following 1 or ≥2 prior bDMARDs). Overall patient data, as well as data for patients who were +/– or those who had 1 or ≥2 previous bDMARDs, are not shown. Estimates of mean difference are from t-test.

Results:

Among 2892 eligible patients in ASCORE, 1748 patients with RF/ACPA status available at BL were included in this analysis (1079 +/+ RA, 326 +/− RA and 343 −/− RA). After 6 months, patients with +/+ RA on first-line abatacept therapy had better improvements in CDAI and SDAI scores from BL than patients on ≥ second-line abatacept therapy (mean difference [95% CI]: –3.4 [–5.6, –1.1]; p=0.0032 and –3.9 [–6.5, –1.3]; p=0.0035, respectively); better improvements in SDAI were also seen after 12 months (mean difference [95% CI]: –3.5 [–6.5, –0.5]; p=0.0207). Changes in CDAI and SDAI scores were comparable after 18 and 24 months. At 6 and 12 months, patients with +/+ RA on first-line therapy had better improvements from BL in DAS28 (ESR) than those on ≥ second-line therapy (mean differences [95% CI]: –0.5 [–0.8, –0.2]; p=0.0002 and –0.4 [–0.7, –0.0]; p=0.0317, respectively); changes were comparable at 18 and 24 months (Figure 1). For patients on ≥ second-line therapy, at 18 months those with +/+ RA had better improvements from BL in DAS28 (ESR) than those with –/– RA (mean difference [95% CI]: –0.7 [–1.2, –0.1]; p=0.0232). For patients not stratified by line of therapy, changes in DAS28 (ESR) were comparable between the +/+ and –/– RA subgroups over time, with the exception of 6 months where patients with –/– RA had better improvements from BL compared with patients with +/+ RA (mean difference [95% CI]: –0.3 [–0.6, –0.0]; p=0.0495).

Conclusion:

In this real-world, post hoc analysis, patients with +/+ RA who received abatacept as a first-line therapy had greater early improvements in disease activity compared with patients who received abatacept as a ≥ second-line therapy. Improvements in disease activity at 24 months were comparable between patients who were +/+ and those who were –/–. Larger studies are needed to further corroborate these findings.

References:

[1]Katchamart W, et al. Rheumatol Int 2015;35:1693–1699.

[2]Malmström V, et al. Nat Rev Immunol 2017;17:60–75.

[3]Alten R, et al. Ann Rheum Dis 2019;78(Suppl 2):A1639.

Acknowledgements:

Professional medical writing and editorial assistance was provided by Rachel Rankin, PhD, at Caudex and was funded by Bristol Myers Squibb. This study was funded by Bristol Myers Squibb.

Disclosure of Interests:

Rieke Alten Speakers bureau: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Consultant of: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Grant/research support from: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Xavier Mariette Consultant of: Bristol Myers Squibb, Galapagos, Gilead, GlaxoSmithKline, Janssen, Pfizer, UCB, Rene-Marc Flipo Speakers bureau: AbbVie, Bristol Myers Squibb, Janssen, Lilly, Medac, Merck Sharp & Dohme, Novartis, Pfizer, Roche-Chugai, Grant/research support from: Amgen, Janssen, Novartis, Pfizer, Roberto Caporali Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Fresenius Kabi, Galapagos, Gilead, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Samsung Bioepis, Sanofi, UCB, Consultant of: Galapagos, Gilead, Janssen, Lilly, Merck Sharp & Dohme, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead, Merck Serono, Pfizer, Roche, Sanofi, Grant/research support from: Gilead, Pfizer, Roche, UCB, Yusuf Patel: None declared, Raimón Sanmartí Speakers bureau: AbbVie, Bristol Myers Squibb, Gebro, Janssen, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, Consultant of: AbbVie, Bristol Myers Squibb, Gebro, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, Grant/research support from: Bristol Myers Squibb, Merck Sharp & Dohme, Pfizer, Sara Marsal Speakers bureau: Bristol Myers Squibb, Celgene, Pfizer, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol Myers Squibb, Celgene, Galapagos, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, UCB, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Sanofi, UCB, M.T. Nurmohamed Speakers bureau: AbbVie, Bristol Myers Squibb, Eli Lilly, Roche, Sanofi, Consultant of: AbbVie, Celgene, Celltrion, Eli Lilly, Janssen, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Mundipharma, Novartis, Pfizer, Roche, Sanofi, Hedley Griffiths Consultant of: AbbVie, Gilead, Janssen, Novartis, Peter Peichl: None declared, Bettina Bannert: None declared, Adrian Forster: None declared, Melanie Chartier Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Yedid Elbez Consultant of: Bristol Myers Squibb, Christiane Rauch Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Karissa Lozenski Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Vadim Khaychuk Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb

AB0207 ANALYSIS OF ABATACEPT TREATMENT RETENTION AND EFFICACY ACCORDING TO DISEASE DURATION AND TREATMENT LINE IN A REAL-WORLD SETTING

Background:

Longer disease duration and greater number of prior DMARDs have been associated with lower treatment efficacy in patients with RA.1 Abatacept is a biologic (b)DMARD for treatment of moderate-to-severe RA and is available in SC formulation, which may offer convenience benefits with efficacy similar to IV administration.2 ASCORE (Abatacept SubCutaneOus in Routine Clinical PracticE; NCT02090556) was a 2-year, observational, prospective, multicentre study of SC abatacept for treatment of RA in routine clinical practice.3

Objectives:

This post hoc analysis was conducted to determine if retention and efficacy of abatacept were impacted by disease duration and/or treatment line.

Methods:

Eligible patients, aged ≥18 years, with active moderate-to-severe RA (ACR/EULAR 2010 criteria) who were IV abatacept-naive and initiated SC abatacept 125 mg once weekly, were enrolled into two cohorts: bDMARD-naive patients and those with ≥1 prior bDMARD treatment failure. This post hoc analysis evaluated abatacept retention using Kaplan-Meier estimates, as well as disease activity scores (DAS28 [ESR]), CDAI and SDAI in patients with disease duration of ≤2, 3–5, 6–10 or >10 years, and in patients taking abatacept as first-line or ≥ second-line treatment.

Results:

Table 1 shows baseline (BL) characteristics. Mean age increased with disease duration; other characteristics were comparable across groups. Retention proportions (95% CIs) at Month 24 were 0.50 (0.4, 0.5), 0.47 (0.4, 0.5), 0.51 (0.5, 0.5) and 0.46 (0.4, 0.5) in the ≤2, 3–5, 6–10 and >10 years’ duration groups, respectively. Proportion of patients (95% CI) with ≤2 years’ duration retaining treatment at Month 24 were 0.51 (0.4, 0.6) among those using abatacept as first-line treatment and 0.44 (0.3, 0.6) among those using abatacept as a ≥ second-line treatment (Figure 1). Proportions (95% CI) at Month 24 were 0.51 (0.5, 0.6), 0.57 (0.5, 0.6) and 0.52 (0.5, 0.6) in first-line patients and 0.43 (0.4, 0.5), 0.48 (0.4, 0.5) and 0.44 (0.4, 0.5) in ≥ second-line patients in the 3–5, 6–10 and >10 years’ duration groups, respectively. Mean (SE) changes from BL in DAS28 (ESR) at Month 24 were –2.12 (0.205), –1.86 (0.151), –2.07 (0.140) and –2.05 (0.115) in the ≤2, 3–5, 6–10 and >10 years’ duration groups, respectively; respective mean (SE) changes in CDAI were –18.74 (1.604), –15.60 (1.099), –18.50 (1.038) and –17.68 (0.850); and respective mean (SE) changes in SDAI were –19.10 (1.873), –15.72 (1.345), –19.54 (1.103) and –17.07 (0.939).

Conclusion:

In this post hoc analysis of the real-world ASCORE trial, patients with RA receiving abatacept in clinical practice as first-line therapy had better retention versus those receiving it as a ≥ second-line treatment, regardless of disease duration at BL. Retention rates were similar across disease duration subgroups. Improvements in disease activity were seen in all duration subgroups, without consistently greater or lesser improvement seen with longer disease duration.

References:

[1]Aletaha D, et al. Ann Rheum Dis 2019;78:1609–1615.

[2]Genovese MC, et al. Arthritis Rheumatol 2011;63:2854–2864.

[3]Alten R, et al. Ann Rheum Dis 2019;78(suppl 2):A1639.

Table 1.

BL characteristics (n=2872)

RA disease duration, years≤2(n=338)3–5(n=655)6–10(n=686)>10(n=1193)Age, years n3386556861193 Mean (SD)55.2 (12.8)55.6 (12.7)56.9 (13.0)59.9 (12.2)Weight, kg n3276296651150 Mean (SD)75.3 (18.1)76.4 (19.0)74.7 (17.4)72.9 (16.0)DAS28 (ESR) n247439441743 Mean (SD)5.2 (1.3)4.9 (1.3)5 (1.2)5.1 (1.3)DAS28 (CRP) n267460467799 Mean (SD)4.7 (1.2)4.6 (1.2)4.7 (1.1)4.7 (1.2)CDAI n269477474805 Mean (SD)26.9 (12.7)25.3 (12.2)26.8 (12.4)26.6 (12.2)SDAI n255448445749 Mean (SD)28.3 (13.3)26.8 (12.9)27.9 (12.6)28.0 (12.7)RF status, n (%) RF+159 (47.0)342 (52.2)345 (50.3)597 (50.0) RF–103 (30.5)152 (23.2)158 (23.0)215 (18.0)Anti-CCP status, n (%) Anti-CCP+165 (48.8)332 (50.7)333 (48.5)516 (43.3) Anti-CCP–89 (26.3)126 (19.2)137 (20.0)175 (14.7)

Patients with missing duration of disease are excluded.

CCP=cyclic citrullinated peptide.

Acknowledgements:

Professional medical writing and editorial assistance was provided by Rob Coover, MPH, at Caudex and was funded by Bristol Myers Squibb. This study was funded by Bristol Myers Squibb.

