AB0344 EFFICACY OF SUBCUTANEOUS INFLIXIMAB (CT-P13 SC) COMPARED WITH INTRAVENOUS INFLIXIMAB IN RHEUMATOID ARTHRITIS: A POST-HOC ANALYSIS OF A PHASE 3 RANDOMIZED CONTROLLED TRIAL

Background

Subcutaneous (SC) CT-P13 is the first and only subcutaneous formulation of infliximab (IFX) approved by the EMA.1 In the pivotal study (NCT03147248), non-inferiority of SC IFX to intravenous (IV) was demonstrated in rheumatoid arthritis (RA) patients using 28-joint Disease Activity Score (DAS28) C-reactive protein (CRP) improvement at Week 22, with a statistically significant treatment difference of 0.27 (95% CI 0.02, 0.52) favoring the SC versus the IV arm.2,3 At Week 30, numerical differences in efficacy outcomes were shown between SC and IV IFX favoring SC IFX. IV group patients switched to SC IFX by Week 30, and the difference between the groups was reduced at Week 54.2

Objectives

To investigate whether there was a statistically significant difference between SC and IV IFX at Weeks 30 and 54 in the phase 3 pivotal study of CT-P13 SC using conservative missing imputation methods.

Methods

Patients with active RA who had an inadequate response to MTX received IV IFX 3mg/kg at Weeks 0 and 2 for induction and were randomized at a 1:1 ratio to receive SC IFX 120mg every 2 weeks or IV 3mg/kg every 8 weeks thereafter for maintenance. Patients who were randomized to receive IV IFX switched to SC at Week 30. In this post-hoc analysis, non-responder imputation (NRI) and last observation carried forward (LOCF) methods were used to investigate whether the difference in efficacy outcomes between SC and IV IFX at Weeks 30 and 54 was statistically significant. Assessments included EULAR (CRP/ESR)/ACR response; remission rate and low disease activity (LDA) rate based on DAS28 (CRP/ESR), Clinical Disease Activity Index (CDAI) and Simplified Disease Activity Index (SDAI); Boolean remission rate; and the proportion of patients achieving a minimal clinically important difference (MCID) in Health Assessment Questionnaire (HAQ).

Results

Of the 343 randomized patients, 165 patients who received SC IFX and 174 patients who received IV IFX from the efficacy population were included in the analysis. There was a statistically significant difference in SC IFX compared to IV treated patients at Week 30 using both NRI and LOCF methods in almost all the clinical variables. However, the difference in efficacy outcomes between SC IFX and IV was reduced at Week 54 after the IV group switched to SC. This supports the improved efficacy of SC IFX at Week 30. Some of the key results (EULAR [CRP] responses, LDA rates based on DAS28 [CRP], CDAI, and SDAI) were presented in Figure 1. Analysis using LOCF and NRI methods yielded consistent results across most of the efficacy outcomes.

Figure 1.

Comparison of clinical outcomes between SC IFX and IV IFX in patients with active rheumatoid arthritis.

*P<0.05.

P-value for difference in proportion between SC and IV treatment group was obtained by asymptotic Wald test.

Low disease activity based on DAS28 (CRP) (< 3.2), CDAI (eatment group AI (≤ 11.0).

Conclusion

Statistical analyses using conservative missing imputation methods showed significantly greater improvements in clinical outcomes with SC IFX compared to IV at Week 30 in patients with RA. Between-group differences was reduced at Week 54, suggesting improved responses after switching from IV to SC.

References

[1]Remsima summary of product characteristics. https://www.ema.europa.eu/en/documents/product-information/remsima-epar-product-information_en.pdf. Published 2021. Accessed 10 January 2022.

[2]Westhovens R, Wiland P, Zawadzki M, et al. Efficacy, pharmacokinetics and safety of subcutaneous versus intravenous CT-P13 in rheumatoid arthritis: a randomized phase I/III trial. Rheumatology (Oxford). 2021;60(5):2277-2287.

[3]Combe B, Allanore Y, Alten R, et al. Comparative efficacy of subcutaneous (CT-P13) and intravenous infliximab in adult patients with rheumatoid arthritis: a network meta-regression of individual patient data from two randomised trials. Arthritis Res Ther. 2021;23(1):119.

Disclosure of Interests

Arnaud Constantin Speakers bureau: Abbvie, Amgen, Boehringer, Celltrion, Galapagos, Janssen, Lilly, Novartis, Sanofi, UCB, Consultant of: Abbvie, Amgen, Boehringer, Celltrion, Galapagos, Janssen, Lilly, Novartis, Sanofi, UCB, Roberto Caporali Speakers bureau: Abbvie, Amgen, BMS, Celltrion, Galapagos, Lilly, Pfizer, Fresenius-Kabi, MSD, UCB, Roche,Janssen, Novartis, Sandoz, Consultant of: Abbvie, Amgen, BMS, Celltrion, Galapagos, Lilly, Pfizer, MSD, UCB, Janssen, Novartis, Sandoz, Christopher John Edwards Speakers bureau: Abbvie, Astra Zeneca, Celltrion, Chugai, Fresenius, Galapagos, Gilead, GSK, Lilly, Janssen, Pfizer, Roche, Consultant of: Abbvie, Astra Zeneca, Chugai, Galapagos, Gilead, GSK, Lilly, Janssen, Pfizer, Roche, Grant/research support from: Celltrion, Pfizer, Abbvie, Joao Eurico Fonseca Speakers bureau: Abbvie, Ache, Janssen, Lilly, Medac, Novartis, Pfizer, Consultant of: Abbvie, Celltrion, Janssen, Lilly, Pfizer, Grant/research support from: Abbvie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, Florenzo Iannone Speakers bureau: Abbvie, BMS, Celltrion, Galapagos, MSD, Eli-Lilly, Janssen, Novartis, Pfizer, UCB, Consultant of: Abbvie, BMS, Celltrion, Galapagos, MSD, Eli-Lilly, Janssen, Pfizer, Grant/research support from: BMS, MSD, Edward Keystone Speakers bureau: Amgen, AbbVie, Celltrion, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi Genzyme, Consultant of: AbbVie, Amgen, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis, Grant/research support from: Amgen, Merck, Pfizer Pharmaceuticals, Hendrik Schulze-Koops Consultant of: Celltrion, Taeksang Kwon Employee of: Celltrion Healthcare, Seungmin Kim Employee of: Celltrion Healthcare, Sangwook Yoon Employee of: Celltrion Healthcare, Dong-Hyeon Kim Employee of: Celltrion Healthcare, Gahee Park Employee of: Celltrion Inc., DaeHyun Yoo Speakers bureau: Celltrion, Celltrion Healthcare

AB1180 COVID-19 HAD DISPROPORTIONATE IMPACTS ON RA SYMPTOMS AND FUNCTION BY SEX AND AGE: RESULTS FROM THE CANADIAN EARLY ARTHRITIS COHORT (CATCH)

Background

During the COVID-19 pandemic, Canadians with RA faced considerable uncertainty due to greater risk of infection, hospitalization, changing access to RA medications, and very limited access to in-person RA care. Further, to reduce transmission of the virus and COVID-related hospitalizations, stringent mitigation measures were implemented across the country to greatly reduce social contacts including curfews, limits on private gatherings and business closures. Little is known about the impact of the COVID-19 pandemic and associated mitigation efforts in RA. We hypothesized that women and younger adults with RA would report greater impairments in HRQL.

Objectives

To compare changes in HRQL prior-to and during the COVID-19 pandemic by sex and age groups in real-world RA patients seen in routine practice settings.

Methods

Data were from patients in the Canadian Early Arthritis Cohort (CATCH) who completed a study visit in the year prior to the COVID-19 pandemic (Mar 2019 through Feb 2020) and a repeat assessment during the pandemic period (Mar 2020 – Jan 2022). RA disease activity was assessed using the RA Flare Questionnaire, a validated patient-reported measure of current RA disease symptoms (pain, stiffness, fatigue) and function (physical, participation). An RA-FQ score ≥ 20 was used to classify RA symptoms consistent with an RA inflammatory flare. HRQL was assessed using PROMIS-29 Adult Profiles. We compared changes in mean Physical (PHS) and Mental Health (MHS) scores, and the proportion of patients with impairments in each domain (i.e., scores ≥ 55 for pain interference, fatigue, anxiety, depression, and sleep and ≤45 for physical function and participation) before and during the COVID-19 pandemic across sex and age groups (<40, 40-64, ≥65 years).

Results

The 938 CATCH participants in the analytic sample with data available at both time periods had a mean (SD) age of 60 (13) and RA symptom duration of 5.8 (3.7) years; 72% were women, 88% were white, and 64% reported >high school education. Most (80%) were in CDAI REM/LDA at the most recent visit prior to start of pandemic. The proportion of patients with RA-FQ ≥20 were similar at both time periods. While physical and emotional RA symptom impacts remained stable in men prior to and during the COVID-19 pandemic, women reported significant increases in anxiety and depression during the pandemic period. Younger RA patients <40 reported increases in depression, and older RA patients (65+) reported increases in anxiety and greater impacts on participation.

Conclusion

Our results illustrate that while the proportions of patients with high inflammatory disease activity were similar prior to and during the COVID-19 pandemic, we observed disproportionate impacts on HRQL by sex and age with a higher proportion of women, adults <40, and those ≥65 years of age experiencing greater impairments in several HRQL domains.

Table 1.DomainWomen (N = 673)Men (N=265)Age <40 (N=84)Age 45-64 (N=492)Age 65+ (N= 362)BeforeDuringBeforeDuringBeforeDuringBeforeDuringBeforeDuringRA Flare >20%17%21%19%18%13%7%18%21%18%21%Anxiety34%*42%*23%23%42%55%32%35%28%*35%*Depression28%*34%*22%20%25%*42%*28%28%24%30%Fatigue36%38%24%23%43%43%36%33%26%32%Pain47%52%48%45%39%48%46%49%49%54%Physical function54%57%46%46%40%40%49%50%59%62%Participation42%47%34%36%37%38%40%41%40%*49%*Sleep30%34%18%22%26%29%29%33%23%28%

*p <0.05

Acknowledgements

CATCH is supported through unrestricted research grants from: Amgen and Pfizer Canada since 2007; AbbVie since 2011; Medexus since 2013; Sandoz Canada since 2019; Fresenius Kabi Canada since 2021 and; Organon Canada since 2021. Previous funding from Janssen Canada (2011-16); UCB Canada and Bristol-Myers Squibb Canada (2011-18); Hoffman La Roche (2011-21); Sanofi Genzyme (2016-17); Eli Lilly Canada (2016-20); Merck Canada (2017-21) and Gilead Sciences Canada (2020-21)

Disclosure of Interests

None declared

OP0308-HPR MORE THAN HALF OF RA PATIENTS WITH A LIFETIME HISTORY OF MOOD DISORDERS WERE ANXIOUS AND DEPRESSED DURING THE COVID-19 PANDEMIC: RESULTS FROM THE CANADIAN EARLY COHORT (CATCH) STUDY

Background

A growing number of studies indicate the considerable mental health impacts of the prolonged COVID-19 pandemic in the general population as chronic stress is a risk factor for the development of depression and anxiety. Mood disorders are more prevalent in RA and a history of anxiety or depressive disorders increases the risk of recurrence in the future.

Objectives

To compare trends in prevalence of anxiety and depressive symptoms, prior to and during the COVID-19 pandemic in RA patients with and without a lifetime history of mood disorders.

Methods

Data were from RA patients diagnosed and treated for RA in rheumatology clinics across Canada enrolled in the Canadian Early Arthritis Cohort (CATCH) Study. We estimated monthly trends in prevalence of clinically significant levels of anxiety and depression (PROMIS Depression and Anxiety 4a score 55+) from all visits between Mar 2019 and Jan 2022 and compared monthly trends in anxiety and depression in the year prior to (Mar 2019- Feb 2020) and during the pandemic (Mar 2020 to Jan 2022) stratified by lifetime history of mood disorders.

Results

4,148 visits were completed from Mar 2019 to Jan 2022 in 1,644 RA patients with a mean (SD) age of 60 (14) and disease duration of 6 (4) years. 73% were women, 84% white, 60% had completed some post-secondary education, and 77% were in CDAI REM/LDA at the visit closest to the start of pandemic. 253 (15%) reported a lifetime history of depression and 217 (13%) a lifetime history of anxiety; 8% reported prior treatment for either.

Patients with a history of mood disorders had higher levels of depression and anxiety prior-to and during the pandemic compared with patients without a history of mood disorders (Table 1). Proportions were highest during COVID waves in all and were substantially higher and more variable in people with a previous history of mood disorders as compared to those without a history (Figure 1). While depressive symptoms peaked early in the pandemic, anxiety increased with each wave, peaking in Wave 3 (May-Jun 2021).

Table 1.

Prevalence of depression and anxiety symptoms prior to and during the COVID-19 pandemic in RA patients with and without a history of mood disorders.

Period Prevalence (monthly range)DepressionAnxietyNo historyPrior HistoryNo HistoryPrior HistoryN observations35276213610538Prepandemic (3/19 - 2/20)21%(14%-30%)51%(29%-64%)27%(20%-35%)58%(31%-89%)Pandemic (3/20 - 1/22)22%(15%-29%)53%(33%-78%)28%(20%-43%)59%(33%-80%)Figure 1.

During the first 22 months of the COVID-19 pandemic, the proportion of patients with depression and anxiety increased in all groups. More than half of those with a history of emotional distress had clinically significant levels of depression and anxiety; proportions were highest during COVID waves in all and were substantially higher in people with previous history as compared to those without a history (see Figure 1). Whereas depressive symptoms peaked early in the pandemic, anxiety increased with each wave, peaking in Wave 3 (May-Jun 2021).

