Treatment Sequences After Discontinuing a Tumor Necrosis Factor Inhibitor in Patients With Rheumatoid Arthritis: A Comparison of Cycling Versus Swapping Strategies

Real-World Treatment and Care Patterns in Patients With Rheumatoid Arthritis Initiating First-Line Tumor Necrosis Factor Inhibitor Therapy in the United States

OBJECTIVE

Treatment guidelines for rheumatoid arthritis (RA) recommend targeting low disease activity or remission and switching therapies for patients not reaching those targets. We evaluated real-world use of disease activity measures, treatment discontinuation, and switching patterns among patients with RA initiating a first-line tumor necrosis factor inhibitor (TNFi).

METHODS

Data from adult patients with RA initiating a first-line TNFi were collected from the American Rheumatology Network (January 2014-August 2021). The proportion of patients with recorded disease activity scores (Clinical Disease Activity Index [CDAI] or Routine Assessment of Patient Index Data 3 [RAPID3]) at TNFi initiation was assessed. Among patients with moderate or severe RA at TNFi initiation, reasons for discontinuation and subsequent advanced therapy were evaluated.

RESULTS

Among TNFi initiators (n = 15,182), 44.8% recorded a CDAI/RAPID3 score at treatment initiation; of those who did not, 47.0% had recorded a tender and/or swollen joint count or pain score. Among patients with moderate or severe RA (n = 1,651), 52% discontinued their initial TNFi during follow-up, of which 15%, 46%, 28%, and 12% initiated the same TNFi, another TNFi, a non-TNFi biologic, or a Janus kinase inhibitor, respectively. The proportion of patients restarting the same TNFi or initiating another TNFi varied according to TNFi discontinuation reason.

CONCLUSION

In clinical practice, over half of patients with RA initiating a first-line TNFi did not have baseline disease activity assessments. Many patients cycled through TNFi despite citing lack of efficacy as the most common reason for discontinuation. Consistent, objective monitoring of treatment response and timely switch to effective therapy is needed in patients with RA.

Management of patients with inflammatory rheumatic diseases after treatment failure with a first tumour necrosis factor inhibitor: A narrative review

The emergence of biologics with different modes of action (MoAs) and therapeutic targets has changed treatment patterns in patients with inflammatory rheumatic diseases. While tumour necrosis factor inhibitors (TNFis) are often utilized as the first biologic disease-modifying antirheumatic drug, some patients may not respond adequately (primary failure), fail to sustain response over time (secondary failure), or experience intolerable adverse events. Whether these patients would benefit more from cycling to a different TNFi or switching to a biologic with a different MoA is still unclear. We discuss here treatment outcomes of TNFi cycling versus MoA switching after treatment failure with a first TNFi in patients with inflammatory rheumatic diseases, focusing specifically on rheumatoid arthritis, psoriatic arthritis, axial spondyloarthritis, and juvenile idiopathic arthritis. Treatment guidelines for these patients are ambiguous and, at times, contradictory in their recommendations. However, this is due to a lack of high-quality head-to-head data to definitively support cycling between TNFis after failure to a first-line TNFi over switching to a different MoA.

One-Year Medication Adherence and Persistence in Rheumatoid Arthritis in Clinical Practice: A Retrospective Analysis of Upadacitinib, Adalimumab, Baricitinib, and Tofacitinib

INTRODUCTION

This study evaluated 12 months adherence and persistence among Janus kinase inhibitors (upadacitinib, baricitinib, tofacitinib) and adalimumab, a tumor necrosis factor inhibitor (TNFi), in patients with rheumatoid arthritis (RA).

METHODS

This retrospective analysis used administrative claims data from the Merative™ MarketScan® Research Databases (2018-2022). Eligible adults had ≥ 1 RA diagnosis before the index date, ≥ 1 pharmacy claim for index medication, and ≥ 12 months of continuous insurance enrollment pre- and post-index. Adherence to treatment [defined as proportion of days covered (PDC) ≥ 80%], risk of treatment discontinuation, and mean time to discontinuation were assessed during the 12 months follow-up. Adjusted odds ratios (aOR), adjusted hazard ratios (aHR), and 95% confidence intervals (CI) were reported.

RESULTS

In total, 6317 patients were included (683 upadacitinib, 3732 adalimumab, 132 baricitinib, 1770 tofacitinib). Compared with upadacitinib, patients initiating adalimumab [aOR (95% CI): 0.82 (0.69, 0.96)], baricitinib [0.46 (0.31, 0.68)], and tofacitinib [0.74 (0.62, 0.88)] were significantly less likely to achieve PDC ≥ 80%. Risk of treatment discontinuation was significantly higher in patients treated with adalimumab [aHR (95% CI): 1.14 (1.01, 1.29)], baricitinib [1.48 (1.16, 1.90)], and tofacitinib [1.22 (1.07, 1.38)] compared with upadacitinib. Mean time to discontinuation was 256 (upadacitinib), 249 (adalimumab), 221 (baricitinib), and 239 (tofacitinib) days. Similar results were observed in patients with prior TNFi use.

