Predictors of response to anti-TNF therapy according to ACR and EULAR criteria in patients with established RA: results from the South Swedish Arthritis Treatment Group Register.

OBJECTIVE: To identify factors predicting response to first TNF blocking treatment course in patients with established RA with a special focus on gender differences.

METHODS: Patients with active RA initiating their first treatment course of TNF-blocking therapy were enrolled. The study period was March 1999 through September 2006. The prospective protocol included information on demographics, clinical characteristics of patients and response measures. Fulfilment of ACR 50-70% improvement and European League Against Rheumatism (EULAR) good response or remission [28-joint disease activity score (DAS28) <2.6] at 3 months were chosen as primary outcome measures. Potential predictors of responses were identified using multivariate binary logistic regression models.

RESULTS: In total, 1565 patients were included in the study. Gender did not influence treatment response. Consistently, concomitant methotrexate (MTX) was significantly associated with EULAR remission, EULAR good response, ACR50 response and ACR70 response with odds ratios (ORs) 1.97, 2.13, 2.10 and 1.75, respectively. Concurrent treatment with other DMARDs was also significantly associated with EULAR remission, EULAR good response and ACR50 response (OR: 1.96, 2.24 and 1.94, respectively). Likewise, low HAQ at baseline consistently predicted good clinical outcome. Disease activity at baseline was directly associated with favourable response when measured by ACR50 and ACR70 (OR: 1.59 and 1.60, respectively), whereas DAS28 score at baseline was inversely associated with EULAR remission (OR: 0.78).

CONCLUSIONS: In this observational study of patients with established RA, gender did not predict response to anti-TNF therapy, whereas treatment with concomitant DMARDs, especially MTX and low disability were associated with good response. Choice of outcome measures may influence the predictive value of baseline features.