Conclusion

Symptoms of anxiety and depression were common in Canadian adults with RA prior to and after the onset of the COVID-19 pandemic. Whereas others have found that high levels of depression and anxiety occurred early in the pandemic but declined fairly rapidly in the general population1, emotional distress was not attenuated over time in this large cohort of RA patients. Individuals reporting lifetime history of mood disorders were more than twice as likely to report anxiety and depression, with depression peaking early in the pandemic and anxiety growing with each successive wave in the first year. The results demonstrate the importance of applying a lifetime perspective as previous episodes of anxiety and depression may be an important marker of increased vulnerability and recurrence in RA patients, particularly during the pandemic.

References

[1]Fancourt D et al. Trajectories of anxiety and depressive symptoms during enforced isolation due to COVID-19 in England. Lancet Psychiatry. 2021;8:141-9.

Acknowledgements

CATCH is supported through unrestricted research grants from: Amgen and Pfizer Canada since 2007; AbbVie Corporation since 2011; Medexus since 2013; Sandoz Canada since 2019; Fresenius Kabi Canada since 2021 and; Organon Canada since 2021. Previous funding from Janssen Canada (2011-16); UCB Canada and Bristol-Myers Squibb Canada (2011-18); Hoffman La Roche Limited (2011-21); Sanofi Genzyme (2016-17); Eli Lilly Canada (2016-20); Merck Canada (2017-21) and; Gilead Sciences Canada (2020-21)

Disclosure of Interests

None declared

OP0262-HPR THE NEURO-QOL UPPER EXTREMITY FUNCTION SCALE: NEW OPPORTUNITIES TO MORE RELIABLY AND PRECISELY MEASURE SELF-REPORTED HAND FUNCTION AND SELF-CARE ACTIVITIES IN PEOPLE WITH RA

Background:

RA is an inflammatory disease that results in pain and loss of function, especially in the hands and wrists. Brief self-assessment tools that can reliably and precisely quantify hand/wrist function are needed to assess inflammatory activity when a physical exam is not feasible and to capture day-to-day experience of living with RA. Neuro-QoL is part of the PROMIS family of self-report measures created using a patient-centred approach and IRT methodology. The Neuro-Qol Upper Extremity Function (UEF) scale measures ability across fine motor and ADLs involving digital, manual and reach-related function and self-care. Little is known about its performance in RA.

Objectives:

To evaluate the validity and responsiveness of the 8-item Neuro-QoL UEF in RA. We hypothesized scores would be strongly (r>.70) associated with MHAQ, MD-HAQ, and PROMIS PF, moderately (r=.4 to .7) to symptoms, disease activity, and QoL indicators, and be responsive to change in disease activity and PF.

Methods:

Data were from the 0 and 6-month visits of adults with early RA (sx <1 yr) enrolled in the Canadian Early Arthritis Cohort, a prospective real-world study at 16 sites across Canada. Participants completed the Neuro-QoL UEF, MHAQ, MDHAQ, PROMIS-29, and PT Global at each visit. Rheumatologists recorded joint counts and MD Global. To evaluate content validity, we examined descriptive statistics across CDAI disease activity levels, and Pearson correlations between the Neuro-QOL UEF, legacy measures, CRP & ESR. Responsiveness was assessed by correlating change scores from visits 0-6 between Neuro-QoL UEF, disease activity and legacy PF scores.

Results:

The 262 participants were mostly white (83%) women (71%) with a mean (SD) age of 55 (13). Summary statistics at 6-months are shown in Table 1. Neuro-QOL UEF was moderately-strongly correlated with MHAQ, MDHAQ, PROMIS-PF (|r|=.63-.75) and moderately correlated with pain and stiffness, (|r|=.59, -.64), and CDAI, SDAI, PT&MD Global, TJ & SJ (|r|=.39-.58). Neuro-QOL UEF was moderately correlated with PROMIS QoL domains Pain, Fatigue, Anxiety, Depression, Sleep & Participation (|r|=.39-.60).

Table 1.

Summary statistics of physical function and RA disease activity indices at 6 months.

MeanSDMdn25%75%(Min, Max)Physical FunctionNeuro-Qol UEF46.59.753.837.553.8(21.8, 53.8)MHAQ (0-3)0.290.430.130.000.38(0.00, 2.25)MD-HAQ (0-10)1.391.640.700.002.00(0.00, 8.00)PROMIS-PF46.48.546.239.556.0(23.3, 56.0)RA Disease ActivityCDAI9.39.96.03.013.0(0.0, 56.0)SDAI10.710.96.83.115.2(0.0, 57.0)Patient Global3.02.5315(0, 10)MD Global1.82.2103(0, 9)Swollen Joints (28)2.13.7002(0, 20)Tender Joints (28)2.43.9103(0, 24)

Neuro-QOL scores decreased in a dose-response manner across worsening CDAI DA states reflecting increasing impairment (Table 2). Persons with HDA reported the highest disability, scoring nearly 0.5 SD lower on the Neuro-QoL UEF than PROMIS PF. Change from baseline to 6 months in Neuro-QoL UEF was moderately correlated with changes in PROMIS PF, MHAQ, PT Global, and CDAI (|r|=.44-.65). The mean change and range from 0-6 months in Neuro-QoL was significantly larger than in PROMIS (8.9 [95% CI 7.5, 10.4] vs. 5.4 [95% CI 4.4, 6.4])(see Figure).

Table 2.

Mean scores (95% CI) at 6 months by CDAI level.

REMLDAMDAHADNeuroQol UEF52.8 (51.8, 53.7)48.1 (46.6, 49.7)42.0 (39.4, 44.6)33.8 (30.5, 37.1)MHAQ (0-3)0.05 (0.02, 0.09)0.19 (0.14, 0.24)0.45 (0.34, 0.57)0.90 (0.63, 1.17)MD-HAQ (0-10)0.31 (0.17, 0.46)1.11 (0.90, 1.32)2.15 (1.71, 2.59)3.56 (2.56, 4.56)PROMIS-PF52.8 (51.4, 54.2)46.8 (45.3, 48.2)42.3 (40.4, 44.2)38.0 (34.4, 41.6)

Conclusion:

Clinicians, researchers, and patients benefit from practical self-report tools that reliably and precisely monitor hand function in RA. Results offer initial evidence of validity and responsiveness and support use of Neuro-QoL UEF to self-assess inflammatory activity in the hands and day-to-day experiences of living with RA.

Acknowledgements:

The CATCH study was designed and implemented by the investigators and financially supported through unrestricted research grants from: Amgen and Pfizer Canada - Founding sponsors since January 2007; AbbVie Corporation and Hoffmann-LaRoche since 2011; Medexus Inc. since 2013;, Merck Canada since 2017, Sandoz Canada, Biopharmaceuticals since 2019,Gilead Sciences Canada since 2020 and Fresenius Kabi Canada Ltd. since 2021. Previously funded by Janssen Biotech from 2011-2016, UCB Canada and Bristol-Myers Squibb Canada from 2011-2018, Sanofi Genzyme from 2016-2017, and Eli Lilly Canada from 2016-2020.

Disclosure of Interests:

None declared

POS0651 CLINICAL AND FUNCTIONAL RESPONSE TO TOFACITINIB IN PATIENTS WITH RHEUMATOID ARTHRITIS: PROBABILITY PLOT ANALYSIS OF RESULTS FROM A 48-WEEK PHASE 3b/4 METHOTREXATE WITHDRAWAL STUDY

Background:

The Phase 3b/4 study ORAL Shift (NCT02831855) demonstrated sustained efficacy/safety of tofacitinib modified-release 11 mg QD following MTX withdrawal, that was non-inferior to continued tofacitinib + MTX use, in patients (pts) with moderate to severe RA who achieved LDA with tofacitinib + MTX at Week (W)24.1

Objectives:

To assess differences and similarities in clinical/functional responses in pts receiving tofacitinib ± MTX in ORAL Shift.

Methods:

In ORAL Shift, pts received open-label tofacitinib + MTX to W24; at W24, pts who achieved CDAI LDA were randomised to receive tofacitinib + MTX or tofacitinib + placebo (PBO) from W24–48. In this post hoc analysis, clinical efficacy endpoints were ACR-N (minimum % change from baseline [BL; Δ] at W48 achieved by each pt in 3 efficacy measures), ΔDAS28-4(ESR), and DAS28-4(ESR) remission/LDA (scores ≤3.2) and moderate/high disease activity (scores >3.2). Functional efficacy endpoints were ΔHAQ-DI and HAQ-DI clinically relevant functional progression (CRFP) status at W48, defined as failure to achieve improvement in HAQ-DI ≥ minimum clinically important difference (MCID; ≥0.22 decrease from BL in HAQ-DI). Thus, CRFP was defined as <0.22 decrease, no change or increase from BL in HAQ-DI at W48. All efficacy endpoints were summarised descriptively. Cumulative probability plots of ACR-N and ΔHAQ-DI were produced. Median of mean CRP values from BL–W24 and >W24–48 were assessed by response subgroups.

Results:

266 pts receiving tofacitinib + MTX and 264 pts receiving tofacitinib + PBO in W24–48 were included. At W48: mean ACR-N was numerically greater with tofacitinib + MTX vs tofacitinib + PBO (60.8 vs 53.1); mean decrease in HAQ-DI was generally similar between groups (-0.71 vs -0.67); mean decrease in DAS28-4(ESR) was numerically greater with tofacitinib + MTX vs tofacitinib + PBO (-2.95 vs -2.68). The differences/similarities between groups in ACR-N and ΔHAQ-DI were also seen in cumulative probability plots (Figure 1). CRFP rates were numerically lower with tofacitinib + MTX (18.7%) vs tofacitinib + PBO (23.5%), and in pts with remission/LDA (tofacitinib + MTX, 12.1%; tofacitinib + PBO, 16.8%) vs moderate/high disease activity (tofacitinib + MTX, 26.2%; tofacitinib + PBO, 30.8%). Median of mean CRP over time was generally numerically lower in pts with CRFP vs non-CRFP and DAS28-4(ESR)-defined remission/LDA vs moderate/high disease activity; and in those receiving tofacitinib + PBO vs tofacitinib + MTX, irrespective of CRFP or DAS28-4(ESR) disease status (Table 1).

Table 1.

Median of mean CRPa up to W48 by response subgroups

Tofacitinib 11 mg QD + MTXTofacitinib 11 mg QD + PBOMean CRP,amedian (IQR) [n]>BL–W24>W24–48>BL–W24>W24–48HAQ-DI CRFP2.84 (1.15–7.30)2.30 (0.82–4.75)1.45 (0.77–4.42)2.28 (0.53–7.28)[45][46][56][56]HAQ-DI non-CRFP2.81 (1.09–6.19)2.91 (1.19–5.84)2.26 (0.98–4.63)2.47 (1.13–5.53)[195][195][176][178]DAS28-4(ESR) remission/LDA2.48 (1.05–4.95)2.46 (1.07–4.76)1.70 (0.89–4.14)1.95 (0.81–3.82)[126][127][115][117]DAS28-4(ESR) moderate/high disease activity3.56 (1.17–7.13)3.58 (1.36–8.33)2.60 (0.87–5.16)2.68 (1.34–8.23)[107][107][115][115]

aMean CRP was calculated as the average CRP value during each time period (>BL–W24 or >W24–48)

CRP, C-reactive protein; DAS28-4(ESR), Disease Activity Score in 28 joints, erythrocyte sedimentation rate; HAQ-DI, Health Assessment Questionnaire-Disability Index; IQR, interquartile range; LDA, low disease activity; MTX, methotrexate; n, number of pts meeting assessment criteria; QD, once daily

Conclusion:

Although clinical/functional responses were generally similar between treatment groups, numerical improvements were seen for some efficacy endpoints with tofacitinib + MTX vs tofacitinib + PBO. A numerically higher CRFP rate may be associated with higher DAS28-4(ESR) disease activity. CRP changes up to W48 may not trend with CRFP status.

References:

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

Acknowledgements:

Study sponsored by Pfizer Inc. Medical writing support was provided by Anthony G McCluskey, CMC Connect, and funded by Pfizer Inc.

Disclosure of Interests:

Stanley B. Cohen Consultant of: AbbVie, Eli Lilly, Genentech, Gilead Sciences, Pfizer Inc, Grant/research support from: AbbVie, Eli Lilly, Genentech, Gilead Sciences, Pfizer Inc, Yi-Hsing Chen Grant/research support from: Bristol-Myers Squibb, GlaxoSmithKline, Pfizer Inc, Naonobu Sugiyama Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jose Luis Rivas Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Annette Diehl Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Tatjana Lukic Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Jerome Paulissen Consultant of: Pfizer Inc, Haiyun Fan Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Tomohiro Hirose Shareholder of: Pfizer Inc, Employee of: Pfizer Inc, Edward Keystone Speakers bureau: AbbVie, Amgen, F. Hoffman-La Roche, Janssen, Merck, Novartis, Pfizer Inc, Sanofi Genzyme, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celltrion, Eli Lilly, F. Hoffman-La Roche, Gilead Sciences, Janssen, Merck, Myriad Autoimmune, Pfizer Inc, Sandoz, Sanofi Genzyme, Samsung Bioepsis, Grant/research support from: Amgen, Merck, Pfizer Inc, PuraPharm

POS1459-HPR IDENTIFYING MEANINGFUL CHANGE IN THE RA FLARE QUESTIONNAIRE SCORES IN RHEUMATOID ARTHRITIS

Background:

The RA-FQ is a patient-reported measure of current disease activity in RA that can be used to identify disease flares. The RA-FQ queries pain, physical function, fatigue, stiffness, and participation and yields a score from 0-50. We previously reported on reliability, validity, and responsiveness.

