Estimating antihypertensive effects of combination therapy in an observational study using marginal structural models.

The evaluation of the antihypertensive effect of multiple antihypertensive drugs using data from an observational study requires adjustment for time-dependent confounders. Marginal structural models (MSMs) have been proposed to address this type of confounding through inverse probability weighting. Generally, the probabilities are estimated using logistic regression models that assume linearity between the logistic link and the predictors, but the linearity might be inaccurate. In this article, we proposed MSMs to assess the blood pressure-lowering effects of combination therapy with olmesartan medoxomil (OLM) plus calcium channel blockers (CCB) (OLM+CCB) in an observational study of OLM, and extended estimation methods of the probabilities for the MSMs using generalized additive models (GAMs). The estimation using GAMs was suggested to improve the balance of the distributions of confounder values between the therapy groups in the pseudo-population. We obtained estimated changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP) for OLM+CCB combination therapy after 12 wk compared with OLM monotherapy of -4.3 mmHg (95% confidence interval (CI): -7.7 and -0.9 mmHg) and -2.9 mmHg (95% CI: -5.1 and -0.7 mmHg), respectively. The estimated target BP (SBP<140 mmHg and DBP<90 mmHg) achievement rates for OLM+CCB combination therapy and OLM monotherapy were 62.0 and 46.7%, respectively. The results of the MSMs were closer to those in the randomized controlled trial, such as the combination of OLM and amlodipine besylate in controlling high blood pressure study, than those of conventional methods. The proposed MSMs provided useful information to evaluate the effects of combination therapy of antihypertensive drugs in the context of an observational study.