ArticleAnnals of internal medicine2017
Detecting Heterogeneous Treatment Effects to Guide Personalized Blood Pressure Treatment: A Modeling Study of Randomized Clinical Trials.
Article in Annals of internal medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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The trial behind it
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Who cites it
28 citing papers in PubMed.
- Individualized Net Benefit of Intensive Blood Pressure Lowering Among Community-Dwelling Older Adults in SPRINT.Journal of the American Geriatrics Society · 2025Trial
- Efficacy of electro-acupuncture in postpartum with diastasis recti abdominis: A randomized controlled clinical trial.Frontiers in public health · 2022Trial
- Assessment of Risk of Harm Associated With Intensive Blood Pressure Management Among Patients With Hypertension Who Smoke: A Secondary Analysis of the Systolic Blood Pressure Intervention Trial.JAMA network open · 2019Trial
- Trial
- Systolic Blood Pressure Response in SPRINT (Systolic Blood Pressure Intervention Trial) and ACCORD (Action to Control Cardiovascular Risk in Diabetes): A Possible Explanation for Discordant Trial Results.Journal of the American Heart Association · 2017Trial
- Benefit and harm of intensive blood pressure treatment: Derivation and validation of risk models using data from the SPRINT and ACCORD trials.PLoS medicine · 2017 · on this mapTrial
- Alternative clinical trial designs to find a clinically important effect size of blood pressure-lowering on cognitive impairment and dementia.Journal of Alzheimer's disease : JAD · 2026Article
- Synthetic data Using Population Profiles for cardiOvascular Risk facTors (SUPPORT) in mainland China.Scientific data · 2026Article
- Generalized framework for identifying meaningful heterogenous treatment effects in observational studies: A parametric data-adaptive G-computation approach.Statistical methods in medical research · 2025Article
- Application of causal forests to randomised controlled trial data to identify heterogeneous treatment effects: a case study.BMC medical research methodology · 2025Article
- Evaluating Treatment Prioritization Rules via Rank-Weighted Average Treatment Effects.Journal of the American Statistical Association · 2025Article
- The potential impact of optimal blood pressure treatment intensity to reduce disparities in dementia between Black and White individuals.Journal of Alzheimer's disease : JAD · 2025Observational
- Integrating predictive modeling and causal inference for advancing medical science.Childhood kidney diseases · 2024Review
- Effect of Population-Level Blood Pressure Treatment Strategies on Cardiovascular and Cognitive Outcomes.Circulation. Cardiovascular quality and outcomes · 2024Article
- Machine-learning-based high-benefit approach versus conventional high-risk approach in blood pressure management.International journal of epidemiology · 2023Article
- Targeting efficacy of spironolactone in patients with heart failure with preserved ejection fraction: the TOPCAT study.ESC heart failure · 2023Article
- Heterogeneity of Treatment Effects for Intensive Blood Pressure Therapy by Individual Components of FRS: An Unsupervised Data-Driven Subgroup Analysis in SPRINT and ACCORD.Frontiers in cardiovascular medicine · 2022Article
- Estimating heterogeneous survival treatment effects of lung cancer screening approaches: A causal machine learning analysis.Annals of epidemiology · 2021Article
- Precision population analytics: population management at the point-of-care.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Heterogeneous Exposure Associations in Observational Cohort Studies: The Example of Blood Pressure in Older Adults.American journal of epidemiology · 2020Article
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3 authors.
Funding
Abstract
backgroundTwo 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).
objectiveTo 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.
designMicrosimulation. 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.
interventionBP 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.
conclusionClinically 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.