Biologic Therapy Tapering In Inflammatory Arthritis
Overview
The aim of this study was to identify predictors of successful biologic tapering in patients with inflammatory arthritis, using baseline characteristics from the BIODOPT trial. The trial included adult patients with rheumatoid arthritis, psoriatic arthritis, or axial spondyloarthritis who had been on a stable biologic dose and in a state of low disease activity for at least 12 months. Those included in the study were randomly assigned to either disease activity-guided biologic tapering or continuation of their baseline biologic treatment. Successful tapering was defined as a reduction of the biologic dose by at least 50%, with no protocol deviations, and maintaining low disease activity at 18 months.
The results showed that successful tapering was achieved by 32% of patients in the tapering group, while only 2% in the control group achieved it. The tapering group was the only statistically significant independent predictor for successful tapering, with a risk ratio (RR) of 14.0. However, higher scores on the Short Form Health Survey 36 mental component summary (SF-36 MCS) were observed as a predictor of potential importance, with an RR of 1.06 (95% CI: 0.99 to 1.13, P = .097).
When the analysis was limited to the tapering group alone, none of the baseline variables were found to be statistically significant independent predictors. However, SF-36 MCS continued to be considered of potential importance, with an RR of 1.05 (95% CI: 0.99 to 1.12, P = .098).
In conclusion, the study found that successful tapering of biologic therapy is achievable for approximately one in three patients with inflammatory arthritis who are interested in reducing their treatment. Apart from the allocation to the tapering group, no other statistically significant predictors were identified. The study suggests that future research should focus on the relationship between mental health, particularly as measured by SF-36 MCS, and the success of tapering in these patients, encouraging further investigation in this area.
Introduction
The European Alliance of Associations for Rheumatology recommends that physicians and patients dealing with inflammatory arthritis (IA) consider a gradual reduction in biologic therapy when sustained remission is achieved, instead of completely withdrawing the treatment. This approach has several advantages, including reduced clinic visits, lower individual patient time costs, decreased risk of adverse drug reactions, and potential cost savings for society due to the high costs of biologic therapies.
While the evidence supporting biologic tapering is strongest in rheumatoid arthritis (RA) due to numerous trials, it is relatively weaker in axial spondyloarthritis (axSpA) and scarce in psoriatic arthritis (PsA). Across different IA diagnoses, biologic tapering appears to be feasible and safe, as it often results in significant dose reductions or extended dosing intervals without compromising therapeutic responses. Most patients who experience a disease flare during tapering can regain stable disease activity with rescue therapy, such as biologic dose escalation or glucocorticoid treatment.
The BIODOPT trial recently evaluated the feasibility of disease activity-guided biologic tapering versus continuing biologics as usual care in patients with RA, PsA, or axSpA who had maintained low disease activity for at least 12 months. The trial found that, at the 18-month follow-up, a significantly higher number of patients in the tapering group had successfully reduced their biologic dose by at least 50% compared to the control group, while maintaining equivalent disease activity levels.
However, there is limited knowledge about potential predictors for successful biologic tapering, as previous studies have not consistently identified predictive variables. This study aims to address this gap by evaluating baseline characteristics from the BIODOPT trial to identify possible predictors for successful biologic tapering. The goal is to improve and personalize the tapering approach, enhancing its effectiveness for patients with IA.
Methods
The BIODOPT trial was an 18-month pragmatic study conducted in Denmark at four different sites. It focused on adult patients diagnosed with inflammatory arthritis (IA), which includes rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA). To be eligible for the trial, patients needed to have maintained low disease activity (LDA) on a stable dose of biologics for at least 12 months. LDA was defined differently for each IA diagnosis: DAS28-CReactive Protein (DAS28-CRP) ≤3.2 for RA, Disease Activity in Psoriatic Arthritis (DAPSA) ≤14 for PsA, and Ankylosing Spondylitis Disease Activity Score (ASDAS) <2.1 for axSpA.
Participants were randomly assigned to either the tapering group or the control group, with a 2:1 ratio. In the tapering group, the biologic dosing interval (except for infliximab) was extended by 25% every four months based on a disease activity-guided algorithm. This process continued until a disease flare occurred or complete drug withdrawal. Infliximab dosing intervals were prolonged by 2 weeks at each infusion. The control group, on the other hand, maintained their baseline biologic dosing intervals, although minor prolongations were allowed upon patient request.
In these secondary analyses, successful tapering at the 18-month mark was predefined as follows: patients who adhered to the trial protocol without any deviations, reduced their biologic dose by at least 50% compared to their baseline, and were still in LDA as defined by specific criteria for each IA diagnosis.
This study aims to identify potential baseline predictive variables associated with successful tapering in IA patients who were in sustained LDA and either tapered their biologics or continued them, based on data gathered during the BIODOPT trial. The analysis considered various categorical and continuous baseline variables, including demographics, disease-related factors, treatment history, and patient-reported outcomes. The goal is to gain insights into the factors that may influence the success of biologic tapering in these patients.
Statistical Analysis
The sample size for the BIODOPT trial was determined based on a previously reported calculation. These secondary analyses adhered to a predefined statistical analysis plan (SAP) inspired by guidelines such as the CONSORT statement and reported in accordance with the TRIPOD statement. The intention-to-treat approach was applied, which means that all participants who were randomized and had baseline data available, regardless of any subsequent protocol deviations, were included in the analysis.
