title: Detecting Heterogeneous Treatment Effects to Guide Personalized Blood Pressure Treatment: A Modeling Study of Randomized Clinical Trials.
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.
  
  
  METHODS
  Microsimulation.
  
  
  METHODS
  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).
  
  
  METHODS
  U.S. adults.
  
  
  METHODS
  5 years.
  
  
  CONCLUSIONS
  Societal.
  
  
  METHODS
  BP treatment.
  
  
  METHODS
  CVD events and mortality.
  
  
  RESULTS
  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
  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).
  
  
  CONCLUSIONS
  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.
  
  
  CONCLUSIONS
  Clinically important heterogeneity in intensive BP treatment effects remains undetectable in conventional trial designs but can be detected in sequential randomization trial designs.
  
  
  BACKGROUND
  National Institutes of Health and U.S. Department of Veterans Affairs.
authors.affiliation: From Stanford University, Stanford, California; Harvard Medical School, Boston, Massachusetts; and University of Michigan, Ann Arbor, Michigan.
authors.forename: Sanjay
authors.initials: S
authors.lastname: Basu
authors.affiliation: From Stanford University, Stanford, California; Harvard Medical School, Boston, Massachusetts; and University of Michigan, Ann Arbor, Michigan.
authors.forename: Jeremy B
authors.initials: JB
authors.lastname: Sussman
authors.affiliation: From Stanford University, Stanford, California; Harvard Medical School, Boston, Massachusetts; and University of Michigan, Ann Arbor, Michigan.
authors.forename: Rod A
authors.initials: RA
authors.lastname: Hayward
mesh_terms: D000328:Adult; D000959:Antihypertensive Agents / Q000627:therapeutic use*; D002318:Cardiovascular Diseases / Q000150:complications / Q000517:prevention & control; D003198:Computer Simulation; D006801:Humans; D006973:Hypertension / Q000150:complications / Q000188:drug therapy*; D016032:Randomized Controlled Trials as Topic / Q000592:standards*; D012107:Research Design / Q000592:standards*; D012307:Risk Factors
chemical_list: D000959:Antihypertensive Agents