Disclosure of Interests:

Rieke Alten Speakers bureau: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Consultant of: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Grant/research support from: AbbVie, Bristol Myers Squibb, Gilead, Janssen, Lilly, Pfizer, Xavier Mariette Consultant of: Bristol Myers Squibb, Galapagos, Gilead, GlaxoSmithKline, Janssen, Pfizer, UCB, Rene-Marc Flipo Speakers bureau: AbbVie, Bristol Myers Squibb, Janssen, Lilly, Medac, Merck Sharp & Dohme, Novartis, Pfizer, Roche-Chugai, Grant/research support from: Amgen, Janssen, Novartis, Pfizer, Roberto Caporali Speakers bureau: AbbVie, Amgen, Bristol Myers Squibb, Celltrion, Fresenius Kabi, Galapagos, Gilead, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Samsung Bioepis, Sanofi, UCB, Consultant of: Galapagos, Gilead, Janssen, Lilly, Merck Sharp & Dohme, Maya H Buch Speakers bureau: AbbVie, Consultant of: AbbVie, Eli Lilly, Gilead, Merck Serono, Pfizer, Roche, Sanofi, Grant/research support from: Gilead, Pfizer, Roche, UCB, Yusuf Patel: None declared, Raimón Sanmartí Speakers bureau: AbbVie, Bristol Myers Squibb, Gebro, Janssen, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, Consultant of: AbbVie, Bristol Myers Squibb, Gebro, Lilly, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, Grant/research support from: Bristol Myers Squibb, Merck Sharp & Dohme, Pfizer, Sara Marsal Speakers bureau: Bristol Myers Squibb, Celgene, Pfizer, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol Myers Squibb, Celgene, Galapagos, Merck Sharp & Dohme, Pfizer, Roche, Sanofi, UCB, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Sanofi, UCB, M.T. Nurmohamed Speakers bureau: AbbVie, Bristol Myers Squibb, Eli Lilly, Roche, Sanofi, Consultant of: AbbVie, Celgene, Celltrion, Eli Lilly, Janssen, Grant/research support from: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Merck Sharp & Dohme, Mundipharma, Novartis, Pfizer, Roche, Sanofi, Hedley Griffiths Consultant of: AbbVie, Gilead, Janssen, Novartis, Peter Peichl: None declared, Bettina Bannert: None declared, Adrian Forster: None declared, Melanie Chartier Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Yedid Elbez Consultant of: Bristol Myers Squibb, Christiane Rauch Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Vadim Khaychuk Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Karissa Lozenski Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb

POS0658 GEOGRAPHIC VARIATION OF EFFICACY IN THE FILGOTINIB RHEUMATOID ARTHRITIS PROGRAM

Background:

The Janus kinase-1 preferential inhibitor filgotinib (FIL) improved signs and symptoms of rheumatoid arthritis (RA) across the FIL clinical program.1–3

Objectives:

To assess FIL efficacy across geographic regions.

Methods:

Pooled data from patients (pts) meeting 2010 ACR/EULAR RA criteria randomised to once-daily FIL 200 mg (FIL200), FIL100 mg (FIL100), or placebo (PBO) with background conventional synthetic disease-modifying antirheumatic drugs in DARWIN 1 (P2; up to week [W]12) and FINCH 1–2 (P3; up to W24) studies were evaluated. Data were analysed by region: North America, South and Central America, Western Europe, Eastern Europe, Asia, South East (SE) Asia, and Other. W12 American College of Rheumatology 20% improvement (ACR20) and W24 Disease Activity Score in 28 joints (C-reactive protein) (DAS28[CRP]) <2.6 and ≤3.2 response rates were analysed by a logistic regression model. Change from baseline (CFB) in Health Assessment Questionnaire-Disability Index (HAQ-DI) at W12 was analysed by a mixed-effects model for repeated measures. Analyses were exploratory and not adjusted for multiplicity.

Results:

Despite high PBO response rates in Eastern Europe and South and Central America, greater proportions of pts receiving FIL200 or FIL100 vs PBO achieved ACR20 at W12 (P <0.05) in all regions, except Other (with lowest sample size, n = 69), where both FIL doses were numerically greater than PBO (Table 1). At W12, least-squares mean CFB in HAQ-DI improved for pts receiving FIL200 or FIL100. vs PBO (P <0.05) in all regions, except SE Asia, where improvement was numeric (Table 1).

Table 1.

Proportion of pts achieving ACR20 and LSM change from baseline HAQ-DI at week 1

ACR20HAQ-DIFIL200FIL100FIL200FIL100FIL200FIL100North America64.8*58.3*33.8−0.63*−0.58*−0.34n = 455(56.7, 72.9)(50.3, 66.4)(26.0, 41.6)(−0.70, −0.56)(−0.65, −0.51)(−0.41, −0.27)South and Central America77.277.357.4−0.77*−0.67*−0.43n = 283(68.1, 86.3)†(65.8, 86.2)†(46.9, 68.0)(−0.85, −0.68)(−0.75, −0.59)(−0.52, −0.35)Western Europe69.4*68.3*24.4−0.69*−0.61*−0.28n = 135(55.5, 83.3)(52.8, 83.8)(10.8. 38.1)(−0.80, −0.58)(−0.73, −0.49)(−0.40, −0.17)Eastern Europe77.1*69.1*54.6−0.62*−0.51*−0.34n = 822(71.9, 82.3)(63.5, 74.7)(48.5, 60.7)(−0.68, −0.56)(−0.57, −0.45)(−0.40, −0.28)Asia81.0*60.0†37.7−0.83*−0.61†−0.42n = 236(71.7, 90.3)(48.6, 71.4)(26.2, 49.1)(−0.92, −0.73)(−0.70, −0.52)(−0.52, −0.33)South East Asia70.2†71.1†39.5−0.61−0.57−0.45n = 135(56.1, 84.4)(56.8, 85.5)(23.8, 55.3)(−0.73, −0.49)(−0.69, −0.45)(−0.58, −0.33)Other60.052.439.1−0.56‡−0.60‡−0.33n = 69(38.8, 81.2)(28.6, 76.1)(17.0, 61.2)(−0.72, −41)(−0.76, −0.43)(−0.49, −0.17)Overall73.4*66.4*45.3−0.71*−0.61*−0.40N = 2135(70.1, 76.8)(62.9, 70.0)(41.5, 49.0)(−0.76, −0.66)(−0.66, −0.56)(−0.45, −0.35)

Includes only patients initially randomised to the treatment groups in each study for the comparison of interest. ACR20 presented as percentage (95% CI); 95% CI was based on normal approximation method with a continuity correction; P values calculated from the logistic regression.HAQ-DI presented as LSM (95% CI); LSM, 95% CI, and P value calculated from a mixed-effects model for repeated measures.*P <0.001, †P <0.01, ‡P <0.05; not adjusted for multiplicity.

ACR20, American College of Rheumatology 20% improvement; CI, confidence interval; FIL, filgotinib; HAQ-DI, Health Assessment Questionnaire-Disability Index; LSM, least square mean; PBO, placebo.

At W24, DAS28(CRP) <2.6 and ≤3.2 response rates were higher for both doses of FIL vs PBO (P <0.05) in all regions, with the exception of Other, where PBO was higher than FIL100 for DAS28(CRP) <2.6 (Figure 1).

Conclusion:

In exploratory analyses, ACR20, DAS28(CRP) <2.6 and ≤3.2 response rates and HAQ-DI scores varied between regions; however, no stable trend was shown in any particular region. Small pt numbers in some subgroups may confound statistical analysis.

References:

[1]Genovese et al. JAMA. 2019;322:315–25.

[2]Westhovens et al. Ann Rheum Dis. 2021; online first.

[3]Combe et al. Ann Rheum Dis. 2021; online first.

Disclosure of Interests:

Maya H Buch Speakers bureau: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB, Consultant of: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB., Grant/research support from: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB., Tsukasa Matsubara Speakers bureau: Pfizer Japan, Nichi-Iko, Astellas, Meiji Seika, Bristol-Myers Squibb, AbbVie GK, Janssen, Chugai, Eisai, AYUMI, Bernard Combe Speakers bureau: BMS; Eli Lilly & Co.; Gilead Sciences, Inc.; MSD; Pfizer; Roche-Chugai; and UCB, Consultant of: AbbVie; Eli Lilly & Co.; Gilead Sciences, Inc.; Janssen; Pfizer; Roche-Chugai; and Sanofi, Grant/research support from: Novartis, Pfizer, and Roche-Chugai, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., YingMeei Tan Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Zhaoyu Yin Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Jaehyung Hong Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Robin Besuyen Shareholder of: Galapagos, BV, Employee of: Galapagos, BV, Antonio Gomez-Centeno Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly & Co., Gebro, Janssen, Menarini, Merck Sharp & Dohme, Pfizer, Roche, Rubio, Sanofi, and UCB, Consultant of: AbbVie, Biogen, Bristol-Myers Squibb, Celgene, Eli Lilly & Co., Gebro, Gilead Sciences, Inc., Hospira, Merck Sharp & Dohme, Pfizer, Roche, Rubio, Sandoz, Sanofi, Grant/research support from: Boehringer Ingelheim, Celltrion, Eli Lilly & Co., Galapagos NV, Gilead Sciences, Inc., Novartis, Pfizer, Roche, Sanofi, UCB, YL Biologics

POS0092 HERPES ZOSTER IN THE FILGOTINIB RHEUMATOID ARTHRITIS PROGRAM

Background:

The once daily, oral Janus kinase (JAK)-1 preferential inhibitor filgotinib (FIL) improved signs and symptoms of rheumatoid arthritis (RA) in phase (P)3 trials.1-3 Patients (pts) with RA have increased herpes zoster (HZ) reactivation risk vs the general population. JAK inhibition is associated with increased infection incidence, including HZ.4

Objectives:

To assess long-term safety of FIL across the global clinical program with respect to HZ.

Methods:

Pts meeting 2010 ACR/EULAR RA criteria in a pooled analysis of P2 DARWIN 1–2 (D1–2), P3 FINCH 1–3 (F1–3), and long-term extension studies (D3, F4) were included. Placebo (PBO)-controlled as-randomised analysis included pts receiving FIL 100 mg (FIL100), FIL 200 mg (FIL200), or PBO up to week (W)12 (D1–2, F1–2); active-controlled as-randomised analysis included pts receiving FIL100, FIL200, adalimumab (ADA), or methotrexate (MTX) up to W52 (F1, F3). Long-term as-treated analysis included pts in all 7 studies receiving FIL100, FIL200, ADA, MTX, or PBO; data after re-randomisation were included and contributed to treatment received. Exposure-adjusted incidence rates (EAIR)/100 patient-years, calculated up to the last follow-up time or day, and differences with 95% confidence intervals (CIs) were calculated from the Poisson model. Logistic regression model was used for treatment-emergent (TE) HZ risk factor analysis and odds ratio (95% CI) and P value were provided.

