Tocilizumab Dose Tapering Based on a Model-Based Algorithm is Feasible in Clinical Practice: A Short Communication

BACKGROUND

Tocilizumab in the treatment of rheumatoid arthritis (RA) is a potential candidate for concentration-guided tapering because the standard dose of tocilizumab results in a wide range of serum concentrations, usually above the presumed therapeutic window, and an exposure-response relationship has been described. However, no clinical trials have been published to date on this subject. Therefore, the objective of this study was to assess the feasibility of the tapering of intravenous (iv) tocilizumab with the use of a pharmacokinetic model-based algorithm in RA patients.

METHODS

A randomized controlled trial with a double-blind design and follow-up of 24 weeks was conducted. RA patients who received the standard of tocilizumab for at least the past 24 weeks, which is 8 mg/kg every 4 weeks, were included. Patients with a tocilizumab serum concentration above 5 mg/L at trough were randomized between concentration-guided dose tapering, referred to as therapeutic drug monitoring (TDM), or the standard 8 mg/kg dose. In the TDM group, the tocilizumab dose was tapered with a recently published model-based algorithm to achieve a target concentration of 4-6 mg/L after 20 weeks of dose tapering.

RESULTS

Twelve RA patients were included and 10 were randomized between the TDM and standard dose group. The study was feasible regarding the predefined feasibility criteria and patients had a positive attitude toward therapeutic drug monitoring. In the TDM group, the tocilizumab trough concentration within patients decreased on average by 24.5 ± 18.3 mg/L compared with a decrease of 2.8 ± 12 mg/L in the standard dose group. None of the patients in the TDM group reached the drug range of 4-6 mg/L. Instead, tocilizumab concentrations of 1.6 and 1.5 mg/L were found for the 2 patients who completed follow-up on the tapered dose. No differences in RA disease activity were observed between the 2 study groups.

CONCLUSIONS

This study was the first to show that it is feasible to apply a dose-reduction algorithm based on a pharmacokinetic model in clinical practice. However, the current algorithm needs to be optimized before it can be applied on a larger scale.

Novel DNA methylome biomarkers associated with adalimumab response in rheumatoid arthritis patients

Background and aims

Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade, such as tumor necrosis factor-alpha (TNFα). Currently, there are no biomarkers to predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood (PBL).

Methods

DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of ADA treatment was determined using Illumina HumanMethylationEPIC BeadChip array. After 6 months, treatment response was assessed according to the European Alliance of Associations for Rheumatology (EULAR) criteria for disease activity. Patients were classified as responders (Disease Activity Score in 28 Joints (DAS28) < 3.2 or decrease of 1.2 points) or as non-responders (DAS28 > 5.1 or decrease of less than 0.6 points). Machine learning models were built through stability-selected gradient boosting to predict response prior to ADA treatment with predictor DNA methylation markers.

Results

Of the 94 RA patients, we classified 49 and 43 patients as responders and non-responders, respectively. We were capable of differentiating responders from non-responders with a high performance (area under the curve (AUC) 0.76) using a panel of 27 CpGs. These classifier CpGs are annotated to genes involved in immunological and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology, and angiogenesis.

Conclusion

Our findings indicate that the DNA methylome of PBL provides discriminative capabilities in discerning responders and non-responders to ADA treatment and may therefore serve as a tool for therapy prediction.

Cardiovascular magnetic resonance in autoimmune rheumatic diseases: a clinical consensus document by the European Association of Cardiovascular Imaging

Autoimmune rheumatic diseases (ARDs) involve multiple organs including the heart and vasculature. Despite novel treatments, patients with ARDs still experience a reduced life expectancy, partly caused by the higher prevalence of cardiovascular disease (CVD). This includes CV inflammation, rhythm disturbances, perfusion abnormalities (ischaemia/infarction), dysregulation of vasoreactivity, myocardial fibrosis, coagulation abnormalities, pulmonary hypertension, valvular disease, and side-effects of immunomodulatory therapy. Currently, the evaluation of CV involvement in patients with ARDs is based on the assessment of cardiac symptoms, coupled with electrocardiography, blood testing, and echocardiography. However, CVD may not become overt until late in the course of the disease, thus potentially limiting the therapeutic window for intervention. More recently, cardiovascular magnetic resonance (CMR) has allowed for the early identification of pathophysiologic structural/functional alterations that take place before the onset of clinically overt CVD. CMR allows for detailed evaluation of biventricular function together with tissue characterization of vessels/myocardium in the same examination, yielding a reliable assessment of disease activity that might not be mirrored by blood biomarkers and other imaging modalities. Therefore, CMR provides diagnostic information that enables timely clinical decision-making and facilitates the tailoring of treatment to individual patients. Here we review the role of CMR in the early and accurate diagnosis of CVD in patients with ARDs compared with other non-invasive imaging modalities. Furthermore, we present a consensus-based decision algorithm for when a CMR study could be considered in patients with ARDs, together with a standardized study protocol. Lastly, we discuss the clinical implications of findings from a CMR examination.

POS1563-PARE SELF-MANAGEMENT STRATEGIES FOR ADVERSE DRUG REACTIONS AS REPORTED BY TNF-ALPHA INHIBITOR USERS: AN OBSERVATIONAL STUDY

Background

Self-management strategies of adverse drug reactions (ADRs) are outside the vision of healthcare professionals (HCPs). Nevertheless, patients consider this information as one of the most important domains regarding ADR information (1). Therefore, identifying these strategies is important for both HCPs and patients.

Objectives

To identify which self-management strategies are applied by patients with immune-mediated inflammatory diseases (IMIDs) who encountered injection site reactions, local/systemic infections, or skin reactions during the use of adalimumab or etanercept.

Methods

Data of the Dutch Biologic Monitor (DBM), a prospective cohort event monitoring system, was used. Patients using biologics for IMIDs were asked to fill out bimonthly questionnaires on biologic use and experienced ADRs including questions on applied self-management strategies in an open-ended text field. For this study we included patients who used adalimumab or etanercept and reported injection site reactions, infections or skin reactions with self-management strategies. Self-management strategies were identified with thematic-analysis of the open-ended text fields.

Results

We included 160 patients and the characteristics are presented in Table 1. Most patients experienced injection site reactions (n=149), followed by infections (n=133), and skin reactions (n=101). Of these patients, the lowest number of applied self-management strategies was reported for injection site reactions (n=42, 28%), followed by skin reactions (n=62, 61%), and infections (n=88, 66%). The self-management strategies included themes such as ‘Changing methods of administration’ for injection site reactions, ‘Change of personal care’ for skin reactions, and ‘Additional treatment for the ADR’ for infections. Figure 1 shows which items are covered by these themes.

Table 1.

Patient characteristics.

Patient characteristics, n=160n (%)GenderFemale110 (68.8)Age (mean (SD))53.6 y (±14.8)IndicationPsoriatic arthritis33 (20.6)RA74 (46.3)Crohn’s disease17 (10.6)Ulcerative colitis3 (1.9)Bechterew’s disease / axial SpA23 (14.4)Othera and RA2 (1.2)Otherb8 (5.0)bDMARDAdalimumab84 (52.5)Etanercept76 (47.5)Most frequently reported ADRsInjection site reactions (pain, pruritis, erythema)85 (100)Infections231 (100) Cystitis25 (10.8) Infection susceptibility increased24 (10.4) Nasopharyngitis21 (9.1)Skin reactions266 (100) Eczema42 (15.8) Psoriasis29 (10.9) Dry skin25 (9.4)

Note: n= number of patients, y= years, RA= rheumatoid arthritis, SpA= spondyloarthritis, bDMARD= biological disease-modifying antirheumatic drug

aRheumatoid arthritis-associated lung disease (n=1), systemic scleroderma (n=1)

bUveitis posterior and panuveitis (n=1), birdshot chorioretinopathy (n=1), hemochromatosis (n=1), hidradenitis suppurativa (n=1), juvenile idiopathic arthritis (n=1), psoriasis (n=1), Bechterew’s disease and RA (n=1), RA and Crohn’s disease (n=1).

Figure 1.

Applied self-management strategies divided in themes. ADR= adverse drug reaction, HCP= Healthcare professional, ISR= injection site reactions, INF= infections, SR= skin reactions.

Conclusion

This study shows that patients apply a wide range of self-management strategies for their ADRs. Further research should focus on the effectiveness of these actions and subsequently dissemination or (de)implementation of these strategies if deemed (in)effective.

References

[1]Kusch MKP, Haefeli WE, Seidling HM. How to meet patients’ individual needs for drug information - a scoping review. Patient preference and adherence [Internet]. 2018 [cited 2022 Jan 12];12:2339–55. Available from: https://pubmed.ncbi.nlm.nih.gov/30464421/

Disclosure of Interests

Marlous Ophoff: None declared, Jette van Lint: None declared, Sander Tas Consultant of: Pfizer, GSK, Celgene, BMS, Sanofi, AstraZeneca, Bart van den Bemt Speakers bureau: UCB, Pfizer, Sanofi-Aventis, Galapagos, Amgen en Eli Lilly, Harald Vonkeman Speakers bureau: Amgen, BMS, Celgene, Galapagos, GSK, Janssen-Cilag, Lilly, Novartis, Pfizer, Roche, Sanofi-Genzyme, UCB, Grant/research support from: Abbvie, Sanofi-Genzyme, Frank Hoentjen Speakers bureau: Frank Hoentjen has served on advisory boards or as speaker for Abbvie, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz and Dr Falk, Consultant of: Celgene, Grant/research support from: Funding (Grants/Honoraria): Dr Falk, Janssen-Cilag, Abbvie, Takeda, Michael Nurmohamed Speakers bureau: Abbvie, Janssen, Celgene, Naomi Jessurun: None declared

POS0355-PARE LONGITUDINAL INVESTIGATION AND VISUALIZATION OF COURSE AND BURDEN OF ADVERSE DRUG REACTIONS IN PATIENTS WITH INFLAMMATORY RHEUMATIC DISEASES USING TNFα INHIBITORS

Background

Patients are increasingly involved in the decision process regarding their medicines, but a discrepancy exists between the information provided and preferred. Information on adverse drug reactions (ADRs) focuses on frequency, but little is known about the course and burden of ADRs.

Objectives

We aimed to investigate the course and burden of ADRs over time attributed to using TNFα-inhibitors in patients with inflammatory rheumatic diseases (IRDs) and to assess whether Sankey diagrams and polar plots are suitable to provide visualization of these aspects.

Methods

We used data of the Dutch Biologic Monitor [1], in which biologic users with an immune-mediated inflammatory disease filled out bimonthly surveys about ADRs experienced and specifically the ADR course and burden. ADRs were coded according to the MedDRA terminology. ADR course was scored as worsening, improving, remaining stable or resolving over time, with room to give a description. Furthermore, it was assessed whether an ADR was recurrent or not. Patients scored burden on a scale ranging from 1 (no burden) to 5 (very high burden). We selected patients with rheumatoid arthritis (RA), psoriatic arthritis or axial spondyloarthritis using a TNFα inhibitor (adalimumab, certolizumab pegol, etanercept, golimumab or infliximab). They also had to report an ADR belonging to the system organ classes ‘Infections and infestations’ or ‘Skin and subcutaneous tissue disorders’, or the high-level term ‘Injection site reactions’ and completed ≥2 consecutive questionnaires (representing circa ≥4 months). These types of ADRs were chosen as they impose the highest burden for patients. [2]

Results

A total of 202 patients met the inclusion criteria (71.8% female, mean age 54.8 years (±12.7 years)). The majority of the patients (61.9%) was diagnosed with RA. Most frequently used TNFα inhibitors were adalimumab (37.1%) and etanercept (54.0%). In total 353 ADRs were reported, of which 76 (21.5%) were categorized as ‘Skin and subcutaneous tissue disorders’, 122 (34.6%) as ‘Infections and infestations’ and 155 (43.9%) as ‘Injection site reactions’. The course of the ADRs is visualized in Sankey diagrams (Figure 1a-c); the flows show possible ADR courses, the width of each is proportional to the number of ADRs following that course. Most skin reactions did not change during follow-up (25.0%, Figure 1a), only a few were recurrent. Most infections resolved over time (50.8%, Figure 1b), with some remaining stable and some being recurrent. Most injection site reactions (72.3%, Figure 1c) were recurrent, and resolved in only a minority of the patients (13.4%) during follow-up. The polar plots (Figure 1d-f) visualizes the burden of the ADRs over time. For skin reactions and infections a decreasing trend was observed, represented by fading of the colors to the periphery. Infections had the highest burden at the start of the ADR, indicated by the darker colors in the inner circle. Injection site reactions had a relatively low and stable burden over time, shown by the lighter colors continuing over the circles.

Conclusion

Skin reactions attributed to the use of TNFα-inhibitors by IRD-patients show a stable course over time with a slightly diminishing burden over time. Infections have the highest burden at start but decrease over time and most of them resolve during follow-up. Injection site reactions are mostly recurrent with a low and stable burden over time. We propose that Sankey diagrams and polar plots are suitable to visualize the course and burden of ADRs over time.

References

[1]Kosse LJ et al. Patients with inflammatory rheumatic diseases: quality of self-reported medical information in a prospective cohort event monitoring system. Rheumatology. 2020; 59(6): 1253-1261.

[2]Davelaar JF, Jessurun NT, Tas SW, Nurmohamed MT, Bemt BJF van den, Vonkeman HE. Patient-reported burden of adverse drug reactions attributed to the use of adalimumab and etanercept in patients with inflammatory rheumatic diseases [abstract]. Arthritis Rheumatology. 2021; 73(10).

Disclosure of Interests

Merel de Boer: None declared, Helen Gosselt: None declared, Jurriaan Jansen: None declared, Martijn van Doorn Speakers bureau: Leopharma, Novartis, Janssen-Cilag and Pfizer, Consultant of: Leopharma, Novartis, Abbvie, BMS, Celgene, Janssen-Cilag, Lilly, MSD, Pfizer and Sanofi-Genzyme, Grant/research support from: Novartis, Frank Hoentjen Speakers bureau: Abbvie, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz and Dr Falk, Consultant of: Celgene​, Grant/research support from: Dr Falk, Janssen-Cilag, Abbvie, Michael Nurmohamed Speakers bureau: Abbvie, Leopharma, BMS, Celgene, Lilly, MSD, Pfizer, Sanofi-Genzyme, Janssen, Novartis, Consultant of: Abbvie, Leopharma, BMS, Celgene, Lilly, MSD, Pfizer, Sanofi-Genzyme, Janssen, Novarti, Grant/research support from: Novartis, Phyllis Spuls Grant/research support from: Prof. dr. Ph.I. Spuls has done consultancies in the past for Sanofi 111017 and AbbVie 041217 (unpaid), receives departmental independent research grants for TREAT NL registry, for which she is Chief Investigator (CI), from pharma companies since December 2019, is involved in performing clinical trials with many pharmaceutical industries that manufacture drugs used for the treatment of e.g. psoriasis and atopic dermatitis, for which financial compensation is paid to the department/hospital., Sander Tas Consultant of: Gebro, GSK, AbbVie, Galvani, Arthrogen, Galapagos, Grant/research support from: Pfizer, GSK, Celgene, BMS, Sanofi, AstraZeneca, Harald Vonkeman Consultant of: AbbVie, Amgen, AstraZeneca, BMS, Celgene, Celltrion, Galapagos, Gilead, GSK, Janssen-Cilag, Lilly, MSD, Novartis, Pfizer, Roche, Sanofi-Genzyme, all outside the submitted work., Grant/research support from: AbbVie, Sanofi, Naomi Jessurun: None declared

POS0158 ADHERENCE TO TELEMONITORING DISEASE ACTIVITY BY ELECTRONIC PATIENT REPORTED OUTCOMES IN PATIENTS WITH INFLAMMATORY ARTHRITIS: A PROSPECTIVE COHORT STUDY

Background

The use of electronic patient reported outcome measures (ePROM’s) enables telemonitoring disease activity in patients with inflammatory arthritis in between consultations. However, recent telemonitoring studies report declining long-term adherence to reporting ePROM’s1,2. What factors are associated with a decline in adherence is not known.

Objectives

To investigate the factors that are associated with adherence to telemonitoring by an ePROM in patients with inflammatory arthritis.

Methods

We performed a prospective cohort study in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ankylosing spondylitis (AS) at Reade Amsterdam, The Netherlands. Patients telemonitored their disease activity weekly for 6 months with a modified Multidimensional Health Assessment Questionnaire including the Routine Assessment of Patient Index Data 3 (RAPID3) that was completed in the “MijnReuma” Reade smartphone application2. Adherence was defined as the percentage of weekly completed ePROM and time to dropout as ≥4 weeks nonresponse. Based on literature and through expert meetings, 13 baseline factors were selected to assess their association with dropout through multivariable Cox-regression analysis. The association with the system usability score (measured at 3 months, 1-100) was analyzed with a linear regression for patients who dropped out in month 1, month 2-3 and month 4-6.

Results

A total of 220 consecutive patients was included (mean age 54, 55% females, median disease duration 9 years), of which 99 had RA, 81 PsA, and 40 AS. Adherence to telemonitoring declined from 81% (week 1) to 39% (week 26). Median time to dropout was 17 weeks; a total of 141 patients (64%) stopped telemonitoring their disease activity. Women had a higher chance to dropout over time compared to men (HR 1.6, p=0.02). The reported usability of the app was higher for patients who were adherent throughout the study (82) compared to patients who dropped out in the 1st month (68, p<0.001), 2nd-3rd month (71, p<0.001) and 4-6th month (78, p=0.18).

Conclusion

Women stopped reporting the ePROM sooner than man and the usability score of the app differed between the adherence and drop-out group. Future research is needed to investigate if the association between the usability score of the app and adherence is causal, and thus if improvements in the usability will lead to lower dropouts. Furthermore, we will perform focus group discussions to identify why women tend to dropout sooner, since this is in contrary to previous research3.

References

[1]Lee YC et al. Outcomes of a Mobile App to Monitor Patient-Reported Outcomes in Rheumatoid Arthritis: A Randomized Controlled Trial. Arthritis Rheumatol. 2021 Aug doi: 10.1002/art.41686.

[2]Seppen BF et al. Feasibility of Self-Monitoring Rheumatoid Arthritis With a Smartphone App: Results of Two Mixed-Methods Pilot Studies. JMIR Form Res. 2020 Sep. doi: 10.2196/20165.

[3]Wiegel J et al. Adherence to Telemonitoring by Electronic Patient-Reported Outcome Measures in Patients with Chronic Diseases: A Systematic Review. Int J Environ Res Public Health. 2021 Sep doi: 10.3390/ijerph181910161.

Table 1.

Hazard ratios for dropout

VariableHR95%CIpWomen1,581,06;2,360,02Higher education1,360,92;2,020,13Biological usage1,180,83;1,680,35High medication adherence1,140,80;1,630,47Diagnosis (relative to RA)PsA1,140,77;1,690,53AS1,090,63;1,900,76Smartphone usage1,080,94;1,230,29Charlson Comorbidity index1,050,78;1,400,76Resident in Amsterdam1,020,72;1,440,93Disease duration1,010,99;1,020,49Interaction patient-physician1,000,92;1,091,00Self-management1,000,98;1,020,72Age0,990,96;1,020,39RAPID30,970,89;1,060,51Figure 1.

Percentage weekly completed ePRO’s during the study.

Disclosure of Interests

Jim Wiegel: None declared, Bart Seppen: None declared, Marieke ter Wee: None declared, Michael Nurmohamed: None declared, W.H. Bos Grant/research support from: novartis and sanofi genzyme

POS1480-HPR SCREENING WITH THE ROUTINE ASSESSMENT OF PATIENT INDEX DATA 3 QUESTIONNAIRE CAN REDUCE THE NUMBER OF CLINIC VISITS

Background

The long-term and frequent evaluation of disease activity in patients with rheumatoid arthritis (RA) leads to a large burden of planned consultations at outpatient clinics. It might be possible to reduce that burden by prescreening to identify patients with low disease activity with the electronic Routine Assessment of Patient Index Data 3 (RAPID3), with the aim to let them skip their visits. For this purpose, accurate classification of patients in the low category with the RAPID3 is required.

Objectives

To evaluate the test characteristics and agreement between the Disease Activity Score 28 (DAS28) and the RAPID3 in patients with RA and low disease activity.

Methods

We performed a retrospective database study with clinical data collected as part of usual care from the electronic medical record at Reade Amsterdam, a secondary care center for rheumatology patients. The dataset comprised each completed RAPID3 between June 2014 and March 2021, that was followed by a DAS28 within 2 weeks in patients with RA. We dichotomized the disease activity for both the RAPID3 and DAS28 into ‘low’ and ‘high’, with cutoffs at 2.0 for RAPID3 and 3.2 for DAS28. We report test characteristics and agreement (Cohen’s kappa).

Results

The dataset comprises 5009 combined RAPID3 and DAS28 measurements recorded in 1681 unique RA patients. Mean age was 60 years, 76% of patients were female with a median disease duration of 4 years. Overall agreement was 0,58, ƙ was fair at 0.26, with 1426 (28%) of the RAPID3 measurements in the ‘low’ category (Table 1). Sensitivity to detect low disease activity was 0.39, specificity 0.94 and positive predicted value 0.92.

Table 1.

Crosstabulation of dichotomised RAPID3 and DAS28* results.

DAS28TotalLow (<3,2)High (>3,2)RAPID3Low (≤2,0)1309 (26%)117 (2%)1426 (28%)High (>2,1)2005 (40%)1578 (32%)3583 (72%)Total3314 (66%)1695 (34%)5009 (100%)

*Disease activity score 28 (DAS28),

Routine Assessment of Patient Index Data 3 (RAPID3).

Conclusion

With a positive predictive value of 0.92 for low disease activity, a RAPID3 score of 2.0 or lower is a good threshold to propose a postponement of the consultation and substantially reduce the clinic burden. Such a proposal is safe if the patient can overrule it.

References

[1]With a positive predictive value of 0.92 for low disease activity, a RAPID3 score of 2.0 or lower is a good threshold to propose a postponement of the consultation and substantially reduce the clinic burden. Such a proposal is safe if the patient can overrule it.

Disclosure of Interests

None declared

POS0381 ALLOCATION OF VISITS ACCORDING TO NEED: SCREENING RHEUMATOID ARTHRITIS PATIENTS WITH PATIENT REPORTED OUTCOMES

Background

Currently, patients with rheumatoid arthritis (RA) require frequent consultations to monitor their disease activity. However, since a majority of patients is in remission during routine follow up, it should be possible to reduce the number of consultations for them.1 Patients that are meeting their treatment goal, based on the results of their electronic patient reported outcome measures (ePROMs), could be eligible to skip their visit. Research revealed that patients who indicate to be in remission or have a low disease activity (remission/LDA) on their ePROMs, such as the routine assessment of patient index data (RAPID3), also have a low disease activity score 28 (DAS28).2 However, in clinical practice the decision to intensify treatment is more complex than not meeting a DAS28 threshold. Therefore, ePROM-results should be compared with treatment intensifications to assess the safety of screening with ePROMs.

Objectives

To assess the probability that patients with low scores on disease activity assessment with ePROMs do not need medication intensification.

Methods

This retrospective study compared results of three ePROMs (RAPID3, patient acceptable symptom state (PASS) and asking patients if they experienced a flare (flare question)) answered during routine care with (disease modifying anti-rheumatic drug) DMARD or steroid intensifications collected from anonymised electronic medical records at Reade. We calculated the positive predictive value (PPV) for not receiving a DMARD or steroid intensifications within two weeks and three months for 1) being in remission/LDA according to the RAPID3, 2) being in PASS and 3) not reporting a flare. The secondary aim of the study was to assess which combination of ePROM-results led to the best PPV for DMARD or steroid intensifications.

Results

A total of 321 records were included that regarded 302 unique patients (77% female, mean age (SD) was 60 (12) years). The PPV for not receiving a DMARD or steroid intensification within 2 weeks of the RAPID3, PASS and flare-question were 99%, 95% and 83%, respectively, and after 3 months 95%, 88%, 85%, for all test characteristics see Table 1. The combination of a RAPID3 < 2 and a negative flare-question resulted in a PPV of 100%; this combination was present in 29% (93/321) of the total study population.

Table 1.

Predictive values of ePROMs for DMARD or steroid intensifications

ePROMsPPVSpecificityNPVSensitivityDirect (<2 weeks) RAPID399992837 PASS95854271 FLARE93745283 RAPID3 + Flare1001003629Follow up (<3 months) RAPID395953940 PASS88755474 FLARE85626385 RAPID3 + Flare96963939

All numbers are percentages. ePROMs: electronic Patient Reported Outcome Measures, NPV: Negative Predictive Value, PPV: Positive Predictive Value, RAPID3: Routine Assessment of Patient Index Data-3, PASS: Patient Acceptable Symptom State.

Conclusion

Our results show that the RAPID3, PASS and flare have a high diagnostic accuracy to identify individuals that will not receive a DMARD or steroid intensification up to 3 months after their initial consultation and are therefore possibly eligible to skip their outpatient clinic visit. The combination of the RAPID3 and the PASS yielded the best combination of diagnostic accuracy and highest number of eligible patients.

References

[1]Haugeberg, G. et al. Ten years of change in clinical disease status and treatment in rheumatoid arthritis: results based on standardized monitoring of patients in an ordinary outpatient clinic in southern Norway. Arthritis Res Ther 17, 219 (2015).

[2]Wiegel J. et al. Reducing the Number of Outpatient Clinic Visits by Using the Routine Assessment of Patient Index Data 3 as a Screening Tool [abstract]. Arthritis Rheumatol. 2021; 73 (suppl 10).

Disclosure of Interests

None declared

POS1532-HPR SEX DIFFERENCES IN THE EXPERIENCED BURDEN OF ADVERSE DRUG REACTIONS ATTRIBUTED TO ADALIMUMAB AND ETANERCEPT BY PATIENTS WITH IMMUNE-MEDIATED INFLAMMATORY DISEASES

Background

Patients experience burden of adverse drug reactions.1 So far, it is not known whether men and women experience adverse drug reactions (ADRs) with the same burden.

Objectives

To examine sex differences in regard to the burden of mutually reported ADRs in patients with immune-mediated inflammatory diseases (IMIDs) treated with adalimumab or etanercept.

