Validation of a Prognostic Multivariable Prediction Model for Insufficient Clinical Response to Methotrexate in Early Rheumatoid Arthritis and Its Clinical Application in Evidencio

Introduction Methotrexate (MTX) constitutes the first-line therapy in rheumatoid arthritis (RA), yet approximately 30% of the patients do not benefit from MTX. Recently, we reported a prognostic multivariable prediction model for insufficient clinical response to MTX at 3 months of treatment in the treatment in the Rotterdam Early Arthritis Cohort (tREACH), including baseline predictors: Disease activity score 28 (DAS28), Health Assessment Questionnaire (HAQ), erythrocyte folate, single-nucleotide polymorphisms (SNPs;ABCB1,ABCC3), smoking, and BMI. The purpose of the current study was (1) to externally validate the model and (2) to enhance the model's clinical applicability. Methods Erythrocyte folate and SNPs were assessed in 91 early disease-modifying antirheumatic drug (DMARD)-naive RA patients starting MTX in the external validation cohort (U-Act-Early). Insufficient response (DAS28 > 3.2) was determined after 3 months and non-response after 6 months of therapy. The previously developed prediction model was considered successfully validated in the U-Act-Early (validation cohort) if the area under the curve (AUC) of the receiver operating characteristic (ROC) was not significantly lower than in the tREACH (derivation cohort). Results The AUCs in U-Act-Early at three and 6 months were 0.75 (95% CI 0.64-0.85) and 0.71 (95% CI 0.60-0.82) respectively, similar to the tREACH. Baseline DAS28 > 5.1 and HAQ > 0.6 were the strongest predictors. The model was simplified by excluding the SNPs, while still classifying 73% correctly. Furthermore, interaction terms between BMI and HAQ and BMI and erythrocyte folate significantly improved the model increasing correct classification to 75%. Results were successfully implemented in Evidencio online platform assisting clinicians in shared decision-making to intensify treatment when appropriate. Conclusions We successfully externally validated our recently reported prediction model for MTX non-response and enhanced its clinical application thus enabling its evaluation in a clinical trial.