Decision Impact Analysis to Measure the Influence of Molecular Signature Response Classifier Testing on Treatment Selection in Rheumatoid Arthritis.

Introduction: Clinical guidelines offer little guidance for treatment selection following inadequate response to conventional synthetic disease-modifying antirheumatic drug (csDMARD) in rheumatoid arthritis (RA). A molecular signature response classifier (MSRC) was validated to predict tumor necrosis factor inhibitor (TNFi) inadequate response. The decision impact of MSRC results on biologic and targeted synthetic disease-modifying antirheumatic drug (b/tsDMARD) selection was evaluated.

Methods: This is an analysis of AIMS, a longitudinal, prospective database of patients with RA tested using the MSRC. This study assessed selection of b/tsDMARDs class after MSRC testing by surveying physicians, the rate of b/tsDMARD prescriptions aligning with MSRC results, and the percentage of physicians utilizing MSRC results for decision-making.

Results: Of 1018 participants, 70.7% (720/1018) had treatment selected after receiving MSRC results. In this MSRC-informed cohort, 75.6% (544/720) of patients received a b/tsDMARD aligned with MSRC results, and 84.6% (609/720) of providers reported using MSRC results to guide treatment selection. The most prevalent reason reported (8.2%, 59/720) for not aligning treatment selection with MSRC results from the total cohort was health insurance coverage issues.

Conclusion: This study showed that rheumatologists reported using the MSRC test to guide b/tsDMARD selection for patients with RA. In most cases, MSRC test results appeared to influence clinical decision-making according to physician self-report. Wider adoption of precision medicine tools like the MSRC could support rheumatologists and patients in working together to achieve optimal outcomes for RA.