Methods

Patients with rheumatoid arthritis (RA), psoriatic arthritis or (axial) spondyloarthritis using etanercept or adalimumab were included from the Dutch Biologic Monitor (DBM).1 In the DBM, questionnaires concerning experienced ADRs and corresponding burden were filled out bimonthly. ADRs were coded according to Medical Dictionary for Regulatory Activities (MedDRA) terminology.

The burden of ADRs (Preferred term level, PT) was reported on a five-point Likert scale ranging from no burden (1) to very high burden (5). If ADRs were present over multiple questionnaires, burden was only assessed the first time the ADR was mentioned. Likert scales reported for burden were compared between male and female patients for mutually reported ADRs that were reported at least four times by both male and female patients, using the Cochran-Armitage test for trend, which considers the ordinal nature of Likert scales.

Results

In total 748 consecutive patients participated, of which 55% were female (Table 1). Almost half (48%) reported at least one ADR during the study. More than half of female patients (55%) reported at least one ADR as compared to 38% of male patients. In total 882 ADRs were reported comprising 264 distinct ADRs, of which the majority (74%) was reported by female patients. 71 (27%) distinct ADRs were mutually reported by male and female patients and 12 (5%) distinct ADRs were reported at least four times by females and males. Pneumonia and headache impose the highest burden of the mutually reported adverse drug reactions. ‘Arthralgia’ (p=0.052) showed the largest differences burden Likert scale scores between male and female patients. Even though male patients experienced higher burden, these differences were not statistically significant (Figure 1).

Conclusion

Although women reported the majority of the ADRs, there was a trend that that men experienced certain ADRs as more burdensome in comparison to women, albeit this did not reach statistical significance.

References

[1]van Lint JA, Jessurun NT, Hebing RCF, et al. Patient-Reported Burden of Adverse Drug Reactions Attributed to Biologics Used for Immune-Mediated Inflammatory Diseases. Drug Saf 2020;43:917-25.

Table 1.

Demographics of females and males that reported at least one of the 12 distinct adverse drug reactions (ADRs) that are included in the analysis of sex-specific burden of ADRs.

ParticipantsFemaleMaleN13870Age, mean ± SDa53.7 ± 13.557.6 ± 11.8Indication for bDMARD therapyb, N (%)Ankylosing spondylitis/axial spondyloarthritis15 (10.9)14 (20.0)Ankylosing spondylitis/axial spondyloarthritis and Psoriatic arthritis1 (0.7)-Ankylosing spondylitis/axial spondyloarthritis and Rheumatoid arthritis1 (0.7)3 (4.3)Psoriatic arthritis26 (18.8)25 (35.7)Rheumatoid arthritis95 (68.8)28 (40.0)bDMARDs, N (%)Adalimumab60 (43.5)32 (45.7)Etanercept77 (55.8)38 (54.3)Switched adalimumab/etanercept1 (0.7)-Comedication, N (%)cMethotrexate55 (39.1)21 (30.0)Corticosteroids17 (12.3)11 (15.7)Thiopurines3 (2.2)1 (1.4)Sulfasalazine9 (6.5)3 (4.3)

aAge was missing for 1 male and 1 female patient. bPatients could report multiple indications. 5 male and 14 female participants also reported other indications.

cReported comedication at the moment of inclusion. Eleven patients (male=3, female=8) did not start with etanercept or adalimumab at the moment they were included. In these cases, comedication is counted from the moment they reported the start of adalimumab or etanercept treatment.

Figure 1.

Sex-specific burden of mutually reported adverse drug reactions.

Disclosure of Interests

Helen Gosselt: None declared, Jette van Lint: None declared, Leanne Kosse: None declared, Sander Tas Consultant of: Gebro, GSK, AbbVie, Galvani, Arthrogen/MeiraGTx, Galapagos, Grant/research support from: Pfizer, GSK, Celgene, BMS, Sanofi, AstraZeneca, Phyllis Spuls Grant/research support from: Prof. dr. Ph.I. Spuls has done consultancies in the past for Sanofi 111017 and AbbVie 041217 (unpaid), receives departmental independent research grants for TREAT NL registry, for which she is Chief Investigator (CI), from pharma companies since December 2019, is involved in performing clinical trials with many pharmaceutical industries that manufacture drugs used for the treatment of e.g. psoriasis and atopic dermatitis, for which financial compensation is paid to the department/hospital.

Harald Vonkeman Speakers bureau: Amgen, BMS, Celgene, Galapagos, GSK, Janssen-Cilag, Lilly, Novartis, Pfizer, Roche, Sanofi-Genzyme, UCB, Grant/research support from: Abbvie, Sanofi-Genzyme, Michael Nurmohamed Speakers bureau: Abbvie, Janssen, Celgene, Grant/research support from: Abbvie, Martijn van Doorn Speakers bureau: Janssen, LEO Pharma, Pfizer, Novartis, Paid instructor for: LEO Pharma, Consultant of: AbbVie, Janssen, LEO Pharma, Pfizer, Celgene, Novartis, TEVA, MSD, Sanofi, AstraZeneca, Grant/research support from: Novartis, Janssen, Bart van den Bemt Speakers bureau: UCB, Pfizer, Sanofi-Aventis, Galapagos, Amgen en Eli Lilly, Naomi Jessurun: None declared

POS0411 COMPARISON OF MTX-POLYGLUTAMATE ACCUMULATION PROFILES IN PERIPHERAL BLOOD MONONUCLEAR CELLS AND ERYTHROCYTES DURING 6 MONTHS MTX-THERAPY IN THE METHOTREXATE MONITORING (MeMo) TRIAL

Background

Optimal dosing of methotrexate (MTX) in rheumatoid arthritis (RA) remains challenging. To this end, monitoring of intracellular MTX polyglutamates (MTX-PGs) in red blood cells (RBCs) has been investigated as a potential marker of MTX (non-)response, with contradictory results. As enucleated, non-proliferative cells, mature RBCs lack regulated folate metabolism and are devoid of folylpolyglutamate synthetase (FPGS) activity catalyzing the conversion of MTX to MTX-PGs. Therefore, it has been argued that analysis of MTX-PG in immune-effector cells, represented by peripheral blood mononuclear cells (PBMCs), would be more relevant. However, no prospective study has been performed measuring MTX-PG levels in PBMCs nor in comparison with RBCs.

Objectives

To investigate the pharmacokinetics of MTX-PG accumulation in RBCs and PBMCs in newly diagnosed RA patients in the early phase of MTX treatment.

Methods

In a clinical prospective cohort study (Methotrexate Monitoring (NTR7149)), RA patients were administered MTX op to 25 mg/week, as described before. (1) At 1, 2, 3 and 6 months after start of therapy, blood was collected and RBCs were isolated by centrifugation and PBMCs after Ficoll density gradient centrifugation. MTX-PG1-6 concentrations in these cells were analyzed using a UPLC-MS/MS method with including custom-made stable isotopes of MTX-PG1-6 as internal standards. (2) UPLC-MS/MS measurements for MTX-PG1-6 were performed with a Waters Acquity BEH C18 column coupled to an AB Sciex 6500+ with the ESI operating on the positive mode. MTX dosing and concomitant treatments were in conformity with clinical practice. (3)

Results

46 consecutive patients were included in this study; 76% female, mean age: 57.8 years, mean baseline DAS28-ESR: 3.5, as described before. (1) Mean dosage was 10.5 mg (SD: 1.5) at baseline, 16.3 mg (2.5) at month 1, 22.7 mg (4.5) at month 2, 19.5 mg (6.3) at month 3 and 19.1 mg (6.2) at month 6.

MTX-PG accumulation in PBMCs and RBCs revealed a disparate profile in both MTX-PG distribution and absolute accumulation levels (Figure 1A/B). Remarkably, MTX-PG distribution in PBMCs was mainly composed of MTX-PG1 (58%), and to a lesser extent MTX-PG2 (27%) and MTX-PG3 (15%). Longer chain MTX-PG4-6 were also detectable in PBMCs, but at lower levels (mean: 4.0 – 6.7 fmol/10^6 cells) than MTX-PG1-3. Moreover, this MTX-PG distribution profile in PBMCs remained constant over a MTX therapy period of 6 months (Figure 1A). The RBC MTX-PG accumulation profile shows mainly MTX-PG1 and lower levels of MTX-PG2-6 at 1 month after the start of therapy. After 3 months of therapy, MTX-PG3 is the main PG-moiety with also MTX-PG4,5,6 being detected. This profile is largely similar after 6 months of therapy. With respect to total intracellular MTX-PG1-6 accumulation, PBMCs had significantly (p<0.001) 10-20-fold higher levels than RBCs at all analyzed time points (Figure 1A/B). Total MTX-PG1-6 levels in RBCs and PBMCs at all time points were weakly correlated (r=0.41, p<0.01) (Figure 1C).

Figure 1.

Individual MTX-PG concentrations in PBMCs (A) and RBCs (B) during the first 6 months of MTX administration (note the different scaling of the y-axes). At 6 months, 36 patients were still on MTX treatment. Panel (C): Spearman’s correlation plot of total MTX-PGs in RBCs versus PBMCs of all time points.

The disparate MTX-PG accumulation and distribution profiles in PBMCs versus RBCs of RA patients may be associated with the shorter life span of PBMCs and the low FPGS activity in RBCs. (4)

No significant relation between MTX-PGs and DAS28 was found (data not shown).

Conclusion

This study shows that in newly diagnosed RA patients starting MTX therapy, MTX-PG concentrations in PBMCs are significantly 10-20-fold higher than in RBCs over a period of 6 months, with a disparate MTX-PG distribution profile in PBMCs (highest: MTX-PG1) than RBCs (highest: MTX-PG3).

References

[1]RCF Hebing, Arthr Rheum (2021)

[2]E den Boer, Anal Bioanal Chem (2013)

[3]J Smolen, Ann Rheum Dis (2020)

[4]IB Muller, Ther Drug Monit (2019)

Acknowledgements

Acknowledgements: We would like to thank all participating patients and Pfizer (grant 53233663 / WI230458), AmsterdamUMC (AI&II extension grant) and NVKC (Noyons grant 2018)

Disclosure of Interests

Renske Hebing Grant/research support from: Pfizer (grant 53233663 / WI230458), NVKC (Netherlands Society for Clinical Chemistry, Noyons grant 2018) and AmsterdamUMC (extension grant), Marry Lin: None declared, Eduard Struys: None declared, Sohaila Mahmoud: None declared, Ittai Muller: None declared, Sandra Heil: None declared, Pieter Griffioen: None declared, WIllem Lems: None declared, Bart van den Bemt Speakers bureau: Pfizer, UCB, Sanofi-Aventis, Galapagos, Amgen and Eli Lilly, Michael Nurmohamed Grant/research support from: Pfizer grant 53233663 / WI230458, Gerrit Jansen: None declared, Robert De Jonge Grant/research support from: NVKC (Netherlands Society for Clinical Chemistry, Noyons grant)

POS0379 SMARTPHONE-ASSISTED PATIENT-INITIATED CARE VERSUS USUAL CARE IN PATIENTS WITH RHEUMATOID ARTHRITIS AND LOW DISEASE ACTIVITY: A RANDOMIZED CONTROLLED TRIAL

Background

Most patients with rheumatoid arthritis (RA) visit their rheumatologist every 3-6 months to evaluate their disease activity. This may be inefficient, as research shows that many patients have minimal disease activity.1 When patients monitor their disease and initiate care at the right moment, they may be able to reduce the number of clinic visits, with a lower health care burden and costs. We developed a smartphone app that allows patients to self-monitor their disease activity through a weekly assessment of patient index data (RAPID-3).

Objectives

To assess safety (non-inferiority in disease activity, DAS28) and efficacy (reduction in number of visits) of patient-initiated care assisted by a smartphone app compared to usual care.

Methods

A twelve month, randomized, non-inferiority clinical trial was conducted in RA patients with low disease activity, on stable treatment for at least 6 months prior to entry. Patients were randomized (1:1) to either app supported patient-initiated care with a scheduled follow-up consultation after a year (app-group), or usual care, see Figure 1. The primary outcomes were non-inferiority in terms of change in disease activity (ΔDAS28) after 12 months and the number of consultations with a rheumatologist. The non-inferiority limit was set at 0.5 difference in ΔDAS28 between the groups.

Figure 1.

Typical routine care versus app-supported self-initiated care.

Results

102 of 103 randomized patients completed the study. The mean age was 58, 60 were female and the mean disease duration was 12 years. At baseline mean (SD) DAS28 was 1.67 (0.68) in the app group, and 1.54 (0.72) in the usual care group. After a year, ΔDAS28 was 0.27 in the app group vs 0.35 in the usual care group: the difference in ΔDAS28 was –0.04 in favor of the app group (95%CI –0.39; 0.30) documenting non-inferiority. The number of rheumatologist consultations was significantly lower in the app group: mean (SD) 1.7 (1.8) vs 2.8 (1.4) visits/year; visit rate ratio: 0.62 (95% CI 0.47;0.81, p<0.001).

Conclusion

Patient-initiated care supported with self-monitoring via a smartphone app was non-inferior to usual care in terms of ΔDAS28 and led to a 38% reduction in rheumatologist consultations rate.

References

[1]Haugeberg G et al. Ten years of change in clinical disease status and treatment in rheumatoid arthritis: results based on standardized monitoring of patients in an ordinary outpatient clinic in southern Norway. Arthritis Res Ther 2015

Disclosure of Interests

Bart Seppen: None declared, Jim Wiegel: None declared, Marieke ter Wee: None declared, Dirkjan van Schaardenburg: None declared, Leo Roorda: None declared, Maarten Boers: None declared, Michael Nurmohamed: None declared, W.H. Bos Grant/research support from: AbbVie sponsored this trial

POS0214 CORONARY MICROVASCULAR DYSFUNCTION IN PATIENTS WITH RHEUMATOID ARTHRITIS AND DIABETES MELLITUS: A CROSS-SECTIONAL STUDY WITH 13NH3 MYOCARDIAL PET/CT

Background

Patients with rheumatoid arthritis (RA) are at increased risk of cardiovascular disease. This risk is similar to that of diabetes mellitus (DM). There have been no studies comparing the coronary microvascular dysfunction assessed with coronary flow reserve (CFR) of RA patients to both patients with DM and a control group (=patients without RA, without DM and no cardiovascular event).

Objectives

To assess the difference in coronary microvascular dysfunction in patients with RA in comparison to patients with DM and control group.

Methods

From our 13NH3 myocardial PET/CT registry we included all patients that were included from December 2013 until March 2019. A total of 33 patients with RA, 299 patients with DM and 179 control patients (=patients without RA and without DM) were analyzed. Myocardial blood flow was quantified at rest and under stress induced by administrating adenosine. Coronary flow reserve was calculated by dividing MBF under stress by MBF in rest. CFR < 2 was indicative for coronary microvascular dysfunction.

Results

The mean age of patients was 66, with more females in the RA and control group vs the DM group (67% and 69% vs 49% respectively). The total MBF, under adenosine administration, measured in RA patients was higher than DM patients albeit that this did not reach statistical significance (2.26 ± -,70 vs 2,05 ± 0,63 mL/min/g, p=0.08). When compared to controls, the MBF of RA patients was significantly lower (2,94 ± 0,44 vs 2,26 ± 0,70, p < 0.001). The coronary flow reserve (CFR) of patients with RA was similar to patients with DM (2.20 ± 0,69 vs 2,21 ± 0,70 mL/min/g, p=0.977). The CFR of the control group was significantly higher than those of the RA patients (3,03 ± 0,64 vs 2.20 ± 0,69 mL/min/g, p<0.000) and of the DM patients (3,03 ± 0,64 vs 2.21 ± 0,70 mL/min/g, p<0.000). 42% of RA- and 38% of DM patients had coronary microvascular dysfunction, compared to 4% in the control group.

Conclusion

Our results indicate an impaired coronary blood flow in both patients with RA and DM in similar levels. Both patient groups had significantly more coronary microvascular dysfunction.

Disclosure of Interests

Bas Dijkshoorn: None declared, Remco Knol: None declared, Friso van der Zant: None declared, Michael Nurmohamed Speakers bureau: Abbvie, Janssen, Celgene, Consultant of: Abbvie, Grant/research support from: Abbvie, Amgen, Pfizer, Galapagos, BMS, Suat Simsek: None declared

OP0178 COVID-19 BREAKTHROUGH INFECTIONS IN VACCINATED PATIENTS WITH IMMUNE-MEDIATED INFLAMMATORY DISEASES AND CONTROLS – DATA FROM TWO PROSPECTIVE COHORT STUDIES

Background

Concerns have been raised regarding risks of COVID-19 breakthrough infections in vaccinated patients with immune-mediated inflammatory diseases (IMIDs) treated with immunosuppressants, but data on COVID-19 breakthrough infections in these patients are still scarce.

Objectives

The primary objective was to compare the incidence and severity of COVID-19 breakthrough infections with the SARS-CoV-2 delta variant between fully vaccinated IMID patients with immunosuppressants, and controls (IMID patients without immunosuppressants and healthy controls). The secondary objective was to explore determinants of breakthrough infections.

Methods

In this study we pooled data collected from two large ongoing prospective multi-center cohort studies (Target to-B! [T2B!] study and ARC study). Clinical data were collected between February and December 2021, using digital questionnaires, standardized electronic case record forms and medical files. Post-vaccination serum samples were analyzed for anti-RBD antibodies (T2B! study only) and anti-nucleocapsid antibodies to identify asymptomatic breakthrough infections (ARC study only). Logistic regression analyses were used to assess associations with the incidence of breakthrough infections. Multivariable models were adjusted for age, sex, cardiovascular disease, chronic pulmonary disease, obesity and vaccine type.

Results

We included 3207 IMID patients with immunosuppressants and 1810 controls (985 IMID patients without immunosuppressants and 825 healthy controls). The incidence of COVID-19 breakthrough infections was comparable between patients with immunosuppressants (5%) and controls (5%). The absence of SARS-CoV-2 IgG antibodies after COVID-19 vaccination was independently associated with an increased incidence of breakthrough infections (P 0.044). The proportion of asymptomatic COVID-19 breakthrough cases that were additionally identified serologically in the ARC cohort was comparable between IMID patients with immunosuppressants and controls; 66 (10%) of 695 patients vs. 64 (10%) of 647 controls. Hospitalization was required in 8 (5%) of 149 IMID patients with immunosuppressants and 5 (6%) of 86 controls with a COVID-19 breakthrough infection. Hospitalized cases were generally older, and had more comorbidities compared with non-hospitalized cases (Table 1). Hospitalization rates were significantly higher among IMID patients treated with anti-CD20 therapy compared to IMID patients using any other immunosuppressant (3 [23%] of 13 patients vs. 5 [4%] of 128 patients, P 0.041; Table 1).

Table 1.

Determinants of the severity of COVID-19 breakthrough infections.

Ambulatory care (n = 222)Hospitalized (n = 13)Group - no. (%)IMID patients with immunosuppressants141(64)8(62)IMID patients without immunosuppressants49(22)3(23)Healthy controls32(14)2(15)Patient characteristicsAge, years – mean (SD)51(14)60(11)Female sex – no. (%)143(64)4(31)Comorbidities – no. (%)Cardiovascular disease17(8)5(39)Chronic pulmonary disease17(8)4(31)Diabetes15(7)3(23)Obesity34(15)5(39)Immunosuppressants– no. (%)Methotrexate36(16)2(15)TNF inhibitor48(22)2(15)Anti-CD20 therapy13(6)3(23)Mycophenolate mofetil3(1)0(0)S1P modulator5(2)0(0)Other immunosuppressants70(32)3(23)

Conclusion

The incidence of COVID-19 breakthrough infections in IMID patients with immunosuppressants was comparable to controls, and infections were mostly mild. Anti-CD20 therapy might increase patients’ susceptibility to severe COVID-19 breakthrough infections, but traditional risk factors also continue to have a critical contribution to the disease course of COVID-19. Therefore, we argue that most patients with IMIDs should not necessarily be seen as a risk group for severe COVID-19, and that integrating other risk factors should become standard practice when discussing treatment options, COVID-19 vaccination, and adherence to infection prevention measures with patients.

Disclosure of Interests

None declared

AB0248 LIPID PROFILE CHANGES FROM PRE-CLINICAL TO ESTABLISHED RHEUMATOID ARTHRITIS: A 12 YEARS FOLLOWUP PILOT STUDY

Background

Patients with rheumatoid arthritis (RA) have an increased risk for developing cardiovascular diseases (CVD). This is partly due to the systemic inflammation characteristic to the disease, but also due to an increased prevalence of ‘traditional’ risk factors such as dyslipidemia. The inflammation in RA often leads to an increased catabolism of lipids, resulting in a subsequent decrease in HDL and LDL, while treatment with anti-inflammatory medication reverses these effects. This decreased cholesterol level in active disease is, unexpectedly, associated with an increased incidence of CVD (the lipid paradox). Additionally, we previously demonstrated pro-atherogenic lipid profile changes in preclinical RA patients.

Objectives

To explore the lipid profile changes in RA patients through different phases of the disease, i.e. from the preclinical stage and RA onset through treatment with biological disease modifying anti-rheumatic drugs (bDMARDs).

Methods

Thirty-nine consecutive patients who were previously included in both Reade’s RA prevention cohort and biological cohort were included in the current study. The prevention cohort consisted of individuals with arthralgia and rheumatoid factor and/or anti-citrullinated protein antibodies without arthritis, and the biological cohort comprised RA patients using bDMARDs. Lipid spectrum was measured longitudinally, at the following points in the disease course identified in each patient (time from baseline was different in each patient due to the natural course of disease progression):

1.Baseline, months prior to RA diagnosis (Start Prevention cohort)

2.Moment of RA diagnosis (End Prevention cohort)

3.Period between diagnosis and start bDMARD treatment

4.Start treatment with bDMARDs

5-7.Continued treatment with bDMARDs

Results

From baseline, high density lipoprotein cholesterol (HDLc) and apolipoprotein A1 (ApoA1) increased up to the start of biological treatment, thereafter they slightly decreased. Low density lipoprotein cholesterol (LDLc) and apolipoprotein B (ApoB) both decreased with higher disease activity, increasing again after starting bDMARD therapy. Total cholesterol/HDL ratio decreased substantially from baseline and onwards and stabilized in the bDMARDs treatment phase. Lipoprotein(a) (Lp(a)) increased slightly up to treatment with bDMARDs, after which it stabilized. Figure 1 shows the progression of HDLc, LDLc and total cholesterol (TC) plotted against C-reactive protein (CRP) over time.

Figure 1.

Time course of cholesterol parameters vs disease activity. CRP = C-reactive protein, RA = rheumatoid arthritis, Dx = diagnosis, TC = total cholesterol, HDL = high-density lipoprotein, LDL = low-density lipoprotein

Conclusion

Our study uniquely shows the change of lipid parameters during the course of RA disease. While LDLc, ApoB and cholesterol/HDL ratio decreased with higher disease activity, HDLc and ApoA1 increased, affirming the expectations. Larger cohort studies are necessary to accurately elucidate the development of lipids through different disease stages in RA patients, to better understand one of the key risk factors for CVD in RA.

References

[1]van Halm, V. P. et al. (2007). Lipids and inflammation: serial measurements of the lipid profile of blood donors who later developed rheumatoid arthritis. Annals of the rheumatic diseases, 66(2), 184–188.

Disclosure of Interests

None declared

POS1520-HPR RHEUMATOLOGY PATIENTS TREATED WITH A bDMARD PERSPECTIVE TOWARDS THERAPEUTIC DRUG MONITORING

Background

Therapeutic Drug Monitoring (TDM) is a tool to determine the optimal dose of a drug for individual patients using measurement of blood concentrations and, optionally, anti-drug antibodies (ADA). In the field of rheumatology interest in applying TDM is increasing. A recent study by Syversen et al., the NOR-DRUM B trail, supports TDM as a treatment strategy. This study showed that treatment with proactive TDM was more effective then treatment without TDM. Applying TDM creates a more personalized treatment for individual patients, therefore it is relevant to understand the patients perspective towards TDM.

Objectives

To study the perspective of rheumatology patients treated with a bDMARD in a personalized fashion using TDM.

Methods

Adult rheumatology patients from the Amsterdam Rheumatology and immunology Center who participate in the COVID-19 prospective cohort study (Nederlands Trial Register, trial ID NL8513) received a digital questionnaire which comprised, in addition to demographic items, of three TDM topics: familiarity, attitude and risk assessment.

Results

Participants were selected based on the following criteria: treatment with a bDMARD and a fully completed questionnaire (n=888). Table 1 shows characteristics of study population.

Table 1.

Characteristics of study population

Total N= 888Age, yr Mean (SD)55(13)Gender, female - N (%)575(65)Diagnosis* - N (%)RA511(58)PSA172(19)AS203(23)Axial and peripheral SpA21(3)Other17(2)bDMARD** - N (%)Adalimumab242(27)Etanercept352(40)Other297(33)

* Some patients reported more than one diagnosis

** Three patients reported more than one bDMARD

Sixty-six percent (n=582) of the participants had never heard of the concept ‘personalized dosing, using TDM’. After explaining the concept 60% (n=535) of the participants answered they have a positive attitude towards the concept (Figure 1). Participants with a positive attitude received a follow-up question. They were asked which of the following related aspects: individual dosing, costs, safety and other, they thought was most relevant regarding the concept. Multiple answers were possible. Ninety-four percent (n=502) reported as the main reason for having a positive attitude, that the treatment can be personally adjusted. The second and third reasons, respectively, were safety 43% (n=230) and costs 27% (n=142) of the treatment.

Figure 1.

Attitude towards concept of TDM against being familiar with concept of TDM

Five percent (n=43) of the participants had a negative attitude towards the concept. Main reasons were; previous experience with unsuccessful dose reduction and unwillingness to change current treatment due to the fact that several previous treatments were ineffective.

Participants were also asked what amount of risk they are willing to take when presented with five different situations; worsening rheumatologically symptoms: e.g. pain and swelling, increased fatigability, necessary treatment with prednisone, switching to another bDMARD or more frequent visits to rheumatologist. Majority of the patients reported for each of the five situations, respectively: 37% (n=330), 40% (n=359), 51% (n=453), 48% (n= 426) and 29% (n=262) that they would only be willing to take a negligible risk, < 0.1%.

Conclusion

Majority of participants was not familiar with the concept of personalized dosing using TDM. However, the majority had a positive attitude towards the concept. The main reason for a positive attitude is that the treatment can be personally adjusted. On the other hand, patients who are currently being treated with a bDMARD were only willing to take a negligible risk when it comes to their own treatment.