Objectives:

To identify changes in RA-FQ that represent minimal and meaningful improvement or worsening from the perspective of people with RA, treating rheumatologists, and in relation to disease activity indices. We hypothesized that

Methods:

Data were from adults with early RA (sx <1 year) enrolled in the Canadian Early Arthritis Cohort, a prospective study of real-world patients treated across Canada. Participants completed the RA-FQ, Patient Global, and RA transition item since last visit (a little vs. a lot better or worse or same) between consecutive 3- and 6-month visits. Rheumatologists recorded joint counts, MD Global, and change in RA. We compared mean change across improvement and worsening using patient anchors and disease activity indicators.

Results:

The 808 adults were mostly white (84%) women (71%) with a mean (SD) age of 55 (15) and moderate-high CDAI level (85%) at enrollment. Most (79%) reported their RA had changed; 59% were better and 20% worse. Patients who were a lot worse had a mean increase of 8.9 points whereas those who rated themselves as a lot better had a -6.0 decrease on the RA-FQ (Figure 1). Minimal worsening and improvement were associated with 4.7 and -1.8 change in RA-FQ scores, respectively, while patients who rated their RA unchanged had stable RA-FQ scores (Table 1).

Similar changes were evident in CDAI, SDAI, and DAS indices (Table 1). Larger differences were observed with patient vs. physician global scores and tender vs. swollen joints. Across measures, the change associated with worsening was greater than for improvement. Results supported all prespecified hypotheses ab.

Table 1.

Spearman’s correlation coefficients of PsAQoL with the other parameters for construct validity

DomainA Lot Better(N=346; 43%)A Little Better(N=132; 16%)The Same(N=174; 21%)A Little Worse(N=94; 12%)A Lot Worse(N=62; 8%)Δ95% CISDΔ95% CISDΔ95% CISDΔ95% CISDΔ95% CISDRA-FQ Total (0-50)-6.0(-7.1, -4.9)10.3-1.8(-3.2, -0.3)8.4-0.1(-1.3, 1.1)8.14.7(2.9, 6.6)9.18.9(5.1, 12.7)15.0 Pain-1.2(-1.4, -0.9)2.4-0.4(-0.8, 0.0)2.30.0(-0.2, 0.3)1.81.3(0.8, 1.7)2.22.0(1.2, 2.9)3.3 Physical Function-1.3(-1.6, -1.1)2.4-0.3(-0.6, 0.1)2.10.0(-0.3, 0.3)2.10.9(0.4, 1.4)2.41.8(0.8, 2.7)3.7 Fatigue-1.1(-1.4, -0.8)2.6-0.4(-0.7, 0.0)1.90.0(-0.3, 0.3)2.10.7(0.3, 1.1)2.11.3(0.5, 2.1)3.2 Stiffness-1.1(-1.4, -0.9)2.4-0.4(-0.7, 0.0)2.0-0.1(-0.4, 0.2)2.01.1(0.6, 1.5)2.21.8(1.0, 2.7)3.3 Participation-1.2(-1.5, -1.0)2.5-0.1(-0.5, 0.3)2.1-0.1(-0.4, 0.2)2.20.8(0.4, 1.3)2.22.0(1.1, 2.8)3.4Disease ActivityCDAI*-5.3(-6.3, -4.3)9.1-3.3(-5.4, -1.3)11.5-0.8(-2.0, 0.5)8.11.7(-0.1, 3.5)8.86.8(3.7, 9.8)12.0SDAI-5.6(-6.8, -4.4)9.2-3.5(-6.1, -0.9)12.2-1.9(-3.6, -0.2)8.91.5(-0.7, 3.7)9.24.7(1.0, 8.4)12.2DAS28-CRP-0.7(-0.8, -0.6)1.01-0.5(-0.7, -0.2)1.2-0.2(-0.4, 0.0)1.00.3(0.1, 0.5)1.00.5(0.2, 0.9)1.2Patient Global (0-10)-1.3(-1.5, -1.0)2.7-0.5(-0.9, -0.1)2.1-0.1(-0.4, 0.2)2.11.3(0.8, 1.8)2.42.9(2.1, 3.6)3.1MD Global (0-10)-1.2(-1.4, -1.0)1.9-0.7(-1.1, -0.3)-0.1-0.1(-0.4, 0.2)1.90.1(-0.3, 0.5)2.80.7(0.0, 1.5)2.8Swollen Joints (28)-1.4(-1.7, 1.0)3.2-1.0(-1.8, -0.2)4.6-0.4(-0.9, 0.0)3.00.0(-0.7, 0.7)3.41.3(0.2, 2.5)4.6Tender Joints (28)-1.5(-1.9, -1.1)3.9-1.3(-2.2, -0.3)5.50.0(-0.7, 0.6)4.30.3(-0.7, 1.2)4.52.2(0.8, 3.5)5.4

Conclusion:

In this large cohort of adults with ERA, the RA-FQ was responsive to change and generally distinguish between minimal and meaningful improvement and worsening. These data add to a growing evidence demonstrating robust psychometric properties of the RA-FQ and offer initial guidance about the amount of change associated with improvement or worsening, supporting its use in RA care, research and decision-making.

Acknowledgements:

The CATCH study was designed and implemented by the investigators and financially supported through unrestricted research grants from: Amgen and Pfizer Canada - Founding sponsors since January 2007; AbbVie Corporation and Hoffmann-LaRoche since 2011; Medexus Inc. since 2013;, Merck Canada since 2017, Sandoz Canada, Biopharmaceuticals since 2019,Gilead Sciences Canada since 2020 and Fresenius Kabi Canada Ltd. since 2021. Previously funded by Janssen Biotech from 2011-2016, UCB Canada and Bristol-Myers Squibb Canada from 2011-2018, Sanofi Genzyme from 2016-2017, and Eli Lilly Canada from 2016-2020.

Disclosure of Interests:

None declared

POS0461 RESPONSE TO BIOLOGIC THERAPY IN RHEUMATOID ARTHRITIS: RETHINKING OUR CLASSIFICATION

Background:

In rheumatoid arthritis (RA), primary failure with biologic treatment may be understood as lack of initial clinical response, while secondary failure would be loss of effectiveness after an initial response. Despite these clinical concepts, there is no unifying operational definition of primary and secondary non-response to RA treatment in observational studies using real-world data. On top of data-driven challenges, when conceptualizing secondary non-responders, it is unclear if the mechanism behind loss of effectiveness after a brief initial response is similar to loss of effectiveness after previous benefit sustained over time.

Objectives:

This viewpoint aims to motivate discussion on how to define primary and secondary non-response in observational studies. Ultimately, we aim to trigger expert committees to develop standard terminology for these concepts.

Methods:

We discuss different methodologies for defining primary and secondary non-response in observational studies. To do so, we shortly overview challenges characteristic of performing observational studies in real-world data, and subsequently, we conceptualize whether treatment response should be a dichotomous classification (Primary response/non-response; Secondary response/non-response), or whether one should consider three response categories (Primary response/non-response; Primary sustained/non-sustained response; Secondary response/non-response).

Results:

RA or biologic registries are a common data source for studying treatment response in real-world data. While registries include disease-specific variables to assess disease progression, missing data, loss of follow-up, and visits restricted to the year or mid-year visit may present a challenge. We believe there is a general agreement to assess primary response within the first 6 month of treatment. However, conceptualizing secondary non-response, one could wonder if a patient with brief initial response and immediate loss of it should belong to the same response category as a patient who relapses after a period of prior benefit that was sustained over time. Until this concern is clarified, we recommend considering a period of sustained response as a pre-requisite for secondary failure. This would result in the following three categories: a) Primary non-response: Lack of response within the first 6 months of treatment; b) Primary sustained response: Maintenance of a positive effectiveness outcome for at least the first 12 months since treatment start; c) Secondary non-response: Loss of effectiveness after achieved primary sustained response. Figure 1 illustrates this classification through a decision tree. Since the underlying mechanisms for treatment failure may differ among the above-mentioned categories, we recommend to use the three-category classification. However, since this may pose additional methodological challenges in real-world data, optionally, a dichotomous 12-month time-point may be used to assess secondary non-response (unfavourable outcome after 12-months) in comparison to primary non-response or non-sustained response (unfavourable outcome within the first 12-months). Similarly, to study primary response, the solely 6-month timepoint may be used.

Conclusion:

A unified operational definition of treatment response will minimize heterogeneity among observational studies and help improve the ability to draw cross-study comparisons, which we believe would be of particular interest when identifying predictors of treatment failure. Thus, we hope to open the room for discussion and encourage expert committees to work towards a common approach to assess treatment primary and secondary non-response in RA in observational studies.

Disclosure of Interests:

Enriqueta Vallejo-Yagüe: None declared, Sreemanjari Kandhasamy: None declared, Edward Keystone Speakers bureau: Amgen, AbbVie, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Novartis, Pfizer Pharmaceuticals, Sanofi Genzyme, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb Company, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis, Grant/research support from: Amgen, Merck, Pfizer Pharmaceuticals, PuraPharm, Axel Finckh Speakers bureau: Pfizer, Eli-Lilly, Paid instructor for: Pfizer, Eli-Lilly, Consultant of: AbbVie, AB2Bio, BMS, Gilead, Pfizer, Viatris, Grant/research support from: Pfizer, BMS, Novartis, Raphael Micheroli Consultant of: Gilead, Eli-Lilly, Pfizer and Abbvie, Andrea Michelle Burden: None declared

POS0445 PHYSICIAN AND PATIENT REPORTED EFFECTIVENESS OUTCOMES ARE SIMILAR IN TOFACITINIB AND TNF INHIBITORS IN RHEUMATOID ARTHRITIS PATIENTS: DATA FROM A RHEUMATOID ARTHRITIS REGISTRY IN CANADA

Background:

Tofacitinib (TOFA) is an oral, small molecule drug used for rheumatoid arthritis (RA) treatment as an alternative option to biologic disease modifying antirheumatic drugs (bDMARDs) including tumor necrosis factor inhibitors (TNFi).

Objectives:

We aimed to evaluate physician and patient reported effectivness outcomes in TNFi compared to TOFA, using real-world data from the Ontario Best Practices Research Initiative (OBRI).

Methods:

RA patients enrolled in the OBRI initiating their TOFA or TNFi (Adalimumab, Certolizumab, Etanercept, Golimumab, Infliximab, and Biosimilars) between 1st June 2014 (TOFA approval date in Canada) and 31st Dec 2019 were included. Patients were required to have physician and patient reported effectivness outcomes data available at treatment initiation and 6-month (± 2 months) follow-up. These included clinical disease activity index (CDAI), rheumatoid arthritis disease activity index (RADAI), HAQ-DI, sleep problem, and anxiety/depression scores. Multiple imputation (Imputation Chained Equation, N=20) was used to deal with missing data for covaraites at treatment initiation. To deal with confounding by indication, we estimated propensity scores for covariates with an absolute standard difference greater than 0.1 between the two treatment groups.

Results:

A total of 419 patients were included. Of those, 226 were initiating a TNFi and 193 TOFA, and had a mean (SD) disease duration of 8.0 (8.7) and 12.6 (9.6) years, respectively. In the TNFi group, 81.9% were female and mean age (SD) at treatment initiation was 56.6 (13.4) years. In the TOFA group, 85% were female and mean (SD) age at treatment initiation was 60.3 (11.2) years. The TNFi group was less likely to have prior biologic use (21.7%) compared to the TOFA group (67.9%). At treatment initiation, physical function measured by HAQ-DI was significantly lower in TNFi compared to the TOFA group (1.2 vs.1.4).

The rate of CDAI LDA/remission at 6 months was 36.7% and 33.2% in TNFi and TOFA group, respectively. The generalized linear mixed models (GLMM) adjusting for propensity score quantile, showed that there was no significant difference in CDAI LDA/remission (ORs: 0.85, 95% CI: 0.51, 1.43), RADAI (coefficient: 0.48, 95% CI: -0.18, 1.14), HAQ-DI (coefficient: -0.01, 95% CI: -0.18, 0.16), sleep problems (coefficient: -0.25, 95% CI: -0.95, 0.45), and anxiety/depression scores (coefficient: 0.12, 95% CI: -0.35, 0.58) between the two treatment groups (TOFA used as reference).

Conclusion:

In this real-world data study, we found that, physician and patient reported effectivness outcomes are similar in the TNFi and TOFA groups 6 months after treatment initiation in patients with RA.

Disclosure of Interests:

Mohammad Movahedi: None declared, Angela Cesta: None declared, Xiuying Li: None declared, Edward Keystone Grant/research support from: Amgen, Merck, Pfizer Pharmaceuticals, PuraPharm. Speaker Honoraria Agreements: AbbVie, Amgen, Bristol-Myers Squibb Company, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis. Consulting Agreements/Advisory Board Membership: AbbVie, Amgen, Bristol-Myers Squibb Company, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis, Claire Bombardier Grant/research support from: OBRI was funded by peer reviewed grants from CIHR (Canadian Institute for Health Research), Ontario Ministry of Health and Long-Term Care (MOHLTC), Canadian Arthritis Network (CAN) and unrestricted grants from: Abbvie, Amgen, Aurora, Bristol-Meyers Squibb, Celgene, Hospira, Janssen, Lilly, Medexus, Merck, Novartis, Pfizer, Roche, Sanofi, & UCB. Dr. Bombardier held a Canada Research Chair in Knowledge Transfer for Musculoskeletal Care and a Pfizer Research Chair in Rheumatology

POS0448 DISCONTINUATION RATE OF TOFACITINIB AS MONOTHERAPY IS SIMILAR COMPARED TO COMBINATION THERAPY WITH METHOTREXATE IN RHEUMATOID ARTHRITIS PATIENTS: POOLED DATA FROM TWO RHEUMATOID ARTHRITIS REGISTRIES IN CANADA

Background:

Tofacitinib (TOFA) is an oral, small molecule drug used for rheumatoid arthritis (RA) treatment and is prescribed alone or with methotrexate (MTX). We previously reported the similarity in retention between TOFA monotherapy and TOFA with MTX using data from two different registries separately; the Ontario Best Practices Research Initiative (OBRI) and the Quebec registry RHUMADATA.