CONCLUSIONS

Patients with RA, regardless of recent TNFi experience, initiating upadacitinib were significantly more likely to be adherent and less likely to discontinue therapy compared to adalimumab, baricitinib, and tofacitinib in the first 12 months of treatment.

Researchers in rheumatology should avoid categorization of continuous predictor variables

BACKGROUND

Rheumatology researchers often categorize continuous predictor variables. We aimed to show how this practice may alter results from observational studies in rheumatology.

METHODS

We conducted and compared the results of two analyses of the association between our predictor variable (percentage change in body mass index [BMI] from baseline to four years) and two outcome variable domains of structure and pain in knee and hip osteoarthritis. These two outcome variable domains covered 26 different outcomes for knee and hip combined. In the first analysis (categorical analysis), percentage change in BMI was categorized as ≥ 5% decrease in BMI, < 5% change in BMI, and ≥ 5% increase in BMI, while in the second analysis (continuous analysis), it was left as a continuous variable. In both analyses (categorical and continuous), we used generalized estimating equations with a logistic link function to investigate the association between the percentage change in BMI and the outcomes.

RESULTS

For eight of the 26 investigated outcomes (31%), the results from the categorical analyses were different from the results from the continuous analyses. These differences were of three types: 1) for six of these eight outcomes, while the continuous analyses revealed associations in both directions (i.e., a decrease in BMI had one effect, while an increase in BMI had the opposite effect), the categorical analyses showed associations only in one direction of BMI change, not both; 2) for another one of these eight outcomes, the categorical analyses suggested an association with change in BMI, while this association was not shown in the continuous analyses (this is potentially a false positive association); 3) for the last of the eight outcomes, the continuous analyses suggested an association of change in BMI, while this association was not shown in the categorical analyses (this is potentially a false negative association).

CONCLUSIONS

Categorization of continuous predictor variables alters the results of analyses and could lead to different conclusions; therefore, researchers in rheumatology should avoid it.

Comparative effectiveness of TNF inhibitor vs IL-6 receptor inhibitor as monotherapy or combination therapy with methotrexate in biologic-experienced patients with rheumatoid arthritis: An analysis from the CorEvitas RA Registry

OBJECTIVE

Randomized controlled trials (RCTs) in biologic-naïve rheumatoid arthritis (RA) patients with high disease activity and inadequate response/intolerance to methotrexate have shown interleukin-6 (IL-6) receptor inhibitors (IL-6Ri) to be superior to tumor necrosis factor inhibitors (TNFi) as monotherapy. This observational study aimed to compare the effectiveness of TNFi vs IL-6Ri as mono- or combination therapy in biologic/targeted synthetic (b/ts) -experienced RA patients with moderate/high disease activity.

METHODS

Eligible b/ts-experienced patients from the CorEvitas RA registry were categorized as TNFi and IL-6Ri initiators, with subgroups initiating as mono- or combination therapy. Mixed-effects regression models evaluated the impact of treatment on Clinical Disease Activity Index (CDAI), patient-reported outcomes, and disproportionate pain (DP). Unadjusted and covariate-adjusted effects were reported.

RESULTS

Patients initiating IL-6Ri (n = 286) vs TNFi monotherapy (n = 737) were older, had a longer RA history and higher baseline CDAI, and were more likely to initiate as third-line therapy; IL-6Ri (n = 401) vs TNFi (n = 1315) combination therapy initiators had higher baseline CDAI and were more likely to initiate as third-line therapy. No significant differences were noted in the outcomes between TNFi and IL-6Ri initiators (as mono- or combination therapy).

CONCLUSION

This observational study showed no significant differences in outcomes among b/ts-experienced TNFi vs IL-6Ri initiators, as either mono- or combination therapy. These findings were in contrast with the previous RCTs in biologic-naïve patients and could be explained by the differences in the patient characteristics included in this study. Further studies are needed to help understand the reasons for this discrepancy in the real-world b/ts-experienced population.

Comparison of the efficacy and risk of discontinuation between non-TNF-targeted treatment and a second TNF inhibitor in patients with rheumatoid arthritis after first TNF inhibitor failure

Objectives:

Despite improved care for rheumatoid arthritis (RA) patients, many still experience treatment failure with biologic disease-modifying antirheumatic drugs (bDMARDs) or targeted synthetic DMARDs [tsDMARDs; typically Janus kinase inhibitors (JAKi)], and eventually switch to other agents. We compared the efficacy of a second tumor necrosis factor inhibitor (TNFi) and non-TNF-targeted treatment as the second-line treatment in patients showing an insufficient response to the first TNFi.