References

[1]Syversen, S. W., Jorgensen, K. K., Goll, G. L., Brun, M. K., Sandanger, O., Bjorlykke, K. H., Haavardsholm, E. A. (2021). Effect of Therapeutic Drug Monitoring vs Standard Therapy During Maintenance Infliximab Therapy on Disease Control in Patients With Immune-Mediated Inflammatory Diseases: A Randomized Clinical Trial. JAMA, 326(23), 2375-2384. doi:10.1001/jama.2021.21316

Disclosure of Interests

Maureen Leeuw: None declared, Sadaf Atiqi: None declared, Fenna de Vries: None declared, Laura Boekel: None declared, Femke Hooijberg: None declared, Michael Nurmohamed Speakers bureau: Abbvie, Jansen, Celgene, Consultant of: Abbvie, Grant/research support from: Abbvie, Amgen, Pfizer, Galapagos, BMS, Gert-Jan Wolbink: None declared, Charlotte Krieckaert: None declared

AB1548-HPR PATIENT-REPORTED ADVERSE DRUG REACTIONS ATTRIBUTED TO THE USE OF ADALIMUMAB: DISTINCTION BASED ON NATURE, FREQUENCY AND BURDEN

Background

Research regarding adverse drug reactions (ADRs) associated with the use of adalimumab in patients with inflammatory rheumatic diseases (IRDs) usually focuses on the nature and frequency of ADRs without considering the burden of the ADRs. However, not every ADR causes the same burden for patients. Information is lacking about the degree of experienced burden per ADR by patients with IRDs.

Objectives

First, to describe ADRs of adalimumab based on nature, frequency and burden, and second to propose a new model for identification of relevant ADRs for health care professionals.

Methods

Data of the Dutch Biologic Monitor (DBM) was used to categorize patient-reported ADRs into high and low burden. In this prospective cohort event monitoring system patients were asked to fill out bimonthly questionnaires on experienced ADRs that they attributed to the use of a biological. The questionnaire included a quantification of the burden of the reported ADRs using a five-point Likert scale ranging from 1 (no burden) to 5 (very high burden). The nature of the reported ADRs were grouped into preferred terms (PTs) according to the Medical Dictionary for Regulatory Activities (MedDRA). Inclusion criteria for this study were patients with IRDs using adalimumab and the reporting of an ADR with at least one burden score. For every patient, the mean burden scores per ADR (MedDRA PT) were analyzed. The burden was classified in two categories: ‘high’ when the mean burden score was equal to or more than 2.5, and ‘low’ when it was less than 2.5.

Text analytics of the reported ADRs (MedDRA PTs) and a comparison word cloud were used to visualize ADRs that were more often reported with high burden or more often reported with a low burden. For this, the relative ADR frequencies of the low burden classes were subtracted from the relative frequencies of the high burden class, resulting in a percentual difference between the high and low burden class for every ADR. Therefore, the highest percentual difference corresponds to the ADRs that are experienced as most burdensome.

Results

A total of 170 patients (68% female) met the inclusion criteria and reported 671 ADRs, of which 271 (40%) were reported with high burden (see Table 1). The word cloud (Figure 1) visualizes which ADRs were more often reported with high or low burden. These ADRs correspond to the greatest difference in relative class frequency. Patients experienced the burden of respiratory tract infections and increased infection susceptibility mainly as high, and the burden of injection site pruritus and injection site pain as low.

Table 1.

Characteristics of patients and reported adverse drug reactions (ADRs)

CharacteristicsTotalPatients (n = 170)Gender (female, %)116 (68)Age (years) (mean ± SD)55.4 ± 12.8IndicationaRheumatoid arthritis (%)91 (54)Ankylosing spondylitis/axial spondyloarthritis (%)31 (18)Psoriatic arthritis (%)48 (28)Adverse drug reactionsTotalHigh burdenLow burdenAdverse drug reactions (ADRs) (%)671 (100)271 (40)400 (60)Drug-induced ADR burden (mean ± SD)2.5 ± 1.03.4 ± 0.71.8 ± 0.4High burden ADRs:Respiratory tract infections12111Infection susceptibilityincreased20146Headache1394Therapeutic product effectdecreases1495Figure 1.

Comparison word cloud visualizing adverse drug reactions that patients reported more often with high burden (orange) and with no to low burden (blue). An ADR increases in size if the relative difference in frequency between classes increases.

Conclusion

The outcomes of the word cloud reveal that infections are more often experienced as burdensome, whereas injections site reactions impose low to no burden. Visualizing the nature, the frequency and the burden of ADRs in one picture, provides simple guidance to the degree of relevance for the reported ADRs in clinical practice.

Disclosure of Interests

Larissa van Boxem: None declared, Helen Gosselt: None declared, Jette van Lint: None declared, Sander Tas Consultant of: Gebro, GSK, AbbVie, Galvani, Arthrogen/MeiraGTx, Galapagos, Grant/research support from: Pfizer, GSK, Celgene, BMS, Sanofi, AstraZeneca, Bart van den Bemt Speakers bureau: paid as speaker for UCB, Pfizer, Sanofi-Aventis, Galapagos, Amgen en Eli Lilly, Harald Vonkeman Speakers bureau: Amgen, BMS, Celgene, Galapagos, GSK, Janssen-Cilag, Lilly, Novartis, Pfizer, Roche, Sanofi-Genzyme, UCB, Grant/research support from: Abbvie, Sanofi-Genzyme, Frank Hoentjen Speakers bureau: Frank Hoentjen has served on advisory boards or as speaker for Abbvie, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz and Dr Falk, Michael Nurmohamed Speakers bureau: Abbvie, Janssen, Celgene, Consultant of: Abbvie, Grant/research support from: Abbvie, Amgen, Pfizer, Galapagos, BMS, Martijn van Doorn Speakers bureau: Janssen, LEO Pharma, Pfizer, Novartis, Paid instructor for: LEO Pharma, Consultant of: AbbVie, Janssen, LEO Pharma, Pfizer, Celgene, Novartis, TEVA, MSD, Sanofi, AstraZeneca, Grant/research support from: Novartis, Janssen, Naomi Jessurun: None declared

AB0061 PHARMACOKINETICS OF METHOTREXATE POLYGLUTAMATES IN PERIPHERAL BLOOD MONONUCLEAR CELLS OF RA PATIENTS IS SIMILAR AFTER SUBCUTANEOUS OR ORAL ADMINISTRATION IN THE METHOTREXATE MONITORING (MeMo) TRIAL

Background

Pharmacokinetics of methotrexate (MTX) after oral and subcutaneous administration to RA patients differs: MTX levels in plasma and MTX-polyglutamate (MTX-PG) accumulation in erythrocytes are higher during equidosed subcutaneous compared to oral MTX treatment. (1,2) No data are available whether administration route of MTX differentially impacts the intracellular concentrations of MTX-PGs in peripheral blood mononuclear cells (PBMCs) during MTX therapy.

Objectives

To investigate the pharmacokinetics of MTX-PGs in PBMCs of newly diagnosed RA patients receiving oral or subcutaneous MTX in the early phase (1, 2, 3 and 6 months) of MTX treatment.

Methods

In a clinical prospective cohort study (MeMo study (NTR7149)), RA patients were

administered oral (n=24) or subcutaneous (n=22) MTX up to 25 mg MTX/week, as described before. (1) At 1, 2, 3 and 6 months after the start of therapy, PBMCs were isolated via Ficoll density gradient centrifugation. Individual MTX-PG forms (MTX-PG1-6) in PBMCs were analyzed by a UPLC-MS/MS method including custom-made stable isotopes of MTX-PG1-6 as internal standards (3). UPLC-MS/MS measurements of the PBMCs were performed with a Waters Acquity BEH C18 column coupled to an AB Sciex 6500+ with the ESI operating on the positive mode. Dosing, concomitant treatments and DAS28-ESR assessments were in conformity with clinical practice. (4)

Results

46 consecutive patients were included in this study; 76% female, mean age: 57.8 years, BMI: 25.8, smokers: 20%, mean baseline DAS28-ESR: 3.5, as described before. (1) MTX dose at baseline was 10.5 mg (SD: 1.5) for both groups, 15.4 mg (4.4) and 16.8 mg (1.8) at 1 month, 22.8 mg (3.9) and 22.4 mg (5.2) at 2 months, 20.1 mg (6.3) and 20.8 mg (5.6) at 3 months, and 19.7 mg (6.1) and 18.5 mg (6.7) at 6 months for oral and subcutaneous use, respectively. MTX-PG analyses in PBMCs for individual and total MTX-PGs revealed no significant differences between oral and subcutaneous administration groups at 1, 2, 3, and 6 months (Figure 1). Linear regression of LN transformed MTX-PG levels in PBMCs and administration route, corrected for age, baseline DAS28, smoking, BMI, eGFR and MTX dose, showed a trend towards higher MTX-PG levels in PBMCs after subcutaneous MTX administration compared to oral administration (data not shown). MTX-PG distribution in PBMCs was mainly composed of MTX-PG1 (58%), and to a lesser extent MTX-PG2 (27%) and MTX-PG3 (15%). Longer chain MTX-PGs beyond MTX-PG4 were detectable in PBMCs, but at levels lower than MTX-PG1-3 (mean: 4.0 – 6.7 fmol/106 cells). Total MTX-PG accumulation in PBMCs was approximately 10-20 fold higher than in erythrocytes. PBMC accumulation was rather stable, whereas RBC MTX-PG accumulation increased between 1 to 3 months to reach a plateau (Figure 1).

Figure 1.

Loess regression of MTX-PG concentrations in PBMCs (MTX-PG1-3) and RBCs (MTX-PG1-6) of RA patients during the first 6 months of oral or subcutaneous MTX administration. At 6 months, 18 patients using oral and 18 patients using subcutaneous MTX were still continuing MTX treatment. Means (lines) and SE (grey areas) are depicted.

Conclusion

This study demonstrated that MTX-PG accumulation in PBMCs early on in the MTX treatment of RA patients was not significantly different between oral or subcutaneous MTX administration routes.

References

[1]RCF Hebing et al, Arthritis Rheum (2021); 60:339-348

[2]M Hoekstra et al, J Rheumatol (2004); 31:645-8

[3]E Den Boer et al, Anal Bioanal Chem (2013); 405: 1673-1681

[4]J Smolen et al, Ann Rheum Dis (2020); 79:685-699

Acknowledgements

We would like to thank all participating patients and Pfizer (grant 53233663 / WI230458), NVKC (Noyons grant) and AmsterdamUMC (AI&II extension grant).

Disclosure of Interests

Renske Hebing Grant/research support from: Pfizer, grant number 53233663 / WI230458, Amsterdam UMC (AI&II extension grant), NVKC (Netherlands Society for Clinical Chemistry, Noyons grant), Marry Lin: None declared, Eduard Struys: None declared, Sohaila Mahmoud: None declared, Ittai Muller: None declared, WIllem Lems: None declared, Bart van den Bemt Speakers bureau: Pfizer, UCB, Sanofi-Aventis, Galapagos, Amgen and Eli Lilly, Gerrit Jansen: None declared, Robert De Jonge Grant/research support from: NVKC (Netherlands Society for Clinical Chemistry, Noyons grant), Michael Nurmohamed Grant/research support from: Pfizer grant

POS0516 PLASMA CALPROTECTIN WAS ASSESSED IN MULTIPLE BIOLOGICAL TREATMENT STRATEGIES FOR EARLY RHEUMATOID ARTHRITIS

Background

Plasma calprotectin is a sensitive inflammatory marker in patients with rheumatoid arthritis (RA) and reflects activation of granulocytes and macrophages. Plasma calprotectin has not previously been studied in a head-to-head trial of multiple biological mechanisms of action versus active conventional therapy (ACT) with methotrexate and prednisolone.

Objectives

To assess the effect of treatment on plasma calprotectin levels in patients with early RA by determining the 24-week change in the four arms of the NORD-STAR Study, a large multicenter randomized head-to-head clinical trial of ACT versus tumor necrosis factor inhibition, T-cell co-stimulation inhibition, and interleukin-6 inhibition (1).

Methods

Calprotectin was analyzed in plasma samples at baseline, week 4 and week 24 from 400 treatment naïve patients with early RA in the NORD-STAR Study. Samples were analyzed using a calprotectin ELISA alkaline phosphatase (ALP) kit from CalproLab (Oslo, Norway) in a Dynex DS2 processing system (normal levels <910 µg/L). Patients were assessed by clinical (CRP, 28 SJC/TJC, physician global) and patients’ reported assessments. Crude and adjusted linear regression analyses were performed in R 4.0.3 with calprotectin levels at week 24 as the outcome. The four arms were represented by three dummy variables. The adjustment variables were age, sex, anti-CCP status and country. Both analyses were adjusted for baseline calprotectin levels.

Results

At baseline, the mean time since diagnosis was 15.7 days (SD) (22.9), mean age 53.7 (15.0) years, ACPA positive 81%, and female 66%. Mean calprotectin levels were 1931 (1495) µg/L at baseline, 866 (951) µg/L at week 4, and 629 (661) µg/L at week 24. At baseline, normal calprotectin levels (<910 µg/L) were observed in 27% of all patients (ACT 22%, certolizumab-pegol and methotrexate 30%, abatacept and methotrexate 25%, tocilizumab and methotrexate 31%). At week 24, normal calprotectin levels were observed in 82% of all patients (ACT 68%, certolizumab-pegol and methotrexate 91%, abatacept and methotrexate 80%, tocilizumab and methotrexate 90%).

Observed calprotectin levels at week 24 were significantly lower in patients treated with certolizumab-pegol and methotrexate -336µg/L (97) (p< 0.006) or tocilizumab and methotrexate -284 (99) (p < 0.004), versus ACT when adjusted for age, sex, anti-CCP status, baseline calprotectin level, and country; however, a significant difference was not observed in patients treated with abatacept and methotrexate -110 (96) (p = 0.25). The Figure 1 shows the average percentage change in calprotectin levels from baseline to week 24 for all treatment groups.

Figure 1.

Average percentage change in calprotectin levels from baseline to week 24. ACT: active conventional therapy, CZP+MTX: certolizumab-pegol and methotrexate, ABA+MTX: abatacept and methotrexate, TCZ+MTX: tocilizumab and methotrexate.

Conclusion

Calprotectin, a sensitive biomarker of inflammation, normalized in the majority of patients. The decline differed between treatment groups and was largest in patients treated with a TNF inhibitor and methotrexate, suggesting that calprotectin reflects the activity of specific inflammatory pathways rather than overall inflammation. The findings of this study should be further explored.

References

[1]Hetland ML, et. al., Active conventional treatment and three different biological treatments in early rheumatoid arthritis: phase IV investigator initiated, randomised, observer blinded clinical trial. BMJ. 2020 Dec 2;371:m4328. doi: 10.1136/bmj.m4328. PMID: 33268527; PMCID: PMC7708829.

Acknowledgements

I would like to acknowledge the NORD-STAR Study group.

Disclosure of Interests

David Stevens: None declared, Marte Heiberg: None declared, Amirhossein Kazemi: None declared, Ronald van Vollenhoven: None declared, Jon Lampa: None declared, Anna Rudin: None declared, Kristina Lend: None declared, Merete Lund Hetland: None declared, Mikkel Østergaard: None declared, Michael Nurmohamed: None declared, Kim Hørslev-Petersen: None declared, Dan Nordström Consultant of: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Björn Gudbjornsson: None declared, Till Uhlig: None declared, Espen A Haavardsholm: None declared, Hilde Berner Hammer Speakers bureau: AbbVie, Novartis, and Lilly.

POS0589 CARDIOVASCULAR DISEASE RISK IN INFLAMMATORY ARTHRITIS STILL ELEVATED IN 2021!

Background

Patients with inflammatory rheumatic diseases as rheumatoid arthritis (RA), psoriatic arthritis (PsA) and spondyloarthritis (SpA) are at higher risk for developing cardiovascular diseases (CVD) than the general population. This is due to a higher prevalence of ‘traditional’ CV risk factors as hypertension and dyslipidemia, and the underlying systemic inflammation. During the past two decades, the burden of inflammation has been reduced by more efficacious anti-rheumatic treatment, leading to a reduced CVD risk, albeit still elevated in comparison to the general population. Therefore, it remains important to monitor the presence of CVD in rheumatic patients in systematically controlled cohorts.

Objectives

To evaluate whether, nowadays, the CVD risk of patients with inflammatory rheumatic diseases still differs from the general population.

Methods

In March 2020, all adult patients with an inflammatory rheumatic disease from the Amsterdam Rheumatology and Immunology Center, location “Reade” were systematically asked to participate in a prospective cohort study, which focused on the impact of the COVID-19 pandemic. The patients were compared with age and sex matched controls. In the third questionnaire, sent out in January 2021, questions regarding CV risk factors and comorbidities were added. Baseline characteristics and prevalence of CV risk factors and CVD were compared between RA, PsA or SpA patients, and healthy controls.

Results

2050 consecutive patients with an inflammatory rheumatic disease (1312 RA patients, 353 PsA patients, 385 SpA patients), and 939 healthy controls completed the questionnaires (Table 1). The prevalence of at least one CV comorbidity was more frequently reported in RA, PsA and SpA patients compared to healthy controls: 69 (5%), 24 (7%), 17 (4%) compared to 31 (3%), respectively. Events were primarily cardiac (i.e. myocardial infarction and coronary angioplasty). Inflammatory arthritis patients more often had hypertension or hypercholesterolemia than healthy controls, which were untreated in nearly half the cases. RA patients most often used anticoagulant medication.

Table 1.

Baseline characteristics. Values are displayed as mean ± standard deviation (SD) or frequencies with percentages (%). RA = rheumatoid arthritis, PsA = psoriatic arthritis, SpA = spondyloarthritis, CV = cardiovascular, DMARD = disease modifying anti-rheumatic drug

Patient characteristicsAll patients (n = 2050)RA(n = 1312)PsA(n = 353)SpA(n = 385)Control(n = 939)Mean age – yr57 ± 1360 ± 1257 ± 1251 ± 1355 ± 13Female sex - no (%)1266 (63)923 (70)164 (47)179 (47)636 (69)CV risk factors - no (%)Hypertension746 (37)482 (38)134 (39)130 (34)213 (23) Antihypertensive med411 (20)271 (21)78 (22)62 (16)131 (14)Hypercholesterolemia594 (30)391 (31)102 (30)101 (27)197 (21) Statins335 (16)223 (17)59 (17)53 (14)98 (10)Anticoagulants246 (12)180 (14)34 (10)32 (8)74 (8)CV diseases - no (%)Overall110 (5)69 (5)24 (7)17 (4)31 (3)Cardiac91 (4)60 (5)17 (5)14 (4)26 (3)Cerebral27 (1)12 (1)9 (3)6 (2)4 (0)Peripheral14 (1)10 (1)3 (1)1 (0)3 (0)Anti-rheumatic drugs - no (%)Prednisone202 (10)175 (13)17 (5)10 (3)n/aConventional synthetic DMARD1118 (55)902 (69)184 (52)32 (8)n/aBiological DMARD895 (44)512 (39)166 (47)217 (56)n/aTargeted synthetic DMARD20 (1)11 (1)5 (1)4 (1)n/a

Conclusion

The prevalence of CVD was approximately 1.5 times higher in patients with inflammatory rheumatic diseases compared to healthy controls (5% vs 3%), similar to older investigations. The prevalence of CV risk factors also remained elevated, and often undertreated. This indicates that the CVD risk in arthritis patients is still elevated in 2021 compared to the general population, despite improved anti-rheumatic treatment. Therefore, adequate and timely treatment of CV risk factors and optimization of anti-rheumatic drug treatment remains important in all inflammatory arthritis patients.

References

[1]Hooijberg F et al. (2020) Patients with rheumatic diseases adhere to COVID-19 isolation measures more strictly than the general population. The Lancet Rheumatology 2, 582-585.

Disclosure of Interests

None declared.

POS0648 SEX DIFFERENCES IN ADVERSE DRUG REACTIONS FROM BIOLOGICAL USE IN PATIENTS WITH IMMUNE-MEDIATED INFLAMMATORY DISEASES

Background

Women generally report more adverse drug reactions (ADRs) than men. Information on sex differences concerning the frequency and the nature of ADRs is still limited and sex differences are often not considered in research on ADRs. Consequently, no sex specific distinction is made when reporting results of ADR analyses or when providing information to patients.

Objectives

To examine sex differences in regard to the nature and frequency of reported ADRs in patients with immune-mediated inflammatory disease (IMIDs) treated with adalimumab or etanercept.

Methods

Patients with rheumatoid arthritis (RA), psoriatic arthritis or axial spondyloarthritis using etanercept or adalimumab, were included from the Dutch Biologic Monitor (DBM). Questionnaires concerning experienced ADRs were filled out bimonthly. ADRs were coded according to Medical Dictionary for Regulatory Activities (MedDRA) terminology. Sex specific ADRs (e.g. concerning menstruation) were excluded. MedDRA Preferred Terms (PTs) were analyzed to assess the nature and frequency of ADRs. Only PTs that were reported at least four times were analyzed. Discrepancies in the distribution of the nature of reported ADRs between male and female patients were assessed using Fisher Freeman Halton with Monte Carlo simulation. Subsequently, differences in frequencies at PT level were examined using Fisher’s exact tests, corrected for multiple testing using Bonferroni correction.

Results

In total 748 consecutive patients were included of which the majority (59%) was female (Table 1). 362 participants (48%) reported at least one ADR during the study. Relatively more female patients (55%) reported at least one ADR compared to male patients (38%, p<0.001). In total 882 ADRs were reported comprising 264 distinct ADRs, of which the majority (74%) was reported by female patients. The ADR distribution differed significantly between male and female patients (p=0.025). ‘Injection site pruritus’ (p=0.004), ‘injection site inflammation’ (p=0.028), ‘injection site hematoma’ (p=0.017), ‘injection site erythema’ (p=0.026), ‘hematoma’ (p=0.011) and ‘cystitis’ (p=0.044) were reported relatively more often by female patients (Figure 1). These differences were no longer statistically significant upon correction for multiple testing.

Table 1.

Demographics of included patients from the Dutch Biologic Monitor stratified on sex

ParticipantsMaleFemaleN304444Age, mean ± SDa58.2 ± 11.956.6 ± 12.9Indicationb, N(%)Bechterew’s disease/axial SpA71 (23.4)39 (8.8)Bechterew’s disease/axial SpA and PsA4 (1.3)8 (1.8)Bechterew’s disease/axial SpA and RA8 (2.6)3 (0.7)PsA89 (29.3)84 (18.9)RA132 (43.4)310 (69.8)bDMARDs, N(%)Adalimumab138 (45.4)199 (44.8)Etanercept159 (52.3)232 (52.3)Switched adalimumab/etanercept7 (2.3)13 (2.9)Comedication, N(%)cMethotrexate107 (35.2)250 (56.3)Corticosteroids27 (8.9)49 (11.0)Thiopurines3 (1.0)10 (2.2)Aminosalicylates14 (4.6)33 (7.4)

aAge was missing for 1 male and 1 female patient. bPatients could report multiple indications. 5 male and 14 female participants also reported other indications.

cReported comedication is from the moment of inclusion. Eleven patients (male=3, female=8) did not start with etanercept or adalimumab at the moment they were included. For these, comedication is from the moment they reported to be treated with adalimumab or etanercept for the first time.

Figure 1.

Top reported ADRs

Percentages on the x-axis were calculated separately for sex, divided by the number of male or female patients with at least one ADR. *p-value<0.05.

Conclusion

Female patients reported relatively more ADRs than male patients. Also, the distribution of the nature of the ADRs significantly differed for male and female patients. In particular injection site reactions were reported relatively more often in female patients than in male patients. Therefore, sex differences in experiencing ADRs may exist and should be taken into consideration when investigating and reporting results on ADRs or when informing patients.

Disclosure of Interests

Helen Gosselt: None declared, Jette van Lint: None declared, Sander Tas Consultant of: Gebro, GSK, AbbVie, Galvani, Arthrogen/MeiraGTx, Galapagos, Grant/research support from: Pfizer, GSK, Celgene, BMS, Sanofi, AstraZeneca, Bart van den Bemt Speakers bureau: paid as speaker for UCB, Pfizer, Sanofi-Aventis, Galapagos, Amgen en Eli Lilly, Harald Vonkeman Speakers bureau: Amgen, BMS, Celgene, Galapagos, GSK, Janssen-Cilag, Lilly, Novartis, Pfizer, Roche, Sanofi-Genzyme, UCB, Grant/research support from: Abbvie, Sanofi-Genzyme, Frank Hoentjen Speakers bureau: Frank Hoentjen has served on advisory boards or as speaker for Abbvie, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz and Dr Falk, Consultant of: Celgene, Grant/research support from: Funding (Grants/Honoraria): Dr Falk, Janssen-Cilag, Abbvie, Takeda, Michael Nurmohamed Speakers bureau: Abbvie, Janssen, Celgene, Consultant of: Abbvie, Grant/research support from: Abbvie, Amgen, Pfizer, Galapagos, BMS, Martijn van Doorn Speakers bureau: Janssen, LEO Pharma, Pfizer, Novartis, Paid instructor for: LEO Pharma, Consultant of: AbbVie, Janssen, LEO Pharma, Pfizer, Celgene, Novartis, TEVA, MSD, Sanofi, AstraZeneca, Grant/research support from: Novartis, Janssen, Naomi Jessurun: None declared

OP0020 SEX DIFFERENCES IN EFFECTIVENESS OF FIRST-LINE TUMOR NECROSIS FACTOR INHIBITORS IN AXIAL SPONDYLOARTHRITIS; RESULTS FROM FIFTEEN COUNTRIES IN THE EuroSpA RESEARCH COLLABORATION NETWORK

Background

Evidence reveals sex differences in physiology, disease presentation and response to treatment in axial spondyloarthritis (axSpA). Pooled data from four randomized controlled trials demonstrated reduced treatment efficacy of a tumor necrosis factor inhibitor (TNFi) in females compared to males with ankylosing spondylitis1. However, real-life evidence confirming these data in large cohorts is scarce. We sought to validate prior studies using data from a large multinational cohort based on real-life clinical practice.

Objectives

To investigate sex differences in treatment response and drug retention rates in clinical practice among patients with axSpA, treated with their first TNFi.