Results:

Table 1 shows TE HZ EAIRs in a pooled analysis. Rates of HZ were lower for FIL200 vs PBO during the 12W PBO-controlled period. At 52W, HZ rates were higher for FIL200/100 vs active control. Long-term HZ rates increased for FIL200 vs FIL100.

Table 1.

EAIR of treatment-emergent herpes zoster

NPatient-years exposureEAIR(95% CI)EAIR diff(95% CI vs PBO/active control)12W PBO-controlled FIL200777179.80.6 (0.1, 3.9)−0.56 (−2.5, 1.3) FIL100788181.61.1 (0.3, 4.4)−0.02 (−2.2, 2.2) PBO781178.41.1 (0.3, 4.5)Active-controlled, as-randomiseda FIL200475439.71.4 (0.6, 3.0)0.69 (−0.7, 2.1) FIL100480443.40.9 (0.3, 2.4)0.23 (−1.1, 1.5) ADA325297.60.7 (0.2, 2.7)Active-controlled, as-randomiseda FIL200626578.01.7 (0.9, 3.2)0.65 (−0.8, 2.2) FIL100207195.01.5 (0.5, 4.8)0.46 (−1.6, 2.5) MTX416372.21.1 (0.4, 2.9)Long-term as-treatedb FIL20022674047.71.8 (1.4, 2.3)NC FIL10016472032.91.1 (0.8, 1.7)NC

aup to W52. bdata cut for LTE FINCH 4, Sept 19, 2019; DARWIN 3, April 26 2019.

ADA, adalimumab; CI, confidence interval; EAIR, exposure-adjusted incidence rate; FIL, filgotinib; MTX, methotrexate; NC, not calculated; PBO, placebo; W week.

Figure 1 shows multivariate logistic regression model of TE risk factors.

Of 104 pts with TE HZ in long-term as-treated analysis set, 5 receiving FIL200 had history of HZ; EAIR (95% CI) was 8.7 (3.6–21.0). Of 8 pts with multiple events, 3 had events of differing severity for the same HZ episode.

EAIRs (95% CI) of TE HZ in Asia were: 3.7 (1.7–8.1) FIL200, n=197; 2.8 (1.3–6.3) FIL100, n=158; 0 ADA, n=40; 2.8 (0.4–19.6) MTX, n=43; and 3.4 (0.5–23.8) PBO, n=77 in long-term as-treated population. EAIRs (95% CI) in rest of the world were: 1.6 (1.2–2.1) FIL200, n=2070; 0.9 (0.6–1.5) FIL100, n=1489; 0.8 (0.2–3.1) ADA, n=285; 0.9 (0.3–2.9) MTX, n=373; and 0.7 (0.2–2.9) PBO, n=704 for all pts as-treated.

Most TE HZ infections were mild to moderate and non-serious; 6 were serious; 2 were recurrences. No visceral TE HZ occurred across the FIL RA program; there was 1 case each of genital, disseminated, and ophthalmic HZ. The disseminated HZ occurred in a pt with prior HZ history. Lymphopenia was not associated with HZ during the PBO-controlled W12 period.

Conclusion:

HZ was more common in both FIL groups vs ADA or MTX up to 52 weeks but comparable vs PBO during the 12-week placebo-controlled period. In multivariate analyses, prior history of HZ, Asian region, and age ≥50 years were associated with increased HZ risk.

References:

[1]Genovese et al. JAMA. 2019;322:315–25.

[2]Westhovens et al. Ann Rheum Dis. 2021; online first.

[3]Combe et al. Ann Rheum Dis. 2021; online first.

[4]Higarashi and Honda. Drugs. 2020;80:1183–201.

Disclosure of Interests:

Kevin Winthrop Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly and Co., Galapagos NV, Gilead Sciences, GlaxoSmithKline, Pfizer, Roche, and UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, and Pfizer, Maya H Buch Speakers bureau: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB, Consultant of: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB, Grant/research support from: AbbVie; Eli Lilly and Company; Gilead Sciences, Inc.; Merck-Serono; Pfizer; Roche; Sandoz; Sanofi; and UCB, Jeffrey Curtis Grant/research support from: AbbVie, Amgen, BMS, Corrona, Eli Lilly, Janssen, Myriad, Pfizer, Regeneron, Roche, and UCB, Gerd Rüdiger Burmester Speakers bureau: AbbVie; Eli Lilly; Pfizer; and Gilead Sciences, Inc., Consultant of: AbbVie; Eli Lilly; Pfizer; and Gilead Sciences, Inc., Daniel Aletaha Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Medac, Merck, Merck Sharp & Dohme, Novartis, Pfizer, Roche, Sandoz, Sanofi/Genzyme, and UCB, Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, and Sanofi/Genzyme, Grant/research support from: AbbVie, Merck Sharp & Dohme, Novartis, and Roche, Koichi Amano Speakers bureau: AbbVie GK, Astellas, Chugai Pharmaceutical Co. Ltd., Eli Lilly, GlaxoSmithKline KK, Pfizer Japan, Mitsubishi-Tanabe Pharma, Grant/research support from: Asahi Kasei Pharma, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Iyabode Tiamiyu Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Cianna Leatherwood Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Lei Ye Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Qi Gong Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Robin Besuyen Shareholder of: Galapagos, BV, Employee of: Galapagos, BV, James Galloway Speakers bureau: Pfizer, Bristol-Myers Squibb, UCB and Celgene

THU0204 A SUBGROUP ANALYSIS OF LOW DISEASE ACTIVITY AND REMISSION FROM PHASE 3 STUDY OF FILGOTINIB IN PATIENTS WITH INADEQUATE RESPONSE TO BIOLOGIC DMARDS

Background:

Despite effective treatments, many patients (pts) with rheumatoid arthritis (RA) have inadequate responses to biologic DMARDs (bDMARD-IR), highlighting an unmet need. It is unclear whether prior bDMARD use affects efficacy of the oral, selective JAK-1 inhibitor filgotinib (FIL).

Objectives:

To explore clinical response to FIL in bDMARD-IR pts stratified by mode of action (MOA) and number of prior bDMARDs.

Methods:

The global, phase 3 FINCH-2 (NCT02873936) study treated 448 bDMARD-IR pts with active RA.1Pts were randomised 1:1:1 to once-daily FIL 200 mg, FIL 100 mg, or placebo (PBO) for 24 weeks. Efficacy was assessed by percent of pts achieving low disease activity (LDA) or remission at week (W)24 as measured by CDAI and DAS28(CRP) stratified by number and MOA of prior bDMARDs. Comparisons were not adjusted for multiplicity. Nonresponder imputation was used.

Results:

In total, 448 bDMARD-IR pts were included, 105 with prior experience with ≥3 bDMARDs (Table). At W24, pts receiving FIL were in LDA at a higher proportion vs PBO, irrespective of number of prior bDMARDs or MOA (Figure 1). For pts receiving FIL 200 vs PBO, DAS28(CRP) ≤3.2 was achieved at W24 by 52% vs 26%, 51% vs 22%, and 38% vs 9% of pts with 1, 2, or ≥3 prior bDMARDs, respectively, and 49% vs 21% and 50% vs 13% of pts exposed to TNF or IL-6 inhibitors; for all subgroups, rates were significantly higher vs PBO (Figure 1). Delta between FIL 200 mg and PBO was maintained irrespective of number or type of prior bDMARDs. At W24, pts receiving FIL achieved remission at numerically higher rates vs PBO (Figure 2). For pts receiving FIL 200 mg vs PBO, DAS28(CRP) <2.6 was achieved at W24 by 36% vs 14%, 30% vs 14%, and 22% vs 6% of pts with 1, 2, and ≥3 prior bDMARDs, respectively, and 31% vs 14% and 29% vs 9% of pts exposed to TNF or IL-6 inhibitors (Figure 2). Delta between FIL 200 mg and PBO was maintained irrespective of number or type of prior bDMARDs. Treatment-emergent adverse events across subgroups were consistent with overall study population.

Table.

Number and MOA of prior bDMARDs

FIL 200 mgn = 147FIL 100 mgn = 153PBOn = 148TotalN = 448Prior bDMARDs 173 (49.7)86 (56.2)77 (52.0)236 (52.7) 237 (25.2)33 (21.6)36 (24.3)106 (23.7) ≥337 (25.2)34 (22.2)34 (23.0)105 (23.4)LOE ≥1 bDMARD125 (85.0)129 (84.3)126 (85.1)380 (84.8)Intolerance ≥1 bDMARD36 (24.5)34 (22.2)32 (21.6)102 (22.8)Prior TNFi121 (82.3)134 (87.6)124 (83.8)379 (84.6) LOE ≥1 TNFi97 (66.0)113 (73.9)103 (69.6)313 (69.9) Intolerance ≥1 TNFi25 (17.0)24 (15.7)24 (16.2)73 (16.3)Prior non-TNFi73 (49.7)62 (40.5)75 (50.7)210 (46.9) LOE ≥1 non-TNFi52 (35.4)43 (28.1)56 (37.8)151 (33.7) Intolerance ≥1 non-TNFi13 (8.8)13 (8.5)11 (7.4)37 (8.3)Prior IL-6i34 (23.1)35 (22.9)32 (21.6)101 (22.5) LOE ≥1 IL-6i25 (17.0)22 (14.4)21 (14.2)68 (15.2) Intolerance ≥1 IL-6i5 (3.4)10 (6.5)5 (3.4)20 (4.5)

Data presented as n (%).

i, inhibitor; LOE, lack of efficacy.

Conclusion:

Treatment with FIL vs PBO led to higher rates of LDA and remission in pts with IR to IL-6 or TNF inhibition, or to 1, 2, or ≥3 prior bDMARDs, with a similar safety profile to the overall study population. A significantly higher proportion of pts overall receiving FIL 200 mg vs PBO were in LDA at W24. Improved efficacy of FIL vs PBO in pts who previously failed multiple bDMARDs indicates distinct benefits of selective JAK-1 inhibition with FIL.