Objectives:

To increase the study power, we propose to evaluate the discontinuation rate (due to any reason) of TOFA with and without MTX, using pooled data from these two registries.

Methods:

RA patients enrolled in the OBRI and RHUMADATA initiating their TOFA between 1st June 2014 (TOFA approval date in Canada) and 31st Dec 2019 were included. Concurrent MTX use was defined as MTX use for more than 75% of the time while using TOFA. Multiple imputation (Imputation Chained Equation method, N=20) was used to deal with missing data for covariates at treatment initiation.

Time to discontinuation was assessed using Cox regression models. To deal with confounding by indication, we estimated propensity scores for selected covariates with an absolute standard difference greater than 0.1. We then adjusted Cox regression models for propensity quantile to compare the discontinuation of TOFA with MTX versus TOFA without MTX.

Results:

A total of 493 patients were included. Of those, 244 (49.5%) and 249 (51.5%) were treated with MTX and without MTX, respectively. Compared to TOFA monotherapy, the TOFA with MTX group had a significantly lower mean HAQ-DI, fatigue score, and the number of prior biologic use at the time of TOFA initiation. A lower proportion of positive ACPA (59% vs. 66%), prevalence of hypertension (31% vs 37%), and concomitant use of Leflunomide (11% vs. 23%) were also observed for patients using TOFA with MTX.

Over a mean follow-up of 19.0 months, discontinuation was reported in 182 (36.9%) of all TOFA patients. After adjusting for propensity score quantile across 20 imputed datasets, there was no significant difference in discontinuation between treatment groups (adjusted HRs: 1.12, 95% CI: 0.83-1.51; p=0.49).

Conclusion:

In this pooled real-world data study, we found that in patients with RA, the retention of TOFA is similar if it is used as monotherapy or in combination with MTX.

Disclosure of Interests:

Movahedi: None declared, Denis Choquette Grant/research support from: Rhumadata is supported by unrestricted grants from Abbvie Canada, Amgen Canada, Eli Lilly Canada, Novartis Canada, Pfizer Canada, Sandoz Canada and Sanofi Canada., Louis Coupal: None declared, Angela Cesta: None declared, Xiuying Li: None declared, Edward Keystone Grant/research support from: Amgen, Merck, Pfizer Pharmaceuticals, PuraPharm. Speaker Honoraria Agreements: AbbVie, Amgen, Bristol-Myers Squibb Company, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis. Consulting Agreements/Advisory Board Membership: AbbVie, Amgen, Bristol-Myers Squibb Company, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis, Claire Bombardier Grant/research support from: OBRI was funded by peer reviewed grants from CIHR (Canadian Institute for Health Research), Ontario Ministry of Health and Long-Term Care (MOHLTC), Canadian Arthritis Network (CAN) and unrestricted grants from: Abbvie, Amgen, Aurora, Bristol-Meyers Squibb, Celgene, Hospira, Janssen, Lilly, Medexus, Merck, Novartis, Pfizer, Roche, Sanofi, & UCB.

Acknowledgment: :

Dr. Bombardier held a Canada Research Chair in Knowledge Transfer for Musculoskeletal Care and a Pfizer Research Chair in Rheumatology

POS0531 FACTORS ASSOCIATED WITH BASELINE HYPERTENSION IN EARLY RHEUMATOID ARTHRITIS: DATA FROM A REAL-WORLD LARGE INCIDENT COHORT

Background:

It is not well understood why hypertension (HTN) is so common in rheumatoid arthritis (RA) patients. Reported prevalence of HTN in RA patients ranges from 4-73%.(1)

Objectives:

This study explored the prevalence of HTN at time of RA diagnosis and which demographic, behavioural and clinical factors were associated with HTN.

Methods:

Data from the Canadian Early Arthritis Cohort (CATCH), a prospective inception cohort of patients with RA <1 year duration, were used to analyze baseline demographic, behavioural and clinical characteristics associated with HTN, which was reported by physicians. Univariate logistic regression models were created to explore associations with baseline HTN. A multivariate logistic regression model was built based on goodness of fit indicated by likelihood ratio tests. Variables included in the model were age, sex, race, body mass index (BMI), education, smoking, alcohol servings, seropositivity, disease activity and comorbidities.

Results:

In total, 2052 subjects were included with mean (±SD) age of 55 (±14) years and symptom duration 5.60(5.47, 5.73) months, 71% of subjects were female and 85% were Caucasian. HTN was reported in 26% of subjects at baseline. Hypertensive subjects were older and more likely to be male. Other factors significantly associated with HTN at baseline were lower education, ever smoking, high BMI, diabetes, hyperlipidemia, worse RA disease activity, longer duration of RA symptoms, being seropositive, as well as the use of NSAIDs and/or corticosteroids (Table 1). In multivariable analysis HTN was associated with older age, overweight and obese BMI, diabetes, and hyperlipidemia. Expression of anti-citrullinated protein antibodies was inversely associated with HTN (Table 1). Other RA disease factors and treatments were not significantly associated with HTN on multivariable analysis.

Table 1.

Results of univariate and multivariate logistic regression analyses exploring the association between baseline characteristics and HTN in early RA.

Univariate Logistic RegressionMultivariable Logistic RegressionVariableCrude OR (95% CI)Adjusted OR (95% CI)Socio-Demographic20-39 years old0.15 (0.07, 0.26)0.14(0.05, 0.34)40-59 years oldReference60-79 years old2.81 (2.26, 3.50)2.26(1.65, 3.11)80-99 years old5.87 (3.36,10.25)3.80(1.53, 9.41)Female0.55 (0.45, 0.68)1.10(0.78, 1.54)Lifestyle/BehaviouralNormal weight (18.5- 24.9kg/m2)ReferenceOverweight (25-29.9 kg/m2)2.33(1.74, 3.11)1.63(1.10, 2.43)Obese (30+ kg/m2)3.19(2.38, 4.27)2.84(1.91, 4.23Ever-smoking1.41(1.15, 1.73)1.02(0.75, 1.40)Post-secondary education0.58(0.47, 0.71)0.88(0.65, 1.20)Clinical CharacteristicsSymptom duration0.99(0.99, 0.99)1.00(1.00, 1.00)DAS-281.09(1.09, 1.17)1.02(0.92, 1.13)ACPA+0.68(0.56, 0.85)0.64(0.44, 0.92)Corticosteroid use pre-baseline1.37(1.04, 1.81)OmittedNSAID use at baseline0.68(0.55, 0.84)OmittedDiabetes5.62(4.09, 7.73)3.20(1.99, 5.15)Hyperlipidemia4.75(3.74, 6.03)2.80(1.94, 4.02),CVD15.59(3.35, 72.64)Omitted

DAS-28; Disease activity score 28, ACPA; Anti-citrullinated protein antibody, CVD; Cardiovascular disease. Pre-baseline is 29 to 365 days before entering the cohort. Baseline is within 28 days before entering the cohort. Omitted variables either failed likelihood ratio test or were colinear. Additional variables tested but found insignificant: race, alcohol servings, depression, RF+, and use of DMARDs.

Conclusion:

Approximately 1 in 4 diagnosed with RA had HTN reported by their rheumatologists, which is similar to that of the general population. This suggests that increased risk of HTN in RA patients may develop as RA disease or treatment time progresses. Factors that may be predictive of this excess risk will be explored in further analysis.

References:

[1]Panoulas VF, Metsios GS, Pace AV, et al. Hypertension in rheumatoid arthritis. Rheumatology (Oxford) 2008;47:1286-98.

Acknowledgements:

The CATCH study was designed and implemented by the investigators and financially supported through unrestricted research grants from: Amgen and Pfizer Canada - Founding sponsors since January 2007; AbbVie Corporation and Hoffmann-LaRoche since 2011; Medexus Inc. since 2013;, Merck Canada since 2017, Sandoz Canada, Biopharmaceuticals since 2019,Gilead Sciences Canada since 2020 and Fresenius Kabi Canada Ltd. since 2021. Previously funded by Janssen Biotech from 2011-2016, UCB Canada and Bristol-Myers Squibb Canada from 2011-2018, Sanofi Genzyme from 2016-2017, and Eli Lilly Canada from 2016-2020.

Disclosure of Interests:

Brook Hadwen: None declared, Saverio Stranges: None declared, Neil Klar: None declared, Kuriya Bindee: None declared, Janet Pope Speakers bureau: UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, BMS, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead, Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB;, Grant/research support from: Abbvie, BMS, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Susan J. Bartlett Consultant of: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Gilles Boire Speakers bureau: Merck, BMS, Pfizer, Janssen, Grant/research support from: Amgen, Abbvie, BMS, Eli Lilly, Merck, Novartis, Pfizer, Sandoz, Louis Bessette Speakers bureau: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Lilly, Novartis, Consultant of: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Lilly, Novartis., Grant/research support from: Amgen, BMS, Janssen, Roche, UCB, AbbVie, Pfizer, Merck, Celgene, Sanofi, Lilly, Novartis., Carol Hitchon Grant/research support from: Pfizer and UCB Canada, Glen Hazlewood: None declared, Edward Keystone Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Consultant of:: AbbVie, Amgen, AstraZeneca Pharma, Bristol-Myers Squibb Company, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis, Grant/research support from: AbbVie, Amgen, Gilead Sciences, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, PuraPharm, Sanofi, Orit Schieir: None declared, Carter Thorne Speakers bureau: Medexus/Medac, Consultant of: Abbvie, Centocor, Janssen, Lilly, Medexus/Medac, Pfizer, Grant/research support from: Amgen, Pfizer, Abbvie, Celgene, CaREBiodam, Novartis, Diane Tin: None declared, Marie-France Valois: None declared, Vivian Bykerk Consultant of: Amgen, BMS, Gilead, Sanofi-Genzyme/Regeneron, Scipher, Pfizer Pharmaceuticals, UCB, NIH, Lillian Barra: None declared

AB0198 EFFICACY AND SAFETY AFTER TRANSITION FROM REFERENCE ADALIMUMAB TO CT-P17 (ADALIMUMAB BIOSIMILAR: 100 MG/ML) IN COMPARISON WITH THE MAINTAINED TREATMENT (CT-P17 OR REFERENCE ADALIMUMAB) IN PATIENTS WITH MODERATE-TO-SEVERE ACTIVE RHEUMATOID ARTHRITIS: 1-YEAR RESULT

Background:

Therapeutic equivalence of CT-P17 to reference adalimumab (ref-adalimumab) has been shown in patients with moderate-to-severe active rheumatoid arthritis (RA) through primary 24-week results [1]. Here, efficacy, pharmacokinetics (PK), safety and immunogenicity results up to 52-week, including transition data from ref-adalimumab to CT-P17 are presented.

Objectives:

To evaluate efficacy, PK, safety and immunogenicity when switched from ref-adalimumab to CT-P17 compared to maintaining CT-P17 or ref-adalimumab.

Methods:

In this study, 648 moderate-to-severe active RA patients despite methotrexate treatment were randomized (1:1) to either CT-P17 or ref-adalimumab and treated with doses of 40 mg every 2 weeks up to Week 24. Prior to dosing at Week 26, 608 patients were randomized again to either maintaining their treatments or being switched from ref-adalimumab to CT-P17. Efficacy, PK, safety, and immunogenicity were assessed up to Week 52.

Results:

After the second randomization, 303 patients continued with CT-P17, 153 patients continued with ref-adalimumab and 151 patients switched from ref-adalimumab to CT-P17 treatments, up to Week 48. Demographics and baseline characteristics were similar among the 3 groups. Sustained and comparable efficacy in terms of ACR20/50/70 response rates was achieved not only in the maintenance groups (CT-P17 or ref-adalimumab) but also in the switched from ref-adalimumab to CT-P17 group up to Week 52 (Figure 1).

Figure 1.

ACR 20/50/70 Response Rates up to 1 YearAbbreviation: ref-adalimumab, reference adalimumab.Note. There were patients who could not visit the study site due to COVID-19 pandemic and were counted as nonresponder for ACR response at Week 52.

In terms of PK, mean trough serum concentration (Ctrough) were maintained after Week 24 in all 3 groups. The observed mean Ctrough were within the reported therapeutic ranges of ref-adalimumab trough levels in RA patients (5-8 μg/mL).

The safety profile after transition was comparable among the 3 groups (Table 1). The most common treatment-emergent adverse events (TEAEs) was neutropenia. Similar proportions of patients in all 3 groups experienced at least 1 TEAE: injection site reactions, hypersensitivity/allergic reactions and infections. One malignancy (basal cell carcinoma; unrelated) was reported in the ref-adalimumab maintenance group. Safety data accumulated over 1 year also showed comparable results among the 3 groups. Anti-drug antibody (ADA) and neutralizing antibody (NAb) results were similar among the 3 groups. At Week 52, the proportions of patients who had ADA/NAbs were 28.4%/24.8% patients in CT-P17 maintenance, 27.0%/24.3% patients in ref-adalimumab maintenance and 28.3%/26.3% patients in switched to CT-P17 groups.

Conclusion:

Single transition from ref-adalimumab to CT-P17 was efficacious and safe without increase in immunogenicity. Also, efficacy, PK, safety and immunogenicity profiles were comparable between CT-P17 and ref-adalimumab up to Week 52.

References:

[1]J Kay et al, 2020. Poster Presented at ACR Convergence 2020.

Table 1.

