OP0266 TREATMENT DISCONTINUATION DUE TO ADVERSE EVENTS AS AN OVERALL MEASURE OF TOLERANCE AND SAFETY OF JAK-INHIBITORS: AN INTERNATIONAL COLLABORATION OF REGISTRIES OF RHEUMATOID ARTHRITIS PATIENTS (THE “JAK-pot” STUDY)

Background

The recently presented “ORAL Surveillance Study” has suggested increased risk of serious adverse events (AEs) with tofacitinib, a JAK-inhibitor (JAKi), compared to a comparator TNF-inhibitor (TNFi). Currently, there is limited real world evidence for the tolerability and safety of JAKi (1).

Objectives

To assess the safety of JAKi compared to other biologic agents in rheumatoid arthritis (RA) patients in a real-world population, by evaluating treatment discontinuation for AEs.

Methods

Pooled patient database from 16 national RA registries from across Europe, Québec (Canada), Turkey, and Israel were used. Treatment discontinuation due to AEs by treatment groups, JAKi versus (vs) TNFi and JAKi vs bDMARDs with other modes of action (OMA), were compared as an overall measure of tolerability and safety of JAKi. Standard descriptive statistics were used for baseline characteristics. We plotted unadjusted cumulative incidence, then the cause-specific Cox model was used to account for competing risks, and to obtain association between covariates and the instantaneous hazard rate for AEs. Variables listed in Table 1 were used for adjustment in the fully-adjusted cause-specific Cox model.

Table 1.

Baseline characteristics of the study population

JAKi1(BARI, FILGO,TOFA,UPA)OMA2(ABA, ANAK, SARI, TOCI)TNFi3(ADA, CERT, ETAN, GOL, INFL)n = 9208n = 16737n = 64533Treatment duration* (yrs)0.7 [0.2, 1.7]1.1 [0.4, 2.8]1.5 [0.5, 3.9]Age57.556.853.2Female (%)81.380.773.2Disease duration (yrs)9.913.110.7Seropositivity (%)78.775.969.8Previous b/tsDMARD (%) 034.030.859.7 120.925.924.3 216.621.710.4 3 or more28.521.55.6Concomitant GC (%)44.650.741.3Concomitant CsDMARD (%)  MTX22.622.028.8  MTX + other9.59.713.1  None50.552.543.5  Other17.415.914.7CRP13.2 (24.1)13.3 (25.6)12.3 (24.1)CDAI23.7 (13.8)22.9 (13.5)22.6 (14.0)DAS 284.7 (1.5)4.7 (1.6)4.6 (1.6)HAQ1.2 (0.7)1.2 (0.7)1.1 (0.7)BMI27.1 (5.9)26.8 (5.8)26.8 (5.8)Patients with at least one Comorbidity (%)51.753.949.6

csDMARDs = classical synthetic DMARDs, MTX = methotrexate, GC = glucocorticoids, CRP = C-reactive protein, CDAI = Clinical Disease Activity Index, DAS 28 = Disease Activity Score 28, HAQ = Health Assessment Questionnaire, BMI = Body Mass Index, *Treatment duration (median [IQR]) = Last visit date – start date (if treatment is ongoing), treatment stop date – treatment start date (if treatment has stopped)

. 1BARI (baricitinib; 44.41 %), FILGO (filgotinib; 0.23%), TOFA (tofacitinib; 49.59%), UPA (upadacitinib; 5.78%); 2ABA (abatacept; 39.96%), ANAK (anakinra; 2.64%), SARI (sarilumab; 3.14%), TOCI (tocilizumab; 52.55%); 3ADA (adalimumab; 31.00%), CERT (certolizumab; 8.33%), ETAN (etanercept; 38.83%), GOLI (golimumab; 9.36%), INFL (infliximab; 12.56%)

Results

90,478 treatment courses were included in the analysis (Table 1). We observed similar crude incidence rate of treatment discontinuation due to AEs between JAKi and TNFi, but less in JAKi vs OMA (Figure 1). The fully adjusted hazard rate of treatment stop for AEs was also similar in JAKi vs TNFi (HR = 1.02 (95% CI 0.92 – 1.13)), and in JAKi vs OMA (HR= 1.08 (95% CI 0.97 – 1.20)). The rate of treatment stop for AEs was higher in women (HR = 1.29 (95% CI 1.21 – 1.37)) and with an increasing number of previous b/tsDMARDs (HR = 1.50; 1.48; 1.68 for 1, 2, and 3 or more previous b/ts DMARDs, respectively).

Figure 1.

Comparison of cumulative incidence of treatment discontinuation for adverse events in JAKi, TNFi, and OMA group

Conclusion

After adjusting for potential confounders, the rate of treatment discontinuation for AEs was comparable between JAKi and OMA or TNFi. Treatment discontinuation for AEs comprises a wide range of AEs; future analyses will be performed to investigate specific AEs, such as cancer, serious infections or major adverse cardiovascular events.

References

[1]Ann Rheum Dis 2022. doi: 10.1136/annrheumdis-2021-221915.