Methods

Data from biologic-naïve axSpA patients initiating a TNFi in the EuroSpA registries were pooled. In the primary analysis, propensity-score weighting was applied to assess the causal effect of sex on clinically important improvement (CII) according to ASDAS-CRP at 6 months. A generalized linear regression model was used to estimate the causal risk difference (RD) and relative risk (RR) of sex on CII. Possible covariates influencing the outcome were determined a priori and selected based on availability in the database (<20% missing). The final covariates included in the model were country, age and TNFi start year. In the secondary analysis, drug retention was assessed over 24 months of follow-up by Kaplan-Meier curves and log-rank test.

Results

In total, 6,451 axSpA patients with available data on ASDAS-CRP at baseline and 6 months were assessed for treatment response. Baseline characteristics are shown in the Table 1. In the adjusted analysis, the probability for females to have CII was 15% (RR, 0.85; 95% confidence interval [CI], 0.82 to 0.89) lower compared to males and the difference in probability for having CII was 9.4 percentage points (RD, 0.094; 95% CI, 0.069 to 0.12). The survival analysis included 28,608 axSpA patients with available data on retention rates. The TNFi 6/12/24-month retention rates were significantly lower in females (81%/69%/58%) compared to males (89%/81%/72%), see Figure 1.

Table 1.FemaleMaleMean (SD), Median [IQR] or percentagesMean (SD), Median [IQR] or percentagesAge (years)42.0 (12.1)41.4 (12.3)Fulfilment of mNYC66%80%Disease duration (years)2.0 [1.0, 7.0]3.0 [1.0, 9.0]TNFi start year Start 1999-20097.2%9.8% Start 2010-201326%27% Start 2014-201637%36% Start 2017-202030%27%BASDAI, mm59 (20)54 (21)BASFI, mm48 (25)46 (24)ASDAS, units3.5 (0.9)3.5 (1.0)CRP (mg/L)6.7 [2.5, 16.0]11.9 [4.0, 25.0]SJC (0-28)0 [0, 0]0 [0, 0]TJC (0-28)0 [0, 2]0 [0, 1]VAS pain, mm63 (22)59 (24)VAS fatigue, mm65 (25)59 (26)

mNYC, modified New York criteria; TNFi, tumor necrosis factor inhibitor; BASDAI, Bath Ankylosing Spondylitis Disease Activity Indexf; BASFI, Bath Ankylosing Spondylitis Functional Index; ASDAS, Ankylosing Spondylitis Disease Activity Score; CRP, C-reactive protein; SJC, swollen joint count; TJC, tender joint count; VAS, visual analogue scale.

Conclusion

Treatment efficacy and retention rates are lower among female patients with axSpA initiating their first TNFi. Females presented with lower C-reactive protein levels and higher scores on patient reported outcomes at baseline, reflecting differences in disease expression. Recognizing these sex differences is of relevance for customized patient care and may improve patient education.

References

[1]van der Horst-Bruinsma et al. Ann Rheum Dis. 2013 Jul;72(7):1221-4.

Acknowledgements

Novartis Pharma AG and IQVIA for supporting the EuroSpA collaboration.

Disclosure of Interests

Pasoon Hellamand Grant/research support from: Novartis, Marleen G.H. van de Sande Speakers bureau: UCB, Consultant of: Abbvie, Eli Lily, Novartis and UCB, Grant/research support from: Novartis, Janssen, UCB and Eli Lilly, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Thomas Klausch: None declared, Michael Nurmohamed Speakers bureau: Abbvie, Janssen and Celgene, Consultant of: Abbvie, Grant/research support from: Abbvie, Amgen, Pfizer, Galapagos, BMS, Ronald van Vollenhoven Consultant of: AbbVie, AstraZeneca, Biogen, BMS, Galapagos, Janssen, Miltenyi, Pfizer, UCB and speaker fees from Abbvie, Galapagos, GSK, Janssen, Pfizer, R-Pharma and UCB, Grant/research support from: BMS, GSK and UCB, Dan Nordström Consultant of: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Anna-Mari Hokkanen Grant/research support from: MSD, Maria Jose Santos Speakers bureau: Abbvie, AstraZeneca, Lilly, Novartis and Pfizer, Elsa Vieira-Sousa Speakers bureau: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Consultant of: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Grant/research support from: MSD, Celgene, Novartis, Janssen, Abbvie and Pfizer, Anne Gitte Loft Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Grant/research support from: Novartis, Bente Glintborg Grant/research support from: Pfizer, Abbvie and BMS, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Grant/research support from: Abbvie, BMS, Merck, Celgene and Novartis, Ulf Lindström: None declared, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly and Novartis, Brigitte Michelsen Grant/research support from: Novartis, Adrian Ciurea Speakers bureau: AbbVie and Novartis, Michael J. Nissen Speakers bureau: AbbVie, Eli Lilly, Janssens, Novartis and Pfizer, Consultant of: AbbVie, Eli Lilly, Janssens, Novartis and Pfizer, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis and Pfizer, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis and Pfizer, Corina Mogosan Speakers bureau: AbbVie, Ewopharma, Lilly, Novartis and Pfizer, Consultant of: AbbVie, Ewopharma, Lilly, Novartis and Pfizer, Gary Macfarlane Grant/research support from: GSK, Gareth T. Jones Grant/research support from: AbbVie, Pfizer, UCB, Amgen and GSK, Karin Laas Speakers bureau: Amgen, Janssen, Novartis and Abbvie, Ziga Rotar Speakers bureau: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek and Janssen, Consultant of: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek and Janssen, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi and Sandoz-Lek, Consultant of: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi and Sandoz-Lek, Isabel Castrejon Speakers bureau: Eli Lilly, BMS, Janssen, MSD and Abbvie, Consultant of: Eli Lilly, BMS, Janssen, MSD and Abbvie, Manuel Pombo-Suarez Consultant of: Abbvie, MSD and Roche, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, Consultant of: Amgen and Novartis, Arni Jon Geirsson: None declared, Eirik kristianslund: None declared, Jiří Vencovský Speakers bureau: Abbvie, Argenx, Boehringer-Ingelheim, Eli-Lilly, Gilead, MSD, Novartis, Octapharma, Pfizer, Roche, Sanofi and UCB, Consultant of: Abbvie, Argenx, Boehringer-Ingelheim, Eli-Lilly, Gilead, MSD, Novartis, Octapharma, Pfizer, Roche, Sanofi and UCB, Lucie Nekvindova: None declared, Semih Gulle: None declared, Berrin Zengin: None declared, Merete Lund Hetland Grant/research support from: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz and Novartis, Irene van der Horst-Bruinsma Speakers bureau: BMS, AbbVie, Pfizer and MSD, Consultant of: Abbvie, UCB, MSD, Novartis and Lilly, Grant/research support from: MSD, Pfizer, AbbVie and UCB.

POS0289 A CONCEPTUAL FRAMEWORK OF THE COURSE AND TIMEFRAME OF PATIENT-REPORTED ADVERSE DRUG REACTIONS OF BIOLOGICS IN IMMUNE-MEDIATED INFLAMMATORY DISEASES

Background

Patients with immune-mediated inflammatory diseases (IMIDs) need chronic drug treatment, including biologics, which may cause adverse drug reactions (ADRs). Information about ADRs is usually restricted to the type of ADRs that may occur with drug use. Common patterns in the course and timeframe of ADRs are often not described while this information may provide valuable insights for patients and healthcare professionals.

Objectives

To identify common and corresponding items with thematic analysis in the described course of ADRs of biologics reported by patients with IMIDs.

Methods

We used qualitative data from the Dutch Biologic Monitor (DBM) to assess the patient’s descriptions of the course of ADRs they experienced. IMID patients were asked to fill out a bimonthly questionnaire on experienced ADRs they attributed to the use of a biologic [1, 2]. Inclusion criteria were: patients reporting an ADR and elaboration on the course of the ADR in an open-ended text field. Answers of the patients on the course of the experienced ADR were analysed by two pharmacovigilance assessors with a thematic analysis with an inductive approach to develop a conceptual framework which was visualised using an Ishikawa diagram.

Results

From 1382 consecutive participants, 730 patients reported 2035 ADRs. Six themes with multiple subthemes were identified from patient descriptions on the course of the ADRs they experienced (Figure 1). Four themes included descriptive items of the course of ADRs: the moment or period of ADR occurrence (e.g. a specific moment of the day or in a specific season), the frequency of an ADR episode (e.g. once, sometimes, often, always or recurring with or without specified frequency), the duration of an ADR episode (e.g. specified duration, constant, variable increasing or decreasing duration) or an association in time with the administration moment (e.g. before, during or after biologic administration or a specific time to onset in relation to the moment of biologic administration). Two themes included factors influencing the course of ADRs: triggering factors for ADR occurrence or aggravation (e.g. administration method, social, physical or mental status, nutrition, external factors, (co)medication or daily activities) and improving factors (e.g. administration method, treatment, physical or mental status, nutrition or selfcare).

Figure 1.

A conceptual framework of descriptions of the course and timeframe of adverse drug reactions reported by patients using a biologic for immune-mediated inflammatory diseases

Conclusion

We identified six themes in patient-reported descriptions of the course of ADRs of biologics. These themes provide information about ADRs on a broader level than the currently available information on nature and frequency. Information about ADRs enriched with details on the course and timeframe of ADRs may support healthcare professionals in improving clinical practice by discussing ADRs with patients and finding practical solutions in dealing with ADRs. This will ultimately lead to more optimised medical treatment.

References

[1]Kosse LJ, Jessurun NT, Hebing RCF, Huiskes VJB, Spijkers KM, van den Bemt BJF, et al. Patients with inflammatory rheumatic diseases: quality of self-reported medical information in a prospective cohort event monitoring system. Rheumatology (Oxford). 2020;59(6):1253-61.

[2]van Lint JA, Jessurun NT, Hebing RCF, Hoentjen F, Tas SW, Vonkeman HE, et al. Patient-Reported Burden of Adverse Drug Reactions Attributed to Biologics Used for Immune-Mediated Inflammatory Diseases. Drug Saf. 2020;43(9):917-925.

Disclosure of Interests

Jette van Lint: None declared, Naomi Jessurun: None declared, Sander Tas Consultant of: Gebro, GSK, AbbVie, Galvani, Arthrogen/MeiraGTx, Galapagos, Grant/research support from: Pfizer, GSK, Celgene, BMS, Sanofi, AstraZeneca, Harald Vonkeman Speakers bureau: Amgen, BMS, Celgene, Galapagos, GSK, Janssen-Cilag, Lilly, Novartis, Pfizer, Roche, Sanofi-Genzyme, UCB, Grant/research support from: Abbvie, Sanofi-Genzyme, Frank Hoentjen Speakers bureau: served on advisory boards or as speaker for Abbvie, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz and Dr Falk, Consultant of: Celgene, Grant/research support from: Funding (Grants/Honoraria): Dr Falk, Janssen-Cilag, Abbvie, Takeda, Martijn van Doorn Speakers bureau: Janssen, LEO Pharma, Pfizer, Novartis, Paid instructor for: LEO Pharma, Consultant of: AbbVie, Janssen, LEO Pharma, Pfizer, Celgene, Novartis, TEVA, MSD, Sanofi, AstraZeneca, Grant/research support from: Novartis, Janssen, Michael Nurmohamed Speakers bureau: Abbvie, Janssen, Celgene, Consultant of: Abbvie, Grant/research support from: Abbvie, Amgen, Pfizer, Galapagos, BMS, Bart van den Bemt Speakers bureau: UCB, Pfizer, Sanofi-Aventis, Galapagos, Amgen en Eli Lilly

POS0659 LONG-TERM DYNAMICS OF ANTIBODY RESPONSE TO ADALIMUMAB DETECTED WITH A DRUG TOLERANT ASSAY

Background

Immunogenicity of adalimumab (ADL) has been the subject of extensive research, with the primary focus on its incidence, antibody titers and effects on clinical outcome. However, the temporal evolution of antibodies, i.e. dynamic and variation in titers, time point of emergent and persistence or transience of the response, remains under elucidated. To investigate this further, it is essential to collect samples at regular intervals and over a longer period of time. Also, a drug tolerant assay should be used to conquer with the phenomenon of drug interference (1).

Objectives

To evaluate the temporal evolution and to distinguish dynamic patterns of antibody response. Secondly, to assess the clinical impact and factors influencing these dynamic patterns.

Methods

ADA and adalimumab concentration were measured in sera of 511 consecutive ADL treated rheumatoid arthritis patients. Serum samples were drawn at week 0, 4, 16, 28, 52, 78 and 104. ADA were measured with a drug tolerant assay (Acid dissociation RadioImmunoAssay). Logistic regression analysis was carried out. Benjamini-Hochberg was used to correct for multiple testing.

Results

Baseline characteristics are depicted in Table 1. Fifty-nine percent of patients (n=300) developed ADA. Based on visual observations patients were clustered in 9 groups, taking the next features in to account (Figure 1); the presence or absence of ADA, the height of ADA titers (higher or lower than 100AU/mL), emergent (early vs. late; cutoff week 28) and its persistence. Based on these features 397 (77%) patients were assigned to one of the groups. Due to missing data at crucial time points the remainder of patients were excluded. In the ‘High early’ and High early LTF’ group was the rate of MTX use (adjusted odds ratio (AOR) 0.033 [95%CI 0.01-0.09] P<0.0001 respectively 0.79 [95%CI 0.03-0.22] P <0.0001), adalimumab concentration above 5mg/L (AOR 0.022[95%CI 0.01-0.08] P<0.001 respectively 0.026 [95%CI 0.01-0.09] P<0.001) and low disease activity (DAS28 <3.2) at week 52 (AOR 0.191[95%CI 0.07-0.56] P<0.002 respectively 0.102 [95%CI 0.03-0.31] P<0.001) significantly lower, compared to the negative group. Furthermore, the failure rate was in both groups significantly higher (AOR 9.19 [95%CI 3.7-22.87] P<0.0001 respectively 23.94 [95%CI 8.13-70.53] P<0.0001). In contrast to forgoing studies, our data does not show any differences in clinical outcomes between groups with persistent and transient ADA response.

Table 1.

Baseline characteristics

Totaal N=511Follow-upMedian weeks (IQR)78 (28-104)DemographicsAge mean SD53,7; ± 12,5Female No (%)409 (79.8)Disease statusDisease duration years median (IQR)6,7 (3-13)IgM rheumatoid factor + (%)327 (68.2)Anti-citrullinated protein antibody + (%)315 (73.2)Erosive (%)296 (61.6)DAS28-score mean SD4.5 ± 1.5MedicationMethotrexate use no (%)378 (73)

Conclusion

The majority of patients have an immune response to ADL. Based on ADA concentration, time point of emergence and its persistence, certain patterns of ADA response can be distinguished. Only high ADA concentration at early time points, causing low ADL concentration, are associated with unfavorable clinical effects. All the remaining distinctive patterns does not have any association with clinical outcomes. This suggests a regulated immune response in the majority of patients.

References

[1]Atiqi S, Hooijberg F, Loeff FC, Rispens T, Wolbink GJ. Immunogenicity of TNF-Inhibitors. Front Immunol. 2020 Feb 26;11:312. doi:10.3389/fimmu.2020.00312. PMID: 32174918; PMCID: PMC7055461

Disclosure of Interests

Sadaf Atiqi: None declared, Maureen Leeuw: None declared, Femke Hooijberg: None declared, Laura Boekel: None declared, Floris Loeff: None declared, Karien Bloem: None declared, Charlotte Krieckaert: None declared, Annick de Vries: None declared, Michael Nurmohamed Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, Roche, and Sanofi, Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Mundipharma, Novartis, Pfizer, Roche, and Sanof, Theo Rispens Speakers bureau: AbbVie, Pfizer, and Regeneron, Grant/research support from: Genmab, Gert-Jan Wolbink Speakers bureau: UCB, Pfizer, AbbVie, Biogen and BMS, Grant/research support from: Pfeizer (paid to institution)

OP0059 PROFOUND ANTICOAGULANT EFFECTS OF INITIAL ANTIRHEUMATIC TREATMENTS IN EARLY RHEUMATOID ARTHRITIS PATIENTS: A NORD-STAR SPIN-OFF STUDY

Background

Patients with rheumatoid arthritis (RA) are at an increased risk of venous thromboembolism. Thus far, there have not been any comparative studies investigating the effects of initial antirheumatic treatments in (very) early RA patients.

Objectives

To assess the effects of different initial treatments on hemostatic parameters in patients with early RA.

Methods

NORD-STAR is an international, multicentre, open-label, assessor-blinded, phase 4 study where patients with newly diagnosed RA started methotrexate (MTX) and were randomised 1:1:1:1 to a) conventional treatment (either prednisolone tapered to 5mg/day, or sulfasalazine combined with hydroxychloroquine and intra-articular corticosteroids), b) certolizumab pegol, c) abatacept, d) tocilizumab1. This study is a spin-off from the main NORD-STAR study extensively investigating hemostatic system in 24 per protocol consecutive Dutch participants at baseline, 12 weeks and 24 weeks after the start of the treatment. Statistical analysis was done using paired samples t-test in SPSS version 28.

Results

The mean age of investigated patients was 51.8 (± 12.7) years and 58.3% were female. At baseline patients had an average DAS28 score of 4.6 (± 0.9) and had elevated levels of investigated coagulation biomarkers: Factor 1 + 2, fibrinogen, D-dimer and parameters of the two global hemostatic assays, i.e. endogenous thrombin potential (ETP) and overall hemostasis potential (OHP). These biomarkers decreased significantly at 12 and 24 weeks in patients in all groups (Table 1). Overall fibrinolytic potential (OFP) was decreased and clot lysis time (CLT) was prolonged at baseline, demonstrating impaired fibrinolytic activity in early RA. The reduction of coagulation parameters was significantly higher in biological treatment arms in comparison to the standard MTX treatment arm. In addition, tocilizumab was more effective compared to certolizumab and abatacept, (Figure 1), which was expected considering the direct inhibitory effect of this drug on the IL-6 synthesis and consequently the coagulation activation as well. After 24 weeks of treatment with methotrexate and tocilizumab, the average fibrinogen of patients was reduced by 63% vs 31% and 36% in the certolizumab and abatacept groups, respectively. The changes in DAS-28 and the changes in fibrinogen had a correlation of 0.385 which did not reach statistical significance.

Table 1.

Measurements are marked with * if p<0.05, ** if p<0.01 and *** if p<0.001

BaselineW12W24Factor 1 + 2 (pmol/L)270.25 (149.4)190.36 (108.6)**179.52 (85.3)***Fibrinogen (g/L)4.64 (1.5)3.61 (1.6)**2.63 (1.2)***D-dimer (mg/L)2.17 (3.0)0.33 (0.23)**0.29 (0.2)**OHP (Abs-sum)157.38 (64.9)120.62 (68.7)*100.49 (53.8)***OCP (Abs-sum)369.52 (58.8)305.04 (101.7)*275.91 (83.1)***OFP (%)57.97 (13.1)63.20 (12.7)*65.25 (11.4)***Lag time (s)304.5 (71.1)306.8 (71.8)312.7 (65.4)Slope0.07 (0.02)0.066 (0.03)0.094 (0.12)Max Abs1.17 (0.3)1.00 (0.4)*0.91 (0.3)**CLT (s)1405 (356)1317 (377)1231 (320)**ETP (nM*min)1480 (471)1395 (395)*1337 (429)*Peak (nM)231 (78)223 (68)223 (74)Lagtime (min)4.06 (2.1)3.28 (1.2)**2.87 (1.0)***ttPeak (min)7.40 (2.2)6.61 (1.5)*6.13 (1.4)**Figure 1.

Conclusion

Our results indicate an enhanced coagulation and fibrinolytic impairment in newly diagnosed RA patients. Effective antirheumatic treatments reduce this hemostatic imbalance, with significantly more pronounced effects of biologic drugs compared to conventional (MTX+glucocorticoids) treatment.

References

[1]Hetland M et al. BMJ. 2020

Disclosure of Interests

Bas Dijkshoorn: None declared, Aleksandra Antovic: None declared, Daisy Vedder: None declared, Anna Rudin: None declared, Dan Nordström Speakers bureau: Novartis, UCB, Consultant of: Abbvie, BMS, Lilly, Novartis, Pfizer, Roche, UCB, Björn Gudbjornsson Speakers bureau: Amgen and Novartis - not related to this work, Consultant of: Novartis - not related to this work, Kristina Lend: None declared, Till Uhlig Speakers bureau: Grünenthal, Novartis, Consultant of: Grünenthal, Novartis, Grant/research support from: NORDFORSK, Espen A Haavardsholm Consultant of: Pfizer, AbbVie, Celgene, Novartis, Janssen, Gilead, Eli-Lilly, UCB, Grant/research support from: NORDFORSK, Norwegian Regional Health Authorities, South-Eastern Norway Regional Health Authority, Gerdur Gröndal: None declared, Merete Lund Hetland Consultant of: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Grant/research support from: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Marte Heiberg: None declared, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Celgene, Eli-Lilly, Galapagos, Gilead, Janssen, Merck, Novartis, Orion, Pfizer, Roche and UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi and UCB, Grant/research support from: Abbvie, Amgen, BMS, Merck, Celgene and Novartis, Kim Hørslev-Petersen: None declared, Jon Lampa Speakers bureau: Pfizer, Janssen, Novartis, Ronald van Vollenhoven Speakers bureau: Abbvie, Galapagos, GSK, Janssen, Pfizer, R-Pharma, UCB, Consultant of: Abbvie, AstraZeneca, Biogen, BMS, Galapagos, Janssen, Miltenyi, Pifzer, UCB, Grant/research support from: BMS, GSK, UCB, Michael Nurmohamed Speakers bureau: Abbvie, Janssen, Celgene, Consultant of: Abbvie, Grant/research support from: Abbvie, Amgen, Pfizer, Galapagos, BMS.

NT-proBNP and sRAGE levels in early rheumatoid arthritis

OBJECTIVE

Several biomarkers of cardiovascular function are found to be increased in rheumatoid arthritis (RA), with some suggesting a relationship with disease activity and improvement with adequate anti-rheumatic treatment. Promising biomarkers include N-terminal pro-brain natriuretic peptide (NT-proBNP) and the soluble receptor form of advanced glycation end-products (sRAGE). The objective of this study was to investigate associations between NT-proBNP and sRAGE levels and markers of inflammation and disease activity in early RA patients and their changes during (effective) anti-rheumatic treatment.

METHOD

Data from 342 consecutive early RA patients participating in the 'Parelsnoer' cohort were used. At baseline and after 6 months' disease activity, NT-proBNP and sRAGE levels were assessed.

RESULTS

After 6 months, NT-proBNP decreased from 83 pmol/L (mean) at baseline to 69 pmol/L at follow-up (p < 0.001), while sRAGE increased from 997 pg/mL to 1125 pg/mL (p < 0.001). A larger decrease in erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP) was associated with larger changes in NT-proBNP and sRAGE. For every point decrease in ESR, there was a 1.7-point decrease in NT-proBNP and a 2.2-point increase in sRAGE. For CRP, these values were 1.7 and 2.7, respectively (p < 0.001).

CONCLUSION

Suppressing inflammation, independently of achieving remission, increases sRAGE levels and decreases NT-proBNP levels significantly. Whether this translates into a decrease in incident cardiovascular disease remains to be elucidated.

Antirheumatic drugs for cardiovascular disease prevention: the case for colchicine

We summarised four pivotal Randomised Controlled Trials (RCTs) with antirheumatic drugs on the secondary prevention of cardiovascular events. The favourable effects of canakinumab and colchicine confirm (low-grade) inflammation as an independent risk factor for cardiovascular events. While colchicine might be the first drug in the clinic, we expect that this is only the first in a future series of anti-inflammatory drugs used in secondary prevention of cardiovascular events.

POS0524 CARDIOVASCULAR DISEASE RISK IN INFLAMMATORY ARTHRITIS PATIENTS STILL SUBSTANTIALLY ELEVATED IN 2020

Background:

Patients with inflammatory rheumatic diseases such as rheumatoid arthritis (RA), psoriatic arthritis (PsA) and ankylosing spondylitis (AS) are at a higher risk for developing cardiovascular diseases (CVD) than the general population. This increased risk is partly due to a higher incidence of traditional cardiovascular (CV) risk factors, such as hypertension and dyslipidemia, and partly due to the underlying systemic inflammation. During the past two decades, the burden of the systemic inflammation has been reduced by more efficacious anti-inflammatory treatment, which somewhat attenuated the increased CV risk of rheumatic patients. However, it remains important to monitor the effects of these new treatment strategies on the prevalence of CVD in patients with a rheumatic disease in systematically controlled cohorts.

Objectives:

The aim of the current report was to evaluate whether the CV risk of patients with inflammatory rheumatic diseases still differs from the general population, despite advances In anti-rheumatic treatment strategies.

Methods:

In March 2020, all adult patients with an inflammatory rheumatic disease from the Amsterdam Rheumatology and Immunology Center, location “Reade” were systematically asked to participate in a prospective cohort study. The primary aim of this study was to monitor the impact of the COVID-19 pandemic on patients with inflammatory rheumatic diseases compared to age and sex matched healthy controls. Between April 26, 2020 and May 27, 2020, participants completed the first online questionnaire of the study. Amongst others, information on demographic data, including CV comorbidities and risk factors, and medication use was collected. The baseline characteristics and prevalence of CVD were compared between RA, PsA or AS and healthy controls.

Results:

In total, 1455 consecutive patients with an inflammatory rheumatic disease (979 RA patients, 261 PsA patients and 215 AS patients), and 414 healthy controls completed the first questionnaire, as shown in table 1. CV comorbidities were more frequently reported in RA, PsA and AS patients compared to healthy controls; 107 (11%), 28 (11%) and 22 (10%) compared to 30 (7%), respectively.

Table 1.

Biological DMARD usage in RA, PsA and AS patients

Patient characteristicsAll patients (n=1455)RA (n=979)PsA (N=261)AS (n=215)Controls (n=414)Mean age - yr55 ± 1358 ± 1255 ± 1348 ± 1353 ± 13Female sex - no (%)934 (64)728 (74)119 (46)87 (41)298 (72)BMI (IQR)25 (23-28)25 (22-28)26 (24-30)25 (22-28)24 (22-27)Smoking - no (%)178 (12)126 (13)17 (7)35 (16)34 (8)Cardiovascular disease – no (%)157 (11)107 (11)28 (11)22 (10)30 (7)Rheumatic medication - no (%)csDMARDs877 (60)712 (73)148 (57)17 (8)N.A.Oral glucocorticoids161 (11)139 (14)17 (7)5 (2)2 (0.4)TNF inhibitor563 (39)336 (34)121 (46)106 (49)N.A.IL-6 inhibitor19 (1)19 (2)00N.A.IL-17 inhibitor17 (1)2 (0.2)7 (3)8 (4)N.A.