Overview of TEAEs from Weeks 26 to 52 (Safety Population – second random subset)

Patients, n (%)Second RandomizationCT-P17 Maintenance(N=303)Ref-ada Maintenance(N=152)Switched to CT-P17 (N=152)≥1 TEAE121 (39.9)69 (45.4)73 (48.0)≥1 TESAE6 (2.0)3 (2.0)5 (3.3)≥1 TEAE leading to study drug discontinuation3 (1.0)2 (1.3)5 (3.3)≥1 TEAE classified as hypersensitivity/allergic reactions2 (0.7)1 (0.7)0 (0)≥1 TEAE classified as injection site reactions1 (0.3)4 (2.6)1 (0.7)≥1 TEAE classified as infection54 (17.8)41 (27.0)28 (18.4)≥1 TEAE classified as malignancy0 (0)1 (0.7)0 (0)

Abbreviations: Ref-ada, reference adalimumab; TEAE, treatment-emergent adverse event; TESAE, treatment-emergent serious adverse event.

Disclosure of Interests:

Daniel Furst Speakers bureau: CME, Consultant of: Amgen, Corbus, Galapagos, Horizon, Kadmon, Pfizer, Talaris, Grant/research support from: Corbus, CSL Behring, Galapagos, Gilead, GSK, Horizon, Kadmon, Novartis, Pfizer, Roche/Genetech, Talaris, Edward Keystone Speakers bureau: Amgen, AbbVie, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Novartis, Pfizer Pharmaceuticals, Sanofi Genzyme, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb Company, Celltrion Inc., Myriad Autoimmune, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc., Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepis, Grant/research support from: Amgen, Merck, Pfizer Pharmaceuticals, PuraPharm, Jonathan Kay Consultant of: AbbVie, Inc., Boehringer Ingelheim GmbH, Celltrion Healthcare Co. Ltd., Jubilant Radiopharma, Merck & Co., Inc., Pfizer Inc., Samsung Bioepis, Sandoz Inc., Scipher Medicine, UCB, Inc., Grant/research support from: Paid to the University of Massachusetts Medical School: Gilead Sciences Inc., Novartis Pharmaceuticals Corp., Pfizer Inc., Janusz Jaworski: None declared, Rafal Wojciechowski: None declared, Piotr Wiland Speakers bureau: Eli Lilly, Sanofi Aventis, Novartis, Sandoz, Consultant of: Eli Lilly, Novartis, Sandoz, Anna Dudek: None declared, Marek Krogulec: None declared, Sławomir Jeka Speakers bureau: Novartis, Pfizer, Roche, Lilly, Teva, MSD, Abbvie, Sandoz, Egis, Medac, Consultant of: Novartis, Pfizer, Roche, Lilly, Teva, MSD, Abbvie, Sandoz, Egis, Medac, Agnieszka Zielinska: None declared, Jakub Trefler: None declared, Katarzyna Bartnicka-Masłowska: None declared, Magdalena Krajewska-Wlodarczyk Speakers bureau: Abbvie, Eli Lilly, Novartis, Roche, Piotr Klimiuk: None declared, Sang Joon Lee Employee of: Celltrion, Inc., Sung Hyun Kim Employee of: Celltrion, Inc., YunJu Bae Employee of: Celltrion, Inc., GoEun Yang Employee of: Celltrion, Inc., JaeKyoung Yoo Employee of: Celltrion, Inc., TaeKyung Kim Employee of: Celltrion, Inc.

OP0179 DISCONTINUATION RATE OF TOFACITINIB IS SIMILAR WHEN COMPARED TO TNF INHIBITORS IN RHEUMATOID ARTHRITIS PATIENTS: POOLED DATA FROM TWO RHEUMATOID ARTHRITIS REGISTRIES IN CANADA

Background:

Tofacitinib (TOFA) is an oral, small molecule drug used for rheumatoid arthritis (RA) treatment as the first or an alternative option to biologic disease- modifying antirheumatic drugs (bDMARDs), including tumor necrosis factor inhibitors (TNFi). The similarity in retention of TNFi and TOFA was previously reported separately by the Ontario Best Practices Research Initiative (OBRI) and the Quebec cohort RHUMADATA®.

Objectives:

To increase the study power, we propose to evaluate the discontinuation rate (due to any reason) of TNFi compared to TOFA, using pooled data from both these registries.

Methods:

RA patients enrolled in the OBRI and RHUMADATA initiating their TOFA or TNFi between 1st June 2014 (TOFA approval date in Canada) and 31st Dec 2019 were included. Time to discontinuation was assessed using adjusted Kaplan-Meier (KM) survival and Cox regression models. To deal with confounding by indication, we estimated propensity scores for covariates with a standard difference greater than 0.1. Models were then adjusted using stratification and inverse probability of treatment weight (IPTW) methods. Multiple imputation (Imputation by Chained Equation method, N=20) was used to deal with missing data for covariates at treatment initiation.

Results:

A total of 1318 patients initiated TNFi (n=825) or TOFA (n=493) with mean (SD) disease duration of 8.9 (9.3) and 13.0 (10.1) years, respectively. In the TNFi group, 78.8% were female and mean age (SD) at treatment initiation was 57.6 (12.6) years. In the TOFA group, 84.6% were female and mean (SD) age at treatment initiation was 59.5 (11.5) years. The TNFi group was less likely to have prior biologic use (33.9%) than the TOFA group (66.9%). At treatment initiation, the mean (SD) CDAI was significantly (p<0.05) lower in the TNFi group [20.0 (11.7)] compared to the TOFA group [22.1(12.4)]. Physical function measured by HAQ-DI was also significantly lower (p<0.05) in the TNFi compared to the TOFA group (1.2 vs.1.3).

Over a mean follow-up of 23.2 months, discontinuation was reported in 309 (37.5%) and 182 (36.9%) of all TNFi and TOFA patients, respectively. After adjusting for propensity score deciles across 20 imputed datasets, there was no significant difference in discontinuation between treatment groups (adjusted HRs: 0.96, 95% CI: 0.78-1.18; p=0.69). The results were similar for two propensity adjustment methods. Figure 1 shows IPTW adjusted KM survival curves comparing discontinuation rates in patients treated with TNFi and TOFA.

Figure 1.

Note: Propensity Score Weighted (IPTW) Survival Curves was performed using one imputed dataset

Conclusion:

In this pooled real -world data study, we found that TNFi and TOFA retention is similar in patients with RA. In the next step we will analysis the data for specific reasons of dicontinutaion. We will also repeat analysis comparing discontinuation in the first users versus those after one or more biologic failure.

Disclosure of Interests:

Mohammad Movahedi: None declared, Denis Choquette Grant/research support from: Rhumadata® is supported by unrestricted grants from Abbvie Canada, Amgen Canada, Eli Lilly Canada, Novartis Canada, Pfizer Canada, Sandoz Canada and Sanofi Canada., Louis Coupal: None declared, Angela Cesta: None declared, Xiuying Li: None declared, Edward Keystone Grant/research support from: Amgen, Merck, Pfizer Pharmaceuticals, PuraPharm. Speaker Honoraria Agreements: AbbVie, Amgen, Bristol-Myers Squibb Company, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis. Consulting Agreements/Advisory Board Membership: AbbVie, Amgen, Bristol-Myers Squibb Company, Celltrion, Myriad Autoimmune, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis, Claire Bombardier Grant/research support from: OBRI was funded by peer reviewed grants from CIHR (Canadian Institute for Health Research), Ontario Ministry of Health and Long-Term Care (MOHLTC), Canadian Arthritis Network (CAN) and unrestricted grants from: Abbvie, Amgen, Aurora, Bristol-Meyers Squibb, Celgene, Hospira, Janssen, Lilly, Medexus, Merck, Novartis, Pfizer, Roche, Sanofi, & UCB.

Dr. Bombardier held a Canada Research Chair in Knowledge Transfer for Musculoskeletal Care and a Pfizer Research Chair in Rheumatology

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

Background:

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

Objectives:

To present FINCH 1 W52 results.

Methods:

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

Results:

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

Table 1.

Efficacy outcomes at week 52

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

aLeast squares mean change from baseline.

bMean change from baseline.

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

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

Table 2.

Treatment-emergent AEs through week 52

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

Data omitted for patients rerandomised from placebo to FIL.

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

Conclusion:

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

References:

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

Disclosure of Interests:

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

SAT0127 REAL-WORLD PREDICTORS OF STARTING DIFFERENT ADVANCED DMARD TREATMENTS IN RHEUMATOID ARTHRITIS: A PROSPECTIVE INVESTIGATION FROM THE CANADIAN EARLY ARTHRITIS COHORT (CATCH) GROUP

Background:

RA patients with inadequate DMARD response may be treated with a TNF inhibitor (TNFi), non-TNFi or janus kinase inhibitor (JAKi) [1].

Objectives:

Compare characteristics of real-world early RA (ERA) patients starting TNFi, non-TNFi, and JAKi post DMARD failure.

Methods:

Data were analyzed from early RA patients (symptoms < 1 year) enrolled in CATCH who started TNFi, non-TNFi or JAKi as first line advanced therapy from 2014 to 2019. Descriptive statistics, t-tests and chi-square tests summarized and compared secular trends and patient characteristics initiating each class of therapy. Multinomial logistic regression analyses were done.

Results:

246 participants started advanced therapy during the study period; (75%) female, mean(SD) age 50(14) years. First line prescriptions for JAKi increased and TNFi decreased (Fig. 1). Those receiving JAKi had longer disease duration, fewer tender joints, and lower DAS28, CDAI, ESR, MD global (all p <0.05) (Table 1). The strongest predictor of starting JAKi was province (Ontario where access is preferential for JAKi and biosimilar TNFi) (Table 2). Those prescribed TNFi had shorter disease duration, younger age, fewer comorbidities, and treatment location outside Ontario (Table 1,2). Those starting non-TNFi had higher DAS28; predictors included older age, higher education, and more comorbidities (Table 1,2).

Table 1.

Characteristics prior to starting advanced therapy

VariableTotal Sample(N = 246)JAKi(N = 61)TNFi(N = 153)Non-TNFi(N = 32)p-value£Disease duration (months) mean (SD)39 (34.1)50.8 (39.3)32.5 (29.1)48 (38.6)0.0006DAS28 (ESR - CRP if ESR was missing) mean (SD)4.2 (1.4)3.6 (1.4)4.3 (1.4)4.8 (1.5)0.0012CDAI mean (SD)21.5 (14.8)16.5 (13.7)22.9 (14.8)24.8 (14.9)0.0089Tender joint count (0-28), median (IQR)§4 (7)2 (6)5 (8)6 (9)0.0224ESR median (IQR)§13 (20)12 (13)13 (20)28.0 (23.5)0.0448MD Global (0-10) mean (SD)4.2 (2.7)3.2 (2.7)4.4 (2.6)4.8 (2.8)0.0030

§IQR: 75 – 25 percentile

£p-value: ANOVA for continuous variable, chi-square for categorical

Table 2.

Multinomial regression for initiating advanced DMARD therapy

Disease stage & Clinical Disease ActivityAdvanced DMARDAdjusted for Age, sex, education, comorbidityFullyAdjustedφNon-TNF vs TNFJAK vsTNFNon-TNF vs TNFJAK vsTNFAge1.01 (0.98, 1.05)1.01 (0.99, 1.04)1.01 (0.97, 1.05)1.02 (0.99, 1.05)Women vs Men1.98 (0.71, 5.58)1.33 (0.63, 2.80)2.35 (0.76, 7.27)1.72 (0.73, 4.02)Education(< HS vs ≥ HS)2.92 (1.28, 6.63)1.49 (0.78, 2.86)2.83 (1.12, 7.15)2.08 (0.97, 4.47)RDCI baseline1.35 (1.01, 1.81)1.21 (0.95, 1.53)1.30 (0.95, 1.78)1.23 (0.94, 1.60)Private Insurance(No vs Yes)NINI1.26 (0.47, 3.40)0.99 (0.44, 2.25)RF PositiveNINI1.47 (0.56, 3.85)1.84 (0.82, 4.12)CDAININI1.01 (0.98, 1.04)0.97 (0.94, 1.00)RegionQuebec vs Ontario (ON)NINI0.59 (0.20, 1.72)0.44 (0.20, 0.94)West vs ONNINI1.32 (0.29, 5.98)0.11 (0.01, 0.99)

φAdjusted for; baseline age, sex, education, RDCI; province; RF positive in first year; private insurance; CDAI at visit prior to initiation

Conclusion:

Patient and physician related factors (location of practice) determined which advanced therapeutic was prescribed. JAKi use is increasing in ERA.

Reference:

[1]Smolen JS, Landewé RBM, Bijlsma JWJ, et al. EULAR recommendations for the management of rheumatoid arthritis with synthetic and biological disease-modifying antirheumatic drugs: 2019 update. Annals of the Rheumatic Diseases Published Online First: 22 January 2020

Disclosure of Interests:

Madina Weiler: None declared, Orit Schieir: None declared, Marie-France Valois: None declared, Susan J. Bartlett Consultant of: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Speakers bureau: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, Gilles Boire Grant/research support from: Merck Canada (Registry of biologices, Improvement of comorbidity surveillance)

Amgen Canada (CATCH, clinical nurse)

Abbvie (CATCH, clinical nurse)

Pfizer (CATCH, Registry of biologics, Clinical nurse)

Hoffman-LaRoche (CATCH)

UCB Canada (CATCH, Clinical nurse)

BMS (CATCH, Clinical nurse, Observational Study Protocol IM101664. SEROPOSITIVITY IN A LARGE CANADIAN OBSERVATIONAL COHORT)

Janssen (CATCH)

Celgene (Clinical nurse)

Eli Lilly (Registry of biologics, Clinical nurse), Consultant of: Eli Lilly, Janssen, Novartis, Pfizer, Speakers bureau: Merck, BMS, Pfizer, Glen Hazlewood: None declared, Carol Hitchon Grant/research support from: UCB Canada; Pfizer Canada, Edward Keystone Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sanofi-Aventis, Consultant of: AbbVie, Amgen, AstraZeneca Pharma, Biotest, Bristol-Myers Squibb Company, Celltrion,

Crescendo Bioscience, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly

Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, UCB., Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb Canada, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Diane Tin: None declared, Carter Thorne Consultant of: Abbvie, Centocor, Janssen, Lilly, Medexus/Medac, Pfizer

, Speakers bureau: Medexus/Medac, Vivian Bykerk: None declared, Janet Pope Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead Sciences, Inc., Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Speakers bureau: UCB

FRI0030 MORE THAN HALF OF NEWLY DIAGNOSED RA PATIENTS ARE NOT CONVINCED OF THE NECESSITY OF RA MEDICINES: ASSOCIATIONS WITH RA CHARACTERISTICS, SYMPTOMS, AND FUNCTION IN THE CANADIAN EARLY ARTHRITIS COHORT (CATCH)

Background:

Although DMARDs are essential for early aggressive control of RA to reduce symptoms and disability, medication adherence is variable. Beliefs about the necessity of medications and safety concerns predict adherence and are modifiable.