Disclosure of Interests

Eric Nham: None declared, Romain Aymon: None declared, Denis Mongin: None declared, Sytske Anne Bergstra: None declared, Denis Choquette Speakers bureau: DC reports speaker or consultant fees from Abbvie, Amgen, Eli Lilly, Fresenius-Kabi,Pfizer, Novartis, Sandoz, Tevapharm, Consultant of: Stated above, Catalin Codreanu Speakers bureau: CC reports speaker/consulting fees from AbbVie, Amgen, Astra Zeneca, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Richter, Consultant of: Stated above, Ori Elkayam Consultant of: OE has received consultant and honorary fees from Pfizer, Lilly, Abbvie, Novartis, Jansen, BI, Kimme Hyrich Speakers bureau: KLH has received speaker honoraria from Abbvie, Grant/research support from: KLH has received grant income from Pfizer and BMS, Florenzo Iannone Speakers bureau: FI has received consulting/speaker’s fees from Abbvie, BMS, Celgene, Eli Lilly, Galapagos, Janssen, MSD, Novartis, Pfizer, SOBI, Roche and UCB, Consultant of: Stated above, Nevsun Inanc Speakers bureau: NI has received consultant and speaker/honoraria from Abbvie, Lilly, MSD, Novartis, Pfizer, Roche, Amgen, Celltrion,UCB., Consultant of: Stated above, Lianne Kearsley-Fleet: None declared, Eirik kristianslund: None declared, Tore K. Kvien Speakers bureau: TKK has received fees for speaking and/or consulting from several companies among them Pfizer, AbbVie, Lilly and Galapagos/Gilead, Consultant of: Stated above, Burkhard Leeb Speakers bureau: BFL has received speaker honoraria from Sandoz, Abbvie, Eli-Lilly, Pfizer, Roche, Grünenthal, Biogen, Celgene, Galina Lukina Speakers bureau: GVL has received speaker fees from Abbvie, Lilly, Novartis, MSD, Roche, Pfizer, Dan Nordström Consultant of: DCN has acted as consultant for AbbVie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Karel Pavelka Speakers bureau: KP has received honoraria for lectures: MSD, Pfizer, Roche, Eli Lilly, Medac, UCB, SOBI, Biogen, Sandoz, Viatris, Manuel Pombo-Suarez Speakers bureau: MPS reports advisor and speaker honoraria from Janssen, Lilly, MSD, Novartis, Sanofi, Consultant of: Stated above, Ziga Rotar Speakers bureau: ZR has received fees for speaking/consulting from several companies among them Pfizer, AbbVie, and Eli Lilly, Consultant of: Stated above, Maria Jose Santos Speakers bureau: MJS has received speaker fees from Abbvie, AstraZeneca, Lilly, Novartis and Pfizer, Delphine Courvoisier: None declared, Kim Lauper Speakers bureau: KL reports speakers fees for Pfizer, Viatris and Celltrion, Consultant of: KL reports consulting fees for Pfizer, Axel Finckh Speakers bureau: AF reports honoraria and consultancies from Pfizer, BMS, MSD, Eli-Lilly, AbbVie, Galapagos, Mylan, UCB, Viatris, Consultant of: Stated above, Grant/research support from: AF reports grants from Pfizer INC, AbbVie, Galapagos, Eli Lilly

AB0895 Residual burden and disease activity of Canadian PsA patients treated with advanced therapies: preliminary results from a multiple registry analysis (UNISON-PsA)

Background

Given the availability of advanced therapies in PsA with different modes of action, it is of interest to characterize their impact on overall clinical outcomes.

Objectives

To describe residual disease activity in Canadians with PsA treated with advanced therapies.

Methods

Multi-region, observational, retrospective analysis of data from Rhumadata (Quebec) and International Psoriasis and Arthritis Research Team (IPART) Canadian registries was performed. Data from each registry and region were analyzed separately using a common statistical analysis plan to generate descriptive statistics. Patients included in the registries were eligible if they were adults at the time of PsA diagnosis and were treated with an advanced therapy for ≥6 months initiated between January 2010 and December 2019. Residual disease activity was defined as failing to achieve MDA (defined as achieving ≥5 of: TJC ≤1; SJC ≤1; PASI ≤1 or BSA ≤3%; patient pain VAS score of ≤15 mm; patient global disease activity VAS score of ≤20 mm; HAQ score ≤0.5; and tender entheseal points ≤1) (primary endpoint), or DAPSA score ≥14 (secondary endpoint) within 6 months of initiation of an advanced therapy (TNFi, IL-12/23i, IL-17i, PDE4i, CTLA4i or JAKi).

Results

1,866 subjects (Atlantic [IPART; Newfoundland]: N=83; Quebec [Rhumadata]: N=687; Ontario [IPART]: N=966; West [IPART; British Columbia, Manitoba]: N=130) were included in this preliminary analysis. Baseline characteristics are presented in Table 1. Overall, 899 were receiving their 1st advanced therapy, 464 were receiving their 2nd, and 264 had received ≥3. The most common therapy class was TNFi, followed by IL-17i. 18/21 (85.7%) subjects in the Atlantic region with an assessment, 184/246 (74.8%) in Quebec, 391/571 (68.1%) in Ontario, and 30/43 (69.8%) in Western Canada failed to achieve MDA within 6 months following advanced therapy initiation. Failure to achieve MDA within the allotted period was higher among patients receiving an IL-17i compared with a TNFi. There was no appreciable effect of lines of therapy. Also, 74 of 110 (67.3%) patients with an assessment in Quebec, 201/365 (55.1%) in Ontario and 3/3 (100%) in the West failed to achieve at least low disease activity (LDA; DAPSA ≤14) within 6 months following initiation of an advanced therapy. Data were not available for the Atlantic region. The proportion of patients not achieving LDA by advanced therapy was similar for those receiving a TNFi and IL-17i but increased with line of therapy.

Table 1.

