Casual effect of methotrexate+etanercept/infliximab on survival of patients with rheumatoid arthritis

Background and objectives: Following the discovery of new drugs, physicians and pharmaceutical companies have become interested in examining patients' mortality and morbidity rates. In this respect, the effects of methotrexate (MTX)+etanercept/infliximab (ETA/INF) therapy on the survival of rheumatoid arthritis patients (RA) were evaluated in this study using marginal structural piecewise constant baseline hazard model. Patients and methods: According to the standard protocol, MTX is considered as the first-line treatment for RA patients. If there is no adequate response to MTX, biologic drugs will be added. To compare the survival rates of RA patients in MTX- and MTX+ETA/INF-treated groups, the piecewise constant baseline hazard model was fitted. Then, due to the existence of the time-dependent confounder (VAS) which was affected by previous treatment, the weight for each person-time was calculated via the inverse probability treatment weighting method. These weights were then used by marginal structural piecewise constant baseline hazard model. Finally, these models were compared. Results: The median (IQR) of the follow-up period in patients receiving MTX+ETN/INF and MTX was 11 (15.25) and 11 (31), respectively, and the 8-year survival rate was reported by 70% versus 68%, respectively. First, the piece-wise constant baseline hazard model was fitted. Fitting the given model showed that MTX+ETA/INF had a significant effect on patients' survival (HR=0.789, 95% CI [0.634, 0.983]). Second, marginal structural piecewise constant baseline hazard model was fitted. But, the results of this model revealed that MTX+ETA/INF did not have a significant impact on patients' survival (HR=0.968, 95% CI [0.860, 1.090]). Conclusion: Adjusting the pain score over time as a time-dependent confounder via marginal structural piecewise constant baseline hazard model, it has been demonstrated that MTX+ETA/INF does not have a significant effect on patients' survival rates. Therefore, a significant difference can be found between survival rates of these groups using longitudinal studies.