References:

[1]Genovese, et al.JAMA2019;322(4):315–25.

Disclosure of Interests: :

Jacques-Eric Gottenberg Grant/research support from: BMS, Pfizer, Consultant of: BMS, Sanofi-Genzyme, UCB, Speakers bureau: Abbvie, Eli Lilly and Co., Roche, Sanofi-Genzyme, UCB, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Roberto Caporali Consultant of: AbbVie; Gilead Sciences, Inc.; Lilly; Merck Sharp & Dohme; Celgene; Bristol-Myers Squibb; Pfizer; UCB, Speakers bureau: Abbvie; Bristol-Myers Squibb; Celgene; Lilly; Gilead Sciences, Inc; MSD; Pfizer; Roche; UCB, Grace C. Wright Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Exagen, Eli Lilly, Myriad Autoimmune, Novartis, Pfizer, Regeneron Pharmaceuticals, Inc., Sanofi Genzyme, UCB, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Exagen, Eli Lilly, Myriad Autoimmune, Novartis, Regeneron Pharmaceuticals, Inc., Sanofi Genzyme, UCB, Tsutomu Takeuchi Grant/research support from: Eisai Co., Ltd, Astellas Pharma Inc., AbbVie GK, Asahi Kasei Pharma Corporation, Nippon Kayaku Co., Ltd, Takeda Pharmaceutical Company Ltd, UCB Pharma, Shionogi & Co., Ltd., Mitsubishi-Tanabe Pharma Corp., Daiichi Sankyo Co., Ltd., Chugai Pharmaceutical Co. Ltd., Consultant of: Chugai Pharmaceutical Co Ltd, Astellas Pharma Inc., Eli Lilly Japan KK, Speakers bureau: AbbVie GK, Eisai Co., Ltd, Mitsubishi-Tanabe Pharma Corporation, Chugai Pharmaceutical Co Ltd, Bristol-Myers Squibb Company, AYUMI Pharmaceutical Corp., Eisai Co., Ltd, Daiichi Sankyo Co., Ltd., Gilead Sciences, Inc., Novartis Pharma K.K., Pfizer Japan Inc., Sanofi K.K., Dainippon Sumitomo Co., Ltd., Kenneth Kalunian Grant/research support from: Pfizer, Lupus Research Alliance, Sanford Consortium, Consultant of: Genentech, Nektar, BMS, Janssen, AstraZeneca, Biogen, Vielabio, Equillium, Eli Lilly, ILTOO, Abbvie, Amgen, Roche, Gilead, Alena Pechonkina Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Ying Guo Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Shangbang Rao Shareholder of: Gilead Sciences Inc., Employee of: Gilead Sciences Inc., YingMeei Tan Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Robin Besuyen Shareholder of: Galapagos, Employee of: Galapagos, Mark C. Genovese Grant/research support from: Abbvie, Eli Lilly and Company, EMD Merck Serono, Galapagos, Genentech/Roche, Gilead Sciences, Inc., GSK, Novartis, Pfizer Inc., RPharm, Sanofi Genzyme, Consultant of: Abbvie, Eli Lilly and Company, EMD Merck Serono, Genentech/Roche, Gilead Sciences, Inc., GSK, Novartis, RPharm, Sanofi Genzyme

THU0188 EFFICACY OF FILGOTINIB IN PATIENTS WITH RHEUMATOID ARTHRITIS WITH POOR PROGNOSTIC FACTORS: POST HOC ANALYSIS OF FINCH 3

Background:

Patients (pts) with rheumatoid arthritis (RA) with poor prognostic factors (PPF) are at risk for RA progression if disease activity is not rapidly controlled. In FINCH 3 (NCT02886728), filgotinib (FIL)—an oral, potent, selective JAK1 inhibitor—was effective relative to methotrexate monotherapy (MTX mono) in MTX-naïve patients with ≥1 PPF—erosions, seropositivity for rheumatoid factor (RF) or anti-cyclic citrullinated peptide (CCP), or hsCRP ≥4 mg/L.1

Objectives:

This post hoc analysis examined FIL efficacy in FINCH 3 pts with multiple PPF.

Methods:

The global, phase 3, double-blind, active-controlled FINCH 3 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 mono, or PBO + MTX up to week (W)52. This subgroup analysis included pts with all 4 of the following PPF at baseline (PPF pts): erosions, seropositivity for RF or anti-CCP, hsCRP ≥4 mg/L, and DAS(28)CRP >5.1. Comparisons were not adjusted for multiplicity.

Results:

Of 1249 pts randomised and treated in FINCH 3, 510 had all 4 PPF. At baseline, relative to the overall FINCH 3 population, PPF pts had longer mean disease duration (2.4 vs 2.2 years); higher mean hsCRP (27.9 vs 17.5 mg/L), mTSS (17.9 vs 13.3), DAS28(CRP) (6.3 vs 5.7), HAQ-DI (1.76 vs 1.56), CDAI (44.3 vs 39.8), and SDAI (47.1 vs 41.5); and greater frequency of seropositivity for RF (90.6% vs 67.9%), anti-CCP (92.4% vs 68.5%), or both (82.9% vs 59.6%). Efficacy in PPF pts was comparable to data from all FINCH 3 pts (Table, Figures 1–2). PPF pts receiving FIL 200 mg with or without MTX vs MTX mono had higher frequencies of ACR20/50/70 response and greater improvement in HAQ-DI at W24; responses were numerically greater for FIL 200 mg + MTX vs FIL 100 mg + MTX or FIL 200 mg mono (Table) and were evident by W12 (data not shown). Radiographic progression at W24 was lower in PPF pts receiving FIL 200 mg + MTX or FIL 200 mg mono vs MTX mono (Figure 1). Proportions of PPF pts receiving FIL 200 mg with or without MTX who achieved DAS28(CRP) <2.6, CDAI ≤2.8, SDAI ≤3.3, and Boolean remission at W24 (Figure 2) were larger vs pts receiving MTX mono and numerically greater vs pts receiving FIL 100 mg + MTX.

Table.

Efficacy outcomes in patients with 4 PPF and all FINCH 3 patients at W24

FIL 200 mg+ MTXFIL 100 mg+ MTXFIL 200 mg monoMTXmonoPPFAllPPFAllPPFAllPPFAlln1724168520787210166416ACR20, %85.5*81.0***83.580.2*81.678.174.771.4ACR50, %70.3***61.5***58.857.0**59.858.1**48.245.7ACR70, %54.1***43.8***37.640.1***43.7*40.0***28.326.0HAQ-DIa−1.2***−0.94***−1.0*−0.90**−1.0*−0.89*−0.9−0.79

aMean change from baseline.

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

FIL, filgotinib; mono, monotherapy; MTX, methotrexate; PPF, poor prognostic factors.

Conclusion:

FIL treatment provided rapid and deep disease control including higher rates of remission and other clinical outcomes, improved physical function, and less radiographic progression compared with MTX alone in MTX-naïve pts with RA with 4 PPF, a population at risk for severe progressive disease. In pts with 4 PPF, W24 remission rates following FIL 200 mg with or without MTX were higher vs MTX mono and numerically higher vs FIL 100 mg + MTX.

References:

[1]Westhovens et al.Ann Rheum Dis2019;78(Suppl2):259–60.

Disclosure of Interests:

Daniel Aletaha Grant/research support from: AbbVie, Novartis, Roche, Consultant of: AbbVie, Amgen, Celgene, Lilly, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi Genzyme, Speakers bureau: AbbVie, Celgene, Lilly, Merck, Novartis, Pfizer, Sanofi Genzyme, UCB, Rene Westhovens Grant/research support from: Celltrion Inc, Galapagos, Gilead, Consultant of: Celltrion Inc, Galapagos, Gilead, Speakers bureau: Celltrion Inc, Galapagos, Gilead, Cecile Gaujoux-Viala Consultant of: AbbVie; Amgen; Bristol-Myers Squibb; Celgene; Gilead Sciences, Inc.; Janssen; Lilly; Medac; Merck-Serono; Mylan; Nordic Pharma; Novartis; Pfizer; Roche; Sandoz; Sanofi; UCB, Speakers bureau: AbbVie; Amgen; Bristol-Myers Squibb; Celgene; Gilead Sciences, Inc.; Janssen; Lilly; Medac; Merck-Serono; Mylan; Nordic Pharma; Novartis; Pfizer; Roche; Sandoz; Sanofi; UCB, Giovanni Adami: None declared, Alan Matsumoto Grant/research support from: AbbVie; BMS; Eli Lilly; Galapagos; Gilead Sciences, Inc.; GSK; Janssen; Novartis; Pfizer; Sanofi; UCB; Regeneron

, Consultant of: AbbVie; Gilead Sciences, Inc.; GSK; Novartis, Paul Bird Consultant of: AbbVie, Celgene Corporation, Eli Lilly, Janssen, Novartis, Pfizer – advisor, Speakers bureau: AbbVie, Celgene Corporation, Eli Lilly, Janssen, Novartis, Pfizer, Osvaldo Messina Speakers bureau: Amgen; Americas Health Foundation; Pfizer, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Beatrix Bartok 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., Thijs Hendrikx Shareholder of: Galapagos (share/warrant holder), Employee of: Galapagos, 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

FRI0236 FIRST PILOT STUDY OF T1 MAPPING MRI WITH ECV MEASUREMENT OF PERIPHERAL MUSCLE IN SYSTEMIC SCLEROSIS PATIENTS SHOWS DIFFUSE FIBROSIS

Background:

Peripheral myositis in systemic sclerosis (SSc) is associated with poor prognosis and myocarditis1but non-inflammatory myopathy, which also represents a significant cause of disability in SSc remains poorly understood. Cardiovascular magnetic resonance (CMR) T1 mapping studies in asymptomatic SSc patients show increased extracellular volume (ECV), suggestive of diffuse fibrosis in both the myocardium and thoracic muscle2.

Objectives:

To evaluate the feasibility of T1 mapping MRI and determine ECV in peripheral muscle of SSc patients with and without myopathy and explore the association between cardiac and peripheral muscle T1 mapping in SSc.