Table 1. Baseline characteristics. Values are displayed as mean ± standard deviation (SD), median with interquartile range (IQR) or frequencies with percentages (%). RA = rheumatoid arthritis, PsA = psoriatic arthritis, AS = ankylosing spondylitis, BMI = body mass index, TNF = anti-tumor necrosis factor, IL = interleukin.

Conclusion:

We demonstrated that the prevalence of CVD is approximately 1.5 times higher in patients with rheumatic diseases compared to healthy controls (11% vs. 7%, respectively). This corresponds with previous research, although the reported prevalence of CVD in PsA and AS patients is even higher compared to prior studies. This suggests that the CVD risk of patients with rheumatic diseases is still elevated in 2020 compared to the general population, despite the improved management of rheumatic disease activity. Therefore, adequate and timely treatment of CV risk factors remains relevant, not only in patients with RA, but in patients other rheumatic diseases as well.

References:

[1]Hooijberg F et al. (2020) Patients with rheumatic diseases adhere to COVID-19 isolation measures more strictly than the general population. The Lancet rheumatology 2(10), 583-585.

Disclosure of Interests:

None declared

AB0251 INCREASED ACCUMULATION OF ERYTHROCYTE METHOTREXATE POLYGLUTAMATES DURING EARLY PHASE SUBCUTANEOUS VERSUS ORAL METHOTREXATE TREATMENT OF RHEUMATOID ARTHRITIS PATIENTS

Background:

Optimal dosing of methotrexate (MTX) for individual rheumatoid arthritis (RA) patients to achieve adequate disease control is an ongoing challenge. Assessment of erythrocyte MTX-polyglutamates (PGs) levels has been employed as a tool to monitor clinical response of RA patients in the first 3-12 months of treatment and MTX-PG2-4 and total MTX-PGs were associated with a lower DAS28 over 9 months.1 However, data from earlier time points, MTX-PG6 and per route of administration are unavailable.

Objectives:

To investigate the pharmacokinetics and -dynamics of erythrocyte MTX-PG accumulation in RA patients receiving oral or subcutaneous MTX in the early phase (1, 2, and 3 months) of MTX treatment initiation.

Methods:

In a clinical prospective cohort study (MeMo study (NTR7149)), newly diagnosed RA patients were administered oral (n=24) or subcutaneous (n=22) MTX, mostly according to the COBRA-light schedule (start 10 mg MTX, increased to 25 mg MTX in 8 weeks). At 1, 2, and 3 months after start of therapy, blood was collected and individual MTX-PGs (MTX-PG1 – MTX-PG6) were analyzed in erythrocytes at a minimal detection limit of 1 nmol/L, using a validated UHPLC-MS/MS method with labeled internal standards.1 Dosing, concomitant treatments and DAS28-ESR assessments were in conformity with clinical practice. Adverse events were recorded.

Results:

46 consecutive patients were included in this study; 76% female, mean age: 57.8 years, BMI: 25.8, 20% smokers, mean baseline DAS28-ESR: 3.5. Notwithstanding marked interpatient variability, patients starting subcutaneous MTX had accumulated significantly higher (approximately 2-fold) long chain MTX-PGs (MTX-PG4-6) when compared to patients in the oral MTX group at 1 and 2 months (Figure 1A, Table 1). Similarly, MTX-PG1-6 and MTX-PG3 accumulation were higher in subcutaneous MTX-users at month 1 (p=0.022 and p=0.011) compared to the oral group (median 68.6 nmol/L (IQR:40.5) vs 51.9 (55.6) and 17.4 (11.1) vs 11.2 (15.6), respectively (Figure 1B, Table 1).

Table 1.

Linear regression of MTX-PG levels and administration route, corrected for age, baseline DAS28, smoking, BMI, eGFR and MTX dose.

monthß (P-value)1ß (P-value)2ß (P-value)3MTX-PG1-61.65 (0.022)1.51 (0.073)1.30 (0.233)MTX-PG1,21.13 (0.599)1.19 (0.470)1.12 (0.623)MTX-PG31.75 (0.011)1.51 (0.071)1.19 (0.439)MTX-PG4-61.97 (0.036)2.04 (0.033)1.55 (0.136)

Mean MTX dose at baseline was 10.5mg (SD 1.5) for both groups, 15.4 (4.4) and 16.8 (1.8) at 1 month and 22.8 (3.9) and 22.4 (5.2) at 2 months for oral and subcutaneous use respectively.

DAS28 decreased with 1.6 in the oral group and 1.1 in the subcutaneous group (p=0.382). With and without corrections for age, baseline DAS28, eGFR, MTX dose (1 month before sampling), smoking and BMI, no significant relation between MTX-PG concentrations and DAS28 was observed during the first 3 months of treatment.

43 patients reported any side effect, mostly headache and dizziness, which was similar in both groups and uncorrelated with MTX-PG levels.

No association was found between MTX-PG1 levels and number of days between timing of blood withdrawal and last administration.

Figure 1.

Erythrocyte long chain MTX-PG(A) and total MTX-PG(B) accumulation in RA patients of the first 3 months of oral(C) or subcutaneous(D) MTX administration. At 3 months, 18 patients using oral and 18 patients using subcutaneous MTX were still continuing MTX treatment. Medians and IQR are depicted.

Conclusion:

This study shows the feasibility of measuring erythrocyte MTX-PGs early on in the treatment of RA patients with MTX and demonstrated significantly higher accumulation of MTX-PGs following subcutaneous versus oral MTX administration. Early phase erythrocyte MTX-PG analyses may hold potential for positioning in optimizing individual patient MTX dose scheduling.

References:

[1]de Rotte MC, et al. Methotrexate polyglutamates in erythrocytes are associated with lower disease activity in patients with rheumatoid arthritis. Ann Rheum Dis 2015(74):408-14.

Acknowledgements:

We would like to thank all participating patients and Pfizer (grant 53233663 / WI230458).

Disclosure of Interests:

Renske Hebing Grant/research support from: Pfizer, Ittai Muller: None declared, Marry Lin: None declared, Sohaila Mahmoud: None declared, Sandra Heil: None declared, WIllem Lems: None declared, Michael Nurmohamed: None declared, Robert De Jonge: None declared, Gerrit Jansen: None declared

POS0271-HPR PATIENT PERSPECTIVE ON A DRUG SAFETY MONITORING SYSTEM FOR IMMUNE-MEDIATED INFLAMMATORY DISEASES BASED ON PATIENT-REPORTED OUTCOMES

Background:

Patient-reported outcomes (PROs) on adverse drug reactions (ADRs) are increasingly used in cohort event monitoring (CEM) to obtain a better understanding of patient’s real-world experience with drugs. Despite the leading role for patients, little is known about their perspectives on these monitoring systems.

Objectives:

To obtain more insight in patients’ perspectives on the perceived usefulness, ease of use and attitude toward using the Dutch Biologic Monitor (DBM), and their preferred design for a national drug safety monitoring system for immune-mediated inflammatory diseases (IMIDs).

Methods:

We developed a cross-sectional open survey following the rationale of the Technology Acceptance Model to obtain insight in patients’ perspectives on the DBM. The DBM is a pilot for a PRO-based drug safety monitoring system focused on ADRs attributed to biologics that are prescribed for IMIDs. This survey consisted of 20 categorical and 1 open-ended question. Seven categorical questions contained a text field for additional comments. Five-point Likert-type scales or multiple-choice questions were used to identify patients’ preferences and perspectives. Patients were eligible for the survey if they were still enrolled in the DBM at the time of the survey opening and if they had completed at least one questionnaire of the DBM. Categorical questions were descriptively analyzed, whereas text fields were analyzed using theoretical thematic analysis.

Results:

At the start of the survey a total of 1,225 patients had participated in the DBM. Approximately 70% had an inflammatory rheumatic disease. The survey was completed by 292 eligible respondents (response rate 44.8%). The respondents generally agreed that it was useful to participate in the DBM and would recommend it to their peers (Figure 1). The response burden of the bimonthly questionnaires was scored as ‘low’, irrespective of the presence of ADRs or education level (Table 1). A number of respondents suggested that the questionnaire frequency should be synchronized with the regular hospital visits or the administration schedule of the biologic. Moreover, questionnaires should be offered less frequent and preferably shortened in case of an unaltered situation or absence of ADRs. Half (49.0%) of the respondents was interested in sharing their questionnaires with a medical specialist, whereas a third (34.2%) advocated sharing the questionnaires with their pharmacist (Figure 1).

Table 1.

Perceived response burden of the Dutch Biologic Monitor questionnaires. The average burden is calculated using a five-point Likert-type scale. Data is represented as the number of respondents (n).

Overall(n = 292)ADRs reportedEducation levelaYes(n = 225)No(n = 54)Do not know(n = 13)Lower(n = 149)Higher(n = 139)Burdenn(%)n(%)n(%)n(%)n(%)n(%)1: No burden224(76.7)169(75.1)46(85.2)9(69.2)106(71.1)115(82.7)2: Low burden58(19.9)48(21.3)7(13.0)3(23.1)36(24.2)22(15.8)3: Moderate burden6(2.1)6(2.7)0(0.0)0(0.0)4(2.7)2(1.4)4: High burden0(0.0)0(0.0)0(0.0)0(0.0)0(0.0)0(0.0)5: Very high burden0(0.0)0(0.0)0(0.0)0(0.0)0(0.0)0(0.0)No opinion4(1.4)2(0.9)1(1.9)1(0.0)3(2.0)0(0.0)Average burden1.21.31.11.21.31.2

aMissing: 4 respondents.

Figure 1.

Stacked bar graph of user perspectives. Agreement scores were measured using a five-point Likert-type scale. The average agreement score per statement is indicated on the far right. The percentages represent the share of respondents. DBM: Dutch Biologic Monitor; ADRs: adverse drug reactions.

Conclusion:

This study provides valuable insights in the patient perspective on a PRO-based drug safety monitoring system for inflammatory rheumatic diseases and other IMIDs, and provides several useful starting points to further stimulate and improve PRO-based CEM systems. Altogether, it appears feasible to establish a PRO-based drug safety monitoring system that monitors IMID patients’ real-world experience with ADRs that has a low burden for the participants.

Disclosure of Interests:

Leanne Kosse: None declared, Gerda Weits: None declared, Harald Vonkeman Grant/research support from: AbbVie, Amgen, AstraZeneca, BMS, Celgene, Celltrion, Galapagos, Gilead, GSK, Janssen-Cilag, Lilly, MSD, Novartis, Pfizer, Roche, Sanofi-Genzyme, all outside the submitted work., Sander Tas Grant/research support from: AbbVie, Arthrogen, AstraZeneca, BMS, Celgene, Galapagos, GSK, MSD, Pfizer, Roche, Sanofi-Genzyme, all outside the submitted work., Frank Hoentjen Speakers bureau: Abbvie, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz and Dr Falk, all outside the submitted work, Consultant of: Celgene, Janssen-Cilag, all outside the submitted work, Grant/research support from: Dr Falk, Janssen-Cilag, Abbvie, Takeda, all outside the submitted work, Martijn van Doorn Grant/research support from: Leopharma, Novartis, Abbvie, BMS, Celgene, Lilly, MSD, Pfizer, Sanofi-Genzyme, Janssen Cilag, outside the submitted work., Phyllis Spuls Grant/research support from: Departmental independent research grant for TREAT NL registry from different companies, is involved in performing clinical trials with many pharmaceutical industries that manufacture drugs used for the treatment of e.g. psoriasis and atopic dermatitis, for which financial compensation is paid to the department/hospital and, is Chief Investigator (CI) of the systemic and phototherapy atopic eczema registry (TREAT NL) for adults and children and one of the main investigators of the SECURE-AD registry, all outside the submitted work., Geert D’Haens Consultant of: Abbvie, Ablynx, Active Biotech AB, Agomab Therapeutics, Allergan, Alphabiomics, Amakem, Amgen, AM Pharma, Applied Molecular Therapeutics, Arena Pharmaceuticals, AstraZeneca, Avaxia, Biogen, Bristol Meiers Squibb/Celgene, Boehringer Ingelheim, Celltrion, Cosmo, DSM Pharma, Echo Pharmaceuticals, Eli Lilly, Engene, Exeliom Biosciences, Ferring, DrFALK Pharma, Galapagos, Genentech/Roche, Gilead, Glaxo Smith Kline, Gossamerbio, Pfizer, Immunic, Johnson and Johnson, Kintai Therapeutics, Lycera, Medimetrics, Takeda, Medtronic, Mitsubishi Pharma, Merck Sharp Dome, Mundipharma, Nextbiotics, Novonordisk, Otsuka, Photopill, ProciseDx, Prodigest, Prometheus laboratories/Nestle, Progenity, Protagonist, RedHill, Robarts Clinical Trials, Salix, Samsung Bioepis, Sandoz, Seres/Nestec/Nestle, Setpoint, Shire, Teva, Tigenix, Tillotts, Topivert, Versant and Vifor, all outside the submitted work, Michael Nurmohamed Speakers bureau: AbbVie, Celgene, Celltrion, Eli Lilly, Janssen, Sanofi, all outside the submitted work, Consultant of: AbbVie, Bristol-Myers Squibb, Eli Lilly, Roche, Sanofi, all outside the submitted work, Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Mundipharma, Novartis, Pfizer, Roche, Sanofi, all outside the submitted work, Eugène van Puijenbroek: None declared, Bart van den Bemt: None declared, Naomi Jessurun: None declared

POS1046 IMPROVEMENTS IN PATIENT-REPORTED IMPACT OF PSORIATIC ARTHRITIS WITH IL-12/23 (USTEKINUMAB) OR TUMOUR NECROSIS FACTOR INHIBITORS: 1-YEAR DATA FROM THE LARGE, REAL-WORLD PsABIO STUDY

Background:

Psoriatic arthritis (PsA) negatively impacts patients’ (pts) quality of life (QoL), with a high burden of pain, fatigue and psychological distress. The 12-item Psoriatic Arthritis Impact of Disease questionnaire (PsAID-12) is a validated measure of pt-reported disease impact.

Objectives:

To analyse PsAID-12 score changes in the overall population and specific subgroups of interest, and assess correlation of these changes using Health Assessment Questionnaire Disability Index (HAQ-DI).

Methods:

PsABio (NCT02627768) is a multinational, prospective, observational study in pts with PsA receiving ustekinumab (UST) or a tumour necrosis factor inhibitor (TNFi) as a 1st/2nd/3rd-line biologic. Descriptive statistics, including 95% CI, are presented at baseline (BL) and 1 year. Linear regression, including propensity score (PS) adjustment for BL covariates, was used to compare change in PsAID-12 total from BL to 1 year between treatments. The relationship between changes in PsAID-12 and HAQ-DI was investigated using Spearman’s correlation.

Results:

Data were available for 438 UST and 455 TNFi pts. From BL to 1 year, significant improvements were seen in total PsAID-12 scores and in all domains with both treatments (Figure 1). PS-adjusted treatment comparison showed no difference in total PsAID-12 improvement (regression coefficient [95% CI]: 0.14 [-0.22; 0.51], p=0.4433), or in any domain, except skin problems, which improved significantly more with UST than TNFi (-0.55 [-1.04, -0.06], p=0.0277). Improvements in PsAID-12 and HAQ-DI showed strong positive correlation with both treatments (UST: r=0.63, p<0.0001; TNFi: r=0.70, p<0.0001). Effectiveness was demonstrated with UST and TNFi in subgroups of interest, including biologic treatment line, sex and psoriasis extent (Table 1. next page).

Conclusion:

Treatment with IL-12/23 (UST) or TNF inhibitors significantly improved pt-reported disease impact at 1 year. PS-adjusted PsAID-12 improvements did not differ significantly between treatments, except skin problems (better with UST). Improvements in disease impact and physical functioning (HAQ-DI) were strongly correlated, emphasising the effect of these biologics on QoL in PsA pts.

Figure 1.Table 1.

PsAID-12 scores by BL characteristic subgroup

Mean (95% CI)USTTNFiBLUnadjusted change from BL at 1 year (LOCF)BLUnadjusted change from BL at 1 year (LOCF)Biologic line1st5.51(5.19; 5.82)-2.14(-2.49; -1.79)5.44(5.15; 5.72)-2.41(-2.72; -2.09)2nd6.05(5.69; 6.41)-2.14(-2.55; -1.72)5.57(5.19; 5.95)-2.37(-2.79; -1.94)3rd5.84(5.33; 6.35)-1.81(-2.45; -1.17)5.34(4.52; 6.15)-1.89(-2.62; -1.16)Sex*Male5.27(4.95; 5.59)-2.35(-2.70; -1.99)4.89(4.56; 5.23)-2.49(-2.83; -2.15)Female6.14(5.86; 6.43)-1.86(-2.20; -1.52)5.95(5.67; 6.23)-2.20(-2.53; -1.87)EnthesitisYes5.95(5.66; 6.24)-2.19(-2.51; -1.86)5.89(5.61; 6.17)-2.65(-2.98; -2.31)No5.51(5.19; 5.83)-1.98(-2.36; -1.59)4.99(4.65; 5.32)-2.02(-2.35; -1.68)Psoriasis BSA, %<35.66(5.32; 6.00)-1.60(-2.03; -1.18)4.97(4.63; 5.31)-1.89(-2.25; -1.52)3–105.44(5.05; 5.83)-2.16(-2.59; -1.74)5.78(5.43; 6.14)-2.99(-3.38; -2.59)>106.15(5.70; 6.60)-2.93(-3.43; -2.43)6.13(5.55; 6.71)-2.86(-3.49; -2.23)Joint involvement†Mono/oligoarticular5.07(4.56; 5.58)-1.96(-2.47; -1.45)4.82(4.38; 5.25)-2.18(-2.66; -1.70)Polyarticular5.98(5.75; 6.22)-2.21(-2.51; -1.92)5.78(5.52; 6.04)-2.47(-2.75; -2.18)FiRST score*<55.15(4.87; 5.44)-2.18(-2.50; -1.87)5.10(4.83; 5.36)-2.44(-2.71; -2.16)≥56.72(6.43; 7.00)-1.95(-2.38; -1.53)6.49(6.15; 6.83)-2.09(-2.57; -1.61)

*At BL, female pts and pts with FiRST score ≥5 (chronic widespread pain) were significantly more impacted than male pts and pts with FiRST score <5, and remained significantly more impacted at 1 year. †Polyarticular pts were significantly more impacted at BL, but not 1 year.

BSA, body surface area; CI, confidence interval; FiRST, Fibromyalgia Rapid Screening Tool; LOCF, last observation carried forward

Acknowledgements:

This study was funded by Janssen.

Disclosure of Interests:

Laure Gossec Consultant of: AbbVie, Amgen, Bioepis, Biogen, Bristol-Myers Squibb, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung, Sanofi-Aventis, UCB, Grant/research support from: Amgen, Galapagos, Janssen, Lilly, Pfizer, Sandoz, Sanofi, Stefan Siebert Speakers bureau: AbbVie, Amgen (previously Celgene), Biogen, Janssen, Novartis, UCB, Consultant of: AbbVie, Janssen, UCB, Grant/research support from: Amgen (previously Celgene), Boehringer Ingelheim, Bristol-Myers Squibb, GSK, Janssen, Novartis, Pfizer, UCB, Paul Bergmans Shareholder of: Johnson & Johnson, Employee of: Janssen, Kurt de Vlam Speakers bureau: AbbVie, Amgen, Eli Lilly, Novartis, UCB, Paid instructor for: Amgen, Galapagos, UCB, Consultant of: Eli Lilly, Galapagos, Johnson & Johnson, Novartis, UCB, Grant/research support from: Celgene, Elisa Gremese: None declared, Beatriz Joven-Ibáñez Speakers bureau: AbbVie, Celgene, Janssen, MSD, Novartis, Pfizer, Tatiana Korotaeva Speakers bureau: AbbVie, Amgen, Biocad, Lilly, Janssen, MSD, Novartis, Novartis-Pfizer, Sandoz, UCB, Consultant of: AbbVie, Amgen, Biocad, Lilly, Janssen, MSD, Novartis, Novartis-Sandoz, Pfizer, UCB, Grant/research support from: Pfizer, Wim Noel Employee of: Janssen, Michael Nurmohamed Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Petros Sfikakis Consultant of: AbbVie, Actelion, Boehringer Ingelheim, Enorasis, Farmaserv-Lilly, Genesis, Gilead, Pfizer, MSD, Novartis, UCB, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Faran, Janssen, Pfizer, Roche, Elke Theander Employee of: Janssen, Josef S. Smolen Speakers bureau: AbbVie, Amgen, AstraZeneca, Astro, Bristol-Myers Squibb, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Lilly, MSD, Novartis- Sandoz, Pfizer, Roche, Samsung, Sanofi, UCB, Grant/research support from: AbbVie, AstraZeneca, Lilly, Novartis, Roche.

POS0213 20 Year Follow-Up Of Cardiovascular Event Risk In Rheumatoid Arthritis Compared To Diabetes

Background:

Patients with rheumatoid arthritis have an increased risk for developing cardiovascular diseases (CVD) compared to the general population, similar to the CVD risk in patients with diabetes mellitus. However, there are no controlled studies investigating the incidence of cardiovascular (CV) events in RA patients with follow up of more than 20 years.

Objectives:

The objectives of the current study were to investigate the incidence rates of CV events in a long-term follow up cohort of RA patients, and to compare these to a similar cohort representing the general population, ie. The Hoorn study.

Methods:

The CARRÉ study is an ongoing prospective cohort study, which started in 2001, investigating CV mortality and morbidity in 353 randomly selected patients with RA. Primary endpoints, i.e. verified medical history of coronary, cerebral or peripheral arterial disease, were determined at baseline, and after three, ten, fifteen and twenty years of follow up. Patients were censored at the date of an experienced CV event or their death. Incidence density rates per 100 patient years were calculated. Data were compared to results from the Hoorn study, a Dutch cohort study of glucose metabolism and other CV risk factors that began in 1989. All 2,484 participants were subject to an extensive and repeated CV screening program similar to that used in the CARRÉ study.

Results:

After 20 years of follow up 118 patients (33%) developed at least one CV event in the Carré group. Mean (SD) follow up time was 11 (6) years with a total of 3,500 years at risk and an incidence rate of 3.4 per 100 patient-years; this is slightly up from the figure reported at 15 years, i.e. 3.2 per 100 patient-years. A CV event-free survival curve is shown in figure 1. After 30 years of follow up, 295 participants of the Hoorn study had developed a CV event, during a mean follow up time 20 (8) years. Total time at risk was 50,000 years, with an incidence rate of 0.6 CV events per 100 patient years.

Conclusion:

In our cohort the incidence rate of CV events in RA patients has remained consistently high when compared with the general population, despite better control of RA inflammation in recent years. This again confirms the need for timely CVD-risk screening and management.

References:

[1]Agca R, Hopman L, Laan KJC, van Halm VP, Peters MJL, Smulders YM, et al. Cardiovascular Event Risk in Rheumatoid Arthritis Compared with Type 2 Diabetes: A 15-year Longitudinal Study. J Rheumatol. 2020;47(3):316-24.

Figure 1.

Survival curve of participants with rheumatoid arthritis. RA = rheumatoid arthritis

Disclosure of Interests:

None declared

POS0669 HYPOGLYCAEMIA FOLLOWING JAK INHIBITOR TREATMENT IN DIABETES MELLITUS PATIENTS WITH RHEUMATOID ARTHRITIS

Background:

Janus kinase (JAK) inhibitors are effective small molecular drugs for rheumatoid arthritis (RA) and other immune mediated inflammatory diseases (IMIDs). JAK inhibitors exert their immunosuppressive effects by suppressing the action of JAK, an intracellular tyrosine. Although infections are the most reported side effects, potential glucose lowering effects in patients with diabetes mellitus (DM) have been described in literature and have also been reported as suspected adverse drug reactions (ADRs) to the National Pharmacovigilance Centre Lareb in the Netherlands (1).

Objectives:

To assess and describe suspected adverse effects of JAK inhibitors on glucose levels in diabetic patients with rheumatic diseases and other IMIDs, as reported in daily practice.

Methods:

We describe ADR reports of tofacitinib and baricitinib in the European pharmacovigilance Eudravigiliance (EV) database from initiation to 12 January 2021. All ADRs in EV are coded according to the Medical Dictionary for Regulatory Activities (MedDRA). We included all reports indicating hypoglycaemia in patients with reported DM type 1 and 2 or with antidiabetic drugs as concomitant medication. This could include oral antidiabetics as well as insulins.

Results:

On 12 January 2021 the EV database included 32 ADR reports, concerning 32 diabetic patients, indicating hypoglycaemia associated with the use of JAK inhibitors (15 tofacitinib, 17 baricitinib), out of 32,484 ADR reports in total concerning tofacitinib or baricitinb (Table 1). Most patients (25 patients, 78%) used the JAK inhibitor for rheumatoid arthritis. The suspected ADR with MedDRA Preferred Term ‘Hypoglycaemia’ was reported for 16 patients and MedDRA Preferred Term ‘Decreased blood glucose’ was reported for 15 patients. In one case, increased insulin sensitivity was described as suspected ADR of baricitinib. In this case, the insulin dose had to be reduced to prevent hypoglycaemia. Of note, the insulin dose had to be increased after temporary discontinuation of baricitinib and was reduced again after baricitinib was restarted. Additionally, in six cases improvements of glycaemic control were described after discontinuation or dose reduction of the JAK inhibitor or antidiabetic drug. Improvements were also described after unknown action or unchanged treatment with JAK inhibitor in eight cases.

Conclusion:

JAK inhibitors may induce hypoglycaemia by increasing insulin sensitivity, and consequently may reduce the need for antidiabetic medication (2-3). Healthcare professionals should be alert for these potential ADRs when starting a JAK inhibitor in patients with DM as comorbidity. More research is needed to support our findings and elucidate the underlying pharmacological mechanisms of this potentially beneficial effect of JAK inhibitors.

Table 1.