Objectives:

To examine associations among RA medication necessity beliefs and concerns, sociodemographics, RA characteristics, symptom level and function in newly diagnosed RA patients.

Methods:

Baseline data were analyzed from participants in the Canadian Early Arthritis Cohort (CATCH) who enrolled between 2017-2020 and completed the Beliefs about Medicine Questionnaire (BMQ) and PROMIS-29. All met ACR1987 or 2010 ACR/EULAR criteria and had active RA at enrollment. BMQ Necessity (N) and Concerns (C) scores were classified ashigh(≥20) orlow(<20) and categorized into: Accepting (↑N ↓C); Ambivalent (↑N↑C); Sceptical (↓N↑C); and 4) Indifferent (↓N↓C). Groups were compared using ANOVA and chi-square tests.

Results:

The 362 patients were mostly white (83%) women (66%) with a mean (SD) age of 56 (15), symptom duration of 6 (3) months, and 32% were obese (BMI≥30). More than half (56%) were DMARD-naive or minimally exposed. Mean N and C scores were similar between men and women; 54% were classified asIndifferent, 31%Accepting, 9%Ambivalent,and 6%Sceptical.

As compared to those classified asAccepting, moreIndifferent participantssmoked, had a healthy weight, lower TJCs, and trend for lower CDAI (Table). Groups were similar by sociodemographics, symptom duration, and DMARD/steroid use, except fewerIndifferentpatients received MTX.Indifferentpatients had statistically and meaningfully lower patient global, depression, anxiety, fatigue and pain interference, and higher function and participation scores (Table).

Conclusion:

Many new RA patients had low medication necessity beliefs and concerns, and only 31% had high necessity beliefs and low concerns around diagnosis. Lifestyle and lower CDAI, TJCs, symptoms and functional impacts were associated with RA medication indifference. Identifying medication indifference can prompt discussions about medication beliefs/concerns to facilitate shared decision-making and adherence.

Disclosure of Interests:

Viviane Ta: None declared, Orit Schieir: None declared, Marie-France Valois: None declared, Glen Hazlewood: None declared, Carol Hitchon Grant/research support from: UCB Canada; Pfizer Canada, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, Diane Tin: None declared, Carter Thorne Consultant of: Abbvie, Centocor, Janssen, Lilly, Medexus/Medac, Pfizer, Speakers bureau: Medexus/Medac, Janet Pope Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead Sciences, Inc., Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Speakers bureau: UCB, Gilles Boire Grant/research support from: Merck Canada (Registry of biologices, Improvement of comorbidity surveillance)

Amgen Canada (CATCH, clinical nurse)

Abbvie (CATCH, clinical nurse)

Pfizer (CATCH, Registry of biologics, Clinical nurse)

Hoffman-LaRoche (CATCH)

UCB Canada (CATCH, Clinical nurse)

BMS (CATCH, Clinical nurse, Observational Study Protocol IM101664. SEROPOSITIVITY IN A LARGE CANADIAN OBSERVATIONAL COHORT)

Janssen (CATCH)

Celgene (Clinical nurse)

Eli Lilly (Registry of biologics, Clinical nurse), Consultant of: Eli Lilly, Janssen, Novartis, Pfizer, Speakers bureau: Merck, BMS, Pfizer, Edward Keystone Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sanofi-Aventis, Consultant of: AbbVie, Amgen, AstraZeneca Pharma, Biotest, Bristol-Myers Squibb Company, Celltrion, Crescendo Bioscience, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, UCB., Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb Canada, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Vivian Bykerk: None declared, Susan J. Bartlett Consultant of: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Speakers bureau: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie

AB0211 DIFFERENTIAL INFLUENCE OF CDAI COMPONENTS BASED ON DISEASE STATE IN RHEUMATOID ARTHRITIS PATIENTS: REAL-WORLD RESULTS FROM THE ONTARIO BEST PRACTICES RESEARCH INITIATIVE (OBRI)

Background:

Treat-to-target recommendations for rheumatoid arthritis (RA) dictate that remission or low disease activity should be aimed. Although numerous composite indices are available, the clinical disease activity index (CDAI) is commonly used in routine clinical care due to its simplicity and non-reliance on acute phase reactants.

Objectives:

The purpose of this analysis was to evaluate the CDAI properties both cross-sectionally and longitudinally in a cohort of RA patients followed in Canadian routine care.

Methods:

RA patients enrolled in the Ontario Best Practices Research Initiative (OBRI), with available follow-up for ≥6 months and data on CDAI, disease activity score based on 28 joints (DAS28), health assessment questionnaire (HAQ), and ACR/EULAR Boolean remission were included. For both the CDAI score and its change from baseline to 6 months, construct validity was assessed with principal component analysis, internal consistency with the Cronbach’s alpha coefficient (α), correlational validity with the Spearman’s rho coefficient, agreement in disease state classification with percent concordant pairs and the kappa statistic. Stratified analysis by presence of CDAI low disease activity (LDA) or remission was performed.

Results:

1,582 patients met the inclusion criteria. Principal component analysis showed that CDAI could be reduced to a single component when CDAI is >10 with SJC28 accounting for most variance in score and patient global assessment (PtGA) the least; whereas, when CDAI is ≤10, two distinct components were identified, the first comprising PtGA and physician global assessment (PhGA) and the second SJC28 and TJC28. In terms of internal consistency, high levels were observed for both CDAI at baseline (α=0.83) and its change from baseline to 6 months (α=0.81); however, the consistency between CDAI components was very low when CDAI is ≤10 (α=0.23).

Overall, a strong positive correlation was observed between CDAI and DAS28 (rho=0.86) and their changes (rho=0.87) while its correlation with HAQ was weak. When stratifying by CDAI levels, the correlation of CDAI with DAS28 was moderate when CDAI is ≤10 and very weak when CDAI is ≤2.8. Similarly, agreement in the classification of LDA between CDAI and DAS28 or HAQ was fair to moderate, and agreement in classification of remission was poor to fair.

Conclusion:

CDAI and DAS28 correlate well when disease activity is moderate or high and poorly in LDA or remission. PtGA had a stronger influence on CDAI at LDA or remission state compared to moderate or high disease state. Thus, careful interpretation of PtGA is necessary particularly in patients who are identified as CDAI non-remitters.

Disclosure of Interests:

Edward Keystone Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sanofi-Aventis, Consultant of: AbbVie, Amgen, AstraZeneca Pharma, Biotest, Bristol-Myers Squibb Company, Celltrion,

Crescendo Bioscience, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly

Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, UCB., Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb Canada, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Mohammad Movahedi Consultant of: Allergan, Angela Cesta: None declared, Claire Bombardier Grant/research support from: Dr Bombardier reports sources of funding for Ontario Best Practice Research Initiative Research grants from Abbvie, Janssen, Amgen, Medexus, Merck, Pfizer, and Novartis outside of the submitted work. Consulting Agreements: Abbvie, Covance, Janssen, Merck, Pfizer, Sanofi and Novartis outside of the submitted work. Advisory Board Membership: Hospira, Sandoz, Merck, Pfizer and Novartis outside of the submitted work., John Sampalis: None declared, Emmanouil Rampakakis: None declared

OP0263-HPR MAJOR STRESSORS IN THE YEAR PRIOR TO RA DIAGNOSIS: IMPACT ON PATIENT-REPORTED OUTCOMES ONE YEAR LATER

Background:

Stress is implicated in RA onset and poorer prognoses through changes in neuro-endocrine and autoimmune function. Although many people with RA link disease onset to recent stressful life events, results from retrospective studies are unclear.

Objectives:

To describe the incidence of major stressors(+STRESS) in year prior to diagnosis and compare characteristics and patient-reported outcomes (PROs) of newly diagnosed RA patients with and without+STRESSat 0 and 12 months.

Methods:

Data were from early RA patients (symptoms <1 yr) enrolled in the Canadian Early Arthritis Cohort (CATCH) from 2007-17 who met 1987/2010 ACR/EULAR criteria and had ≥12 months of follow-up. Patients reported major psychological (death, divorce/separation, family, financial, other) and physical (motor vehicle accident, surgery, major illness/infection, other) stressors in previous year. We used independent t-tests and chi square to compare characteristics by stressors at baseline, and multivariable regression to examine the impact of+STRESSon disease activity and PROs at 1 year, adjusting for age, sex, education, fibromyalgia, and SJC.

Results:

The 1933 adults were mostly female (72%), with a mean (SD) age of 55 (15) years. 52% reported 1+ stressors in previous year; family (48%), financial stress (36%), death (35%), surgery (28%), and major illness (26%) were the most common stressors. Patients with +STRESS were more likely to be women, younger, have more comorbidities including fibromyalgia, and higher mean DAS28. Patients with +STRESS also had significantly higher mean pain, fatigue, depression, sleep disturbance, patient global, and HAQ scores at baseline.

At 1 year, SJC and the proportion in DAS28 REM was similar between groups. However, PROs (pain, HAQ, Fatigue, Pt Global, Depression, Poor Sleep) remained higher in+STRESS, with evidence of an additive effect for number of stressors and having both physical and psychological stressors (Table). The greatest impacts were on mood, sleep disturbance, and fatigue.

Conclusion:

In this pan-Canadian early RA cohort, more than half reported 1+ stressful life events in the year prior to diagnosis. Individuals reporting major stressors had significantly worse pain, patient global, disability, depression, fatigue, and sleep disturbance at diagnosis; 1 year later, though disease activity was similar between groups, the effects of +STRESS on PROs persisted. Early RA patients with recent major stressors may benefit from emotional support and stress reduction to optimize how they feel and function.

Mean (SD) or N (%)No Stress(N=928; 48%)Physical(N=131; 7%)Psychological(N=658; 34%)Both(N=216; 11%)Age56 (15)56 (15)53 (14)52 (15)Women622 (67%)82 (63%)512 (78%)174 (81%)College Education464 (50%)76 (58%)345 (52%)126 (58%)Rheum Dis Comorbid Index1.1 (1.2)1.4 (1.4)1.1 (1.3)1.4 (1.3)OA or Spinal pain168 (18%)35 (27%)117 (18%)55 (25%)Fibromyalgia diagnosis15 (2%)2 (2%)13 (2%)11 (5%)Symptom duration (months)5.6 (3.0)5.7 (3.0)5.9 (3.0)5.9 (3.0)DAS28 – mean5.0 (1.4)5.1 (1.5)5.0 (1.5)5.2 (1.4)MTX ±csDMARDs679 (73%)100 (76%)489 (74%)166 (77%)Oral Steroids295 (32%)40 (31%)215 (33%)55 (25%)Pain (0-10)5.3 (2.8)5.5 (2.9)5.7 (2.8)6.2 (2.8)HAQ-DI1.0 (0.7)1.2 (0.7)1.1 (0.7)1.3 (0.7)Fatigue (0-10)4.7 (3.1)5.0 (3.0)5.7 (2.9)5.9 (2.9)Patient Global (0-10)5.6 (2.9)6.0 (2.9)6.0 (2.9)6.4 (3.0)Depression (SF12 MCS < 45.6)329 (35%)54 (41%)356 (54%)123 (57%)Poor sleep (0-10)4.5 (3.4)4.8 (3.3)5.3 (3.2)6.0 (3.1)

Disclosure of Interests:

Nicole Andersen: None declared, Orit Schieir: None declared, Marie-France Valois: None declared, Gilles Boire Grant/research support from: Merck Canada (Registry of biologices, Improvement of comorbidity surveillance)

Amgen Canada (CATCH, clinical nurse)

Abbvie (CATCH, clinical nurse)

Pfizer (CATCH, Registry of biologics, Clinical nurse)

Hoffman-LaRoche (CATCH)

UCB Canada (CATCH, Clinical nurse)

BMS (CATCH, Clinical nurse, Observational Study Protocol IM101664. SEROPOSITIVITY IN A LARGE CANADIAN OBSERVATIONAL COHORT)

Janssen (CATCH)

Celgene (Clinical nurse)

Eli Lilly (Registry of biologics, Clinical nurse), Consultant of: Eli Lilly, Janssen, Novartis, Pfizer, Speakers bureau: Merck, BMS, Pfizer, Janet Pope Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead Sciences, Inc., Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Speakers bureau: UCB, Glen Hazlewood: None declared, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, Carol Hitchon Grant/research support from: UCB Canada; Pfizer Canada, Diane Tin: None declared, Carter Thorne Consultant of: Abbvie, Centocor, Janssen, Lilly, Medexus/Medac, Pfizer

Speakers bureau: Medexus/Medac, Edward Keystone Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sanofi-Aventis, Consultant of: AbbVie, Amgen, AstraZeneca Pharma, Biotest, Bristol-Myers Squibb Company, Celltrion,

Crescendo Bioscience, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly

Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, UCB., Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb Canada, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Vivian Bykerk: None declared, Susan J. Bartlett Consultant of: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Speakers bureau: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie

FRI0024 HOW OFTEN DOES REACHING TARGET MISS THE MARK? LONGITUDINAL PATTERNS OF REMISSION IN REAL-WORLD EARLY RHEUMATOID ARTHRITIS PATIENTS

Background:

Early diagnosis and rapid initiation of DMARDs following a treat-to-target approach have made remission a realizable goal for many with RA. Yet, some patients are unable to sustain remission over time.

