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JOURNAL ARTICLE
OBSERVATIONAL STUDY
Necessity of TNF-alpha inhibitor discontinuation in rheumatoid arthritis is predicted by smoking and number of previously used biological DMARDs.
Clinical and Experimental Rheumatology 2017 March
OBJECTIVES: 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.
METHODS: 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.
RESULTS: 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).
CONCLUSIONS: 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.
METHODS: 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.
RESULTS: 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).
CONCLUSIONS: 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.
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