Suspected adverse drug reaction reports indicating hypoglycaemia in diabetic patients using tofacitinib or baricitinib in the Eudravigilance database

Tofacitinib N (%)Baricitinib N (%)No. of reports15 (100)17 (100)Mean age years (range)65 (56 - 78)62.2 (48 - 78)Female gender13 (87)13 (76)Indication for JAK inhibitor Rheumatoid arthritis11 (73)14 (82) Unknown3 (20)3 (18) Arthritis1 (7)Reported adverse drug reaction Hypoglycaemia6 (40)11 (65)a Decreased blood glucose9 (60)6 (35) aTime to onset after start JAK inhibitorb Within 1 month6 (40)3 (18) 2-6months2 (13)2 (12) More than 6 months1 (7)Improvement after action: Drug withdrawal3 (20)c1 (6)d Dose adjustments1 (6)e Other1 (7)f

a.In one case of baricitinib hypoglycaemia as well as decreased blood glucose were reported as adverse drug reactions.

b.Time to onset was unknown in 6 reports of tofacitinib and 12 reports of baricitinib

c.Tofacitinib withdrawal: 1, sitagliptin withdrawal: 1, tofacitinib and insulin withdrawal: 1

d.Baricitinib withdrawal: 1

e.Baricitinib: after insulin dose adjustments: 1

f.After tofacitinib withdrawal and insulin dose adjustments

References:

[1]Fujita Y, et al. Case Rep Rheumatol. 2019.

[2]Bako HY, et al. Life Sci. 2019.

[3]Chaimowitz NS, et al. N Engl J Med. 2020.

Disclosure of Interests:

Jette van Lint: None declared, Florence van Hunsel: None declared, Sander Tas Consultant of: Gebro, GSK, AbbVie, Galvani, Arthrogen, Galapagos, Grant/research support from: Pfizer, GSK, Celgene, BMS, Sanofi, AstraZeneca, Michael Nurmohamed Speakers bureau: speaker’s fees from AbbVie, Bristol-Myers Squibb, Eli Lilly, Roche, and Sanofi, Consultant of: consulting fees from AbbVie, Celgene, Celltrion, Eli Lilly, Janssen, and Sanofi, Grant/research support from: research funding from AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Mundipharma, Novartis, Pfizer, Roche, and Sanofi, Harald Vonkeman Grant/research support from: AbbVie, Amgen, AstraZeneca, BMS, Celgene, Celltrion, Galapagos, Gilead, GSK, Janssen-Cilag, Lilly, MSD, Novartis, Pfizer, Roche, Sanofi-Genzyme, all outside the submitted work., Renske Hebing: None declared, Frank Hoentjen Speakers bureau: served on advisory boards or as speaker for Abbvie, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz and Dr Falk, Consultant of: Celgene, Janssen-Cilag, Grant/research support from: Dr Falk, Janssen-Cilag, Abbvie, Takeda, Martijn van Doorn Grant/research support from: reports personal fees from Leopharma, grants and personal fees from Novartis, personal fees from Abbvie, personal fees from BMS, personal fees from Celgene, personal fees from Lilly, personal fees from MSD, personal fees from Pfizer, personal fees from Sanofi-Genzyme, personal fees from Janssen Cilag, outside the submitted work., Bart van den Bemt: None declared, Eugène van Puijenbroek: None declared, Naomi Jessurun: None declared

OP0232 FEMALE VERSUS MALE BURDEN OF PSORIATIC ARTHRITIS IS HIGHER AND TREATMENT PERSISTENCE SHORTER AFTER USTEKINUMAB OR TUMOUR NECROSIS FACTOR INHIBITOR TREATMENT: 1-YEAR DATA FROM THE PSABIO STUDY

Background:

Sex-related differences in biologic treatment of psoriatic arthritis (PsA) have been insufficiently studied in a real-world setting.

Objectives:

To evaluate impact of sex on PsA, treatment effectiveness and persistence after 1 year of biologic treatment.

Methods:

PsABio (NCT02627768) is a multinational, prospective real-world study in PsA with ustekinumab (UST) or TNF inhibitor (TNFi) as 1st/2nd/3rd-line biologic. Males and females were compared for disease activity and patient-reported outcomes. Descriptive statistics including 95% CI at baseline (BL) and 12 (±3) months (LOCF) follow-up are presented. Intra-sex comparisons between UST and TNFi cohorts were done by logistic regression analysis, with propensity score adjustment for imbalanced BL covariates and non-response imputation for stopping/switching biologic drugs.

Results:

Among 494 females and 399 males, age and disease duration were similar. However, differences in disease characteristics at BL were considerable: females had worse scores than males for cDAPSA, HAQ-DI, EQ5D VAS, PsAID-12, pain and comorbidities. At 1 year, similar improvements from BL were observed between sexes, but females remained in a worse health state than males (Table). Achievement of composite endpoints MDA (including VLDA) and cDAPSA LDA (including remission) was high overall (38.6% and 61.5%, respectively), but reached by >2-fold and 3-fold more males than females, respectively. HAQ-DI scores remained worse for females at 1 year (0.95) than for males at BL (0.93). Enthesitis resolution was achieved in 46% of females and 75% of males. No significant differences in effectiveness of UST vs TNFi were detected between sexes (Figure). Kaplan–Meier estimated drug persistence was significantly better in males than females (log-rank p=0.0007). There was no intra-sex difference between UST or TNFi in risk of stopping/switching in males or females.

Table 1.

Patient and disease characteristics at BL and 1-year by sex

BL femaleBL male1-year LOCF female1-year LOCF maleBiologic line, %1st4655N/AN/A2nd34333rd2013Co-treatment, %MTX37.434.3N/AN/ACorticosteroids34.632.1NSAIDs59.964.4Antidepressant7.92.5Comorbidities, %N/AN/ACardiovascular69.059.4metabolic syndrome40.131.7Obesity35.223.7Anxiety/depression12.67.5Smoking status, %N/AN/ANever54.941.9Past16.826.6Current22.724.3Unknown5.77.3Joint counts, nSwollen 666.1 (5.4; 6.9)5.6 (4.7; 6.4)2.2 (1.7; 2.6)1.3 (1.0; 1.6)Tender 6813.2 (12.0; 14.4)10.0 (8.9; 11.1)6.0 (5.2; 6.7)3.6 (2.9; 4.3)cDAPSA score, mean (95% CI)cDAPSA, %32.5 (30.5; 34.4)26.9 (24.9; 29.0)15.9 (14.5; 17.2)10.3 (9.0; 11.6)Remission1.0 (0.3; 2.6)4.0 (2.1; 6.7)17.8 (14.1; 22.0)37.7 (32.4; 43.2)Low6.7 (4.4; 9.7)15.0 (11.3; 19.4)33.0 (28.3; 37.9)36.5 (31.3; 42.0)Moderate38.9 (34.0; 44.0)42.6 (37.2; 48.2)34.3 (29.6; 39.2)16.9 (13.0; 21.4)High53.4 (48.2; 58.4)38.3 (33.0; 43.9)14.9 (11.6; 18.9)8.9 (6.0; 12.5)MDA2.3 (1.0; 4.3)7.7 (5.1; 11.2)27.5 (23.1; 32.1)52.2 (46.6; 57.7)VLDA0.00.9 (0.2; 2.6)6.2 (4.1; 9.0)19.7 (15.6; 24.3)HAQ-DI score1.31 (1.25; 1.37)0.93 (0.86; 1.00)0.95 (0.89; 1.02)0.53 (0.47; 0.59)PsAID-12 score6.1 (5.9; 6.3)5.1 (4.9; 5.3)4.0 (3.8; 4.3)2.7 (2.4; 2.9)EQ5D VAS score48.6 (46.6; 50.5)53.8 (51.6; 55.9)59.2 (56.9; 61.4)68.0 (65.5; 70.4)Enthesitis50.7 (45.9; 55.5)48.1 (42.8; 53.3)32.6 (28.3; 37.3)18.0 (14.1; 22.3)Dactylitis15.6 (12.4; 19.3)24.7 (20.4; 29.3)5.7 (3.8; 8.3)4.8 (2.9; 7.4)

Data are % (95% CI) unless indicated otherwise. Bold data are significantly different (non-overlapping 95% CI).

Conclusion:

These real-world data from PsABio on sex differences with biologic treatment suggest that females generally start biologics in a worse PsA state than males. Although treatment improvements were similar between sexes, females remained in worse health at 1 year, and stopped/switched biologic earlier. More comprehensive treatment before severe disease manifestations evolve may improve management in females.

Acknowledgements:

This study was funded by Janssen

Disclosure of Interests:

Irene van der Horst-Bruinsma Consultant of: AbbVie, Lilly, MSD, Novartis, UCB, Grant/research support from: AbbVie, MSD, Pfizer, UCB, Michael Nurmohamed Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Arno Van Kuijk Consultant of: AbbVie, Janssen, LEO Pharma, Novartis, Grant/research support from: Janssen, Stefan Siebert Speakers bureau: AbbVie, Amgen (previously Celgene), Biogen, Janssen, Novartis, UCB, Consultant of: AbbVie, Janssen, UCB, Grant/research support from: Amgen (previously Celgene), Boehringer Ingelheim, Bristol-Myers Squibb, GSK, Janssen, Novartis, Pfizer, UCB, Paul Bergmans Shareholder of: Johnson & Johnson, Employee of: Janssen, Kurt de Vlam Speakers bureau: AbbVie, Amgen, Eli Lilly, Novartis, UCB, Paid instructor for: Amgen, Galapagos, UCB, Consultant of: Eli Lilly, Johnson &Johnson, Novartis Galapagos, UCB, Grant/research support from: Celgene, Elisa Gremese: None declared, Beatriz Joven-Ibáñez Speakers bureau: AbbVie, Celgene, Janssen, MSD, Novartis, Pfizer, Tatiana Korotaeva Speakers bureau: AbbVie, Amgen, Biocad, Janssen, Lilly, MSD, Novartis, Novartis-Sandoz, Pfizer, UCB, Consultant of: AbbVie, Amgen, Biocad, Janssen, Lilly, MSD, Novartis, Novartis-Sandoz, Pfizer, UCB, Grant/research support from: Pfizer, Wim Noel Employee of: Janssen, Petros Sfikakis Consultant of: AbbVie, Actelion, Boehringer Ingelheim, Enorasis, Farmaserv-Lilly, Genesis, Gilead, MSD, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Faran, Janssen, Pfizer, Roche, Elke Theander Employee of: Janssen, Josef S. Smolen Speakers bureau: AbbVie, Amgen, AstraZeneca, Astro, Bristol-Myers Squibb, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Lilly, MSD, Novartis-Sandoz, Pfizer, Roche, Samsung, Sanofi, UCB, Consultant of: AbbVie, AstraZeneca, Lilly, Novartis, Roche, Laure Gossec Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Biogen, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Bioepis, Sanofi-Aventis, UCB, Grant/research support from: Amgen, Galapagos, Janssen, Lilly, Pfizer, Sandoz, Sanofi

AB0530 EFFECT OF SKIN SYMPTOMS ON DISEASE IMPACT IN PATIENTS WITH PSORIATIC ARTHRITIS RECEIVING THE IL-12/23 INHIBITOR USTEKINUMAB OR TNF INHIBITORS IN THE REAL-WORLD PSABIO STUDY

Background:

Psoriatic arthritis (PsA) is characterised by musculoskeletal symptoms, and patients (pts) with PsA usually experience psoriasis concurrently. Real-world data reflecting impact of skin symptoms on PsA disease burden are limited.

Objectives:

Analyse effectiveness of ustekinumab (UST) and tumour necrosis factor inhibitor (TNFi) therapy on extent of skin involvement, and the impact this has on PsA disease burden and drug persistence.

Methods:

PsABio (NCT02627768) is a prospective, observational study of 1st/2nd/3rd-line UST or TNFi treatment in PsA in 8 European countries. Extent of skin involvement was categorised as body surface area (BSA): clear/almost clear; <3% but not clear/almost clear; 3–10%; or >10%. Pt-reported disease impact was evaluated by PsAID-12, including assessment of two skin-related domains (D): D3 (skin problems, including itching) and D10 (embarrassment and/or shame because of appearance). Estimated persistence at 1 year was assessed across baseline (BL) BSA categories.

Results:

At BL, significantly more pts receiving UST than TNFi had BSA >10% (Figure 1). BL disease impact (PsAID-12) was worse in pts with BSA >10% than <3% in D3, D10 and total (non-overlapping 95% CIs suggest significance) (Table 1). BSA improved from BL to 1 year with both treatments. At 1 year, 64% of pts in both groups had clear/almost clear skin and only 3% had BSA >10% (Figure 1). At 1 year, both treatments significantly reduced disease impact (PsAID-12 total), and D3 and D10 scores, irrespective of BL BSA category, but most markedly in pts with higher BL BSA (Table 1). Worse BL psoriasis was generally associated with longer persistence for both treatments; however, at 1 year, pts with BSA >10% had significantly shorter persistence with TNFi (mean [95% CI]: 361 [336; 387] days) than with UST (410 [394; 426] days).

Conclusion:

In PsA, interleukin-12/23 inhibition (UST) and TNFi therapy in routine care rapidly and substantially reduced extent of skin involvement and related disease impact. Pts with highest BL skin involvement had significantly longer drug persistence with UST than with TNFi. Together, PsABio data suggest that successful treatment of skin involvement in PsA with biologics reduces disease burden and may improve persistence, especially in pts with worse BL psoriasis.

Figure 1Table 1.

PsAID-12 scores at BL and change from BL scores at 6 months and 1 year, by BL BSA category

Mean (95% CI)Domain 3(skin problems, including itching)Domain 10(embarrassment and/orshame because of appearance)Total PsAID-12USTTNFiUSTTNFiUSTTNFiPsAID-12 score at BL by BL BSA <3%4.2 (3.7; 4.8)3.1 (2.7; 3.6)3.9 (3.3; 4.4)3.1(2.6; 3.6)5.7(5.3; 6.0)5.0 (4.6; 5.3) 3–10%6.4 (5.9; 6.8)5.8 (5.3; 6.3)4.1 (3.5; 4.7)4.5 (3.9; 5.1)5.4 (5.1; 5.8)5.8 (5.4; 6.1) >10%7.9 (7.5; 8.3)6.7 (6.0; 7.5)6.1 (5.4; 6.8)5.8 (4.8; 6.8)6.2 (5.7; 6.6)6.1 (5.6; 6.7)Change from BL in PsAID-12 score at 6 months by BL BSA <3%-1.5 (-2.1; -0.9)-0.8 (-1.3; -0.3)-1.5 (-2.0; -0.9)-1.2 (-1.6; -0.7)-1.6 (-2.0; -1.2)-1.9 (-2.2; -1.5) 3–10%-3.2 (-3.8; -2.7)-2.4 (-3.0; -1.9)-1.9 (-2.5; -1.3)-2.0 (-2.5; -1.5)-2.0 (-2.4; -1.6)-2.4 (-2.8; -2.0) >10%-4.2 (-4.9; -3.6)-2.5 (-3.2; -1.9)-2.9 (-3.5; -2.2)-1.6 (-2.4; -0.8)-2.4 (-2.8; -2.0)-2.2 (-2.7; -1.7)Change from BL in PsAID-12 score at 1 year (LOCF) by BL BSA <3%-1.5 (-2.1; -0.9)-0.8 (-1.3; -0.3)-1.6 (-2.2; -1.1)-1.2 (-1.7; -0.7)-1.6 (-2.0; -1.2)-1.9 (-2.3; -1.5) 3–10%-3.5 (-4.0; -2.9)-3.2(-3.7; -2.7)-2.0 (-2.6; -1.4)-2.5 (-3.0; -2.0)-2.2 (-2.6; -1.7)-3.0 (-3.4; -2.6) >10%-4.9 (-5.5; -4.3)-3.1 (-4.0; -2.3)-3.5 (-4.2; -2.8)-2.7 (-3.7; -1.8)-2.9 (-3.4; -2.4)-2.9 (-3.5; -2.2)

PsAID-12 total score ≤4 is considered a patient-acceptable symptom state.

BL, baseline; BSA, body surface area; CI, confidence interval; LOCF, last observation carried forward; PsAID-12, 12-item Psoriatic Arthritis Impact of Disease questionnaire; TNFi, tumour necrosis factor inhibitor; UST, ustekinumab

Acknowledgements:

This study was funded by Janssen.

Disclosure of Interests:

Josef S. Smolen Speakers bureau: AbbVie, Amgen, AstraZeneca, Astro, Bristol-Myers Squibb, Celgene, Celltrion, Chugai, Gilead, ILTOO, Janssen, Lilly, MSD, Novartis- Sandoz, Pfizer, Roche, Samsung, Sanofi, UCB, Grant/research support from: AbbVie, AstraZeneca, Lilly, Novartis, Roche, Tatiana Korotaeva Speakers bureau: AbbVie, Amgen, Biocad, Janssen, Lilly, MSD, Novartis, Novartis-Sandoz, Pfizer, UCB, Consultant of: AbbVie, Amgen, Biocad, Janssen, Lilly, MSD, Novartis, Novartis-Sandoz, Pfizer, UCB, Grant/research support from: Pfizer, Michael Nurmohamed Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Menarini, MSD, Mundipharma, Pfizer, Roche, Sanofi, UCB, Stefan Siebert Speakers bureau: AbbVie, Amgen (previously Celgene), Biogen, Janssen, Novartis, UCB, Consultant of: AbbVie, Janssen, UCB, Grant/research support from: Amgen (previously Celgene), Boehringer Ingelheim, Bristol-Myers Squibb, GSK, Janssen, Novartis, Pfizer, UCB, Paul Bergmans Shareholder of: Johnson & Johnson, Employee of: Janssen, Kurt de Vlam Speakers bureau: AbbVie, Amgen, Eli Lilly, Novartis, UCB, Paid instructor for: Amgen, Galapagos, UCB, Consultant of: Eli Lilly, Galapagos, Johnson & Johnson, Novartis, UCB, Grant/research support from: Celgene, Elisa Gremese: None declared., Beatriz Joven-Ibáñez Speakers bureau: AbbVie, Celgene, Janssen, Novartis, MSD, Pfizer, Wim Noel Employee of: Janssen, Petros Sfikakis Consultant of: AbbVie, Actelion, Boehringer Ingelheim, Enorasis, Farmaserv-Lilly, Genesis, Gilead, MSD, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Faran, Janssen, Pfizer, Roche, Elke Theander Employee of: Janssen, Laure Gossec Consultant of: AbbVie, Amgen, Bioepis, Biogen, Bristol-Myers Squibb, Celgene, Galapagos, Gilead, Janssen, Lilly, Novartis, Pfizer, Samsung Sanofi-Aventis, UCB, Grant/research support from: Amgen, Galapagos, Janssen, Lilly, Pfizer, Sandoz, Sanofi.

POS0660 CONCOMITANT USE OF STATINS IN FILGOTINIB-TREATED PATIENTS WITH RHEUMATOID ARTHRITIS

Background:

The Janus kinase-1 preferential inhibitor filgotinib (FIL) improved rheumatoid arthritis (RA) signs and symptoms in phase (P)3 trials.1–3 RA elevates cardiovascular disease risk; statins are used to reduce risk.

Objectives:

To assess safety of statin and filgotinib coadministration across the clinical program.

Methods:

Patients (pts) meeting 2010 ACR/EULAR RA criteria in P2 DARWIN 1–2 (D1–2; NCT01888874, NCT01894516), P3 FINCH 1–3 (F1–3; NCT02889796, NCT02873936, NCT02886728), and long-term extensions DARWIN 3 and FINCH 4 (D3, F4; NCT02065700, NCT03025308) receiving FIL 100 mg (FIL100) QD, FIL 200 mg QD (FIL200), adalimumab (ADA), methotrexate (MTX), or placebo (PBO) were included. Events related to statin use were analysed as exposed by treatment received. N and % were provided.

Week (W)12 PBO-controlled safety analysis included pts receiving FIL100, FIL200, or PBO for ≤12W (D1–2, F1–2); as-treated safety analysis included pts receiving long-term FIL100 QD (n=1647), FIL200 QD (n=2267), ADA (n=325), MTX (n=416), or PBO (n=781) (D1–3, F1–4); P3 as-randomised analysis included data up to W52 (F1–3) per assigned treatment.

Results:

In each arm, similar proportions of pts took statins at baseline (9.4%–11.9%); initiation during study was low (1.2%–6.8%). Through W12 in PBO-controlled analysis, mean creatine phosphokinase (CPK; Figure 1), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) levels were similar regardless of statin use and remained within normal levels across all arms.

Mean baseline ALT and AST levels were 20–23 and 20–22 U/L, respectively; at W12, ALT and AST ranged from 22–24 and 20–25 U/L, respectively. Graded CPK, ALT, and AST elevations are in Table 1.

Table 1.

Graded laboratory abnormalities at week 12 by baseline statin use in PBO-controlled analysis

ConcomitantNoneFIL200(n=68)FIL100(n=95)PBO(n=93)FIL200 (n=709)FIL100(n=693)PBO(n=688)CPK increased*598281562549537G1 (≤2.5×ULN)10 (16.9)13 (15.9)6 (7.4)71 (12.6)47 (8.6)18 (3.4)G2 (>2.5 to 5×ULN)3 (5.1)006 (1.1)2 (0.4)3 (0.6)G3 (>5 to 10×ULN)0001 (0.2)03 (0.6)G4 (>10×ULN)0001 (0.2)2 (0.4)0AST increased**689492708692684G1 (≤3.0×ULN)9 (13.2)11 (11.7)7 (7.6)97 (13.7)79 (11.4)60 (8.8)G2 (>3.0 to 5.0×ULN)0003 (0.4)2 (0.3)3 (0.4)G3 (>5.0 to 20.0×ULN)01 (1.1)02 (0.3)00G4 (>20.0×ULN)000000ALT increased**689492708692684G1 (≤3.0×ULN)13 (19.1)14 (14.9)13 (14.1)98 (13.8)92 (13.3)72 (10.5)G2 (>3.0 to 5.0×ULN)02 (2.1)010 (1.4)5 (0.7)6 (0.9)G3 (>5.0 to 20.0×ULN)0001 (0.1)01 (0.1)G4 (>20.0×ULN)000000

Data are n (%). Grading per Common Terminology Criteria for Adverse Events v4.03

*FINCH 1–2

**DARWIN 1–2, FINCH 1–2

ALT, alanine aminotransferase; AST, aspartate aminotransferase; CPK, creatine phosphokinase; csDMARD, conventional synthetic disease-modifying antirheumatic drug; FIL200/100, filgotinib 200/100 mg + csDMARDs; Grade, G; PBO, placebo; ULN, upper limit of normal.

In the long-term as-treated analysis, 1 (0.5%)/6 (3.2%)/0/0/0 treatment-emergent adverse events (AE) of myalgia occurred in pts on statins at baseline receiving FIL200/FIL100/ADA/MTX/PBO and in 12 (0.6%)/8 (0.5%)/3 (1.0%)/2 (0.5%)/1 (0.1%) pts not on statins. Muscle spasms occurred in 2 (0.9%)/3 (1.6%)/1 (3.2%)/0/1 (1.1%) pts on statins at baseline receiving FIL200/FIL100/ADA/MTX/PBO and 21 (1.0%)/8 (0.5%)/0/3 (0.8%)/1 (0.1%) pts not on statins at baseline. One patient not on statins receiving FIL200 reported rhabdomyolysis. For all treatment arms in P3 as-randomised analysis, mean LDL and HDL increased similarly from baseline (108–110 and 56–59 mg/dL, respectively) to W52 (119–130 and 59–71 mg/dL, respectively).

Conclusion:

No increases in statin-induced AEs such as muscle or liver toxicities occurred with statins and filgotinib coadministration; results are supported by a drug-drug interaction study.4 Mean LDL and HDL increased at W52 in all treatment arms.

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]Anderson et al. EULAR 2021 abstract.

Disclosure of Interests:

Peter C. Taylor Consultant of: AbbVie, Biogen, Eli Lilly, Fresenius, Galapagos, Gilead, GlaxoSmithKline, Janssen, Nordic Pharma, Pfizer, Roche, BMS, Sanofi, Celltrion, and UCB, Grant/research support from: Celgene, Eli Lilly, Galapagos, and Gilead, Christina Charles-Schoeman Consultant of: Gilead, Pfizer, and Regeneron-Sanofi, Grant/research support from: AbbVie, Bristol-Myers Squibb and Pfizer Inc, Muhsen Alani Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Mona Trivedi Shareholder of: Gilead Sciences, Inc., Employee of: Gilead Sciences, Inc., Vanessa Castellano 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., Sander Strengholt Shareholder of: Galapagos BV, Employee of: Galapagos BV, Michael Nurmohamed Speakers bureau: AbbVie, Bristol-Myers Squibb, Eli Lilly, Roche, and Sanofi, Consultant of: AbbVie, Celgene, Celltrion, Eli Lilly, Janssen, and Sanofi, Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, MSD, Mundipharma, Novartis, Pfizer, Roche, and Sanofi, Gerd Rüdiger Burmester Speakers bureau: AbbVie, Eli Lilly, Pfizer, and Gilead Sciences, Inc., Consultant of: AbbVie, Eli Lilly, Pfizer, and Gilead Sciences, Inc.

OP0018 A MULTICENTER RANDOMIZED STUDY IN EARLY RHEUMATOID ARTHRITIS TO COMPARE ACTIVE CONVENTIONAL THERAPY VERSUS THREE BIOLOGICAL TREATMENTS: 24 WEEK EFFICACY RESULTS OF THE NORD-STAR TRIAL

Background:

The optimal first-line treatment of patients (pts) with early rheumatoid arthritis (RA) is yet to be established.

Objectives:

The primary aim was to assess and compare the proportion of pts who achieved remission with active conventional therapy (ACT) and with three different biologic therapies after 24 wks. Secondary aims were to assess and compare other efficacy measures.

Methods:

The investigator-initiated NORD-STAR trial (NCT01491815) was conducted in the Nordic countries and Netherlands. In this multicenter, randomized, open-label, blinded-assessor study pts with treatment-naïve, early RA with DAS28>3.2, and positive RF or ACPA, or CRP >10mg/L were randomized 1:1:1:1. Methotrexate (25 mg/week after one month) was combined with: 1) (ACT): oral prednisolone (tapered quickly);or: sulphasalazine, hydroxychloroquine and mandatory intra-articular (IA) glucocorticoid (GC) injections in swollen joints <wk 20; 2) certolizumab 200 mg EOW SC (CZP); 3) abatacept 125 mg/wk SC (ABA); tocilizumab 162 mg/wk SC (TCZ). IA GC was allowed in all arms <wk 20. Primary outcome was clinical disease activity index remission (CDAI≤2.8) at wk 24. Secondary outcomes included CDAI remission over time and other remission criteria. Dichotomous outcomes were analyzed by adjusted logistic regression with non-responder imputation (NRI). Non-inferiority analyses had a pre-specified margin of 15%.

