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.