Predicting future response to certolizumab pegol in rheumatoid arthritis patients: features at 12 weeks associated with low disease activity at 1 year.

OBJECTIVE: To determine the prognostic significance of data collected early after starting certolizumab pegol (CZP) to predict low disease activity (LDA) at week 52.
METHODS: Data from 703 CZP-treated patients in the Rheumatoid Arthritis Prevention of Structural Damage 1 (RAPID 1) trial through week 12 were used as variables to predict LDA (Disease Activity Score in 28 joints-erythrocyte sedimentation rate ≤3.2) at week 52. We identified variables, developed prediction models using classification trees, and tested performance using training and testing data sets. Additional prediction models were constructed using the Clinical Disease Activity Index (CDAI) and an alternate outcome definition (composite of LDA or American College of Rheumatology criteria for 50% improvement [ACR50]).
RESULTS: Using week 6 and 12 data and across several different prediction models, response (LDA) and nonresponse at 1 year were predicted with relatively high accuracy (70-90%) for most patients. The best performing model predicting nonresponse by 12 weeks was 90% accurate and applied to 46% of the population. Model accuracy for predicted responders (30% of the RAPID 1 population) was 74%. The area under the receiver operating curve was 0.76. Depending on the desired certainty of prediction at 12 weeks, ~12-25% of patients required >12 weeks of treatment to be accurately classified. CDAI-based models and those evaluating the composite outcome (LDA or ACR50) achieved comparable accuracy.
CONCLUSION: We could accurately predict within 12 weeks of starting CZP whether most established rheumatoid arthritis (RA) patients with high baseline disease activity would likely achieve/not achieve LDA at 1 year. Decision trees may be useful to guide prospective management for RA patients treated with CZP and other biologics.

RCT Entities:   Population Interventions Outcomes