Predicting the Treatment Response of Biologics for Individual Patients with Rheumatoid Arthritis: An Individual Participant Data Meta-Analysis

Lead Investigator: Yan Luo, Kyoto University
Title of Proposal Research: Predicting the Treatment Response of Biologics for Individual Patients with Rheumatoid Arthritis: An Individual Participant Data Meta-Analysis
Vivli Data Request: 5990
Funding Source: None
Potential Conflicts of Interest: None

Summary of the Proposed Research:

Rheumatoid arthritis (RA) is a chronic inflammatory disease, for which currently we cannot expect complete cure. The drugs that can slow the disease progression are known as disease modifying anti-rheumatic drugs (DMARDs), which have many types. Most RA patients experience long-term treatment. According to the treat-to-target strategy proposed by the practice guideline, a physician should select an intervention for a patient, then re-evaluate after 3 to 6 months, based on which a next-step strategy is given. In order to improve long-term prognosis of RA (such as delaying the progression of bone fusion or functional deficiency), we should try to assure 3-6 months short-term clinical outcome to be good primarily. In other words, physicians should select an optimal intervention that would probably benefit the patient within the next 3 to 6 months treatment.

It is not an easy task for doctors to choose the right drug from so many alternatives. Especially evidence based on randomized controlled trials (RCTs) or their meta-analyses (MAs) at the aggregate level can only imply an average effect. But different patients would have different responses even if they are treated with the same drug. Thus it is necessary to identify subgroups of patients who show different responses. One way to achieve it is to build a prediction model of treatment response, taking account patients’ clinical and biological characteristics. We believe this prediction model would help physicians personalize treatment strategy.

For this purpose, we decide to develop a prediction model of treatment response using individual participant data meta-analysis (IPD-MA) of RCTs. It is regarded as a preferred approach, compared with usual observational study-based prediction models, since it has the following merits: (1) RCTs have more rigorously collected data; (2) RCTs are superior in computing relative treatment effects under alternative treatment conditions due to fewer confounders. In addition, IPD-MA, as a collection of multiple RCTs, can increase the statistical power in dealing with complex models.

Several promising modeling approaches of using IPD-MA to predict treatment response have been established and validated in some simulation studies, yet only one study has applied the method to real clinical settings (depression). The lead researcher of that study is also a co-researcher of our study. Besides, improving the modeling method is also one of our goal in this study. We will apply a new two-stage approach in developing this prediction model.

In summary, we are motivated to develop a prediction model via IPD-MA that can predict treatment effect for individual RA patients based on their baseline characteristics. Our final aim is to build a model that can predict treatment response for several key DMARDs, including adalimumab (ADA), a very important TNF-a inhibitors, tocilizumab (TCZ), an anti-IL6 antibody, and Rituximab (RTX), an anti-CD20 antibody, all with plenty of IPD.

The general study process is: (1) search/selection/risk of bias assessment of eligible studies; (2) applying for IPD; (3) conducting IPD-MA for average effect; (4) developing the prediction model using a two-stage approach: stage 1 – risk modeling; stage 2 – meta-regression.

Requested Studies:

A Phase 2b, Multicenter, Open-Label Study in Rheumatoid Arthritis Subjects Who Completed Preceding Study M13-390 With Adalimumab
Sponsor: AbbVie
Study ID: NCT01752855
Sponsor ID: M13-692

Study to Assess the Pharmacokinetic, Pharmacodynamic, Safety and Immunogenicity of a New Adalimumab Formulation in Subjects With Active Rheumatoid Arthritis
Sponsor: AbbVie
Study ID: NCT01712178
Sponsor ID: M13-390

A Multicenter, Randomized, Single-Blind Crossover Study of the Safety and Tolerability of Two Adalimumab Formulations in Adult Subjects With Rheumatoid Arthritis.
Sponsor: AbbVie
Study ID: NCT01561313
Sponsor ID: M12-783

A Multicenter, Randomized, Single-Blind Crossover Study of the Safety and Tolerability of Two Adalimumab Formulations in Adult Subjects With Rheumatoid Arthritis
Sponsor: AbbVie
Study ID: NCT01502423
Sponsor ID: M11-964

A Double-Blind, Randomized, Parallel-Arm, Multicenter Study to Determine the Dose Response of Methotrexate (MTX) in Combination Therapy With Adalimumab in Subjects With Early Rheumatoid Arthritis (CONCERTO)
Sponsor: AbbVie
Study ID: NCT01185301
Sponsor ID: M12-073

A Multicenter, Double-Blind, Randomized, Parallel-Arm Study to Determine the Effect of Methotrexate Dose on Clinical Outcome and Ultrasonographic Signs in Subjects With Moderately to Severely Active Rheumatoid Arthritis Treated With Adalimumab (MUSICA)
Sponsor: AbbVie
Study ID: NCT01185288
Sponsor ID: M12-071

A Multicenter, Randomized, Open-Label Study of the Injection Time and Usability of the Physiolis Syringe and Autoinjector in Injection-Experienced Rheumatoid Arthritis Patients
Sponsor: AbbVie
Study ID: NCT01163617
Sponsor ID: M12-088

A Phase 3 Multi-Center, Randomized, Double-Blind, Parallel Group, Placebo-Controlled Study Comparing Adalimumab and Placebo in Adult Japanese Subjects With Rheumatoid Arthritis
Sponsor: AbbVie
Study ID: NCT00870467
Sponsor ID: M06-859

Open Label Study to Assess Efficacy and Safety of the Fully Human Anti-TNF-Alpha Monoclonal Antibody Adalimumab
Sponsor: AbbVie
Study ID: NCT00650390
Sponsor ID: M02-532

Multicenter Early Access Program of the Safety of Human Anti-TNF Monoclonal Antibody Adalimumab in Subjects With Active Rheumatoid Arthritis
Sponsor: AbbVie
Study ID: NCT00650026
Sponsor ID: M03-583

A Multi-Center Study of the Safety and Efficacy of Human Anti-TNF Monoclonal Antibody Adalimumab (D2E7) in Patients With Active Rheumatoid Arthritis
Sponsor: AbbVie
Study ID: NCT00649545
Sponsor ID: M02-574