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

Abstract

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. 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. 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. 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. 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.