Traditional versus marginal structural models to estimate the effectiveness of beta-blocker use on mortality after myocardial infarction

Abstract

Background: Observational studies of the effect of beta-blockers on all-cause mortality after an acute myocardial infarction (AMI) have tended to overestimate the effectiveness of this treatment.

Objective: To compare the estimates of the effect of beta-blocker use on mortality post-AMI derived from a traditional adjusted regression model with those from a marginal structural model.

Methods: A population-based cohort spanning the period of 2002-2004 was formed from the United Kingdom General Practice Research Database (GPRD). The cohort included all subjects who survived 90 days after their first AMI, who were then followed for 9 months. beta-Blocker use and blood pressure were identified in both the 90-day period before and the 90-day period after the AMI. Rate ratios (RR) were estimated using pooled logistic regression.

Results: The cohort included 9939 participants who survived 90 days after their AMI, of whom 633 died during the 9-month follow-up. Over 23% were taking beta-blockers pre-AMI, compared with 71% post-AMI. Using the traditional adjusted regression analysis, the RR of death with post-AMI beta-blocker use was 0.54 (95% confidence interval (CI): 0.45-0.67), while using the inverse probability of treatment weighting (IPTW) model it was 0.72 (95%CI: 0.61-0.84). The IPTW estimate is compatible with the estimate derived from a meta-analysis of randomized controlled trials (RCTs) while the adjusted regression estimate exaggerates the effectiveness.

Conclusions: Observational studies of the association of anti-hypertensive medications with all-cause mortality should consider adding a marginal structural model to their armamentarium of data analysis.