For the primary outcome, which was successful tapering, missing data were conservatively treated as trial failures. In other words, if patients couldn’t reduce their biologic dose by at least 50% and/or did not maintain low disease activity, it was considered as not achieving successful tapering.
The analysis initially involved univariable modified Poisson regression with a robust variance estimator. This method was used to estimate the relative risk (RR) along with 95% confidence intervals (95% CI) and p-values for potential predictors. To identify any nonlinear predictors, continuous variables were categorized into clinically relevant groups based on expert opinion and analyzed as categorical variables. If no evidence of nonlinearity was found, continuous variables were treated as linear.
Two multivariable modified Poisson regression analyses with robust variance estimators were conducted. The data-driven model included variables with a univariate p-value less than 0.10, while the clinical-driven model considered variables selected based on expert opinion as potentially important for achieving successful tapering. The analysis also checked for collinearity among predictors to ensure that correlated variables did not affect the results.
Leave-1-out cross-validation was used to assess the model’s performance, and the concordance index (c-index) was calculated, which is similar to the area under the receiving operator characteristic curve (AUC) for binary outcomes. Classification trees were employed to identify and visualize the most relevant predictors, and cross-validation was applied to determine the optimal sub-tree. The Gini index was used as a measure of node purity to evaluate the results. All statistical analyses were conducted using STATA version 16.1.
Results
Between May 2018 and April 2020, a total of 142 patients were enrolled in the study. Among them, 95 patients were assigned to the tapering group, while 47 patients were assigned to the control group. The study included patients diagnosed with various forms of inflammatory arthritis, including rheumatoid arthritis (RA), psoriatic arthritis (PsA), and axial spondyloarthritis (axSpA). The majority of patients received treatment with tumor necrosis factor inhibitors (TNFi), with the rest being treated with abatacept or tocilizumab. Most participants were in remission at the beginning of the study.
At the 18-month follow-up, 64% of patients in the tapering group had successfully tapered their biologic dose by at least 50% and maintained low disease activity (LDA), while only 15% of patients in the control group achieved this. Notably, 32% of patients in the tapering group achieved successful tapering, compared to just 2% in the control group.
The analysis examined potential predictors for successful tapering. While several variables were considered, allocation to the tapering group was the only statistically significant independent predictor for successful tapering, with a relative risk (RR) of 14.0. However, better mental health at baseline, as measured by the SF-36 Mental Component Summary (MCS) score, was considered potentially important, with a RR of 1.06 (although not statistically significant).
Further sensitivity analysis highlighted the potential importance of baseline mental health, as patients with higher SF-36 MCS scores were more likely to achieve successful tapering. Internal validation of the prediction model confirmed its validity, with an AUC of 0.72. Sensitivity analysis also supported the robustness of the data-driven model.
A clinical-driven model that included variables deemed important by experts did not yield significant predictors for successful tapering. Leave-1-out cross-validation for this model indicated that it performed no better than chance.
Post hoc analyses focused on the tapering group alone, revealing associations between successful tapering and certain baseline variables, including HAQ-DI, Pain VAS, Patient Global Health VAS, and SF-36 MCS. While none of these variables were statistically significant independent predictors, better mental health at baseline remained a potentially important predictor.
In conclusion, allocation to the tapering group was the most significant predictor of successful biologic tapering. Mental health, as indicated by the SF-36 MCS score, showed potential importance, with patients having higher scores being more likely to achieve successful tapering. However, additional research and caution in interpretation are warranted in this regard.
Discussion
This study represents a pioneering effort to investigate potential predictors for successful biologic tapering among patients with inflammatory arthritis (IA), encompassing conditions from rheumatoid arthritis (RA) to psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA). The study followed an 18-month randomized-controlled trial (RCT) approach and enrolled a total of 142 patients. Among these patients, approximately two-thirds in the tapering group who maintained low disease activity (LDA) at 18 months were able to reduce their biologic dose, with one-third achieving a significant reduction of ≥50% compared to baseline, signifying successful tapering. This indicates that a substantial biologic dose reduction is a feasible goal for one in three well-treated IA patients who opt for tapering following shared decision-making.
The study’s multivariable regression analyses did not identify any statistically significant predictors other than the allocation to the tapering group itself. However, the analyses suggested that evaluating baseline mental health could be of potential importance since individuals with better mental health appear to achieve successful tapering more frequently. Future research should delve into the impact of mental health during the tapering process.
The BIODOPT trial exhibited several strengths, such as being an investigator-initiated RCT with minimal patient attrition. The eligibility criteria ensured a study population representative of real-life outpatient settings. Notably, the study adhered to recommended practices for handling continuous variables unless nonlinearity was observed, demonstrating methodological rigor. Additionally, it addressed potential collinearity concerns and underwent robust internal validation.
One of the noteworthy findings was the potential significance of baseline mental health, particularly as indicated by the SF-36 Mental Component Summary (MCS) score. Post-hoc analyses revealed that patients with higher SF-36 MCS scores had a significantly higher chance of achieving successful tapering. This underscores the importance of considering mental health before initiating tapering and underscores the need for further research in this area.
In conclusion, this study, while demonstrating certain limitations, provides valuable insights into the challenges and potential predictors of successful biologic tapering in IA patients. Notably, it highlights the role of mental health as a factor that may influence tapering outcomes. Given the limited sample size, these findings should be interpreted with caution, emphasizing the need for future research to expand our understanding of this complex process.
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