Patient demographic and baseline characteristics, and response to treatment

Atlantic (N=83)Quebec (N=687)Ontario (N=966)West (N=130)Age (years, mean [SD])50.3 (11.1)50.7 (12.1)49.1 (12.9)46.7 (12.1)Female (n [%])44/83 (53.0)346/687 (50.4)427/966 (44.2)81/128 (62.3)BMI (kg/m2, n, mean [SD])15, 30.8 (3.6)553, 29.6 (6.6)579, 30.6 (6.9)45, 32.8 (10.6)Time since diagnosis (years, N, mean [SD])83, 8.7 (8.7)687, 7.1 (7.9)895, 11.7 (11.1)74, 11.7 (8.9)HLA-B27 positive (n/N [%])N/A58/335 (17.3)86/648 (13.3)N/APresence of EAMs (n/N [%])4/44 (9.1)27/687 (3.9)65/693 (9.4)2/33 (6.1%)Fulfillment of CASPAR (n/N [%])N/A391/687 (56.9)100/100 (100)N/ATherapy class (n [%]):*TNFi66 (79.5)478 (69.6)651 (67.3)104 (80.0)IL-17i11 (13.3)106 (15.4)191 (19.9)21 (16.2)IL-12/23i6 (7.2)33 (4.8)124 (12.9)5 (3.9)PDE4i48 (7.0)Other22 (3.2)Failure to achieve MDA within 6 months of starting therapy (n/N [%])**18/21 (87.5)184/246 (74.8)391/571 (68.1)30/43 (69.8)Failure to achieve DAPSA ≤14 within 6 months of starting therapy (n/N [%])**N/A74/110 (67.3)201/365 (55.1)3/3 (100.0)

*Patients may be taking >1 advanced therapy, **Not all patients had assessments of disease activity.

Conclusion

Preliminary data show approximately three quarters of Canadians with PsA failed to achieve MDA or LDA within 6 months of initiating an advanced therapy. Disease duration is a possible explanation for not achieving MDA or LDA; better therapeutic approaches are needed to achieve these outcomes in patients with PsA.

Acknowledgements

The authors wish to thank Dr. Steve Ramkissoon, for supporting the statistical analysis of the IPART registry. Medical writing and statistical support (funded by Abbvie) were provided by John Howell and Hong Chen, respectively, from McDougall Scientific. Financial support for the study was provided by AbbVie. AbbVie participated in the design of the study, interpretation of data, review, and approval of this publication. All authors contributed to the development of the publication and maintained control over the final content.

Disclosure of Interests

Denis Choquette Speakers bureau: Amgen, Abbvie, CIHR, Novartis, Pfizer, Fresenius-Kabi, Eli Lilly, Sandoz, Tevapharm, Consultant of: Amgen, Abbvie, CIHR, Novartis, Pfizer, Fresenius-Kabi, Eli Lilly, Sandoz, Tevapharm, Grant/research support from: Rhumadata is supported through grants and research contracts from Amgen, Abbvie, CIHR, Novartis, Pfizer, Fresenius-Kabi, Eli Lilly, Sandoz, Tevapharm., Vinod Chandran Consultant of: AbbVie, Amgen, BMS, Eli Lilly, Janssen, Novartis, UCB, Pfizer, Employee of: Spouse is an employee of AstraZeneca, Marie-Claude Laliberté Shareholder of: AbbVie Corp., Employee of: AbbVie Corp., Pierre-André Fournier Shareholder of: AbbVie Corp., Employee of: AbbVie Corp., Tanya Girard Shareholder of: AbbVie Corp., Employee of: AbbVie Corp., Mitchell Sutton: None declared, Dafna D Gladman Consultant of: AbbVie, Amgen, BMS, Galapagos, Gilead, Eli Lilly, Janssen Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pfizer, UCB

POS0093 HETEROGENEITY IN ADVERSE EVENT ASSESSMENT BETWEEN COUNTRIES PARTICIPATING IN AN INTERNATIONAL COLLABORATION OF REGISTRIES OF RHEUMATOID ARTHRITIS PATIENTS USING JANUS KINASE INHIBITORS (THE JAK-POT STUDY)

Background:

Industry, regulators, and the rheumatology community have recognized the need for observational studies to monitor the safety of new antirheumatic agents. Registries provide a unique opportunity to understand the safety of newer therapies, but pharmacovigilance studies require large number of patients to evaluate rare drug-related adverse-events (AEs). Because JAK-inhibitors (JAKi) have only recently been approved for the treatment of rheumatoid arthritis, it makes sense to combine data from several registries in order to obtain a sufficiently large sample size to promote earlier detection of adverse events.

Objectives:

The purpose of this analysis was to evaluate how AEs are assessed in the various registries in preparation for a collaborative pharmacovigilance analysis, and present preliminary results.

Methods:

The “JAK-pot” collaboration includes 19 RA registries. The principal investigators of the participating registries were sent a structured questionnaire on AE assessment and 18 (94%) provided complete responses on the AE assessment procedures of their registries. We present simple descriptive statistics of the AE assessment procedures employed by the participating registries.

Results:

The 19 registries represent 7186 patients initiating a JAKi (Table 1), who are on average 57 years old, with a mean disease duration 11 years, seropositive (83%), female (82%) and with moderate disease activity at treatment initiation.

Table 1.Country, registryN° of patients on JAKi includedAustria, BIOREG87Belgium, TARDIS2113Canada, RHUMADATA363Czech Republic, ATTRA197Denmark, DANBIO506Finland, ROB-FIN229Germany, RABBIT620Italy, GISEA244Israel, I-RECORD96Netherlands, METEOR4Norway, NOR-DMARD97Portugal, REUMA.PT44Romania, RRBR252Russia, ARBITER428Slovenia, biorx.si141Spain, BIOBADASER139Switzerland, SCQM738Turkey, TURKBIO404UK, BSRBR484

After ineffectiveness, AEs was the second most common reason for JAKi discontinuation (25.5%), with large differences between registries (Figure 1).

Of the participating registries, 2 registries do not collect AEs, while 16 (89%) assess incident AEs, by means of a pre-specified extraction form (3 registries), by free text (5 registries), by a combination of both (6 registries) and/or the use of linkage to external electronic records (3registries). AEs are coded using a predefined coding system by 11 registries (MeDRA (8), other (3)), but nearly all are recording the severity of the AE (15, 94%), AE related-death (15, 94%), or AE-related hospitalisation (15, 94%). AEs of special interest, such as serious infections (15, 94%), thromboembolic events (15, 94%), or shingles (9, 56%), are recorded by most registries. Incident AEs are linked by the treating physician to specific therapies in 11 registries (69%), while the other 5 registries extrapolate potential causal associations based on therapy start and stop dates. A pre-specified adjudication process for AEs is made only by 5 registries (31%).

