Comparing marginal structural models to standard methods for estimating treatment effects of antihypertensive combination therapy

نویسندگان

  • Tobias Gerhard
  • Joseph AC Delaney
  • Rhonda M Cooper-DeHoff
  • Jonathan Shuster
  • Babette A Brumback
  • Julie A Johnson
  • Carl J Pepine
  • Almut G Winterstein
چکیده

BACKGROUND Due to time-dependent confounding by blood pressure and differential loss to follow-up, it is difficult to estimate the effectiveness of aggressive versus conventional antihypertensive combination therapies in non-randomized comparisons. METHODS We utilized data from 22,576 hypertensive coronary artery disease patients, prospectively enrolled in the INternational VErapamil-Trandolapril STudy (INVEST). Our post-hoc analyses did not consider the randomized treatment strategies, but instead defined exposure time-dependently as aggressive treatment (≥3 concomitantly used antihypertensive medications) versus conventional treatment (≤2 concomitantly used antihypertensive medications). Study outcome was defined as time to first serious cardiovascular event (non-fatal myocardial infarction, non-fatal stroke, or all-cause death). We compared hazard ratio (HR) estimates for aggressive vs. conventional treatment from a Marginal Structural Cox Model (MSCM) to estimates from a standard Cox model. Both models included exposure to antihypertensive treatment at each follow-up visit, demographics, and baseline cardiovascular risk factors, including blood pressure. The MSCM further adjusted for systolic blood pressure at each follow-up visit, through inverse probability of treatment weights. RESULTS 2,269 (10.1%) patients experienced a cardiovascular event over a total follow-up of 60,939 person-years. The HR for aggressive treatment estimated by the standard Cox model was 0.96 (95% confidence interval 0.87-1.07). The equivalent MSCM, which was able to account for changes in systolic blood pressure during follow-up, estimated a HR of 0.81 (95% CI 0.71-0.92). CONCLUSIONS Using a MSCM, aggressive treatment was associated with a lower risk for serious cardiovascular outcomes compared to conventional treatment. In contrast, a standard Cox model estimated similar risks for aggressive and conventional treatments. TRIAL REGISTRATION Clinicaltrials.gov Identifier: NCT00133692.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Structural accelerated failure time models for survival analysis in studies with time-varying treatments.

BACKGROUND In the absence of unmeasured confounding factors and model misspecification, standard methods for estimating the causal effect of time-varying treatments on survival are biased when (i) there exists a time-dependent risk factor for survival that also predicts subsequent treatment and (ii) past treatment history predicts subsequent risk factor level. In contrast, structural models pro...

متن کامل

Controlling for time-dependent confounding using marginal structural models

Longitudinal studies in which exposures, confounders, and outcomes are measured repeatedly over time have the potential to allow causal inferences about the effects of exposure on outcome. There is particular interest in estimating the causal effects of medical treatments (or other interventions) in circumstances in which a randomized controlled trial is difficult or impossible. However, standa...

متن کامل

Estimating the causal effect of zidovudine on CD4 count with a marginal structural model for repeated measures.

Even in the absence of unmeasured confounding factors or model misspecification, standard methods for estimating the causal effect of a time-varying treatment on the mean of a repeated measures outcome (for example, GEE regression) may be biased when there are time-dependent variables that are simultaneously confounders of the effect of interest and are predicted by previous treatment. In contr...

متن کامل

How to use marginal structural models in randomized trials to estimate the natural direct and indirect effects of therapies mediated by causal intermediates.

BACKGROUND Although intention-to-treat analysis is a standard approach, additional supplemental analyses are often required to evaluate the biological relationship among interventions, intermediates, and outcomes. Therefore, we need to evaluate whether the effect of an intervention on a particular outcome is mediated by a hypothesized intermediate variable. PURPOSE To evaluate the size of the...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره 12  شماره 

صفحات  -

تاریخ انتشار 2012