Objectives:

To describe longitudinal patterns of remission and identify predictors of sustained vs transient remission in real-world early RA patients.

Methods:

Data were from the Canadian Early Arthritis Cohort (CATCH), a prospective study of early RA patients (symptoms < 1 year) treated in rheumatology clinics across Canada from 2007- 2019. The sample was limited to patients with active disease at enrolment who later reached remission (SDAI<=3.3) and were followed for 12-24 months thereafter. Patients were classified as in sustained remission (Pattern 1) or transient remission with transient remission patients divided into those who transitioned from REM to LDA only (Pattern 2) and those who transitioned from REM to MDA or HDA (Pattern 3), over FU. Multi-adjusted multinomial regression was used to identify predictors of transient remission patterns.

Results:

The study included 1,419 (46%) CATCH participants that reached remission. At enrolment, most (70%) were female, mean(sd) SDAI was high (27(15)) and 92% were treated with csDMARDs. Only 47% remained in sustained remission by 12-months and, only 40% by 24 months (Pattern 1) (Figure). Among patients with transient remission patterns, transitions to LDA only (Pattern 2) were more common than to MDA/HDA over FU (Pattern 3) (Fig 1). Older age, female sex, smoking, higher comorbidity index and positive serology, were significantly associated with transient remission patterns (Table). There were also borderline significant associations between transient remission patterns and longer time to remission, lack of early MTX treatment and reducing treatment after remission (Table).

Table .

Adjusted Multinomial Regression Results of Predictors of Transient Remission Patterns over 24-Month Follow Up

Pattern 2 vs, Pattern 1OR (95% CI)Pattern 3 vs. Pattern 1OR (95% CI)Age1.01 (1.00, 1.02)1.01 (0.99, 1.02)Women vs Men1.78 (1.33, 2.39)1.63 (1.09, 2.44)Current smoker1.57 (1.09, 2.28)1.53 (0.95, 2.47)RDCI at baseline1.11 (0.99, 1.25)1.30 (1.13, 1.50)Seropositive1.38 (1.03, 1.85)1.21 (0.81, 1.80)MTX first 3 months1.18 (0.85, 1.63)0.76 (0.51, 1.12)Time to remission (months)1.01 (1.00, 1.01)1.01 (1.00, 1.02)Treatment reduction after REM vs. No Change1.33 (0.96, 1.86)1.01 (0.99, 1.02)

  Pattern 1: Sustained REM

  Pattern 2: Transient REM: Transitions to LDA only

  Pattern 3: Transient REM: Transitions to MDA/HDA

   RDCI: Rheumatic Disease Comorbidity Index (range 0-9)

  Treatment reduction: Change from biologic or JAK to csDMARD(s) OR reduction in number of csDMARDs OR change from MTX +/- csDMARDs to non-MTX csDMARD

Figure.

Distribution of Disease Activity States over 12-24 After First Achieving SDAI REM

Conclusion:

Results of this large longitudinal analysis of real-world data suggests that < 50% of patients that reach remission sustain remission for 12-24months. Closer monitoring of patients with prognostic indicators for transient remission and additional research focusing on why remission is lost may help improve the rates of sustained remission.

References:

[1]Ajeganova S, Huizinga T. Sustained remission in rheumatoid arthritis: latest evidence and clinical considerations. Ther Adv Musculoskelet Dis. 2017;9(10):249-62.

Disclosure of Interests:

Orit Schieir: None declared, Glen Hazlewood: None declared, Susan J. Bartlett Consultant of: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Speakers bureau: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Marie-France Valois: None declared, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, Gilles Boire Grant/research support from: Merck Canada (Registry of biologices, Improvement of comorbidity surveillance)

Amgen Canada (CATCH, clinical nurse)

Abbvie (CATCH, clinical nurse)

Pfizer (CATCH, Registry of biologics, Clinical nurse)

Hoffman-LaRoche (CATCH)

UCB Canada (CATCH, Clinical nurse)

BMS (CATCH, Clinical nurse, Observational Study Protocol IM101664. SEROPOSITIVITY IN A LARGE CANADIAN OBSERVATIONAL COHORT)

Janssen (CATCH)

Celgene (Clinical nurse)

Eli Lilly (Registry of biologics, Clinical nurse), Consultant of: Eli Lilly, Janssen, Novartis, Pfizer, Speakers bureau: Merck, BMS, Pfizer, Carol Hitchon Grant/research support from: UCB Canada; Pfizer Canada, Edward Keystone Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sanofi-Aventis, Consultant of: AbbVie, Amgen, AstraZeneca Pharma, Biotest, Bristol-Myers Squibb Company, Celltrion, Crescendo Bioscience, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, UCB., Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb Canada, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Janet Pope Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead Sciences, Inc., Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Speakers bureau: UCB, Carter Thorne Consultant of: Abbvie, Centocor, Janssen, Lilly, Medexus/Medac, Pfizer, Speakers bureau: Medexus/Medac, Diane Tin: None declared, Vivian Bykerk: None declared

FRI0032 REGIONAL AND WIDESPREAD PATTERNS OF NON-ARTICULAR PAIN ARE COMMON AT RA DIAGNOSIS AND CONTRIBUTE TO POOR OUTCOMES AT 12 MONTHS: A PROSPECTIVE STUDY OF PAIN PATTERNS IN CANADIANS WITH RA

Background:

Persistent pain can occur in early RA patients, despite improvement in synovitis and may be due to coexisting non-articular pain (NAP). Though NAP is often attributed to fibromyalgia and widespread NAP, regional NAP syndromes may be more common and under-recognized.

Objectives:

To describe patterns of NAP, predictors of persistent NAP and impact on outcomes in the first year following early RA diagnosis.

Methods:

Data were from participants enrolled in the Canadian Early Arthritis Cohort (CATCH) between2017-2019who completed 0,6,12-month evaluations with patient-reported outcomes [PROs] and clinical data available. We used the McGill Body Pain Diagram (BPD) to classify patients as experiencing no NAP, regional (RP:1-2 regions) or widespread NAP (WP:3-5 regions). Multinomial regression was used to identify baseline predictors of persistent RP and WP at 12-months. Multi-adjusted GEE with linear and logit links were used to estimate time-varying associations of NAP patterns with outcomes updated at each time point.

Results:

Study included 421 participants: 66% were female, with a mean(sd) age 56 (14); 72% were seropositive and 90% were treated with MTX ± csDMARDs as initial therapy. NAP at baseline was common (55%), with majority (62%) reporting regional NAP. NAP prevalence was 33% at 12 months (Figure). Female sex and baseline depressive symptoms were independent predictors of widespread NAP at 12 months while poorer function and lack of early MTX treatment independently predicted regional NAP, at 12 mos. Regional and widespread NAP were associated with lower likelihood of remission in adjusted models that accounted for changes in NAP and remission over time (Table).

Figure.

Point prevalence of regional and widespread NAP at baseline, 6 and 12 months.

Table .

Results of Multi-Adjusted GEE Logistic Regression showing Regional and Widespread NAP is associated with a reduced likelihood of achieving Stringent Remission Targets

Conclusion:

NAP is commonly reported in early RA pts seen in real world settings. Regional NAP was more common than WSP at all time-points, but both NAP patterns were associated lower odds of achieving remission targets by 12 months. These data support considering the role of NAP when assessing RA treatment efficacy during clinical visits and warrant different treatment approaches to reduce symptoms in RA patients receiving target-based care.

Disclosure of Interests:

Vivian Bykerk: None declared, Orit Schieir: None declared, Marie-France Valois: None declared, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, Gilles Boire Grant/research support from: Merck Canada (Registry of biologices, Improvement of comorbidity surveillance)

Amgen Canada (CATCH, clinical nurse)

Abbvie (CATCH, clinical nurse)

Pfizer (CATCH, Registry of biologics, Clinical nurse)

Hoffman-LaRoche (CATCH)

UCB Canada (CATCH, Clinical nurse)

BMS (CATCH, Clinical nurse, Observational Study Protocol IM101664. SEROPOSITIVITY IN A LARGE CANADIAN OBSERVATIONAL COHORT)

Janssen (CATCH)

Celgene (Clinical nurse)

Eli Lilly (Registry of biologics, Clinical nurse), Consultant of: Eli Lilly, Janssen, Novartis, Pfizer, Speakers bureau: Merck, BMS, Pfizer, Glen Hazlewood: None declared, Carol Hitchon Grant/research support from: UCB Canada; Pfizer Canada, Edward Keystone Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sanofi-Aventis, Consultant of: AbbVie, Amgen, AstraZeneca Pharma, Biotest, Bristol-Myers Squibb Company, Celltrion,

Crescendo Bioscience, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly

Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, UCB., Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb Canada, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Diane Tin: None declared, Carter Thorne Consultant of: Abbvie, Centocor, Janssen, Lilly, Medexus/Medac, Pfizer, Speakers bureau: Medexus/Medac, Janet Pope Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead Sciences, Inc., Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Speakers bureau: UCB, Susan J. Bartlett Consultant of: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Speakers bureau: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie

SAT0046 MODIFIED DISEASE ACTIVITY SCORE AT 3 MONTHS IS A SIGNIFICANT PREDICTOR FOR RAPID RADIOGRAPHIC PROGRESSION AT 12 MONTHS COMPARED WITH OTHER MEASURES

Background:

Progressive rheumatoid arthritis (RA) is responsible for joint damage causing disabilities with no agreement on which disease measures best predict radiographic progression

Objectives:

We aimed to determine which disease activity measures including disease activity score (DAS), modified (M) DAS28 (CRP), clinical disease activity index (CDAI), and health assessment questionnaire disability index (HAQ-DI) best predict rapid radiographic progression (RRP) in early RA patients at baseline (BL) and 3 months.

Methods:

PREMIER data, a 2-year, multicenter, double-blind active comparator–controlled study with methotrexate (MTX) naïve RA patients and active disease <3 years, were used. Only patients in the MTX arm were analyzed. RRP was defined as change in modified total Sharp (mTSS) > 3.5 at month 12. Logistic regression analysis assessed impact of measures at BL and 3 months on RRP at 12 months. Best cut-off points of M-DAS28(CRP) was also estimated using area under the receiver operating characteristic curve.

Results:

149 patients were included: female (n=113; 75.8%), positive RF (n=127; 85.2%), mean (SD) age 52.9 (13.3) years, disease duration 0.8 (0.9) year, DAS28(CRP) 6.3 (0.9). After adjusting for potential confounders, only M-DAS28(CRP) at BL (adjOR=3.29; 95% CI: 1.70-6.36) and 3 months (adjOR=2.56; 95% CI: 1.43-4.56) strongly predicted RRP at 12 months. M-DAS28(CRP) 4.5 and 2.6 at BL and 3 months maximized sensitivity and specificity for prediction of RRP.

Conclusion:

M-DAS28(CRP) was a stronger predictor at BL and 3 months for RRP compared with other disease activity measures. Removing tender joint count and patient global assessment from DAS28(CRP) improves prediction of RRP.

References:

[1] Breedveld FC, Weisman MH, Kavanaugh AF, Cohen SB, Pavelka K, van Vollenhoven R, et al. The PREMIER study: A multicenter, randomized, double-blind clinical trial of combination therapy with adalimumab plus methotrexate versus methotrexate alone or adalimumab alone in patients with early, aggressive rheumatoid arthritis who had not had previous methotrexate treatment. Arthritis and rheumatism. 2006;54(1):26-37.

Acknowledgments :

The authors wish to knowledge AbbVie Canada Inc. for providing patients data.

Disclosure of Interests:

Mohammad Movahedi Consultant of: Allergan, Deborah Weber: None declared, Pooneh Akhavan: None declared, Edward Keystone Grant/research support from: AbbVie; Amgen; Gilead Sciences, Inc; Lilly Pharmaceuticals; Merck; Pfizer Pharmaceuticals; PuraPharm; Sanofi, Consultant of: AbbVie; Amgen; AstraZeneca Pharma; Bristol-Myers Squibb Company; Celltrion; F. Hoffman-La Roche Ltd.; Genentech, Inc; Gilead Sciences, Inc.; Janssen, Inc; Lilly Pharmaceuticals; Merck; Myriad Autoimmune; Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis., Speakers bureau: AbbVie; Amgen; Bristol-Myers Squibb; Celltrion; F. Hoffman-La Roche Ltd, Janssen, Inc; Merck; Pfizer Pharmaceuticals; Sanofi-Genzyme; UCB

SAT0053 ESTIMATING REAL-WORLD UNMET NEEDS FOR REACHING REMISSION IN THE FIRST YEAR FOLLOWING EARLY RA DIAGNOSIS: RESULTS FROM THE CANADIAN EARLY ARTHRITIS COHORT (CATCH)

Background:

Several composite RA disease activity indices are commonly used in clinical practice and research. Different disease activity indices however can be inconsistent in classifying remission (REM).

Objectives:

1) Compare remission prevalence across 4 common RA indices; 2) compare changes in remission across indices; and, 3) Identify predictors of persistent active disease across all indices, in real-world early RA patients over 1 year follow up.

Methods:

Data were from patients with early RA (symptoms < 1 year) enrolled in the Canadian Early Arthritis Cohort (CATCH) between 2007 and 2018. Participants had active disease at enrolment, were treated with csDMARDs and completed standardized clinical assessments every 3-months. Remission status was assessed using 4 indices: 1) DAS28< 2.6 OR DAS28CRP < 2.5, 2) CDAI ≤ 2.8, 3) SDAI≤ 3.3, and 4) ACR/EULAR Boolean remission – SJC28, TJC28, CRP, PGA all ≦1. T-tests/ chi-squared tests were used to compare differences in remission prevalence by 1 year, and changes in remission before and after a QI program. Logistic regression was used to identify predictors of persistent active disease on all 4 indices.