Conclusion:

Substantial heterogeneity exists among registries regarding AE assessment within the JAK-pot collaboration. These differences must be taken into account when analysing the safety of JAKi across different countries in collaborative studies. For comparative analyses, stratified analyses by country are required to account for differential AE assessment and varying degrees of potential under-reporting.

Disclosure of Interests:

Kim Lauper: None declared, Denis Mongin: None declared, Sytske Anne Bergstra: None declared, Denis Choquette: None declared, Catalin Codreanu: None declared, Diederik De Cock: None declared, Lene Dreyer: None declared, Ori Elkayam: None declared, Kimme Hyrich: None declared, Florenzo Iannone: None declared, Nevsun Inanc: None declared, Eirik kristianslund: None declared, Tore K. Kvien: None declared, Burkhard Leeb: None declared, Galina Lukina: None declared, Dan Nordström: None declared, Karel Pavelka: None declared, Manuel Pombo-Suarez: None declared, Ziga Rotar: None declared, Maria Jose Santos: None declared, Anja Strangfeld: None declared, Delphine Courvoisier: None declared, Axel Finckh Speakers bureau: Eli-Lilly, Pfizer, Consultant of: Eli-Lilly, Pfizer, Grant/research support from: BMS, Pfizer.

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

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

OP0231 COMPARATIVE EFFECTIVENESS OF JAK-INHIBITORS, TNF-INHIBITORS, ABATACEPT AND IL-6 INHIBITORS IN AN INTERNATIONAL COLLABORATION OF REGISTERS OF RHEUMATOID ARTHRITIS PATIENTS (THE “JAK-POT” STUDY)

Background:

In many countries, JAK-inhibitors (JAKi) have only recently been approved as treatment for patients with rheumatoid arthritis (RA).

Objectives:

To evaluate the effectiveness of JAKi compared to bDMARDs in RA patients in the real-world population in an international collaboration of registers (the “JAK-pot” collaboration).

Methods:

Patients initiating either JAKi, TNFi, IL-6i or abatacept (ABA) during a time period when JAKi were available in each country (19 registers, Table) were included. We compared the effectiveness of JAKi and bDMARDs in terms of retention using crude and adjusted survival analysis. Missing covariates were imputed using multiple imputation.

Results:

Among 25521 included patients, 6063 initiated a JAKi, 13879 a TNFi, 2348 ABA, and 3231 an IL-6i. Patients were on average 55 years old, with a mean disease duration 10 years, mostly seropositive (67%), female (77%) and with moderate disease activity at treatment initiation. The main reason of stopping treatment was ineffectiveness (49%), followed by adverse events (21%). Patients on JAKi were treated more often as monotherapy, had higher CRP and disease activity at baseline and had experienced more previous ts/bDMARDs. Crude median retention was 1.4 (95% CI 1.2-1.5) years for JAKi, 1.6 (1.6-1.7) for TNFi, 1.5 (1.3-1.7) for IL6i and 1.1 (1.0-1.3) for ABA. After adjustment, the hazard ratio (HR) for discontinuation tended to be lower for JAKi (HR 0.86 (0.65-1.13)) compared to TNFi, but comparable for ABA (1.02 (0.94-1.10)) and IL6i (0.99 (0.88-1.10)) (Figure 1). HRs differed notably between countries (Figure 2).

Table 1.

Registers

Country, registerNJAKi, n (%)Austria, BIOREG*Belgium, TARDIS62882113 (33.6)Canada, RHUMADATA528114 (21.6)Czech Republic, ATTRA374253 (67.6)Denmark, DANBIO4721506 (10.7)Finland, ROB-FIN807234 (29.0)Germany, RABBIT*Italy, GISEA757250 (33.0)Israel, I-RECORD40094 (23.5)Netherlands, METEOR16424 (0.2)Norway, NOR-DMARD50799 (19.5)Portugal, REUMA.PT79744 (5.5)Romania, RRBR593328 (55.3)Russia, ARBITER526483 (91.8)Slovenia, BIORX.SI583146 (25.0)Spain, BIOBADASER781139 (17.8)Switzerland, SCQM2956796 (26.9)Turkey, TURKBIO2150397 (18.5)UK, BSRBR111163 (5.7)

*Registers planning to participate in future studies but not included yet

Conclusion:

The adjusted overall drug retention of JAKi tended to be higher than for TNFi, with large variation between countries. Other measures of effectiveness, such as the evaluation of CDAI remission and low disease activity are planned to shape a more comprehensive picture of JAKi effectiveness in the real world.

Disclosure of Interests:

Kim Lauper: None declared, Denis Mongin: None declared, Sytske Anne Bergstra: None declared, Denis Choquette Grant/research support from: Rhumadata is supported by grants from Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Consultant of: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Speakers bureau: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Catalin Codreanu Consultant of: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Speakers bureau: Speaker and consulting fees from AbbVie, Accord Healthcare, Alfasigma, Egis, Eli Lilly, Ewopharma, Genesis, Mylan, Novartis, Pfizer, Roche, Sandoz, UCB, Diederik De Cock: None declared, Lene Dreyer: None declared, Ori Elkayam Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Novartis, Jansen, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Nevsun Inanc: None declared, Eirik kristianslund: None declared, Tore K. Kvien Grant/research support from: Received grants from Abbvie, Hospira/Pfizer, MSD and Roche (not relevant for this abstract)., Consultant of: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Paid instructor for: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Speakers bureau: Have received personal fees from Abbvie, Biogen, BMS, Celltrion, Eli Lily, Hospira/Pfizer, MSD, Novartis, Orion Pharma, Roche, Sandoz, UCB, Sanofi and Mylan (not relevant for this abstract)., Burkhard Leeb Grant/research support from: chairman of BioReg, Consultant of: AbbVie, Pfizer, Roche, Lilly, Grünenthal, Gebro,, Paid instructor for: Lilly, Biogen, Speakers bureau: Biogen, Lilly, Pfizer, Grünenthal, Astropharma,, Galina Lukina Speakers bureau: Novartis, Pfizer, UCB, Abbvie, Biocad, MSD, Roche, Dan Nordström Consultant of: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Speakers bureau: Abbvie, Celgene, Lilly, Novartis, Pfizer, Roche and UCB., Karel Pavelka Consultant of: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Speakers bureau: Abbvie, MSD, BMS, Egis, Roche, UCB, Medac, Pfizer, Biogen, Manuel Pombo-Suarez Consultant of: Janssen, Lilly, MSD and Sanofi., Speakers bureau: Janssen, Lilly, MSD and Sanofi., Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Delphine Courvoisier: None declared, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific

FRI0331 COMPARISON OF THE THERAPEUTIC TRAJECTORIES OF PATIENTS WITH OLIGO AND POLYARTICULAR PSORIATIC ARTHRITIS. A REPORT FROM THE RHUMADATA® CLINICAL DATABASE AND REGISTRY

Background:

Psoriatic Arthritis (PsA) most frequently presents as a polyarthritis or (less often) as an oligoarthritis [1]. Most of the patients in the original description of Moll and Wight had an oligoarticular presentation [2]. However, other studies have not found the same distribution in all patient populations [3]. Treatment response over time across presentation types has not been explored thoroughly in recent medical literature.

Objectives:

Using our proposed definition of oligo and polyarticular PsA status, based on the (rounded) mean of the first four available joint counts, we examine treatment sequences in each group.

Methods:

Data from patients participating in the RHUMADATA® clinical database and registry diagnosed with PsA were extracted on January 5th, 2020. Joint count classification (oligo vs. poly) was assessed from the average of the first four available 66/68 joint counts. Patients were classified as having a polyarticular form of PsA if the (rounded) average, five or more of their joints were assessed as being swollen and/or tender. Subjects with four or less swollen or tender joints were classified as patients having oligoarticular PsA. Time spent treated with non-DMARDs, csDMARDs and bDMARDs, time to treatment (to csDMARDs and bDMARDs) and treatment selection were assessed from the entire PsA cohort. Continuous variables were tested using t-tests and binary variables using Fisher’s exact test.

Results:

The data from all patients diagnosed with PsA (n=1029) was extracted from the RHUMADATA® clinical database and registry. All but 151 (15%) were classifiable, 470 (46%) were classified as oligoarticular PsA patients and 408 (39%) as polyarticular. Time from the first symptoms to the first clinic visit was 4.6 ± 6.5 years and 3.7 ± 6.6 (p-value=0.1311) years for the patients classified as oligo and poly respectively. A total oh 951 patients were treated with a csDMARD (144 of those could not be classified as oligo or poly). For those, time from diagnosis to first csDMARD (prior to any bDMARD) treatment was 1.7 ± 5.3 (oligo) years and 2.0 ± 7.0 (poly) years (p-value=0.4114). Methotrexate (MTX), hydroxychloroquine (HCQ) and leflunomide (LEF) were more frequently prescribed to polyarticular than oligoarticular PsA patients (MTX: 70% (poly) vs. 48% (oligo), p-value<.0001, HCQ: 41% vs. 25%, p-value <.0001, LEF: 17% vs. 8%, p-value<.0001, Sulfasalazine (SSZ): 17% vs. 19%, p-value=0.5232, Other csDMARDs: 5% vs. 4.5%, p-value=0.8688). A total of 648 patients were treated with a bDMARD (151 of those could not be classified as oligo or poly). For those, time from first csDMARD Rx to first bDMARD treatment was 6.3 ± 4.6 (oligo) years and 7.0 ± 4.7 years (p-value=0.0865). On average, over the entire treatment history, oligoarticular patients received 1.7 ± 1.2 biologic agents and polyarticular 2.0 ± 1.4, p-value=0.0110. bDMARDs were administered over 3.6 ± 3.6 years for oligo and 4.5 ± 3.9 years for poly, p-value=0.2122.

Conclusion:

Polyarticular PsA patients appear to be more aggressively treated than oligoarticular patients during the csDMARDs period. Although durations on bDMARDs are statistically similar, polyarticular patients change biotreatment more frequently.

References:

[1]Gladman DD, Ritchlin C, et al. Clinical manifestations and diagnosis of psoriatic arthritis. Update 2019.

[3]Wright V, Moll JM. Psoriatic arthritis. Bull Rheum Dis 1971; 21:627.

[3]Gladman DD. Psoriatic arthritis. Baillieres Clin Rheumatol 1995; 9:319.