Results:

812 pts were randomized. Age was 54.3±14.7 yrs (mean±SD), 31.2% were male, DAS28 5.0±1.1, 74.9% were RF and 81.9% ACPA positive. Fig 1 shows the adjusted CDAI remission rates over time with 95% CI. Table shows crude remission and response rates and absolute differences in adjusted remission and response rates (superiority analysis). Differences in remission and response rates with CZP and TCZ, but not with ABA, remained within the pre-defined non-inferiority margin versus ACT, Fig 2.

Figure 1.

CDAI remission over time (adj. estimates with 95% CI)

Figure 2.

Non-inferiority analysis of protocol population. Estimated differences in CDAI remission rates between Arm 1 (active conventional therapy) and Arms 2, 3, and 4 (biologic arms) as reference with 95% confidence intervals, adjusted for gender, ACPA status, country, age, body-mass index and baseline DAS28-CRP. ABA, abatacept; CZP, certolizumab-pegol; MTX, methotrexate; TCZ, tocilizumab.

Conclusion:

High remission rates were found across all four treatment arms at 24 wks. Higher CDAI remission rate was observed for ABA versus ACT (+9%) and for CZP (+4%), but not for TCZ (-1%). With the predefined 15% margin, ACT was non-inferior to CZP and TCZ, but not to ABA. This underscores the efficacy of active conventional therapy based on MTX combined with glucocorticoids and may guide future treatment strategies for early RA.

Table.

Primary and key secondary outcomes at 24 weeks (ITT)

Active conventional therapy (ACT)Certolizumab+MTXAbatacept+MTXTocilizumab+MTXNo of pts (ITT)200203204188§Crude remission and response ratesCDAI remission42.0%47.8%52.5%41.0%ACR/EULAR Boolean remission34.0%38.4%37.3%31.4%DAS28 remission63.5%68.5%69.6%63.3%SDAI remission41.5%49.8%51.5%42.6%EULAR good response71.5%76.9%79.9%71.3%Difference (95% CI) in rates with Arm 1 as reference (adjusted)CDAI remissionRef4% (-5 to 13%)9% (0.1 to 19%)-1% (-10 to 9%)ACR/EULAR Boolean remissionRef4% (-6 to 13%)5% (-5 to 14%)-4% (-13 to 6%)DAS28 remissionRef3% (-6 to 11%)5% (-4 to 13%)-1% (-10 to 8%)SDAI remissionRef6% (-3 to 18%)9% (-0.3 to 18%)1% (-8 to 11%)EULAR good responseRef4% (-4 to 14%)8% (-2 to 18%)0.4% (-10 to 11%)

§17 patients allocated to Tocilizumab did not receive it due to its unavailability and were excluded from ITT.

Acknowledgments:

Manufacturers provided CZP and ABA.

Disclosure of Interests:

Merete L. Hetland Grant/research support from: BMS, MSD, AbbVie, Roche, Novartis, Biogen and Pfizer, Consultant of: Eli Lilly, Speakers bureau: Orion Pharma, Biogen, Pfizer, CellTrion, Merck and Samsung Bioepis, Espen A Haavardsholm Grant/research support from: AbbVie, UCB Pharma, Pfizer Inc, MSD Norway, Roche Norway, Consultant of: Pfizer, AbbVie, Janssen-Cilag, Gilead, UCB Pharma, Celgene, Lilly, Paid instructor for: UCB Pharma, Speakers bureau: Pfizer, AbbVie, UCB Pharma, Celgene, Lilly, Roche, MSD, Anna Rudin Consultant of: Astra/Zeneca, Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Björn Gudbjornsson Speakers bureau: Novartis and Amgen, Jon Lampa Speakers bureau: Pfizer, Janssen, Novartis, Kim Hørslev-Petersen: None declared, Till Uhlig Consultant of: Lilly, Pfizer, Speakers bureau: Grünenthal, Novartis, Gerdur Gröndal: None declared, Mikkel Ǿstergaard Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Merck, and Novartis, Consultant of: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Speakers bureau: AbbVie, Bristol-Myers Squibb, Boehringer Ingelheim, Celgene, Eli Lilly, Hospira, Janssen, Merck, Novartis, Novo Nordisk, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, and UCB, Marte Heiberg: None declared, Jos Twisk: None declared, Simon Krabbe: None declared, Kristina Lend: None declared, Inge Olsen: None declared, Joakim Lindqvist: None declared, Anna-Karin H Ekwall Consultant of: AbbVie, Pfizer, Kathrine L. Grøn Grant/research support from: BMS, Meliha C Kapetanovic: None declared, Francesca Faustini: None declared, Riitta Tuompo: None declared, Tove Lorenzen: None declared, Giovanni Cagnotto: None declared, Eva Baecklund: None declared, Oliver Hendricks Grant/research support from: Pfizer, MSD, Daisy Vedder: None declared, Tuulikki Sokka-Isler: None declared, Tomas Husmark: None declared, Maud-Kristine A Ljosa: None declared, Eli Brodin: None declared, Torkell Ellingsen: None declared, Annika Soderbergh: None declared, Milad Rizk Speakers bureau: AbbVie, Åsa Reckner: None declared, Per Larsson: None declared, Line Uhrenholt Speakers bureau: Abbvie, Eli Lilly and Novartis (not related to the submitted work), Søren Andreas Just: None declared, David Stevens: None declared, Trine Bay Laurberg Consultant of: UCB Pharma (Advisory Board), Gunnstein Bakland Consultant of: Novartis, UCB, Ronald van Vollenhoven Grant/research support from: BMS, GSK, Lilly, UCB, Pfizer, Roche, Consultant of: AbbVie, AstraZeneca, Biogen, Biotest, Celgene, Gilead, Janssen, Pfizer, Servier, UCB, Speakers bureau: AbbVie, Pfizer, UCB

OP0209 INTERVAL PROLONGATION IN ETANERCEPT-TREATED PATIENTS WITH RHEUMATOID ARTHRITIS, ANKYLOSING SPONDYLITIS OR PSORIATIC ARTHRITIS: AN OPEN-LABEL, RANDOMISED CONTROLLED TRIAL

Background:

The majority of patients with a rheumatic disease treated with etanercept may be overexposed. Data regarding etanercept tapering is scarce, particularly in psoriatic arthritis (PsA) and ankylosing spondylitis (AS). Dose reductions can potentially reduce blood drug levels too much, resulting in loss of effect.

Objectives:

We compared extending the dose interval to continuation of the standard dose and studied the success rate of etanercept discontinuation. Etanercept concentrations were measured throughout the study.

Methods:

160 consecutive patients with rheumatoid arthritis (RA), PsA or AS with sustained minimal disease activity (MDA) were enrolled in this 18-month, open-label, randomised controlled trial. The intervention group doubled the dosing-interval at baseline and discontinued etanercept 6 months later. The control group continued the standard dose up to 6 months, after which the dosing-interval was doubled. Primary outcome was the proportion of patients maintaining MDA after 6 months follow-up.

Results:

At 6 months, MDA status was maintained in 47 (63%) patients in the intervention group and 56 (74%) in the control group (p=0.15), with comparable results in all rheumatic diseases. Median etanercept concentrations decreased from 1.50 µg/mL (25-75thpercentile 1.06-2.65) to 0.46 µg/mL (0.28-0.92) after 6 months of interval prolongation (figure 1). In total, 40% discontinued etanercept successfully with maintained MDA for at least 6 months.

Figure 1.

Median (with Q1 to Q3 boxplots) etanercept concentrations (per protocol) during the first 6 months of follow-up in the intervention group (prolongation; gray boxplots) and the control group (continuation; white boxplots), separated by disease (RA, PsA, AS). Bars represent 10-90 percentile and outliers are shown separately (dots).

Conclusion:

As observed in RA, etanercept tapering can be safely attempted in PsA and AS patients in sustained MDA. A substantial proportion of patients could stop etanercept for at least 6 months. In many patients low drug concentrations proved sufficient to control disease activity. However, the risk of minor and major flares is substantial, even in patients continuing standard dosing.

References:

none

Disclosure of Interests:

Merel J. l’Ami Speakers bureau: Novartis, Jill Ruwaard: None declared, Eva L. Kneepkens: None declared, Charlotte L.M. Krieckaert: None declared, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Femke Hooijberg: None declared, J.C. van Denderen: None declared, Arno Van Kuijk: None declared, Lot Burgemeister: None declared, Maarten Boers: None declared, Gert-Jan Wolbink: None declared

AB0230 STATINS TO PREVENT RHEUMATOID ARTHRITIS: INCONCLUSIVE RESULTS OF THE STAPRA TRIAL

Background:

Persons at high risk for developing rheumatoid arthritis (RA) may benefit from a low-risk pharmacological intervention aimed at primary prevention. Statins are safe and widely-used drugs; previous studies demonstrated disease-modifying effects of statins in RA patients1as well as an association between statin use and a decreased risk of RA development2.

Objectives:

We designed a multi-center, randomized, double-blind, placebo-controlled trial to investigate if atorvastatin use for 3 years could prevent arthritis.

Methods:

Persons at high risk for RA, defined by the presence of arthralgia and anti-citrullinated protein antibody (ACPA) concentration >3xULN or both ACPA and rheumatoid factor (RF), were randomized to atorvastatin 40 mg daily or placebo for 3 years. Eligible participants were ≥18 years, had no indication for lipid-lowering therapy and had no clinical synovitis. The primary endpoint was development of clinical arthritis. Our goal was to include 220 patients, based on an anticipated 30% risk reduction by atorvastatin. Analysis was by intention-to-treat.

Results:

189 patients were screened, 175 were eligible, but only 67 persons were included of whom 62 were randomized (figure 1). The main reason for non-inclusion was unwillingness to use study medication (n=58, 54%). Inclusion was stopped after 38 months due to the low inclusion rate. Analyses were performed 1 year after inclusion stop. Mean follow up was 18 (0-36) months. Mean age was 48 years and 74% of participants were female. 14 persons (23%) developed clinical arthritis: 8/31 (26%) in the atorvastatin group and 6/31 (19%) in the placebo group (HR 0.8, 95% CI 0.3-2.2) after a median period of 7.5 (IQR 5.3-21.8) months (atorvastatin) and 4 (0-14.8) months (placebo). In the atorvastatin group, 17 persons completed the study according to protocol, 6 dropped out and 8 continued follow-up after prematurely stopping study medication. In the placebo group, 16 persons completed the study according to protocol, 11 dropped out and 4 continued follow-up after prematurely stopping study medication. Median duration of study medication use was 9 (6-26) months (atorvastatin group) and 8 (3-17) months (placebo group).

Conclusion:

The results of this trial are inconclusive due to severe difficulties with patient inclusion and low treatment adherence. The difficulty to enter and retain participants in this prevention trial is highly relevant given the current interest in treating RA in an ever earlier phase. At-risk individuals’ perceptions should be taken into account when designing preventive trials and will be important in optimizing acceptance and adherence to preventive treatment. Currently we are finalizing research into the motivation and barriers for participation in different primary prevention trials of RA and the willingness to initiate different types of preventive treatment in individuals in the at-risk phase of RA.

References:

[1]McCary et al. Lancet. 2004; 19;363(9426):2015-21

[2]Chodick G et al. PLoS Med. 2010;7(9):e1000336

Disclosure of Interests:

Laurette van Boheemen: None declared, S.A. Turk: None declared, M.H. van Beers - Tas: None declared, W.H. Bos Grant/research support from: abbvie, sanofi, roche, celgene, ucb, novartis, Speakers bureau: abbvie, Sanofi, eli lilly, Diane Marsman: None declared, E.N. Griep: None declared, M. Starmans: None declared, C.D. Popa: None declared, A.M. van Sijl: None declared, Maarten Boers: None declared, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Dirkjan van Schaardenburg: None declared

AB1080 OPTICAL SPECTRAL TRANSMISSION IMAGING SCORES DECREASE AFTER ONE MONTH OF BIOLOGICAL THERAPY, ESPECIALLY IN RHEUMATOID ARTHRITIS PATIENTS WHO RESPOND TO THERAPY

Background:

Optical spectral transmission imaging (OST) is a new imaging method that measures inflammation in the hands of rheumatoid arthritis (RA) patients. OST might be used to assess disease activity instead of disease activity score 28 (DAS28) or ultrasonography (US). The advantage of OST is that it is fast and not operator dependent. Up to now OST has only been investigated cross-sectionally and it is unknown if and to what extent OST can detect inflammatory changes due to anti-inflammatory treatment for RA.

Objectives:

To compare OST measurements before and after 1 month of biological treatment for RA and to compare these OST changes with changes on US and disease activity.

Methods:

The HandScan device from Hemics, the Netherlands, was used to measure OST scores for 13 RA patients before and after 1 month of anti-inflammatory therapy. Treatment included tumor necrosis factor inhibitor (n=10), tocilizumab (n=2) and tofacitinib (n=1). OST scores range from 0-66 (one score for both hands) and are based on bilateral wrist, MCP and PIP joints. US was performed in the same joints as OST and semi-quantitatively scored on a scale of 0-3 for grey-scale (GS) synovitis and power Doppler (PD) signal. Joint scores of GS synovitis or PD were summed, resulting is a total GS synovitis score and a total PD score, both also ranging from 0-66. Furthermore, tender joint count 28 (TJC28), swollen joint count 28 (SJC28), DAS28, C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were determined. Response to therapy was defined as achieving the minimal clinically interesting improvement of DAS28 (DAS28 difference after 1 month > -1) as proposed by Ward et al. [1]

Results:

Baseline OST was 17.73 ± 6.10 and this significantly decreased to 16.01 ± 6.68 (difference -1.71, 95%CI 0.05-3.38, p=0.045) after 1 month of therapy. This decrease was only present in patients who responded to therapy (n=8; OST decreased from 17.24 ± 5.98 to 14.26 ± 5.65, p=0.01) and not in non-responders (n=5; OST increased from 18.52 ± 6.90 to 18.83 ± 7.87, p=0.03).

In the total group, also DAS28 (difference -1.59, 95%CI 0.74-2.45, p=0.002), SJC28 (difference 4.62, 95%CI 1.50-7.73, p=0.007), ESR (Wilcoxon Rank p=0.008) and CRP (Wilcoxon Rank p=0.03) significantly decreased after 1 month of therapy, but TJC28 did not (difference 2.62, 95%CI -2.7-7.91, p=0.30).

OST change after 1 month of therapy significantly correlated with TCJ28 change (table 1). For GS synovitis the correlation coefficient nearly reached statistical significance. Changes in all other disease activity parameters were not correlated with OST change.

Table 1.

Correlation of change in OST measurement with change in disease activity after 1 months of anti-inflammatory therapy

Spearman rp-valueTotal GS synovitis0.540.06Total PD0.220.47DAS280.350.25SJC280.290.33TJC280.630.02ESR-0.420.15CRP-0.230.45

Conclusion:

OST scores significantly decreased after 1 month of anti-inflammatory therapy and only in the RA group that responded well to this therapy. This indicates that OST is capable of detecting therapy induced inflammatory changes in the hands of RA patients. Larger studies are needed to further assess the monitoring value of OST for therapy efficacy in RA patients.

References:

[1]Ward et al. 2015 Clinically important changes in individual and composite measures of rheumatoid arthritis activity: thresholds applicable in clinical trials. Ann Rheum Dis 74(9): p. 1691-6.

Disclosure of Interests:

Annelies Blanken: None declared, C.J. van der Laken: None declared, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research

AB0238 SERUM LEVELS OF E-SELECTIN AND IL-8 DECREASE AFTER 6 MONTHS OF ANTI-INFLAMMATORY THERAPY AND MIRROR FAVORABLE VASCULAR CHANGES IN RHEUMATOID ARTHRITIS

Background:

Accelerated atherosclerosis is a systemic manifestation of rheumatoid arthritis (RA). E-selectin, VCAM-1, MCP1/CCL2 and IL-8/CXCL8 are involved in leukocyte migration through endothelial cells in both atherosclerosis and RA [1]. Therefore, these endothelial function markers might reflect endothelial function and systemic inflammation in RA. If so, such a marker could be used to assess cardiovascular risk in RA patients.

Objectives:

The aim of this study was to investigate the effect of 6 months of anti-inflammatory treatment on RA serum levels of endothelial function markers and whether these serum levels are related to prognostic imaging markers for atherosclerosis.

Methods:

E-selectin, VCAM-1, MCP1 and IL-8 serum levels were determined at baseline and after 6 months of therapy with MTX monotherapy or in combination with adalimumab for 40 RA patients and 19 osteoarthritis (OA) controls using commercial ELISA kits. Prognostic imaging markers for atherosclerosis were pulse wave velocity (PWV) and augmentation index (AIx) as measured with SphygmoCor tonometry. Parametric analyses were used for E-selectin, VCAM-1 and MCP1 and non-parametric or parametric analyses after log transformation for IL-8.

Results:

Baseline VCAM-1 and IL-8 were significantly higher for RA patients than OA controls with and without adjustment for age and sex or traditional risk factors (table 1).

Table 1.

Comparison between RA and OA serum levels of endothelial function markers at baseline

OARACrude analysisAdjusted age sexAdjusted traditional risk factors*Mean ±SD or median (IQR)Mean ±SD or median (IQR)Difference OA and RA (95%CI)pDifference OA and RA (95%CI)pDifference OA and RA (95%CI)PE-selectin (ng/ml)29 ±1532 ±173 (-6-12)0.493 (-6-12)0.533 (-7-13)0.54VCAM-1 (ng/ml)786 ±102897 ±200110 (13-208)0.03103 (4-202)0.04110 (2-218)0.05MCP1 (pg/ml)248 ±248316 ±16568 (-15-150)0.1171 (-10-152)0.0949 (-41-138)0.28IL-8 (pg/ml)15 (10-25)37 (17-117)n/a0.01n/a0.01n/a0.02

* Age, hypertension, bmi and pack years

After 6 months of anti-inflammatory therapy, E-selectin and IL-8 serum levels significantly decreased (table 2). This decrease was especially present in the RA patients with good EULAR-DAS28 response to the medication and not in patients with no/moderate response (E-selectin: -7, 95%CI -13- -2, p=0.007 versus -0.1, 95%CI -3-2, p=0.925; IL-8: -2, p=0.033 versus -1, p=0.267).

Table 2.

Endothelial function markers difference after 6 months of therapy in RA patients

Difference (95%CI)p-valueE-selectin (ng/ml)-4 (-7-1)0.010VCAM-1 (ng/ml)+10 (-56-77)0.753MCP1 (pg/ml)-14 (-34-62)0.557IL-8 (pg/ml)-11 (n/a)0.014

Furthermore, in the RA patients we found a significant correlation between the difference in PWV after 6 months and the difference in E-selectin (Pearson r=0.450, p=0.018) and IL-8 (Spearman r=0.401, p=0.038). All other possible correlations of the endothelial function markers with PWV and AIx were not significant (data not shown).

Conclusion:

Serum levels of E-selectin and IL-8 decreased after 6 months of anti-inflammatory therapy, and both correlated with the PWV changes. This is the first study investigating both serologic as well as imaging markers of endothelial function and atherosclerosis in RA patients undergoing anti-inflammatory therapy. Our study suggests that E-selectin and IL-8 circulatory levels may reflect the best both systemic inflammation as well as endothelial function in RA, and might be therefore useful in the future as markers of cardiovascular risk in these patients.

References:

[1]Haringman et al. Targeting cellular adhesion molecules, chemokines and chemokine receptors in rheumatoid arthritis. Expert Opin Emerg Drugs, 2005. 10(2): p. 299-310.

Disclosure of Interests:

Annelies Blanken: None declared, Rabia Agca: None declared, C.D. Popa: None declared, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research

OP0268-HPR RHEUMATIC DISEASE PATIENTS’ PREFERENCES IN ADVERSE DRUG REACTION INFORMATION REGARDING BIOLOGICS

Background:

Patient-reported outcomes (PROs) are increasingly used in studies and medical practice to obtain information on patients’ perspectives towards their treatment or disease. However, study outcomes are primarily directed at and shared with healthcare professionals, even though the results may also be relevant for patients.

Objectives:

The objective of this study was to obtain insight in which results patients with immune-mediated inflammatory diseases (IMIDs), including inflammatory rheumatic disease patients, prefer to receive after participating in the Dutch Biologic Monitor.

Methods:

The Dutch Biologic Monitor is a PRO-based prospective cohort event monitoring study focused on adverse drug reactions (ADRs) [1]. A survey was conducted among the participants of the Dutch Biologic Monitor who wanted to be informed about the results. Patients’ preferences were identified using twelve statements and rated with five-point Likert-type scales. Averages described the preference per statement. Preference for the results per IMID or altogether was assessed using Mann-Whitney U Test.

Results:

Respondents (N=591, response rate 67.6%) preferred results per IMID over aggregated results (p=<0.001). Information on whether patients with the same IMID experience ADRs (average 4.5), which biologics are most likely to cause ADRs (4.4) and whether the ADRs subside or disappear (4.4) were regarded as most interesting. Outcomes of patients with other IMIDs (3.5), patient characteristics (3.7) and injection site reactions (3.8) were least interesting.

Table 1.

Respondent characteristics.

CharacteristicsAllInflammatory rheumatic disease patients(n=591)(%)(n=453)(%)Female gender,n(%)353(59.7)286(63.1)Age, median (IQR), years59.0(51.0-67.0)60.0(51.0-67.5)BiologicsAdalimumab220(37.2)164(36.2)Etanercept196(33.2)189(41.7)Infliximab43(7.3)8(1.8)Tocilizumab21(3.6)17(3.8)Ustekinumab21(3.6)7(1.5)Other90(15.2)68(15.0)Combination therapyMethotrexate195(33.0)183(40.4)Corticosteroids65(11.0)51(11.3)Thiopurines41(6.9)10(2.2)No combination therapy231(39.1)157(34.7)Other123(20.8)106(23.4)Indications for biologic therapyRheumatoid arthritis277(46.9)277(61.1)Psoriatic arthritis111(18.8)111(24.5)Ankylosing spondylitis/axSpA83(14.0)83(18.3)Other159(26.9)17(3.8)

IQR: interquartile range; axSpA: axial spondyloarthritis.

Figure 1.

The preferences of patients on the communication of the reported adverse drug reaction information resulting from the Dutch Biologic Monitor.

Conclusion:

Participants of the Dutch Biologic Monitor that use a biologic for their IMID prefer to receive ADR information tailored to their own biologic and IMID. Furthermore, they want to obtain insight in the course of ADRs. Therefore, we advocate to generate disease-specific information on ADRs for IMID patients.

References:

[1]Kosse LJ, Jessurun NT, Hebing RCF, Huiskes VJB, Spijkers KM, van den Bemt BJF, et al. Patients with inflammatory rheumatic diseases: quality of self-reported medical information in a prospective cohort event monitoring system.Rheumatol.published on 30 Sept 2019. doi: 10.1093/rheumatology/kez412.

Disclosure of Interests:

Gerda Weits: None declared, Leanne Kosse: None declared, Harald Vonkeman: None declared, Phyllis Spuls Grant/research support from: Departmental independent research grant for TREAT NL registry LeoPharma December 2019; Contract support: I am involved in performing clinical trials with many pharmaceutical industries that manufacture drugs used for the treatment of e.g. psoriasis and atopic dermatitis for which we get financial compensation paid to the department/hospital, Consultant of: Consultancies in the past for Sanofi 111017 and AbbVie 041217 (unpaid), Bart van den Bemt Grant/research support from: UCB, Pfizer and Abbvie, Consultant of: Delivered consultancy work for UCB, Novartis and Pfizer, Speakers bureau: Pfizer, AbbVie, UCB, Biogen and Sandoz., Sander Tas: None declared, Frank Hoentjen Grant/research support from: Received grants from Dr Falk, Janssen-Cilag, and AbbVie., Consultant of: Served on advisory boards, or as speaker or consultant for AbbVie, Celgene, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz, and Dr Falk, Speakers bureau: Served on advisory boards, or as speaker or consultant for AbbVie, Celgene, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz, and Dr Falk, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Martijn van Doorn Grant/research support from: Unrestricted grants, advisory board, speaker fees and/or other (investigator) from Novartis, Abbvie, Janssen Cilag, Leopharma and Pfizer, Speakers bureau: Unrestricted grants, advisory board, speaker fees and/or other (investigator) from Novartis, Abbvie, Janssen Cilag, Leopharma and Pfizer, Eugène van Puijenbroek: None declared, Naomi Jessurun: None declared

AB1320-HPR THE ASSOCIATION BETWEEN PHYSICAL ACTIVITY AND CARDIORESPIRATORY FITNESS IN PATIENTS WITH RHEUMATOID ARTHRITIS AND HIGH CARDIOVASCULAR RISK

Background:

Rheumatoid arthritis (RA) is associated with increased risk of cardiovascular disease (CVD) disease and CV mortality1. High values of cardiorespiratory fitness (CRF) are protective against CVD and CV mortality2. Physical activity levels in patients with RA are low. Knowledge on whether physical activity is associated with CRF in patients with RA and high CV risk is scarce. This knowledge is important because improving the level of physical activity could improve CRF and lower CV risk in this group of patients with RA and high CV risk. However, it is unclear whether physical activity is associated with CRF in this group of patients. This study presents the preliminary results at baseline of the association of physical activity with CRF from an ongoing pilot study aimed at improving CRF through exercise therapy in patients with RA and high CV risk.

Objectives:

To determine (i) the level of physical activity in patients with RA and high CV risk and (ii) whether physical activity is associated with CRF in patients with RA and high CV risk.

Methods:

Patients with RA and high CV risk participated in this pilot study. Increased 10-year risk of CV mortality was determined by using the Dutch SCORE-table. Anthropometrics and disease characteristics were collected. Physical activity was assessed with an Actigraph accelerometer to determine the number of steps and intensity of physical activity expressed in terms of sedentary, light, and moderate-to-vigorous time per day. Participants wore the accelerometer for seven days. A minimum of four measurement days with a wear time of at least 10 hours was required. The VO2max measured with a graded maximal exercise test was used to determine the CRF. Pearson correlation coefficients were calculated for the associations between the different measures of physical activity and VO2max. For the variables that were associated, linear regression analysis was carried out, with pain and disease activity as possible confounders.

