Abstract

BackgroundTreatment persistence is an important consideration when selecting a therapy for chronic conditions such as rheumatoid arthritis (RA). We assessed the long-term persistence of abatacept or a tumor necrosis factor inhibitor (TNFi) following (1) inadequate response to a conventional synthetic disease-modifying antirheumatic drug (first-line biologic agent) and (2) inadequate response to a first biologic DMARD (second-line biologic agent).MethodsData were extracted from the Rhumadata® registry for patients with RA prescribed either abatacept or a TNFi (adalimumab, certolizumab, etanercept, golimumab, or infliximab) who met the study selection criteria. The primary outcome was persistence to abatacept and TNFi treatment, as first- or second-line biologics. Secondary outcomes included the proportion of patients discontinuing therapy, reasons for discontinuation, and predictors of discontinuation. Persistence was defined as the time from initiation to discontinuation of biologic therapy. Baseline characteristics were compared using descriptive statistics; cumulative persistence rates were estimated using Kaplan-Meier methods, compared using the log-rank test. Multivariate Cox proportional hazard models were used to compare the persistence between treatments, controlling for baseline covariates.ResultsOverall, 705 patients met the selection criteria for first-line biologic agent initiation (abatacept, n = 92; TNFi, n = 613) and 317 patients met the criteria for second-line biologic agent initiation (abatacept, n = 105; TNFi, n = 212). There were no clinically significant differences in baseline characteristics between the treatments with either first- or second-line biologics. Persistence was similar between the first-line biologic treatments (p = 0.7406) but significantly higher for abatacept compared with TNFi as a second-line biologic (p = 0.0001). Mean (SD) times on first-line biologic abatacept and TNFi use were 4.53 (0.41) and 5.35 (0.20) years, and 4.80 (0.45) and 2.82 (0.24) years, respectively, as second-line biologic agents. The proportion of patients discontinuing abatacept and TNFi in first-line was 51.1% vs. 59.5% (p = 0.1404), respectively. In second-line, it was 57.1% vs. 74.1% (p = 0.0031). The main reasons for stopping both treatments were inefficacy and adverse events.ConclusionsAbatacept and TNFi use demonstrated similar persistence rates at 9 years as a first-line biologic agent. As a second-line biologic agent, abatacept had better persistence rates over a TNFi.

Highlights

  • Treatment persistence is an important consideration when selecting a therapy for chronic conditions such as rheumatoid arthritis (RA)

  • Patient disposition and baseline characteristics Overall, 705 patients were selected for first-line biologic agent initiation in this study following an inadequate response to a conventional synthetic disease-modifying antirheumatic drug (csDMARD); of these, 92 patients received abatacept and 613 received a tumor necrosis factor inhibitor (TNFi)

  • No clinically significant differences were seen between the treatment groups for the majority of baseline characteristics, in both the first- and the second-line biologic agent initiation cohorts (Table 2); significant differences in a few key characteristics were noted (e.g., Clinical Disease Activity Index and Simplified Disease Activity Index scores and concomitant medications); these differences were controlled for using a multivariate analysis

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Summary

Introduction

Treatment persistence is an important consideration when selecting a therapy for chronic conditions such as rheumatoid arthritis (RA). Using a second-line TNFi after a first-line TNFi has failed can be an effective treatment strategy [8, 9], second-line TNFi use often results in a lower response [4, 6, 7] These results are supported by several studies reporting that switching to a different mode of action when first-line therapy fails is more effective than cycling between agents with the same mode of action [10,11,12,13,14,15]. These studies investigated the differences between cycling and switching in the real world, no long-term data are available to assess the long-term persistence rates between the two treatment strategies

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