Can clinical factors at presentation be used to predict outcome of treatment with methotrexate in patients with early inflammatory polyarthritis?

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Abstract

Purpose:

Methotrexate (MTX) is the first choice conventional disease-modifying antirheumatic drug (DMARD) for rheumatoid arthritis. It is not universally effective, however; although to date it is not possible to predict with any accuracy which patients will respond to treatment. The aim of this analysis was to examine whether clinical and genetic variables could be used to predict response to MTX.

Methods:

Patients recruited to the Norfolk Arthritis Register (NOAR), a primary care based inception cohort of patients with inflammatory polyarthritis, were eligible for this analysis if they were commenced on MTX as their first DMARD within 3 months of their baseline visit and had at least 2 years of follow-up data. Outcome on MTX was defined as: (1) stopped for adverse events; (2) stopped for inefficacy or second DMARD added; (3) stopped for other reasons; or (4) remained on MTX monotherapy. Multiple logistic regression was used to establish which variables (including demographics, disease activity and Health Assessment Questionnaire score) predicted stopping monotherapy for inefficacy or adverse event (with those remaining on treatment taken as the referent category). The area under the Receiver Operating Characteristic curves (AUC ROC), were used to determine how accurate the model was at predicting outcome.

Results:

309 patients were included in this analysis. At 1 year (2 years), 34 (46) patients had stopped for adverse events and 25 (49) had either stopped monotherapy for inefficacy or had a second DMARD added. 231 (188) patients remained on MTX monotherapy. The strongest predictor of inefficacy at both time points was shared epitope positivity: odds ratios (OR) 5.8 (95% confidence intervals (CI) 1.3 to 25.6) at 1 year, OR 3.0 (95% CI 1.3 to 7.3) at 2 years. High Health Assessment Questionnaire score (OR 1.84 95% CI 1.12 to 3.01) and female gender (OR 2.2, 95% CI 0.92 to 5.28) were associated with adverse events on MTX at 1 year. However, even the most optimal combinations of the factors analysed were only weakly predictive of treatment outcome: AUC ROC for adverse events 0.68 (95% CI 0.58 to 0.78) and for inefficacy AUC ROC 0.71 (95% CI 0.6 to 0.81).

Conclusions:

Within this cohort, routine clinical and laboratory factors were poor at predicting outcome of treatment with MTX. Given the major therapeutic advantage to be derived from accurate prediction of treatment outcome, further studies will need to investigate novel biological and other markers.

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