Results:

Thirteen females and five males were included in the study. The mean age was 66.5 (± 15.0) years. Only 22% of the patients met public health physical activity guidelines for the minimal amount of 150 minutes a week. The mean step count was 6237 (± 2297) steps per day and mean moderate-to-vigorous physical activity time was 16.50 (± 23.56) minutes per day. The median VO2max was 16.23 [4.63] ml·kg-1·min-1, which is under the standard. Pearson correlations showed a significant positive association for step count with VO2max. No associations were found for sedentary, light, and moderate-to-vigorous physical activity with VO2max. The significant association between step count and VO2max(p = 0.01) was not confounded by disease severity and pain.

Discussion:

Since better CRF protects against CVD, increasing daily step count may be a simple way to reduce the risk of CVD in patients with RA and high CV risk. However, these results need to be confirmed in a larger study group. Future research should investigate if improving daily step count will lead to better CRF levels and ultimately will lead to a reduction in CV risk in patients with RA and high CV risk.

Conclusion:

Physical activity levels of patients with RA and high CV risk do not meet public health requirements for physical activity criteria and the VO2max was under the standard. Step count is positively associated with CRF.

References:

[1]Agca et al. Atherosclerotic cardiovascular disease in patients with chronic inflammatory joint disorders. Heart. 2016;102(10):790-795.

[2]Lemes et al. Cardiorespiratory fitness and risk of all-cause, cardiovascular disease, and cancer mortality in men with musculoskeletal conditions. J Phys Act Health. 2019;16;134-140.

Disclosure of Interests:

Joëlle van den Hoek: None declared, Marike van der Leeden: None declared, George Metsios: None declared, Georeg Kitas: None declared, Harald Jorstad: None declared, WIllem Lems Grant/research support from: Pfizer, Consultant of: Lilly, Pfizer, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Martin van der Esch: None declared

FRI0308 ANKYLOSING SPONDYLITIS PATIENTS AT RISK OF DEVELOPING AORTIC VALVE REGURGITATION, NEED FOR MANDATORY ECHOCARDIOGRAPHY?

Background:

The overall mortality rate in ankylosing spondylitis (AS) patients is increased by 60–90% compared with the general population. This higher mortality rate is predominately caused by cardiovascular disease (CVD) comprising an increased prevalence of cardiac diseases such as valvular heart disease, conduction disturbances and cardiomyopathies as well as atherosclerotic diseases such as myocardial infarctions. However, there is a lack of contemporary studies. Therefore, we investigated current prevalences of cardiac disorders in a well characterized cohort of Dutch patients with AS compared to osteoarthritis (OA) controls.

Objectives:

To assess the prevalence of CVD in AS patients in comparison to OA controls in a Dutch population.

Methods:

We performed a cross-sectional study in AS and OA patients between 50-75 years. Subjects were recruited from a large rheumatology outpatient clinic (Reade) in Amsterdam, the Netherlands. Patients underwent echocardiography with 2D, spectral and Color Doppler imaging. The echocardiogram was evaluated by an experienced and certified cardiologist. Diastolic dysfunction was assessed according to the ASE/EACVI 2016 guideline. Furthermore, blood sample, surveys and physical examination were done. Disease activity and function were measured with the BASFI, BASDAI and the ASDAS-CRP.

Results:

A total of 193 consecutive AS patients were included with a median age of 60 (±7) years of which 72% men (138). The control group consisted of 70 OA patients (table 1). In the AS cohort the disease activity measures, BASDAI, ASDAS-CRP and BASFI, indicated moderate disease activity and were, respectively 3.1 (1.6-5.0), 2.1 (±1.0) and 3.5 (1.7-5.7). Anti-TNF was used by 43% of the AS patients. History of cardiovascular disease (CVD), i.e. angina pectoris, myocardial infarction, stroke and/or peripheral ischemia was comparable between the AS and OA cohort, respectively 9% (17) and 10% (7), p=0.81. Antihypertensives were significantly more often used in AS patients, 85 (44%) vs 19 (27%), p=0.02. Prevalences of systolic dysfunction and diastolic dysfunction did not differ significantly in AS and OA patients, respectively 6 (5%) vs 2 (5%), p=0.96 in systolic dysfunction and 7 (3%) vs 2 (3%), p=0.86 in diastolic dysfunction. Prevalence of aortic valve (AV) regurgitation was significantly higher in AS patients compared to OA patients, respectively 41 (22%) and 7 (10%), mostly with mild severity. The prevalence of mitral valve (MV) regurgitation did not differ between the AS and OA patients, respectively 68 (36%) vs 21 (33%), p=0.59. When corrected for age, gender and cardiovascular risk factors in a regression analysis, AS patients still had a substantially increased risk for AV regurgitation, odds ratio (OR) 2.8 95%CI 1.1-7.2, p=0.038.

Table 1.

Patient characteristics

ASOApN19370Men (n, %)138 (72)40 (57)0.028*Age (years)60 ±763 ±70.004*Disease activityBASDAI3.1 (1.6-5.0)-ASDAS-CRP2.1 ±1.0-BASFI3.5 (1.7-5.7)-CVDHistory of CVD* (n, %)17 (9)7 (10)0.81Antihypertensives (n, %)85 (44)19 (27)0.02Aortic valve regurgitation (n, %)41 (22)7 (10)0.04* Trace (n, %)16 (9)6 (9) Mild (n, %)23 (12)6 (9) Moderate (n, %)1 (1)0 Severe (n, %)1 (1)0 Prosthesis (n, %)1(1)0Mitral valve regurgitation (n, %)68 (36)21 (33)0.59Diastolic dysfunction (n, %)7 (3)2 (3)0.86

*Angina pectoris, myocardial infarction, stroke and/or peripheral ischemia

Conclusion:

This study demonstrates an almost tripled risk for developing AV regurgitation in Dutch AS patients. Although mostly mild in this age, due to the progressive nature of AV regurgitation in AS, echocardiographic screening should be considered in elderly AS patients.

Disclosure of Interests:

Milad Baniaamam: None declared, Sjoerd C. Heslinga: None declared, M.L. Handoko: None declared, Laura Boekel: None declared, Thelma C. Konings: None declared, Otto Kamp: None declared, Vokko P. van Halm: None declared, J.C. van Denderen: None declared, Irene van der Horst-Bruinsma Grant/research support from: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Consultant of: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research

AB0781 OPTIMIZATION OF APREMILAST USE IN DAILY PRACTICE BY EXPECTATION MANAGEMENT

Background:

Apremilast is an oral phosphodiesterase 4 inhibitor and approved drug for treatment of Psoriatic Arthritis(PsA). Previous studies show apremilast to be efficacious and safe. (1) However, physician are sometimes reluctant to prescribe apremilast in clinical practice due to its perceived side effects, and relatively small effect size (1).

Objectives:

In this study we investigated the occurrence and frequencies of adverse events, and the effects of patient expectation management on drug survival for PsA patient starting apremilast.

Methods:

From March 2017 to December 2019, 21 consecutive patients have been included in the apremilast PsA cohort at Reade in Amsterdam, the Netherlands. The initial high dropout rate that was observed with usual care led to a revision in the baseline visit with more emphasis placed on patient expectation management.

Results:

From the usual care group (UCG; n=12), 10 patients (83%) stopped apremilast within the first year: 6 (50%) due to adverse events, 4 (33%) due to inefficacy. Only 2 patients (17%) completed one year of follow-up. In contrast, in the expectation management group (EMG; n=9), only 1 patient (11%) dropped out due to adverse events, and none stopped due to inefficacy. 2 patients (22%) completed one year of follow-up, the other 6 patients (67%) are within the first year of treatment (median 5 months, range 1-10; figure 1). In total 55 adverse event were reported during the study, of which 40% were gastro-intestinal (table 1). There was one serious adverse event (within in the EMG group, stroke leading to hospitalization) which was considered not related to apremilast, and the patient remained on drug.

Conclusion:

The most common adverse event for apremilast are gastrointestinal side effects that subsided during prolonged use. Managing patient expectations before start of apremilast increases drug survival and is helpful for optimizing apremilast use in daily practice.

References:

[1]Kavanaugh A, Mease PJ, Gomez-Reino JJ, Adebajo AO, Wollenhaupt J, Gladman DD, et al. Treatment of psoriatic arthritis in a phase 3 randomised, placebo-controlled trial with apremilast, an oral phosphodiesterase 4 inhibitor. Ann Rheum Dis. 2014;73(6):1020-6.

Table 1.

Patient reported adverse events apremilast

Adverse eventsMildModerateSevereSAETotalGastro-intestinal AE1570022(40%)Mood complaints21003 (5%)Infections81009 (17%)Headache41005(9%)Others1511116(29%)Total44111155(100%)

Disclosure of Interests:

Romy Hansildaar: None declared, Annelies Blanken: None declared, Maaike Heslinga: None declared, Arno Van Kuijk: None declared, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research

OP0208 PATIENTS REPORT FATIGUE AS AN ADVERSE DRUG REACTION OF BIOLOGICS

Background:

Chronic fatigue is a well-known symptom in patients with rheumatic diseases and other immune-mediated inflammatory diseases (IMIDs). Therefore, fatigue as an adverse drug reaction (ADR) to biologics may remain unrecognised or may erroneously be attributed to the disease.

Objectives:

To assess patient-reported fatigue attributed to biologics for IMIDs and investigate predisposing factors of patient-reported fatigue.

Methods:

The Dutch Biologic Monitor is a multicenter patient-reported ADR monitoring system that surveys patients using a biologic for an IMID. Patients completed web-based questionnaires regarding ADRs attributed to biologics and the course and experienced burden (5 point Likert scale) of these ADRs. All patient-reported ADRs with MedDRA Preferred Term ‘fatigue’ were defined as biologic-associated fatigue (BA-fatigue). Basic demographics and treatment characteristics were compared between patients reporting BA-fatigue and patients not reporting BA-fatigue (reported other ADRs or no ADRs).

Results:

Out of 1369 participating IMID patients, 696 patients reported 1844 unique ADRs. BA-fatigue was reported by 100 patients and 48 patients described a consistent pattern of recurring fatigue after each administration. Most of these patients (88%) described recovery from BA-fatigue within one week after biologic administration and 73 patients reported health care professional (HCP) contact following BA-fatigue, with dose adjustment in 8 and discontinuation in 5 patients.

Basic demographics and characteristics that differ significantly between patients reporting BA-fatigue and patients not reporting BA-fatigue are summarized in table 1. No significant difference was found for other biologics, IMIDs, combination therapy and comorbidities. BA-fatigue was reported by 27% of rituximab users (n=33), 27% of vedolizumab users (n=26), 16% of tocilizumab users (n=50), 14% of infliximab users (n=159) and 3% of etanercept users (n=418). Although 29 patients in the BA-fatigue population had RA and 29 patients had Crohn’s disease (CD), 571 patients in our overall study population had RA and 194 patients had CD, suggesting BA-fatigue was reported by CD patients more often. The mean burden of BA-fatigue was higher than the mean burden of other ADRs (p<0.001).

Table 1.

Characteristics of patients with BA-fatigue compared to patients with other ADRs and without ADRs

Patients with BA-fatigue n (%)Patients with other ADRs n (%)Patients without ADRs n (%)n100 (100%)596 (100%)673 (100%)Basic demographicsAge (years) (mean ± SD)50.0 ± 14.653.4 ± 13.6 *55.7 ± 14.2 ***Gender (Female)59 (59%)398 (67%)ns342 (51%)nsSmoking n (%)25 (25%)97 (16%) *100 (15%) *BMI (kg/m2) (mean ± SD)25.7 ± 4.425.9 ± 4.7ns26.6 ± 5.5nsBiologicInfliximab22 (22%)53 (9%) ***84 (12%) *Etanercept13 (13%)177 (30%) ***228 (34%) ***Rituximab9 (9%)18 (3%) **6 (1%) ***Tocilizumab8 (8%)29 (5%)ns13 (2%) **Vedolizumab7 (7%)12 (2%) *7 (1%) ***IMIDRheumatoid arthritis29 (29%)270 (45%) **272 (40%) *Crohn’s disease29 (29%)77 (13%) ***88 (13%) ***Other indication16 (16%)53 (9%) *39 (6%) ***Combination therapyMethotrexate23 (23%)167 (28%)ns227 (34%) *ComorbidityPsychiatric disorder11 (11%)49 (8%)ns31 (5%) *Other comorbidity30 (30%)124 (21%) *102 (15%) ***Mean burden of ADR ± SD2.9 ± 0.92.4 ± 1.1 ***

Mann Whitney U, independent t-test and Fisher’s exact as appropriate

ns: not significant *p ≤ 0.05 **p ≤ 0.01 ***p ≤ 0.001

Conclusion:

HCPs should be aware that fatigue may be associated with biologic therapy and has a significant burden on patients. Evaluating the course of the symptoms might be helpful in recognizing BA-fatigue.

Disclosure of Interests:

Jette van Lint: None declared, Tom Bakker: None declared, Jouke Ubbink: None declared, Martijn van Doorn Grant/research support from: Unrestricted grants, advisory board, speaker fees and/or other (investigator) from Novartis, Abbvie, Janssen Cilag, Leopharma and Pfizer, Speakers bureau: Unrestricted grants, advisory board, speaker fees and/or other (investigator) from Novartis, Abbvie, Janssen Cilag, Leopharma and Pfizer, Phyllis Spuls Grant/research support from: Departmental independent research grant for TREAT NL registry LeoPharma December 2019; Contract support: I am involved in performing clinical trials with many pharmaceutical industries that manufacture drugs used for the treatment of e.g. psoriasis and atopic dermatitis for which we get financial compensation paid to the department/hospital, Consultant of: Consultancies in the past for Sanofi 111017 and AbbVie 041217 (unpaid), Sander Tas: None declared, Harald Vonkeman: None declared, Frank Hoentjen Grant/research support from: Received grants from Dr Falk, Janssen-Cilag, and AbbVie., Consultant of: Served on advisory boards, or as speaker or consultant for AbbVie, Celgene, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz, and Dr Falk, Speakers bureau: Served on advisory boards, or as speaker or consultant for AbbVie, Celgene, Janssen-Cilag, MSD, Takeda, Celltrion, Teva, Sandoz, and Dr Falk, Bart van den Bemt Grant/research support from: UCB, Pfizer and Abbvie, Consultant of: Delivered consultancy work for UCB, Novartis and Pfizer, Speakers bureau: Pfizer, AbbVie, UCB, Biogen and Sandoz., Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Eugène van Puijenbroek: None declared, Naomi Jessurun: None declared

AB1079 CORRELATION OF OPTICAL SPECTRAL TRANSMISSION IMAGING WITH ULTRASOUND AND DISEASE ACTIVITY IN RHEUMATOID ARTHRITIS PATIENTS

Background:

Optical spectral transmission imaging (OST) is a new imaging method that measures inflammation in the hands of rheumatoid arthritis (RA) patients. OST might be used to assess disease activity instead of disease activity score 28 (DAS28) or ultrasonography (US), with the advantage of OST that it is fast and not operator dependent. Detection of joint inflammation with OST and with US as reference, has provided varying outcomes with ROC AUCs ranging from 0.69-0.88 [1-3]. Further evaluation of the currently available OST device (HandScan) is needed in other RA cohorts.

Objectives:

To assess the correlation of OST measurement with US and disease activity, and to compare OST measurements of RA patients with healthy controls.

Methods:

OST was done in 24 consecutive RA patients with active disease and 37 age and sex matched healthy controls using the HandScan device from Hemics, the Netherlands. The HandScan calculates OST values for each bilateral wrist, MCP and PIP joint, ranging from 0 to 3. OST total score is then composed of the sum of the 22 OST joint scores and therefore ranges from 0 to 66. US was performed in the same joints as OST and semi-quantitatively scored on a scale of 0 to 3 for grey-scale (GS) synovitis and power Doppler (PD) signal individually. A separate total score for GS synovitis and PD was calculated by summation of the individual joint US scores. Joint scores (at joint level) and total scores (at patient level) were used in separate analyses. Additionally, we measured swollen joint count 28 (SJC28), tender joint count 28 (TJC28), DAS28, erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP). For all statistical analyses, the non-parametric variant was used.

Results:

Patient level

Median OST total score of RA patients was 16.88 (IQR 12.68-19.72). This was significantly higher than healthy controls (OST total score 12.06, IQR 10.32-14.93; p=0.0002).

OST total score of RA patients (patient level) did not significantly correlate with both US total scores (GS synovitis 0.37, p=0.08; PD 0.21, p=0.33), nor with disease activity parameters (DAS28 0.22, p=0.31; SJC28 0.32, p=0.12; TJC28 0.28, p=0.19; ESR -0.02, p=0.93; CRP 0.05, p=0.81).

Joint level

At joint level, there was a significant correlation for almost all joints with GS synovitis on US (table 2). For PD too few joints scored above 0 to allow for statistical comparisons, however for all joints median OST values were higher in PD positive joints than PD negative joints (differences in median OST values ranging from 0.2-0.5).

Table 2.

Correlation of individual joint OST values and GS synovitis

GS synovitisSpearman rp-valueWrist0.360.02MCP10.270.06MCP20.440.002MCP30.400.005MCP40.270.07MCP50.390.006IP10.350.01PIP20.300.04PIP30.130.37PIP40.290.04PIP50.370.01

Conclusion:

OST total score was higher for RA than healthy controls. At patient level, OST total score did not correlate with other disease activity measures. At joint level, GS synovitis scores correlated with OST joint values for almost all joints. In addition, higher OST values were found in PD positive joints but frequency of PD positivity was too low to allow statistical comparisons. The results of this small cohort of new RA patients do not yet demonstrate additional value as compared to US and clinical examination to detection of joint inflammation at cross-sectional assessment, although fast and non-operator dependent OST assessment may also be weighed in further evaluation for clinical use.

References:

[1]Van Onna et al. 2016 ARD 75(3):511-8

[2]Besselink et al. 2018 Rheumatology 57(5): 865-72

[3]Krabbe et al. 2016 ARD 75(3):632-3

Disclosure of Interests:

Annelies Blanken: None declared, C.J. van der Laken: None declared, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research

AB0728 MICROVASCULAR CHANGES OF THE RETINA IN ANKYLOSING SPONDYLITIS, AND THE ASSOCIATION WITH CARDIOVASCULAR DISEASE – THE EYE FOR A HEART STUDY

Background:

Patients with ankylosing spondylitis (AS) have an increased risk at cardiovascular disease (CVD). Microvasculature changes might precede overt CVD, but have been poorly studied in AS. The small vessels of the retina are accessible for non-invasive visualization, and microvascular changes (retinal arteriolar narrowing, venular widening, loss of tortuosity) are described in association with CVD in other diseases.

Objectives:

The aim of this study was to compare the retinal microvasculature of AS patients with healthy controls, and to assess gender differences.

Methods:

A cross-sectional, case-control study comparing AS patients (fulfilling the modified New York criteria, Rheumatology outpatient clinic of Reade and Amsterdam UMC) with healthy controls (EMIF-AD PreClinAD cohort of the Dutch Twins Register(1)), men:women=1:1. Most important inclusion criteria were: age 50-75 years, diabetes mellitus was excluded. All subjects underwent Optical Coherence Tomography Angiography and fundus photography (≥1 eye), analyzed with Singapore I Vessel Assessment software (Table 2). Differences between AS and controls were evaluated with generalised estimating equations (GEE), adjusted for demographics and cardiovascular risk, and stratified for gender.

Results:

In total, 59 AS patients (mean disease duration 36 years) and 105 controls were included. Controls were significantly older than patients, but did not differ in cardiovascular profile (Table 1). Patients had a significantly lower retinal arteriolar tortuosity (β-0.1;p=0.02), and higher vessel density (β 0.5,p=0.02), than controls (Table 2). Also, male AS patients showed a lower arteriovenular ratio compared to male controls (β -0.03,p=0.04). There were no differences between women with and without AS. In AS, a high disease activity was associated with a wider (unfavorable) venular diameter (p=0.05), whereas biologic use showed a wider (more favorable) arteriolar diameter (p<0.01).

Conclusion:

This study detected several retinal microvascular changes, in AS patients compared to controls, of which some are associated with CVD based on previous studies. Some changes were only observed in male-, but not in female, patients. A new finding was an increased capillary density in AS, of which the association with CVD-risk has not yet been studied before.

References:

[1]Konijnenberg E et al. The EMIF-AD PreclinAD study: study design and baseline cohort overview. Alzheimers Res Ther. 2018; 10:75.

Table 1.

Patient characteristics AS (n=57) and controls (n=105)

ASControlspGender, women (%)30 (51)52 (50)nsAge, mean yrs (SD)60 (6)68 (4)<0.01Smoking currently, yes (%)11 (19)8 (8)0.06Body mass index, mean (SD)26 (4)26 (3)nsHypertension, yes (%)23 (39)39 (37)nsDyslipidemia, yes (%)9 (15)18 (17)nsCardiovascular disease history, yes (%)9 (15)15 (14)nsNSAIDS (%)24 (41)6 (6)<0.01Biological (mostly TNF inhibitor)* (%)29 (49)0 (0)<0.01AS Disease Activity Score, mean (SD)2.1 ±0.9Table 2.

Retinal vascular parameters, differences AS and Control subjects

CrudeAdjusted for:Age, gender, BMI smoking, hypertension, dyslipidemiaRetinal vascular parametersβ(95%CI)pβ(95%CI)pDiameterArteriolar1.6(-2.0, 5.2)0.37-0.2(-4.8, 4.4)0.92Venular5.4(-0.66, 11.5)0.082.5(-5.4, 10.4)0.53Arteriovenular ratio-0.01(-0.03, 0.01)0.43-0.01(-0.03, 0.02)0.65TortuosityArteriolar-0.05(-0.12, 0.03)0.19-0.1(-0.2, -0.01)0.02ComplexityFractal dimension0.01(0.00, 0.03)0.040.0(-0.02, 0.02)0.88Vessel DensityInner ring0.8(0.5, 1.1)<0.0010.5(0.1, 0.9)0.02Outer ring0.7(0.4, 1.0)<0.0010.2(-0.2, 0.6)0.42

Disclosure of Interests:

Rianne van Bentum: None declared, Milad Baniaamam: None declared, Buket Kinaci-Tas: None declared, Jacoba van de Kreeke: None declared, Pieter Jelle Visser: None declared, Erik Serné: None declared, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research, Irene van der Horst-Bruinsma Grant/research support from: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma, Consultant of: AbbVie, Novartis, Eli Lilly, Bristol-Myers Squibb, MSD, Pfizer, UCB Pharma

AB1081 BLOOD PRESSURE, BMI AND SEX AFFECT OPTICAL SPECTRAL TRANSMISSION IMAGING MEASUREMENTS OF THE HANDS

Background:

Optical spectral transmission imaging (OST) is a new imaging method designed to measure inflammation in the hands of rheumatoid arthritis (RA) patients. The device uses a pressure cuff to occlude venous blood flow, resulting in an increased blood pool in the hands of the patient. In inflamed joints transmission of light through this blood pool is altered due to higher blood content, lower oxygenation and stronger hemodynamics at the location of inflammation [1]. However, altered hemodynamics not related to inflammatory arthritis might also influence OST measurements.

Objectives:

In this study we investigated whether hemodynamic and other cardiovascular parameters affect OST measurements in healthy participants.

Methods:

OST measurement was done in 37 healthy participants using the HandScan device from Hemics, the Netherlands. Carotid intima media thickness (IMT), pulse wave velocity (PWV) and augmentation index (AIx) were measured with ultrasound and SphygmoCor tonometry. Age, sex, diastolic and systolic blood pressure, pulse, hypertension (defined as systolic blood pressure >140 mmHg or diastolic blood pressure > 90 mmHg or antihypertensive treatment), total cholesterol, HDL, LDL, total/HDL cholesterol ratio, body mass index (BMI), European SCORE risk assessment, smoking status, cardiovascular history and medication use were collected during the same visit. Associations were investigated using univariate linear regression and multivariate regression adjusting for age and sex.

Results:

Participants were 53 ± 8 years old and 65% was female. Systolic and diastolic blood pressure was 129 ± 19 mmHg and 80 ± 9 mmHg respectively and 22% used antihypertensive treatment, 8% an anticoagulant and 11% a statin. In total 38% had hypertension and 8% had a history of cardiovascular disease.

Mean OST value was 12.69 ± 3.47 and all values were between 5.00 and 20.78. Cardiovascular and hemodynamic parameters that were associated with higher OST measurement were: hypertension (14.18 ± 1.12 versus 11.79 ± 0.69), systolic and diastole blood pressure, BMI and European SCORE (table 1). Also, male sex was associated with a higher OST with and without adjustment for age (15.05 ± 1.04 versus 11.41 ± 0.62 for females).

Table 1.

Cardiovascular and hemodynamic parameters associated with higher OST measurement

UnivariateAdjusted for age and sexB95%CIpB95%CIpHypertension (y/n)2.390.124.670.042.410.374.450.02Systolic blood pressure0.080.030.140.0050.070.020.120.01Diastolic blood pressure0.200.080.320.0010.190.090.290.001BMI0.24-0.010.480.060.260.050.470.02Sex (male/female)*3.671.565.780.0013.541.295.790.003European SCORE**1.240.092.390.04n/a

*Adjusted for age only, **Not adjusted because age and sex are included in the European SCORE

Other parameters (age, cholesterol, pulse, IMT, having carotid plaque, PWV, AI, cardiovascular history, smoking status and statin, antihypertensive drug and/or anticoagulant use) were not associated with the OST measurement (p>0.13, data not shown)

Excluding the 5 (14%) participants with hand osteoarthritis showed comparable results, except for BMI and hypertension. BMI was also significantly associated with OST in the univariate analysis (B 0.24, 95%CI 0.01-0.47, p=0.039), while hypertension lost its statistical significance (uni B 1.74, 95%CI -0.69-4.17, p=0.15; multi B 1.44, 95%CI -0.61-3.48, p=0.16).

Conclusion:

High blood pressure, BMI, male sex and European SCORE are associated with increased OST values in healthy participants. This indicates that differences in OST measurements of RA patients might not only reflect inflammatory burden but is also dependent on sex, blood pressure and body composition. This should be taken into account when using optical spectral transmission imaging for the assessment of inflammation in RA patients.

References:

[1]Meier et al. 2012 J Biomed Opt 17(8):081420

Disclosure of Interests:

Annelies Blanken: None declared, C.J. van der Laken: None declared, Michael Nurmohamed Grant/research support from: Not related to this research, Consultant of: Not related to this research, Speakers bureau: Not related to this research