Disclosure of Interests:

Denis Choquette Grant/research support from: Rhumadata is supported by grants from Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Consultant of: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Speakers bureau: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Loïc Choquette Sauvageau: 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, Isabelle Ferdinand Consultant of: Pfizer, Abbvie, Amgen, Novartis, Speakers bureau: Pfizer, Amgen, Paul Haraoui Grant/research support from: AbbVie, Amgen, BMS, Janssen, Pfizer, Roche, and UCB, Consultant of: AbbVie, Amgen, BMS, Celgene, Eli Lilly, Janssen, Merck, Pfizer, Roche, and UCB, Speakers bureau: Pfizer, Speakers bureau: Amgen, BMS, Janssen, Pfizer, and UCB, Frédéric Massicotte Consultant of: Abbvie, Janssen, Lilly, Pfizer, Speakers bureau: Janssen, Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica, Speakers bureau: TRB Chemedica and Mylan, Jean-Pierre Raynauld Consultant of: ArthroLab Inc., Marie-Anaïs Rémillard Consultant of: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Paid instructor for: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Speakers bureau: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Diane Sauvageau: None declared, Édith Villeneuve Consultant of: Abbvie, Amgen, BMS, Celgene, Pfizer, Roche, Sanofi-Genzyme,

UCB, Paid instructor for: Abbvie, Speakers bureau: AbbVie, BMS, Pfizer, Roche, Louis Coupal: None declared

AB0752 PSORIATIC ARTHRITIS: OLIGOARTHRITIS AND POLYARTHRITIS PATTERN CHANGES OVER THE INITIAL YEAR OF THE PRESENTATION. A REAL-WORLD EVIDENCE REPORT FROM THE QUEBEC REGISTRY RHUMADATA®

Background:

Psoriatic Arthritis (PsA) most frequently presents as a polyarthritis or (less often) as an oligoarthritis [1]. Upon reassessment, patients may change category during follow-up [2-3]. Historically, the patients in the original description of Moll and Wight had an oligoarticular presentation [4]. However, other studies have not found the same distribution in all patient populations [5]. Currently, none of the accepted diagnostic or classification criteria set for PsA consider the variation in the number of involved joints in the early phase of PsA.

Objectives:

To evaluate the change in pattern between oligoarticular and polyarticular psoriatic arthritis, within the first year of follow-up.

Methods:

Data from RHUMADATA® patients diagnosed with PsA were extracted on December 8th, 2019. In the current analysis, we consider the first year of care patients following their first encounter with clinic staff. Patients with at least two 66/68 joint counts completed during this initial year are the subjects of this analysis. Joint count classification (Oligo vs Poly) was assessed from the first and last available joint counts. Patients were classified as having a polyarticular form of PsA if 5 or more of their joints were assessed as being swollen and/or tender. Subjects with 4 or less swollen and/or tender joints were classified as oligoarticular PsA patients.

Results:

A total of 287 patients with at least two 66/68 joint counts are used in the present analysis. At baseline, the mean age of patients was 47.8 ± 13.5 with average disease duration of 1.6 ± 5.2 years. 49 % of patients were women. Average joint count at baseline was 7.1 ± 7.2 (swollen) and 7.1 ± 7.5 (tender) joints. Considering only 28 joints, the average was 4.2 ± 5 and 3.9 ± 4.8 for swollen and tender joints respectively. At the first joint count, 115 (40%) patients were assessed as “Oligo” and 172 (60%) as “Poly”, while 159 (55%) and 128 (45%) were similarly assessed at the last assessment. The two assessments agreed for 179 (62%) and disagreed for 108 (38%). Of the 115 patients initially classified as “Oligo”, 32 (28%) were reassessed as “Poly” within the initial year, while 76 (44%) of the 172 patients initially classified as “Poly” were reassessed as “Oligo”. All 172 patients initially classified as “Poly” initiated a DMARD during this period (167 (97%) initiated a csDMARD and 5 (3%) initiated a bDMARS). All patients initially classified as “Oligo” also initiated treatment during this period (98 (85%) and 17 (15%) of the 115 patients initially classified as “Oligo” initiated csDMARDs and bDMARD respectively).

Conclusion:

These observations suggest that a single assessment of joint count may be misleading in establishing the oligo or polyarticular pattern of PsA. This classification should take treatment into account.

References:

[1]Gladman DD, Ritchlin C, et al. Clinical manifestations and diagnosis of psoriatic arthritis. Uptodate 2019.

[2]Jones SM, Armas JB, Cohen MG, et al. Psoriatic arthritis: outcome of disease subsets and relationship of joint disease to nail and skin disease. Br J Rheumatol 1994; 33:834.

[3]McHugh NJ, Balachrishnan C, Jones SM. Progression of peripheral joint disease in psoriatic arthritis: a 5-yr prospective study. Rheumatology (Oxford) 2003; 42:778.

[4]Wright V, Moll JM. Psoriatic arthritis. Bull Rheum Dis 1971; 21:627.

[5]Gladman DD. Psoriatic arthritis. Baillieres Clin Rheumatol 1995; 9:319.

Disclosure of Interests:

Sana Chambah: None declared, Louis Coupal: None declared, Denis Choquette Grant/research support from: Rhumadata is supported by grants from Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Consultant of: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Speakers bureau: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,

THU0179 PERSISTENCE IN RHEUMATOID ARTHRITIS PATIENTS ON BIOSIMILAR AND BIO-ORIGINATOR ETANERCEPT: A POOLED ANALYSIS OF PAN-CANADIAN COHORTS

Background:

Biosimilar etanercept (ETA-B) was recently introduced in Canada but real-world data descriptions of drug persistence (and comparisons with the originator product, ETA-O) are still scarce.

Objectives:

To describe and compare persistence of ETA-B and ETA-O in RA.

Methods:

We used data from four ongoing, prospective cohorts in Canada: the Canadian Early Arthritis Cohort (CATCH), the Rheumatoid Arthritis Pharmacovigilance Program and Outcomes Research in Therapeutics (RAPPORT), the Early Undifferentiated Polyarthritis (EUPA) cohort, and the RHUMADATA® registry. We studied biologic-naïve and biologic-experienced RA adults initiating ETA-B or ETA-O between Jan. 2015 and Oct. 2019. Switchers from ETA-O to ETA-B (or vice-versa) were included. We assessed persistence of therapy in the first 12 or 24 months, measured as time from therapy initiation (time zero) to discontinuation. Individuals switching between products could contribute further person-time to the new exposure category. Multivariable Cox regression models were performed with each cohort dataset separately, following a common protocol. Model variables included age, sex, comorbidity, past biologic use, and disease duration. After testing for between-study heterogeneity (Higgin’s I2), cohort-estimated hazard ratios (HR) were pooled using random effects meta-analysis.