Methods:

Patients were included if they had received at least one prescription for a TNFi, and at least one follow-up prescription for a second TNFi or non-TNF-targeted treatment after discontinuation of the first drug. In total, 209 patients were analyzed, including 69 with a second TNFi and 140 with a non-TNF-targeted treatment (106 non-TNFi biologics and 34 JAKi). Cox regression was used to estimate the hazard ratio (HR) for discontinuation.

Results:

The mean follow-up period after switching was 28.0 (range: 0–80) months and 24.4% of the 209 patients switched or discontinued the second drug. In multivariate Cox proportional hazard analysis, the non-TNF-targeted treatment group had a lower likelihood of discontinuing their treatment than the second TNFi group [HR = 0.326, 95% confidence interval (CI): 0.170–0.626, p = 0.001]. When analyzed separately, the risk of discontinuation was significantly lower in both the non-TNFi biologic (HR = 0.318, 95% CI: 0.160–0.633, p = 0.001) and JAKi (HR = 0.356, 95% CI: 0.129–0.980, p = 0.046) groups than in the second TNFi group.

Conclusion:

Our study supported switching to a non-TNF-targeted treatment instead of TNF cycling in patients with RA showing an inadequate response to initial TNFi.

[Innovative strategies for treatment of rheumatoid arthritis]

Besides excellent guidelines and newly developed highly effective drugs, evidence-based strategic use of these new drugs has especially contributed to enormous advances in rheumatoid arthritis treatment, apparent especially since 2000. Currently, the treat-to-target (T2T) strategy has proven to be the most successful in several studies and systematic reviews. The target is to achieve remission, which should be reached and sustained for an optimal outcome (i.e. stable over a long time period). If the initial disease-modifying antirheumatic drug (DMARD) treatment fails, the best strategy for continuing treatment is controversial, with swap or switch being open to debate (change within a class of drugs or change in the mechanism of action). Recent studies seem to indicate that switching to another mechanism of action is the most successful approach. A hotly discussed topic is the question whether DMARD treatment can or should be tapered when sustained remission has been achieved? Many patients wish for a reduction of drugs in cases of stable remission; however, the stable disease control might become destabilized by tapering. The main priority is the reduction or tapering of glucocorticoid treatment. When the decision for reduction of DMARD treatment is made together with the patient, a complete cessation bears a high risk of a flare, therefore, a careful step by step reduction of DMARD treatment should be preferred. In the case of a running combination, the question whether the conventional DMARD (mostly methotrexate), the biological (b)DMARD or targeted synthetic (ts)DMARD should be reduced first, must be decided on an individual basis. Most patients prefer to first reduce methotrexate and transfer to a monotherapy.

The sequence of disease-modifying anti-rheumatic drugs: pathways to and predictors of tocilizumab monotherapy

BACKGROUND

There are numerous non-biologic and biologic disease-modifying anti-rheumatic drugs (bDMARDs) for rheumatoid arthritis (RA). Typical sequences of bDMARDs are not clear. Future treatment policies and trials should be informed by quantitative estimates of current treatment practice.

METHODS

We used data from Corrona, a large real-world RA registry, to develop a method for quantifying sequential patterns in treatment with bDMARDs. As a proof of concept, we study patients who eventually use tocilizumab monotherapy (TCZm), an IL-6 antagonist with similar benefits used as monotherapy or in combination. Patients starting a bDMARD were included and were followed using a discrete-state Markov model, observing changes in treatments every 6 months and determining whether they used TCZm. A supervised machine learning algorithm was then employed to determine longitudinal patient factors associated with TCZm use.

RESULTS

7300 patients starting a bDMARD were followed for up to 5 years. Their median age was 58 years, 78% were female, median disease duration was 5 years, and 57% were seropositive. During follow-up, 287 (3.9%) reported use of TCZm with median time until use of 25.6 (11.5, 56.0) months. Eighty-two percent of TCZm use began within 3 years of starting any bDMARD. Ninety-three percent of TCZm users switched from TCZ combination, a TNF inhibitor, or another bDMARD. Very few patients are given TCZm as their first DMARD (0.6%). Variables associated with the use of TCZm included prior use of TCZ combination therapy, older age, longer disease duration, seronegative, higher disease activity, and no prior use of a TNF inhibitor.

CONCLUSIONS

Improved understanding of treatment sequences in RA may help personalize care. These methods may help optimize treatment decisions using large-scale real-world data.