Methods:

This was a hypothesis-generating pilot and feasibility study. SSc patients, fulfilling the 2013 ACR/EULAR criteria, with no cardiovascular disease or myositis but either minimal muscle symptoms (non-inflammatory myopathy) or no muscle involvement and healthy volunteers (HV) underwent peripheral muscle T1 mapping-MRI for native T1 and extracellular volume (ECV) quantification of the dominant thigh. Patients also had T1 mapping CMR, and creatine-kinase (CK) measured. Non-inflammatory myopathy was defined as current/history of minimally raised CK (<600 IU/l) +/- presence of clinical signs-symptoms (including proximal myasthenia and/or myalgia) +/- a Manual Muscle Testing (MMT) score <5 in the thighs.

Results:

12 SSc patients and 10 HV were recruited. SSc patients had a median (IQR) age of 52 (41,65) years, 9/12 had limited cutaneous SSc, 4/12 interstitial lung disease, 7/12 non-inflammatory myopathy. Higher skeletal muscle ECV was recorded in SSc patients compared to HV [mean (SD) 23(11)%, vs 11(4)% p=0.04]. Skeletal muscle native T1 values were comparable between the 2 groups although modestly higher in SSc patients [mean (SD) 1396ms (56) vs 1387ms (42)] (Figure 1A).

Peripheral muscle ECV associated with CK (R2=0.307, rho=0.554, p=0.061) and was higher in SSc patients with evidence of myopathy compared to those with no myopathy [28 (10)% vs 15 (5)%, p=0.023] (Figure 1B). An ECV of 22% was determined to best identify myopathy with a sensitivity of 71% and a specificity of 80%.

SSc patients had raised myocardial ECV and native T1 with means (SD) of 31 (3) % and 1287 (54) ms respectively (normal reference range ECV ≤29%, native T1 ≤1240ms). No clear association between myocardial and peripheral muscle ECV (rho=-0.485) or between myocardial ECV and peripheral muscle native T1 (rho=0.470) of SSc patients was observed.

Conclusion:

This pilot study to determine ECV-MRI of the peripheral muscle showed higher ECV in SSc patients compared to HV, suggesting the presence of diffuse fibrosis in the peripheral muscle of SSc patients. These data support further investigation to understand the pathophysiological involvement and relationship of peripheral and cardiac muscle in SSc.

References:

[1]Follansbee WP et al, Am Heart J. 1993

[2]Barison A et al, Eur Heart J Cardiovasc Imaging. 2015

Disclosure of Interests:

Raluca-Bianca Dumitru: None declared, Alex Goodall: None declared, David Broadbent: None declared, Ananth Kidambi: None declared, Sven Plein: None declared, Francesco Del Galdo: None declared, Ai Lyn Tan: None declared, John Biglands: None declared, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi

THU0175 REAL-WORLD EXPERIENCE OF SWITCHING FROM ORIGINATOR TO BIOSIMILAR RITUXIMAB IN RHEUMATOID ARTHRITIS

Background:

Pre-clinical and trial data confirm biosimilar rituximab (RTX-B) has equivalent physicochemical properties, function, efficacy and safety as originator (RTX-O)1,2. However, real-world data are lacking, including non-medical switch to RTX-B in patients established on RTX-O. Loss of response (LOR) has been observed following open-label switch to other biosimilars3, and it is unclear how patients who develop LOR after switching should be managed.

Objectives:

To describe our real-world experience of non-medical switch from RTX-O to RTX-B in RA and explore treatment strategies for patients developing LOR to RTX-B (switch back to RTX-O versus other b/tsDMARDs).

Methods:

We conducted a retrospective observational study of RTX-treated RA patients in Leeds from May 2002–Jan 2020. From Oct 2017, all patients on RTX-O were switched to RTX-B unless specified by treating clinician or informed consent not obtained. Demographic and clinical data were collected from electronic health records. Effectiveness was assessed by DAS28-CRP and RTX retention (using Kaplan-Meier method). Changes in treatment were based on clinician judgment.

Results:

944 patients with RA received ≥1 cycle of RTX in Leeds over the past 17 years. Of these, 358 required RTX re-treatment during the study period (Oct 2017–Jan 2020); 263 (73.5%) switched to RTX-B, whilst 95 (26.5%) remained on RTX-O (medical reason=46.3%; patient decision=53.7%). 256/263 patients on RTX-B with 4-month data were analysed. 201/256 (78.5%) were female, mean (SD) age 63.1 (12.4), 97.7% seropositive, 81.6% on csDMARD (62.9% methotrexate), 14.8% oral steroid, 58.6% had previous bDMARDs, and mean (SD) RTX-O cycles pre-switch was 6 (3.6). Total follow-up was 378 patient-years. Mean (SD) DAS28-CRP was 3.01 (1.17) 4 months post-last cycle RTX-O and 3.32 (1.31) post-switch to RTX-B (mean diff +0.30, 95% CI 0.004-0.60; p=0.047), with increase in VAS (+5.7, 95% CI 0.09-11.37; p=0.047), but not SJC, TJC or CRP. At last follow-up, 185/256 (72.3%) patients remained on RTX-B [median (range) RTX-B cycles 2 (1-4)]. RTX-B retention rate estimates were 79.4% and 71.3% at 12 and 18 months respectively. Following RTX-B discontinuation, 33/256 patients (12.8%) switched back to RTX-O [LOR=30 (11.7%), adverse effects (AEs)=3 (1.2%)], 13/256 (5.1%) started other b/tsDMARDs, and 25/256 (9.7%) stopped treatment (no longer indicated=7, deaths=7, loss to follow-up=6, patient choice=3, new contraindication=2). Of 46 patients with LOR/AE to RTX-B, 39 discontinued after cycle 1 (C1), 5 after C2 and 2 after C3. 31/33 patients switched back to RTX-O remained on treatment but follow-up was limited [mean (SD) 7.5 (5.2) months; 23/33 had 1 cycle only]. Compared with patients treated with other b/tsDMARDs, those switched back to RTX-O had more previous RTX-O cycles [mean (SD) 6.67 (3.28) versus 2.62 (2.10); p<0.0001]. Compared with patients who remained on RTX-B (n=185), those who discontinued for LOR/AE/death (n=53) had more previous bDMARDs (mean 1.26 vs 0.83; difference 0.43, 95% CI 0.10-0.77, p=0.01), but no differences in other clinical characteristics, treatment or B-cell numbers.

Conclusion:

Our real-world single-centre experience of non-medical switch from RTX-O to RTX-B in RA showed approx. three quarters of patients remained on RTX-B and maintained stable disease activity. However, apparent LOR occurred in 16%. Of >10% switched back to RTX-O, the majority remained on treatment at short-term follow-up.

References:

[1]Lee at al, MAbs 2018.

[2]Shim et al, Rheumatology 2019.

[3]Tweehuysen et al, AR 2018.

Disclosure of Interests:

Andrew Melville: None declared, Md Yuzaiful Md Yusof: None declared, John Fitton Speakers bureau: Pfizer, Lynda Bailey Speakers bureau: Chugai, Sanofi, Paul Emery Grant/research support from: AbbVie, Bristol-Myers Squibb, Merck Sharp & Dohme, Pfizer, Roche (all paid to employer), Consultant of: AbbVie (consultant, clinical trials, advisor), Bristol-Myers Squibb (consultant, clinical trials, advisor), Lilly (clinical trials, advisor), Merck Sharp & Dohme (consultant, clinical trials, advisor), Novartis (consultant, clinical trials, advisor), Pfizer (consultant, clinical trials, advisor), Roche (consultant, clinical trials, advisor), Samsung (clinical trials, advisor), Sandoz (clinical trials, advisor), UCB (consultant, clinical trials, advisor), Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Shouvik Dass Consultant of: Roche, Speakers bureau: Roche, Benazir Saleem Speakers bureau: Sanofi

FRI0131 SUSTAINABILITY OF RESPONSE BETWEEN UPADACITINIB AND ADALIMUMAB AMONG PATIENTS WITH RHEUMATOID ARTHRITIS AND PRIOR INADEQUATE RESPONSE TO METHOTREXATE

Background:

The primary treatment goal for patients (pts) with rheumatoid arthritis (RA) is a state of sustained clinical remission (REM) or low disease activity (LDA).1,2

Objectives:

To assess the long-term sustainability of response to upadacitinib (UPA), a JAK inhibitor, and adalimumab (ADA), both with background methotrexate (MTX), among pts with RA and prior inadequate response to MTX.

Methods:

In the phase 3, randomized, placebo (PBO) and active-controlled SELECT-COMPARE trial, pts on stable background MTX received UPA 15 mg once daily, PBO, or ADA 40 mg every other week. Pts not achieving 20% improvements in tender/swollen joint counts (Weeks 14-22) or LDA (CDAI ≤10 at Week 26) were rescued from UPA to ADA or PBO/ADA to UPA; all non-rescued PBO pts were switched to UPA at Week 26. This post hoc analysis evaluated clinical REM (CDAI ≤2.8; SDAI ≤3.3), LDA (CDAI≤10; SDAI≤11), and DAS28(CRP) <2.6/≤3.2 at first occurrence before Week 72 or prior to treatment switch; additionally, these measures were evaluated at 3, 6, and 12 months after the first occurrence for the total number of pts randomized to UPA (n=651) or ADA (n=327). Sustainability of response was evaluated by Kaplan-Meier only for those pts who achieved REM/LDA and was defined as time to the earliest date of losing response at two consecutive visits, discontinuation of study drug, or losing response at the time of rescue. The predictive ability of time to clinical REM/LDA was assessed using Harrell’s concordance (c)-index (for reference, an index ~ 0.5, indicates no ability to predict; an index of 1 or -1 would be a perfect prediction). The date of the last follow up was 6 July, 2018, when all pts had reached the Week 72 visit.

Results:

Through Week 72, a significantly higher proportion of pts receiving UPA + MTX vs ADA + MTX achieved CDAI REM (41% vs 31%, p=.0035) as well as CDAI LDA (70% vs 59%, p=.0007). 26%/22% of pts randomized to UPA + MTX and 16%/14% of pts randomized to ADA + MTX achieved sustained CDAI REM at 6/12 months after the first occurrence. Additionally, 49%/46% of pts randomized to UPA + MTX and 36%/34% of pts randomized to ADA + MTX achieved sustained CDAI LDA at 6/12 months after the first occurrence (Figure 1). Time to initial clinical REM/LDA did not appear to be associated with sustained disease control. The c-indices (95% CI) for CDAI REM in the UPA +MTX and ADA + MTX groups were 0.528 (0.48, 0.58) and 0.510 (0.43, 0.59) and that of LDA were 0.601 (0.56, 0.64) and 0.555 (0.50, 0.61), respectively. Through last follow-up visit, 51% of UPA + MTX pts and 45% of ADA + MTX pts remained in CDAI REM while 65% of UPA + MTX pts and 58% of ADA + MTX pts remained in CDAI LDA, respectively (Figure 2). Similar results were observed across other disease activity measures (SDAI REM/LDA and DAS28(CRP) <2.6/≤3.2).