Results:

We identified 262 episodes of etanercept use (118 ETA-B and 144 ETA-O) from 250 RA patients. Sex, age, and other baseline characteristics across the four cohorts are shown in Table 1. Across cohorts, there was considerable variation in RA duration at the time of initiating ETA-B or ETA-O. In the pooled analysis, the HR for discontinuation at 24 months comparing ETA-B to ETA-O was 0.51 (95% confidence interval, CI: 0.26-0.98). The pooled analysis for therapy discontinuation at 12 months adjusted HR in this analysis was 0.82 (95% CI: 0.42-1.60).

Table 1.

Characteristics of studied patients according to their treatment episodes, biosimilar etanercept (ETA-B) or bio-originator etanercept (ETA-O).

CharacteristicEUPARAPPORTRHUMADATACATCHETA-BETA-OETA-BETA-OETA-BETA-OETA-BETA-ON=19N=27N=32N=30N=39N=52N=28N=35Female sex, (%)12 (63)18 (67)20 (63)22 (73)28 (72)38 (73)20 (71)27 (77)Mean age in years1, SD59 (13)59 (16)51 (15)54 (15)59 (15)54 (15)55 (12)51 (13)Current smoker, (%)3 (17)5 (21)9 (32)5 (19)8 (21)9 (17)5 (18)8 (23)Cardiovascular disease, (%)0 (0)0 (0)1 (3.1)1 (3.3)8 (21)2 (4)NANADiabetes, (%)0 (0)0 (0)4 (13)1 (3)2 (5)3 (6)NANAHypertension, (%)NANA5 (16)4 (13)14 (36)22 (42)NANARA duration in years1, SD2 (3)7 (13)8 (6)12 (15)12 (12)9 (9)4 (4)3 (3)DAS-2812 (NA)4 (2.8)6 (1)6 (1)4 (2)4 (1)4.0 (2)4 (2)SDAI113 (14)44 (5)NANA21 (15)23 (8)23 (14)25 (16)Past oral steroids, N(%)Past biologic, N(%)15 (79)17 (63)6 (19)4 (13)29 (74)31 (60)9 (32)13 (37)Past non-biologic DMARD,8 (42)6 (22)2 (6)0 (0)21 (54)20 (38)19 (68)21 (60)N(%)19 (100)27 (100)30 (94)26 (87)39 (100)52(100)25 (89)33 (94)

1At time zero or at the closest date before time zero. SD=standard deviation

Conclusion:

Despite wide confidence intervals, the 24-month data suggested potential better persistence with ETA-B versus ETA-O, with a similar trend at 12 months. Some of the observed associations may be related to residual confounding (e.g. disease activity, time-dependent effects of concomitant medications) and/or survivorship bias (in patients transitioning from ETA-O to ETA-B).

Disclosure of Interests:

Cristiano S Moura: None declared, Denis Choquette Grant/research support from: Rhumadata is supported by grants from Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Consultant of: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Speakers bureau: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Louis Coupal: None declared, Orit Schieir: None declared, Marie-France Valois: None declared, Vivian Bykerk: 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, Walter P Maksymowych Grant/research support from: Received research and/or educational grants from Abbvie, Novartis, Pfizer, UCB, Consultant of: WPM is Chief Medical Officer of CARE Arthritis Limited, has received consultant/participated in advisory boards for Abbvie, Boehringer, Celgene, Eli-Lilly, Galapagos, Gilead, Janssen, Novartis, Pfizer, UCB, Speakers bureau: Received speaker fees from Abbvie, Janssen, Novartis, Pfizer, UCB., Sasha Bernatsky: None declared

AB0337 TOFACITINIB MONOTHERAPY OR COMBINED WITH METHOTREXATE IN PATIENTS WITH RHEUMATOID ARTHRITIS SHOW SIMILAR RETENTION OVER FOUR YEARS. REPORT FROM RHUMADATA ®

Background:

Since the introduction of biologic agents around the turn of the century, the scientific evidence shows that the majority of agents, independent of the therapeutic target, have a better outcome when used in combination with methotrexate (MTX). In 2014, tofacitinib (TOFA), an agent targeting Janus kinase 1 and 3, has reached the Canadian market with data showing that the combination with MTX may not be necessary [1,2].

Objectives:

To evaluate the efficacy and retention rate of TOFA in real-world patients with rheumatoid arthritis (RA).

Methods:

Two cohorts of patients prescribed TOFA was created. The first cohort was formed of patients who were receiving MTX concomitantly with TOFA (COMBO) and the other of patients using TOFA in monotherapy (MONO). MONO patients either never use MTX or were prescribed MTX post-TOFA initiation for at most 20% of the time they were on TOFA. COMBO patients received MTX at the time of TOFA initiation or were prescribed MTX post-TOFA initiation for at least 80% of the time. For all those patients, baseline demographic data definitions. Disease activity score and HAQ-DI were compared from the initiation of TOFA to the last visit. Time to medication discontinuation was extracted, and survival was estimated using Kaplan-Meier calculation for MONO and COMBO cohorts.

