Despite the success of TNF-alpha inhibitor (TNFi) treatment in rheumatoid arthritis (RA), a substantial number of patients necessitate discontinuation. Prediction thereof would be clinically relevant and guide the decision whether to start TNFi treatment.
Data were used from the observational BiOCURA cohort, in which patients initiating biological treatment were enrolled and followed up for one year. In the model development cohort (n=192), a model predicting TNFi discontinuation was built using Cox-regression with backward selection (p<0.05). The parameters of the model were tested again in a model refinement cohort (n=60), for significance (p<0.05) and consistency of effect. In addition, we performed a systematic review to put our study results into perspective.
Of the 252 patients who initiated TNFi treatment, 103 (41%) had to discontinue treatment. Discontinuation was predicted at baseline by female gender, current smoking, high visual analogue scale of general health, and higher number of previously used biological disease-modifying anti-rheumatic drugs (bDMARDs). At refinement, smoking status and number of previously used bDMARDs remained with re-estimated hazard ratios (HRs) in the total cohort of 1.74 (95%-CI 1.15-2.63, p<0.01) and 1.40 (95%-CI 1.1-1.68, p<0.01), respectively. Using these two predictors, we developed a simple score predicting discontinuation (PPV=72.3%). From literature, predictors were pack years of smoking, number of previously used bDMARDs, lack of any concomitant DMARD therapy and in particular lack of concomitant methotrexate (MTX).
TNFi discontinuation is predicted by current smoking and number of previously used bDMARDs, as well as by pack years of smoking and lack of any concomitant DMARD/MTX therapy.