Conclusion:

A significantly greater proportion of pts with RA and prior inadequate response to MTX receiving UPA + MTX vs ADA + MTX achieved clinical REM or LDA across disease activity measures. REM and LDA were sustained through Week 72 in both treatment arms, with numerically higher proportions retaining response among UPA-treated pts.

References:

[1]EULAR: Smolen JS, et al. Ann Rheum Dis 2017;76:960–977.

[2]ACR: Singh et al. Arthritis & Rheumatology Vol. 68, No. 1, January 2016, pp 1–26.

Disclosure of Interests:

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, Arthur Kavanaugh Grant/research support from: Abbott, Amgen, AstraZeneca, BMS, Celgene Corporation, Centocor-Janssen, Pfizer, Roche, UCB – grant/research support, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, 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, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, In-Ho Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Yanna Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Jessica Suboticki Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Roy Fleischmann Grant/research support from: AbbVie, Akros, Amgen, AstraZeneca, Bristol-Myers Squibb, Boehringer, IngelhCentrexion, Eli Lilly, EMD Serono, Genentech, Gilead, Janssen, Merck, Nektar, Novartis, Pfizer, Regeneron Pharmaceuticals, Inc., Roche, Samsung, Sandoz, Sanofi Genzyme, Selecta, Taiho, UCB, Consultant of: AbbVie, ACEA, Amgen, Bristol-Myers Squibb, Eli Lilly, Gilead, GlaxoSmithKline, Novartis, Pfizer, Sanofi Genzyme, UCB

SAT0145 EFFICACY AND SAFETY OF UPADACITINIB MONOTHERAPY IN MTX-NAÏVE PATIENTS WITH EARLY ACTIVE RA RECEIVING TREATMENT WITHIN 3 MONTHS OF DIAGNOSIS: A POST-HOC ANALYSIS OF THE SELECT-EARLY

Background:

Early treatment of RA within the therapeutic window(0-3 months from symptom onset), has been associated with improved clinical outcomes and physical function. However, ≤42% of RA patients(pts) visit a rheumatologist within 90 days of symptom onset1,2.

Objectives:

To assess safety and efficacy of Upadacitinib(UPA), an oral, reversible, potent JAK-1 selective inhibitor3, in pts with moderate to severely active RA who were MTX-naïve or had an inadequate response to csDMARDs/bDMARDs4-6.

Methods:

In SELECT–EARLY, MTX-naïve pts with active RA and poor prognosis were randomized 1:1:1 to once-daily UPA monotherapy at 15 or 30 mg or weekly MTX (titrated up to 20 mg/week through Week 8). Efficacy (including ACR, DAS28(CRP), CDAI responses and change in mTSS) and safety outcomes from a post-hoc analysis of patients who received treatment within 90 days from diagnosis are reported here. The statistical significance defined asp<0.05was exploratory in nature.

Results:

A total of 270 pts commenced treatment within 90 days from RA diagnosis (median: 44 days [11, 89]). Pts in each arm were mostly female (70%), had moderately to severely active RA with mean DAS28(CRP) =5.9±1.02, had structural joint damage (mean mTSS =7.7±21.5) and were seropositive for both ACPA and RF at baseline (72%)4. At Week 24, compared to MTX, significantly greater proportions of pts receiving UPA 15 or 30 mg monotherapy achieved efficacy outcomes including ACR20, 50 and 70 responses, DAS28CRP<2.6, CDAI≤2.8 or Boolean remission. Improvements in physical function (HAQ-DI) and decrease in pain were also significantly greater in pts receiving UPA 15 and 30 mg vs MTX at Week 24. Treatment with UPA was also associated with a greater inhibition of structural joint damage compared with MTX (Figure 1). Safety outcomes were consistent with the full study and the integrated safety analysis (all phase 3 studies of UPA). Compared to MTX, higher frequencies of serious infections and herpes zoster were reported in both UPA groups. There were 2 deaths in total (UPA 30 mg: 1 due to cardiovascular death and 1 due to pneumonia and sepsis) (Figure 2).

Conclusion:

In RA pts, early initiation of treatment with UPA 15 mg and 30 mg monotherapy within 3 months from diagnosis was associated with clinically meaningful improvements in efficacy, including remission and inhibition of progression of structural joint damage compared to MTX. The safety profile was consistent with the overall study and the integrated phase 3 safety analysis7. UPA seems to be a promising treatment option for more patients to reach their treatment targets of remission or low disease activity when treated within 3 months of diagnosis.

References:

[1]Raza K et al. Ann Rheum Dis. 2011;70(10):1822-5.

[2]Stack RJ et al. BMJ Open. 2019;9:e024361.

[3]Parmentier et al. BMC Rheumatol. 2018;2:23.

[4]van Vollenhoven R et al, Arth Rheumatol. 2018; 70 (s10) [Abs ACR2018].

[5]Burmester GR et al. Lancet 2018;391:2503-12.

[6]Genovese MC et al, Lancet 2018;391:2513-24.

[7]Cohen S et al, Ann Rheum Dis [Abs EULAR2019].

Disclosure of Interests:

Meliha C Kapetanovic: None declared, Maria Andersson Shareholder of: AbbVie, Employee of: AbbVie, Alan Friedman Shareholder of: AbbVie Inc, Employee of: AbbVie Inc, Tim Shaw Shareholder of: AbbVie, Employee of: AbbVie, Yanna Song Shareholder of: AbbVie Inc., Employee of: AbbVie Inc., Daniel Aletaha Grant/research support from: AbbVie, Novartis, Roche, Consultant of: AbbVie, Amgen, Celgene, Lilly, Medac, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi Genzyme, Speakers bureau: AbbVie, Celgene, Lilly, Merck, Novartis, Pfizer, Sanofi Genzyme, UCB, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Ulf Müller-Ladner Speakers bureau: Biogen, Janet Pope Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead Sciences, Inc., Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Speakers bureau: UCB

THU0342 DECLINE IN SUBCLINICAL SYSTEMIC SCLEROSIS PRIMARY HEART INVOLVEMENT ASSOCIATES WITH POOR PROGNOSTIC FACTORS AND ACTIVE INTERSTITIAL LUNG DISEASE

Background:

Primary systemic sclerosis heart involvement (pSSc-HI) is described in the majority of SSc patients when sensitive methods such as cardiovascular magnetic resonance (CMR) are used1. The natural history of these subclinical findings are unknown.

Objectives:

To evaluate for interval change in subclinical pSSc-HI, the association between change in CMR abnormalities and disease phenotype and whether disease modifying antirheumatic (DMARD) and/or vasodilator treatment influence the CMR course.

Methods:

SSc patients, fulfilling the 2013 ACR/EULAR criteria, with no cardiovascular (CV) disease, diabetes and no more than 2 CV risk factors had two CMRs performed (V1 & V2; minimum 1 year apart). A 3T CMR with late gadolinium enhancement (LGE), T1 mapping for extracellular volume (ECV of diffuse fibrosis) quantification and stress perfusion was undertaken.

Results:

31 SSc patients were evaluated, with median (IQR) follow up (between the 2 CMR scans) of 33 (17, 37) months. Median (IQR) age was 52 (47,60), 32% had diffuse cutaneous SSc, 52% interstitial lung disease (ILD), 29% Scl70+.

4/31 patients had a non-ischaemic LGE pattern suggesting focal fibrosis at V1, with no change in the pattern, distribution, or median (IQR) LGE scar mass between V1 and V2 [1.88 (1.01, 6.34) vs 1.70 (1.21, 4.18)]. At V2, 2 additional patients showed focal fibrosis, of which one had an episode of clinically diagnosed myocarditis. No significant change in ECV, T1 native, myocardial perfusion reserve (MPR) or left ventricle (LV) volumes and function were noted at V2 compared with V1 (p>0.01).

SSc patients with either increase in pre-existing LGE scar mass (n=1) or new fibrosis were all dcSSc, with ILD, 2 Scl70+. A reduction in forced vital capacity and total lung capacity associated with a reduction in LV ejection fraction (LVEF) (rho=0.413, p=0.021; rho-0.335, p=0.07) and MPR (rho=0.543, p=0.007; rho=0.627, p=0.002).

Patients receiving DMARD treatment had higher baseline LV end-diastolic volume compared to those with no DMARD treatment [mean (SD) 78 (19) vs 69 (10), p=0.167]. A decrease in LV stroke volume and an increase in T1 native at V1 vs V2 was noted for those on DMARD [mean (SD) 49 (8) vs 46 (8), p =0.023; 1208 (65) vs 1265 (56), p=0.008 respectively] (Figure 1). No significant change in CMR measures in those receiving vasodilator or angiotensin-converting-enzyme inhibitor treatment was noted (p>0.01).

Figure 1.

Mean (SD) of T1 native, LVSV/BSA, LVEF, and LVEDV/BSA at V1 compared to V2 in those with and without DMARD treatment. BSA, body surface area; DMARD, disease modifying antirheumatic drugs; EDV, end-diastolic volume; SV, stroke volume; LV left ventricular; EF, ejection fraction.

Conclusion:

This first, pilot longitudinal study of CMR-defined subclinical pSSc-HI suggests largely stable appearances with follow-up. Progression of new focal fibrosis and decline in LV function and MPR, where observed, associated with poor prognostic factors of SSc and ILD progression. Consistent with this, individuals on DMARD appeared to show interval decline. Larger longitudinal studies are warranted to confirm these findings and inform on utility of CMR monitoring of subclinical pSSc-HI in poor prognosis SSc.