Results:

Overall, 194 patients were selected. Most were women (83%) on average younger than the men (men: 62.6 ± 11.0 years vs. women: 56.9 ± 12.1 years, p-value=0.0130). The patient’s assessments of global disease activity, pain and fatigue were respectively 5.0 ± 2.7, 5.2 ± 2.9, 5.1 ± 3.1 in the COMBO group and 6.2 ± 2.5, 6.5 ± 2.6, 6.3 ± 2.8 in the MONO group all differences being significant across groups. HAQ-DI at treatment initiation was 1.3 ± 0.7 and 1.5 ± 0.7 in the COMBO and MONO groups, respectively, p-value=0.0858. Similarly, the SDAI score at treatment initiation was 23.9 ± 9.4 and 25.2 ± 11.5, p-value=0.5546. Average changes in SDAI were -13.4 ± 15.5 (COMBO) and -8.9 ± 13.5 (MONO), p-value=0.1515, and changes in HAQ -0.21 ± 0.63 and -0.26 ± 0.74, p-value 0.6112. At treatment initiation, DAS28(4)ESR were 4.4 ± 1.4 (COMBO) and 4.6 ± 1.3 (MONO), p-value 0.5815, with respective average changes of -1.06 ± 2.07 and -0.70 ± 1.96, p-value=0.2852. The Kaplan-Meier analysis demonstrated that the COMBO and MONO retention curves were not statistically different (log-rank p-value=0.9318).

Conclusion:

Sustainability of TOFA in MONO or COMBO are not statistically different as are the changes in DAS28(4)ESR and SDAI. Despite this result, some patients may still benefit from combination with MTX.

References:

[1]Product Monograph - XELJANZ ® (tofacitinib) tablets for oral administration Initial U.S. Approval: 2012.

[2] Reed GW, Gerber RA, Shan Y, et al. Real-World Comparative Effectiveness of Tofacitinib and Tumor Necrosis Factor Inhibitors as Monotherapy and Combination Therapy for Treatment of Rheumatoid Arthritis [published online ahead of print, 2019 Nov 9].Rheumatol Ther. 2019;6(4):573–586. doi:10.1007/s40744-019-00177-4.

Disclosure of Interests:

Denis Choquette Grant/research support from: Rhumadata is supported by grants from Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Consultant of: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, Speakers bureau: Pfizer, Amgen, Abbvie, Gylead, BMS, Novartis, Sandoz, eli Lilly,, 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, Loïc Choquette Sauvageau: None declared, Isabelle Ferdinand Consultant of: Pfizer, Abbvie, Amgen, Novartis, Speakers bureau: Pfizer, Amgen, Boulos Haraoui Grant/research support from: Abbvie, Amgen, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, BMS, Janssen, Pfizer, Roche, and UCB, Consultant of: Abbvie, Amgen, Lilly, Pfizer, Sandoz, UCB, Consultant of: AbbVie, Amgen, BMS, Celgene, Eli Lilly, Janssen, Merck, Pfizer, Roche, and UCB, Speakers bureau: Pfizer, Speakers bureau: Amgen, BMS, Janssen, Pfizer, and UCB, Frédéric Massicotte Consultant of: Abbvie, Janssen, Lilly, Pfizer, Speakers bureau: Janssen, Jean-Pierre Pelletier Shareholder of: ArthroLab Inc., Grant/research support from: TRB Chemedica, Speakers bureau: TRB Chemedica and Mylan, Jean-Pierre Raynauld Consultant of: ArthroLab Inc., Marie-Anaïs Rémillard Consultant of: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Paid instructor for: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Speakers bureau: Abbvie, Amgen, Eli Lilly, Novartis, Pfizer, Sandoz, Diane Sauvageau: None declared, Édith Villeneuve Consultant of: Abbvie, Amgen, BMS, Celgene, Pfizer, Roche, Sanofi-Genzyme,

UCB, Paid instructor for: Abbvie, Speakers bureau: AbbVie, BMS, Pfizer, Roche, Louis Coupal: None declared

Rheumatoid Arthritis Patients after Initiation of a New Biologic Agent: Trajectories of Disease Activity in a Large Multinational Cohort Study

Background

Response to disease modifying antirheumatic drugs (DMARDs) in rheumatoid arthritis (RA) is often heterogeneous. We aimed to identify types of disease activity trajectories following the initiation of a new biologic DMARD (bDMARD).

Methods

Pooled analysis of nine national registries of patients with diagnosis of RA, who initiated Abatacept and had at least two measures of disease activity (DAS28). We used growth mixture models to identify groups of patients with similar courses of treatment response, and examined these patients' characteristics and effectiveness outcomes.

Findings

We identified three types of treatment response trajectories: ‘gradual responders’ (GR; 3576 patients, 91·7%) had a baseline mean DAS28 of 4·1 and progressive improvement over time; ‘rapid responders’ (RR; 219 patients, 5·6%) had higher baseline DAS28 and rapid improvement in disease activity; ‘inadequate responders’ (IR; 103 patients, 2·6%) had high DAS28 at baseline (5·1) and progressive worsening in disease activity. They were similar in baseline characteristics. Drug discontinuation for ineffectiveness was shorter among inadequate responders (p = 0.03), and EULAR good or moderate responses at 1 year was much higher among ‘rapid responders’ (p < 0.001).

Interpretation

Clinical information and baseline clinical characteristics do not allow a reliable prediction of which trajectory the patients will follow after bDMARD initiation.

•

This study examined disease activity trajectories in a multinational cohort of 3898 rheumatoid arthritis patients.

•

Growth mixture models identified three groups: gradual, rapid, and inadequate responders (GR: 91·7%, RR: 5·6%, IR: 2·6%).

•

At baseline, groups were similar in demographic and clinical characteristics, and moderately different in function and disease activity.

•

The groups had large difference in drug retention and in good or moderate response rate.

Using nine national registries, this study of 3898 established RA patients initiating a new bDMARD identified distinct types of responders: gradual, rapid and inadequate responders. Neither socio-demographic nor clinical characteristics at baseline allowed the prediction of the type of response trajectory after treatment initiation, but effectiveness outcomes strongly differed, suggesting that these empirically derived subgroups have clinical relevance.

As a major aim of precision medicine is to make anti-rheumatic therapy more personalized, the detection of responder types following initiation of a specific bDMARD underscores the need to find reliable predictors of trajectories to identify patients needing a distinct treatment strategy.