- Home
- Featured Publications
- Center Publications
- Detecting Heterogeneous Treatment Effects to Guide Personalized Blood Pressure Treatment: A Modeling Study of Randomized Clinical Trials.
Detecting Heterogeneous Treatment Effects to Guide Personalized Blood Pressure Treatment: A Modeling Study of Randomized Clinical Trials.
Citation | “Detecting Heterogeneous Treatment Effects To Guide Personalized Blood Pressure Treatment: A Modeling Study Of Randomized Clinical Trials.”. Annals Of Internal Medicine, pp. 354-360. . |
Center | University of Michigan |
Author | Sanjay Basu, Jeremy B Sussman, Rod A Hayward |
Abstract |
Background: Two recent randomized trials produced discordant results when testing the benefits and harms of treatment to reduce blood pressure (BP) in patients with cardiovascular disease (CVD). Objective: To perform a theoretical modeling study to identify whether large, clinically important differences in benefit and harm among patients (heterogeneous treatment effects [HTEs]) can be hidden in, and explain discordant results between, treat-to-target BP trials. Design: Microsimulation. Data Sources: Results of 2 trials comparing standard (systolic BP target <140 mm Hg) with intensive (systolic BP target <120 mm Hg) BP treatment and data from the National Health and Nutrition Examination Survey (2013 to 2014). Target Population: U.S. adults. Time Horizon: 5 years. Perspective: Societal. Intervention: BP treatment. Outcome Measures: CVD events and mortality. Results of Base-Case Analysis: Clinically important HTEs could explain differences in outcomes between 2 trials of intensive BP treatment, particularly diminishing benefit with each additional BP agent (for example, adding a second agent reduces CVD risk [hazard ratio, 0.61], but adding a fourth agent to a third has no benefit) and increasing harm at low diastolic BP. Results of Sensitivity Analysis: Conventional treat-to-target trial designs had poor (<5%) statistical power to detect the HTEs, despite large samples (n > 20 000), and produced biased effect estimates. In contrast, a trial with sequential randomization to more intensive therapy achieved greater than 80% power and unbiased HTE estimates, despite small samples (n = 3500). Limitations: The HTEs as a function of the number of BP agents only were explored. Simulated aggregate data from the trials were used as model inputs because individual-participant data were not available. Conclusion: Clinically important heterogeneity in intensive BP treatment effects remains undetectable in conventional trial designs but can be detected in sequential randomization trial designs. Primary Funding Source: National Institutes of Health and U.S. Department of Veterans Affairs. |
Year of Publication |
2017
|
Journal |
Annals of internal medicine
|
Volume |
166
|
Issue |
5
|
Number of Pages |
354-360
|
Date Published |
03/2017
|
ISSN Number |
1539-3704
|
DOI |
10.7326/M16-1756
|
Alternate Journal |
Ann. Intern. Med.
|
PMID |
28055048
|
PMCID |
PMC5815372
|
Download citation |