References:

[1]Ntusi NA et al, J Cardiovasc Magn Reson. 2014

Disclosure of Interests:

Raluca-Bianca Dumitru: None declared, Lesley Anne Bissell: None declared, Bara Erhayiem: None declared, Graham Fent: None declared, Ananth Kidambi: None declared, Giuseppina Abignano: None declared, John Greenwood: None declared, John Biglands: None declared, Francesco Del Galdo: None declared, Sven Plein: None declared, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi

AB0556 PRIMARY SYSTEMIC SCLEROSIS HEART INVOLVEMENT (PSSCHI): A SYSTEMATIC LITERATURE REVIEW (SLR), CONSENSUS-BASED DEFINITION AND PRELIMINARY VALIDATION

Background:

pSScHI may cause tissue, functional and conduction abnormalities with varied clinical manifestations. The absence of a clear definition of pSScHI impairs the significance and ability of focussed research, frequently not allowing the distinction between primary and secondary involvement.

Objectives:

We aimed to establish an expert consensus definition for pSScHI, to be used in clinical trials and everyday clinical practice, and to start its validation process.

Methods:

A SLR for cardiac manifestations and alterations in SSc was conducted using PubMed, Web of Science and Embase. Articles published from inception to December 31st, 2018 were identified. Inclusion criteria included papers in English on adult SSc patients, with heart involvement as outcome. We excluded non-human studies, secondary heart involvement (eg PAH, drugs, infections), reviews and case reports. PRISMA recommendations were followed where applicable. Extracted data were categorized into relevant domains (signs, symptoms, anatomical site involved, physiological abnormalities, pathological changes, prognostic outcomes), which informed the consensus definition. Sixteen senior experts (7 rheumatologists, 8 cardiologists, 1 pathologist) discussed the data and, using a nominal group technique, added expert opinion, provided statements to consider and ranked them. Consensus was attained for agreement >70%. Sixteen clinical cases were evaluated in two rounds to test for face validity, feasibility, inter- and intra-rater reliability and criterion validity (gold standard set by agreed evaluation between expert rheumatologist, cardiologist and methodologist).

Results:

2593 publications were identified and screened, 251 full texts were evaluated,172 met eligibility criteria. Data from the 7 domains were extracted and used to develop the World Scleroderma Foundation – Heart Failure Association (WSF-HFA) consensus-derived definition of pSSc-HI, as follows:

“pSScHI comprises cardiac abnormalities that are predominantly attributable to SSc rather than other causes and/or complications*. pSScHI may be sub-clinical and must be confirmed through diagnostic investigation. The pathogenesis of pSScHI comprises one or more of inflammation, fibrosis and vasculopathy. *Non SSc-specific cardiac conditions (e.g. Ischaemic heart disease, arterial hypertension, drug toxicity, other cardiomyopathy, primary valvular disease) and/or SSc non cardiac conditions (e.g. PAH, Renal involvement, ILD).”

Face validity was determined by a 100% agreement on credibility; application was feasible, with a median 60 (5-600) seconds taken per case; inter rater agreement was moderate [mKappa (95%CI) 0.56 (0.46-1.00) and 0.55 (0.44-1.00) for the two rounds] and intra rater agreement was good [mKappa (95%CI) 0.77 (0.47-1,00)]. Content validity was reached based on the wide variety of patients in the SLR, criterion validity was reached with 78 (73-84) % correctness.

Conclusion:

Using a SLR and modified nominal technique, we have developed a preliminary pSScHI consensus-based definition and started a validation process for it to be used in clinical research and clinical practice.

Acknowledgments:

Aleksandra Djokovic, Giacomo De Luca, Raluca B. Dumitru,

Alessandro Giollo, Marija Polovina, Yossra Atef Suliman, Kostantinos Bratis, Alexia Steelandt, Ivan Milinkovic, Anna Baritussio, Ghadeer Hasan, Anastasia Xintarakou, Yohei Isomura, George Markousis-Mavrogenis, Silvia Bellando-Randone, Lorenzo Tofani, Sophie Mavrogeni, Luna Gargani, Alida L.P. Caforio, Carsten Tschoepe, Arsen Ristic, Karin Klingel, Sven Plein, Elijah Behr, Yannick Allanore, Masataka Kuwana, Christopher Denton, Daniel E. Furst, Dinesh Khanna, Thomas Krieg, Renzo Marcolongo.

Disclosure of Interests:

Cosimo Bruni Speakers bureau: Actelion, Eli Lilly, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Petar Seferovic: None declared, Marco Matucci-Cerinic Grant/research support from: Actelion, MSD, Bristol-Myers Squibb, Speakers bureau: Acetelion, Lilly, Boehringer Ingelheim

OP0332 MUSCLE DETERIORATION DUE TO RHEUMATOID ARTHRITIS: ASSESSMENT BY QUANTITATIVE MRI AND STRENGTH TESTING

Background:

As well as joint damage, rheumatoid arthritis (RA) is also associated with altered body composition known as rheumatoid cachexia (RC). RC is characterised by reduced skeletal muscle and increased (white) fat mass and decreased strength. RC is associated with increased disease severity and disability (1). It is unknown at what stage muscle involvement begins in RA, and if the muscle damage is modifiable when patients achieve disease control.

Quantitative MRI (qMRI) can measure the biomarkers associated with RC. MRI T2 is sensitive to fluid related to physiological changes at the molecular level, and is regarded as an indirect measure of muscle inflammation (2). MRI muscle fat fraction (FF) measurements are useful for identifying myosteatosis (3).

Objectives:

To obtain preliminary estimates of the extent to which muscle imaging phenotype differs between RA and healthy controls (HC); and to describe the RA phenotype at different levels of disease activity.

Methods:

39 RA patients (comprising three groups) and 13 age and gender directly matched HC had a MRI scan of their dominant thigh. The RA groups were:

[1]13 ‘New RA’ - newly diagnosed, treatment naïve

[2]13 ‘Active RA’ - diagnosed >1 year, persistent DAS28 >3.2 for >1 year

[3]13 ‘Remission RA’ - diagnosed >1 year, persistent DAS28 <2.6 for >1 year

MR images of the mid-thigh were acquired using Dixon imaging to assess FF and a fat-suppressed multi-echo spin-echo to measure T2. Regions of interest were drawn around the quadriceps and hamstrings. All participants had knee extension and flexion torque measured on an isokinetic dynamometer, and isometric dynamometer to measure grip strength. One-Way ANOVA with Dunnett’s post-hoc analysis provided preliminary indication of potential differences between T2, FF, muscle volume and strength measurements between the disease stages.

Results:

39 RA patients were recruited: 13 new RA (mean age [years] 63 ± 15, DAS28 5.2 ± 3), 13 active RA (mean age [years] 65 ± 10, DAS28 4.8 ± 3), 13 remission RA (mean age [years] 67 ± 19, DAS28 1.7 ± 0.7) and also 13 HC. T2 and FF were higher in RA patients compared to HC (fig. 1). Within the hamstrings for T2, the mean differences between HC versus new, active and remission patients were 4.5ms (95% CI 2.5, 6.4; p<0.001), 3ms (95% CI 1.1, 4.9; p=0.001), and 5.0ms (95% CI 3.0, 6.4; p<0.001) respectively. Quadriceps results were similar. For muscle volume, the mean differences between HC versus new, active and remission patients were -517.3cm3(95% CI -751, -283; p<0.001), -370.5cm3(95% CI -605, -136; p=0.001), and -312.3cm3(95% CI -546. -77; p=0.006) respectively (fig. 2). Knee flexion/extension and handgrip strength were lower in all 3 groups of RA patients compared to HC. For knee flexion, the mean differences between HC versus new, active and remission patients were 18.4Nm (95% CI -35, -1; p=0.03), 10.1Nm (95% CI -27, 7; p=0.3), and 13.3Nm (95% CI -33, 0; p=0.1) respectively.

Figure 1.

Quantitative T2 and FF MRI of RA patients and healthy controls

Conclusion:

This pilot study suggests muscle health may be adversely affected in RA patients compared to matched HC. Our results suggest that muscle changes occur in the earliest stages of RA and persist throughout the disease duration, even in clinical remission. If confirmed, these data imply the need for adjunctive muscle intervention to current RA treatment strategies in order to improve patient outcomes.

References:

[1]Giles JT, et al. Arthritis Care & Research. 2008

[2]Maillard SM, et al. Rheumatology (Oxford, England). 2004

[3]Grimm A, et al. The Journal of Frailty & Aging. 2018.

Figure 2.

MRI muscle volume in RA patients and healthy controls

Disclosure of Interests:

Matt Farrow: None declared, John Biglands: None declared, Steven Tanner: None declared, Elizabeth Hensor: None declared, Maya H Buch Grant/research support from: Pfizer, Roche, and UCB, Consultant of: Pfizer; AbbVie; Eli Lilly; Gilead Sciences, Inc.; Merck-Serono; Sandoz; and Sanofi, Paul Emery Grant/research support from: AbbVie, Bristol-Myers Squibb, Merck Sharp & Dohme, Pfizer, Roche (all paid to employer), Consultant of: AbbVie (consultant, clinical trials, advisor), Bristol-Myers Squibb (consultant, clinical trials, advisor), Lilly (clinical trials, advisor), Merck Sharp & Dohme (consultant, clinical trials, advisor), Novartis (consultant, clinical trials, advisor), Pfizer (consultant, clinical trials, advisor), Roche (consultant, clinical trials, advisor), Samsung (clinical trials, advisor), Sandoz (clinical trials, advisor), UCB (consultant, clinical trials, advisor), Ai Lyn Tan: None declared

Cardiovascular MRI evidence of reduced systolic function and reduced LV mass in rheumatoid arthritis: impact of disease phenotype

The accelerated risk of cardiovascular disease (CVD) in Rheumatoid Arthritis (RA) requires further study of the underlying pathophysiology and determination of the at-risk RA phenotype. Our objectives were to describe the cardiac structure and function and arterial stiffness, and association with disease phenotype in patients with established) RA, in comparison to healthy controls, as measured by cardiovascular magnetic resonance imaging (CMR). 76 patients with established RA and no history of CVD/diabetes mellitus were assessed for RA and cardiovascular profile and underwent a non-contrast 3T-CMR, and compared to 26 healthy controls. A univariable analysis and multivariable linear regression model determined associations between baseline variables and CMR-measures. Ten-year cardiovascular risk scores were increased in RA compared with controls. Adjusting for age, sex and traditional cardiovascular risk factors, patients with RA had reduced left ventricular ejection fraction (mean difference - 2.86% (- 5.17, - 0.55) p = 0.016), reduced absolute values of mid systolic strain rate (p < 0.001) and lower late/active diastolic strain rate (p < 0.001) compared to controls. There was evidence of reduced LV mass index (LVMI) (- 4.56 g/m2 (- 8.92, - 0.20), p = 0.041). CMR-measures predominantly associated with traditional cardiovascular risk factors; male sex and systolic blood pressure independently with increasing LVMI. Patients with established RA and no history of CVD have evidence of reduced LV systolic function and LVMI after adjustment for traditional cardiovascular risk factors; the latter suggesting cardiac pathology other than atherosclerosis in RA. Traditional cardiovascular risk factors, rather than RA disease phenotype, appear to be key determinants of subclinical CVD in RA potentially warranting more effective cardiovascular risk reduction programs.