Results:

1202 adults were eligible for this analysis. At enrolment, 877 (73%) were women, mean (sd) age was 55 (14), average disease activity was high (DAS28 5.1 (1.4); CDAI 27 (14); SDAI 29 (15)). Prevalence of remission by 12-months follow up was 14-21% higher when estimated with the DAS28 compared with CDAI, SDAI and Boolean criteria, and 378 (31%) did not achieve remission according to any of the 4 indices (Fig 1). Improvement in remission after a QI program however was similar across all 4 indices(~+15-17%). In adjusted logistic regression, Persistent active disease across all measures was most strongly associated with positive serostatus and smoking in men, and with obesity and more tender joints in women. Pain and lower education were predictors in BOTH men and women (Table 2)

Table 1.

Multivariable Logistic Regression Predicting Persistent Active Disease by 12-months across ALL RA indices

Conclusion:

In the absence of a single “best measure” that also takes in to account the patient’s perspective, we estimate unmet needs for achieving remission in the first year of follow up in 1 in 3 ERA patients who did not achieve remission by ANY of the 4 indices.

References:

[1] Kuriya B, Sun Y, Boire G, Haraoui B, etal. Remission in Early Rheumatoid Arthritis – A Comparison of New ACR/EULAR Remission Criteria to Established Criteria.J Rheumatol2012;39:1155-1158.

Disclosure of Interests:

Orit Schieir: None declared, Susan J. Bartlett Consultant of: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Speakers bureau: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Marie-France Valois: None declared, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, Gilles Boire Grant/research support from: Merck Canada (Registry of biologices, Improvement of comorbidity surveillance)

Amgen Canada (CATCH, clinical nurse)

Abbvie (CATCH, clinical nurse)

Pfizer (CATCH, Registry of biologics, Clinical nurse)

Hoffman-LaRoche (CATCH)

UCB Canada (CATCH, Clinical nurse)

BMS (CATCH, Clinical nurse, Observational Study Protocol IM101664. SEROPOSITIVITY IN A LARGE CANADIAN OBSERVATIONAL COHORT)

Janssen (CATCH)

Celgene (Clinical nurse)

Eli Lilly (Registry of biologics, Clinical nurse), Consultant of: Eli Lilly, Janssen, Novartis, Pfizer, Speakers bureau: Merck, BMS, Pfizer, Glen Hazlewood: None declared, Carol Hitchon Grant/research support from: UCB Canada; Pfizer Canada, Edward Keystone Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sanofi-Aventis, Consultant of: AbbVie, Amgen, AstraZeneca Pharma, Biotest, Bristol-Myers Squibb Company, Celltrion,

Crescendo Bioscience, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly

Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, UCB., Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb Canada, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Janet Pope Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead Sciences, Inc., Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Speakers bureau: UCB, Carter Thorne Consultant of: Abbvie, Centocor, Janssen, Lilly, Medexus/Medac, Pfizer

, Speakers bureau: Medexus/Medac, Diane Tin: None declared, Vivian Bykerk: None declared

FRI0037 ALL-CAUSE MORTALITY IN EARLY RHEUMATOID ARTHRITIS PREDICTED BY HEALTH ASSESSMENT QUESTIONNAIRE AT ONE YEAR

Background:

Patients with RA are at greater risk of mortality than the general population. Higher HAQ disability has been associated with hospitalizations and mortality in established RA; whether HAQ disability predicts mortality in early RA (ERA) is unknown.

Objectives:

The objective of this study is to analyze how well the HAQ can predict future mortality in patients with early RA.

Methods:

Data were from adult early RA patients (symptoms <1 year) enrolled in the Canadian Early Arthritis Cohort (CATCH) between 2007 and 2017; who initiated treatment with 1 or more DMARDs and had completed HAQ data at baseline and 1 year. Descriptive statistics, t-tests and chi-square tests were used to summarize and compare baseline patient characteristics including sociodemographic variables, RA characteristics and comorbidities amongst deceased and non-deceased patients. Discrete-time proportional hazards models were used to estimate crude and multi-adjusted associations between HAQ at baseline and 1 year, respectively, with all-cause mortality in each year of follow up.

Results:

This study included 1724 patients with early RA; mean age was 55 years and 72% were female. In 10 years of follow up, 62 deaths (2.4%) occurred. Deceased patients had higher HAQ scores and DAS28 scores at baseline and at 1 year versus the non-deceased group. Age, male sex, lower education, smoking, more comorbidities, higher baseline disease activity and steroid use were associated with mortality in unadjusted survival models (Table 1). Contrary to HAQ at baseline, the association between all-cause mortality and HAQ at 1 year remained significant even after adjusting for age, gender, comorbidities, disease activity, smoking, education, seropositivity, symptom duration and steroid use in adjusted survival models (Table 2).

Table 1.

Unadjusted survival model: Association of each variable with all-cause mortality

Baseline VariableUnadjustedHazard OR95% CISocio-DemographicAge (years)1.101.07 – 1.13Female0.370.22 – 0.62Caucasian (white or European)1.010.46 – 2.24Aboriginal1.710.61 – 4.76Education > high school degree0.480.28 – 0.82Current Smoker1.811.01 – 3.24Rheumatic Disease Comorbidity Index (0-9)1.601.36 – 1.87RA CharacteristicsSymptom duration (months)0.990.91 – 1.08Seropositivity in first year1.110.55 – 2.23DAS28 ESR or CRP if ESR is missing1.261.06 – 1.51Oral Steroid use1.751.03 – 2.98Table 2.

Multivariable discrete-time survival models: HAQ baseline vs 1 year

ModelModel 1:Crude(Time + HAQ-DI)Model 2:Adjusted for age + sexModel 3:Adjusted for Model 2 + DAS28 + RDCIModel 4:Adjusted for Model 3 + education, smoking, seropositivity, symptom duration and oral steroids useModel 5:Adjusted for Model 3 + smoking, symptom duration onlyHAQ-DI (0-3) (at baseline)1.461.02 – 2.091.370.96 – 1.951.250.81 – 1.941.320.85 – 2.041.300.84 – 2.00HAQ-DI (0-3) (at 1 year)2.581.78 – 3.722.401.63 – 3.521.751.10 – 2.771.871.16 – 3.021.731.09 – 2.74

*Hazard OR, 95% CI

~HAQ-DI: (Health Assessment Questionnaire Disability Index); RDCI: Rheumatic Disease Comorbidity Index; DAS28: Disease Activity Score

Conclusion:

Higher HAQ at 1 year was significantly associated with all-cause mortality in a large early RA cohort suggesting that poorer disease control and function in the first year of RA contributes to higher mortality.

Disclosure of Interests:

Safoora Fatima: None declared, Orit Schieir: None declared, Marie-France Valois: None declared, Susan J. Bartlett Consultant of: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Speakers bureau: Pfizer, UCB, Lilly, Novartis, Merck, Janssen, Abbvie, Louis Bessette Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Consultant of: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Roche, Sanofi, UCB Pharma, Speakers bureau: AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Merck, Novartis, Pfizer, Sanofi, Gilles Boire Grant/research support from: Merck Canada (Registry of biologices, Improvement of comorbidity surveillance)

Amgen Canada (CATCH, clinical nurse)

Abbvie (CATCH, clinical nurse)

Pfizer (CATCH, Registry of biologics, Clinical nurse)

Hoffman-LaRoche (CATCH)

UCB Canada (CATCH, Clinical nurse)

BMS (CATCH, Clinical nurse, Observational Study Protocol IM101664. SEROPOSITIVITY IN A LARGE CANADIAN OBSERVATIONAL COHORT)

Janssen (CATCH)

Celgene (Clinical nurse)

Eli Lilly (Registry of biologics, Clinical nurse), Consultant of: Eli Lilly, Janssen, Novartis, Pfizer, Speakers bureau: Merck, BMS, Pfizer, Glen Hazlewood: None declared, Carol Hitchon Grant/research support from: UCB Canada; Pfizer Canada, Edward Keystone Grant/research support from: AbbVie, Amgen, Bristol-Myers Squibb, F. Hoffmann-La Roche Inc, Gilead, Janssen Inc, Lilly Pharmaceuticals, Pfizer Pharmaceuticals, Sanofi-Aventis, Consultant of: AbbVie, Amgen, AstraZeneca Pharma, Biotest, Bristol-Myers Squibb Company, Celltrion,

Crescendo Bioscience, F. Hoffmann-La Roche Inc, Genentech Inc, Gilead, Janssen Inc, Lilly

Pharmaceuticals, Merck, Pfizer Pharmaceuticals, Sandoz, UCB., Speakers bureau: Amgen, AbbVie, Bristol-Myers Squibb Canada, F. Hoffmann-La Roche Inc., Janssen Inc., Merck, Pfizer Pharmaceuticals, Sanofi Genzyme, UCB, Diane Tin: None declared, Carter Thorne Consultant of: Abbvie, Centocor, Janssen, Lilly, Medexus/Medac, Pfizer, Speakers bureau: Medexus/Medac, Vivian Bykerk: None declared, Janet Pope Grant/research support from: AbbVie, Bristol-Myers Squibb, Eli Lilly & Company, Merck, Roche, Seattle Genetics, UCB, Consultant of: AbbVie, Actelion, Amgen, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Eicos Sciences, Eli Lilly & Company, Emerald, Gilead Sciences, Inc., Janssen, Merck, Novartis, Pfizer, Roche, Sandoz, Sanofi, UCB, Speakers bureau: UCB

OP0211 TIME TO DISCONTINUATION OF TOFACITINIB AND TNF INHIBITORS IN RHEUMATOID ARTHRITIS PATIENTS WITH AND WITHOUT METHOTREXATE: DATA FROM A RHEUMATOID ARTHRITIS COHORT

Background:

Tofacitinib (TOFA) is an oral, small molecule drug used for rheumatoid arthritis (RA) treatment and is prescribed alone or with methotrexate (MTX). Tofa can be used as an alternative to biologic disease modifying antirheumatic drugs (bDMARDs) including tumor necrosis factor inhibitors (TNFi).

Objectives:

We aimed to evaluate the discontinuation rate of this drug, with and without concurrent MTX in comparison with TNFi, in patients with RA in the Ontario Best Practices Research Initiative (OBRI).

Methods:

RA patients enrolled in the OBRI initiating their TOFA or TNFi (adalimumab, certolizumab, etancercept, golimumab, and infliximab) within 30 days prior to or any time after enrolment between 1stJune 2014 (TOFA approval date in Canada) and 31stDec 2018 were included. Time to discontinuation (due to any reason) were assessed using Kaplan-Meier survival (adjusted for propensity score using inverse probability of treatment weight) to compare patients with and without MTX use at initiation of TOFA or TNFi.

Results:

A total of 565 patients initiated TOFA (n=208) or TNFi (n=357). Of those, 106 (51%) and 222 (62%) were treated with MTX in the TOFA and TNFi group, respectively and mean (SD) disease duration were 13.1 (9.4) and 9.5 (9.4) years. In the TOFA group, 86% were female and mean (SD) age at treatment initation was 60.4 (10.6) years. In the TNFi group 82% were female and mean age (SD) at treatment initation was 57.0 (12.6) years. The TOFA group was more likely to have prior biologic use (61.5%) compared with the TNFi group (31%). At treatment initiation, the mean (SD) clinical disease activcity index was 24.8 (12.1) in the TOFA group and 21.8 (12.0) in the TNFi group.

Over a mean of 17.3 month follow-up, discontinuation was reported in 75 (36%) and 103 (29%) of all TOFA and TNFi patients, respectively. After adjusting for propensity score, patients treated with TNFi and MTX remained on treatment longer than those treated without MTX (Logrank p=0.002) while there was no significant difference in TOFA discontinuation in patients with and without MTX (Logrank p=0.31).

Conclusion:

In this real world data study, we found that TOFA retention is similar in patients with and without MTX, while patients treated with TNFi and MTX remained on treatment longer than those treated without MTX. Merging data with other RA registries in Canada is proposed to increase study power and to provide more robust results.

Disclosure of Interests:

Mohammad Movahedi Consultant of: Allergan, Angela Cesta: None declared, Xiuying Li: None declared, Edward Keystone Grant/research support from: AbbVie; Amgen; Gilead Sciences, Inc; Lilly Pharmaceuticals; Merck; Pfizer Pharmaceuticals; PuraPharm; Sanofi, Consultant of: AbbVie; Amgen; AstraZeneca Pharma; Bristol-Myers Squibb Company; Celltrion; F. Hoffman-La Roche Ltd.; Genentech, Inc; Gilead Sciences, Inc.; Janssen, Inc; Lilly Pharmaceuticals; Merck; Myriad Autoimmune; Pfizer Pharmaceuticals, Sandoz, Sanofi-Genzyme, Samsung Bioepsis., Speakers bureau: AbbVie; Amgen; Bristol-Myers Squibb; Celltrion; F. Hoffman-La Roche Ltd, Janssen, Inc; Merck; Pfizer Pharmaceuticals; Sanofi-Genzyme; UCB, Claire Bombardier Grant/research support from: Dr Bombardier reports sources of funding for Ontario Best Practice Research Initiative Research grants from Abbvie, Janssen, Amgen, Medexus, Merck, Pfizer, and Novartis outside of the submitted work. Consulting Agreements: Abbvie, Covance, Janssen, Merck, Pfizer, Sanofi and Novartis outside of the submitted work. Advisory Board Membership: Hospira, Sandoz, Merck, Pfizer and Novartis outside of the submitted work.