Profiling microRNAs in individuals at risk of progression to rheumatoid arthritis

Background

Individuals at risk of rheumatoid arthritis (RA) demonstrate systemic autoimmunity in the form of anti-citrullinated peptide antibodies (ACPA). MicroRNAs (miRNAs) are implicated in established RA. This study aimed to (1) compare miRNA expression between healthy individuals and those at risk of and those that develop RA, (2) evaluate the change in expression of miRNA from “at-risk” to early RA and (3) explore whether these miRNAs could inform a signature predictive of progression from “at-risk” to RA.

Methods

We performed global profiling of 754 miRNAs per patient on a matched serum sample cohort of 12 anti-cyclic citrullinated peptide (CCP) + “at-risk” individuals that progressed to RA. Each individual had a serum sample from baseline and at time of detection of synovitis, forming the matched element. Healthy controls were also studied. miRNAs with a fold difference/fold change of four in expression level met our primary criterion for selection as candidate miRNAs. Validation of the miRNAs of interest was conducted using custom miRNA array cards on matched samples (baseline and follow up) in 24 CCP+ individuals; 12 RA progressors and 12 RA non-progressors.

Results

We report on the first study to use matched serum samples and a comprehensive miRNA array approach to identify in particular, three miRNAs (miR-22, miR-486-3p, and miR-382) associated with progression from systemic autoimmunity to RA inflammation. MiR-22 demonstrated significant fold difference between progressors and non-progressors indicating a potential biomarker role for at-risk individuals.

Conclusions

This first study using a cohort with matched serum samples provides important mechanistic insights in the transition from systemic autoimmunity to inflammatory disease for future investigation, and with further evaluation, might also serve as a predictive biomarker.

Electronic supplementary material

The online version of this article (doi:10.1186/s13075-017-1492-9) contains supplementary material, which is available to authorized users.

What is the utility of routine ANA testing in predicting development of biological DMARD-induced lupus and vasculitis in patients with rheumatoid arthritis? Data from a single-centre cohort

OBJECTIVE

To determine whether serial ANA testing predicts biological disease modifying antirheumatic drugs (bDMARD)-associated ANA/dsDNA production in patients with rheumatoid arthritis (RA).

METHODS

Serial autoantibody profiles, bDMARD treatment sequences and clinical data were collected from patients identified from our database that since 2005 received (i) a first bDMARD (tumour necrosis factor inhibitor (TNFi)) and (ii) tocilizumab and/or abatacept.

RESULTS

Of over 1000 patients, 454 RA patients received a first TNFi. Infliximab group demonstrated higher ANA seroconversion rates (31.2%) compared with etanercept (11.8%) and adalimumab (16.1%) (p<0.001). Median (range) treatment duration prior to ANA seroconversion was 10.9 (1.3-80.0) months. Positive anti-dsDNA titres of IgG class (median (range) of 77 IU/mL (65-109)) were noted in six (7.2%) patients, within a median (range) of 2.0 (0.8-4.2) years. Three patients developed classifiable lupus. 4 of 74 (5.4%) primary non-responders and 24 of 111 (21.6%) secondary non-responders developed positive ANA antibodies after TNFi initiation (p=0.003). Seven (9.5%) tocilizumab-treated patients changed to positive ANA; five (8.6%) abatacept-treated patients changed to positive ANA status.

CONCLUSIONS

This study demonstrates no utility of serial ANA/dsDNA testing that could be used to predict onset of seroconversion and therefore the development of lupus/vasculitis. An association however between seroconversion and the development of a secondary non-response to bDMARD therapy is suggested.

A randomised controlled trial of etanercept and methotrexate to induce remission in early inflammatory arthritis: the EMPIRE trial

OBJECTIVE

To compare the efficacy of etanercept (ETN) and methotrexate (MTX) versus MTX monotherapy for remission induction in patients with early inflammatory arthritis.

METHODS

In a 78-week multicentre randomised placebo-controlled superiority trial, 110 DMARD-naïve patients with early clinical synovitis (≥1 tender and swollen joint, and within 3 months of diagnosis) and either rheumatoid factor, anticitrullinated protein antibodies or shared epitope positive were randomised 1:1 to receive MTX+ETN or MTX+placebo (PBO) for 52 weeks. Injections (ETN or PBO) were stopped in all patients at week 52. In those with no tender or swollen joints (NTSJ) for >26 weeks, injections were stopped early. If patients had NTSJ >12 weeks after stopping the injections, MTX was weaned. The primary endpoint was NTSJ at week 52.

RESULTS

No statistically significant difference was seen for the primary endpoint (NTSJ at week 52 (32.5% vs 28.1% [adjusted OR 1.32 (0.56 to 3.09), p=0.522]) in the MTX+ETN and MTX+PBO groups, respectively). The secondary endpoints did not differ between groups at week 52 or 78. Exploratory analyses showed a higher proportions of patients with DAS28-CRP<2.6 in the MTX+ETN group at week 2 (38.5% vs 9.2%, adjusted OR 8.87 (2.53 to 31.17), p=0.001) and week 12 (65.1% vs 43.8%, adjusted OR 2.49 (1.12 to 5.54), p=0.026).

CONCLUSIONS

In this group of patients with early inflammatory arthritis, almost a third had no tender, swollen joints after 1 year. MTX+ETN was not superior to MTX monotherapy in achieving this outcome. Clinical responses, however, including DAS28-CRP<2.6, were achieved earlier with MTX+ETN combination therapy.

TRIAL REGISTRATION NUMBER

The EMPIRE trial is registered on the following trial registries: Eudract-2005-005467-29; ISRCTN 55428162 (http://www.controlled-trials.com/ISRCTN55428162/EMPIRE). The full trial protocol can be obtained from the corresponding author.

Remission induction comparing infliximab and high-dose intravenous steroid, followed by treat-to-target: a double-blind, randomised, controlled trial in new-onset, treatment-naive, rheumatoid arthritis (the IDEA study)

OBJECTIVES

In disease modifying antirheumatic drug (DMARD)-naive early rheumatoid arthritis (RA), to compare the efficacy of methotrexate (MTX) and infliximab (IFX) with MTX and intravenous corticosteroid for remission induction.

METHODS

In a 78-week multicentre randomised controlled trial, double-blinded to week 26, 112 treatment-naive RA patients (1987 American College of Rheumatology classification criteria) with disease activity score 44 (DAS44)>2.4 were randomised to MTX + IFX or MTX + single dose intravenous methylprednisolone 250 mg. A treat-to-target approach was used with treatment escalation if DAS44>2.4. In the IFX group, IFX was discontinued for sustained remission (DAS44<1.6 for 6 months). The primary outcome was change in modified total Sharp-van der Heijde score (mTSS) at week 50.

RESULTS

The mean changes in mTSS score at week 50 in the IFX and intravenous steroid groups were 1.20 units and 2.81 units, respectively (adjusted difference (95% CI) -1.45 (-3.35 to 0.45); p=0.132). Radiographic non-progression (mTSS<2.0) occurred in 81% vs 71% (OR 1.77 (0.56 to 5.61); p=0.328). DAS44 remission was achieved at week 50 in 49% and 36% (OR 2.13 (0.91 to 5.00); p=0.082), and at week 78 in 48% and 50% (OR 1.12 (0.47 to 2.68); p=0.792). Exploratory analyses suggested higher DAS28 remission at week 6 and less ultrasound synovitis at week 50 in the IFX group. Of the IFX group, 25% (14/55) achieved sustained remission and stopped IFX. No substantive differences in adverse events were seen.

CONCLUSIONS

In DMARD-naive early RA patients, initial therapy with MTX+high-dose intravenous steroid resulted in good disease control with little structural damage. MTX+IFX was not statistically superior to MTX+intravenous steroid when combined with a treat-to-target approach.

Differential effects of infliximab on absolute circulating blood leucocyte counts of innate immune cells in early and late rheumatoid arthritis patients

Anti-tumour necrosis factor (TNF) biologics have revolutionized therapy of rheumatoid arthritis (RA). We compared the effects of infliximab on numbers of circulating leucocyte subsets in early RA (disease/symptom duration of ≤1 year) and late RA patients (>1 year). A control group consisted of early RA patients treated with a combination of methotrexate (MTX) and methylprednisolone. Blood samples were obtained at baseline (pre-therapy) from all RA patients, divided into three groups: (i) late RA receiving infliximab/MTX, (ii) early RA-infliximab/MTX, (iii) early RA-steroid/MTX, and also from follow-up patients at 2 and 14 weeks. Significant differences in absolute counts of monocytes and granulocytes were observed between healthy controls and RA patients. At baseline CD14(bright) monocytes and CD16(+) granulocytes were increased in both early RA and late RA patients. CD4(+) T cells, CD8(+) T cells and B cells were all increased at baseline in early RA, but not in late RA. At 2 weeks following infliximab treatment decreased granulocytes were observed in both early and late RA and decreased natural killer (NK) cells in late RA. CD16(+) granulocytes and NK cells were also decreased at 14 weeks post-infliximab in early RA. Biotinylated infliximab was used to detect membrane-associated TNF (mTNF)-expressing leucocytes in RA patients. CD16(+) granulocytes, NK cells and CD14(dim) monocytes all expressed higher levels of mTNF in RA patients. In summary infliximab is associated with decreased CD16(+) granulocyte and NK cell counts, possibly through binding of mTNF. Differential effects of infliximab between early and late RA suggest that pathogenic mechanisms change as disease progresses.