Evidence map›Paper›PMID 28055048›Full record

ArticleAnnals of internal medicine2017

Detecting Heterogeneous Treatment Effects to Guide Personalized Blood Pressure Treatment: A Modeling Study of Randomized Clinical Trials.

Sanjay Basu, Jeremy B Sussman, Rod A Hayward

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

28 citing papers in PubMed.

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  19. Precision population analytics: population management at the point-of-care.Journal of the American Medical Informatics Association : JAMIA · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Sanjay BasuFrom Stanford University, Stanford, California; Harvard Medical School, Boston, Massachusetts; and University of Michigan, Ann Arbor, Michigan.
Jeremy B SussmanFrom Stanford University, Stanford, California; Harvard Medical School, Boston, Massachusetts; and University of Michigan, Ann Arbor, Michigan.
Rod A HaywardFrom Stanford University, Stanford, California; Harvard Medical School, Boston, Massachusetts; and University of Michigan, Ann Arbor, Michigan.

Funding

PUBLIC HEALTH DEMONSTRATIONP60DK020572 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MYERS, MARTIN G · 1985 to 2012
$26.5M
Trial of strategies to communicate genetic information to different ethnic and racial subpopulationsU54MD010724 · NIMHD · STANFORD UNIVERSITY · PI MALDONADO, YVONNE A. · 2016 to 2021
$16.3M
Cohort filtering models to identify social program effects on health disparitiesDP2MD010478 · NIMHD · STANFORD UNIVERSITY · PI BASU, SANJAY · 2015 to 2015
$2.4M
Studying social factors in sodium consumption to reduce hypertension disparitiesK08HL121056 · NHLBI · STANFORD UNIVERSITY · PI BASU, SANJAY · 2014 to 2017
$599k
HSRD VA IK2 HX001368NHLBI NIH HHS K08 HL121056NIDDK NIH HHS P60 DK020572NIMHD NIH HHS DP2 MD010478NIMHD NIH HHS U54 MD010724
6 · The paper itself

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.

Indexed as

AdultAntihypertensive AgentsCardiovascular DiseasesComputer SimulationHumansHypertensionRandomized Controlled Trials as TopicResearch DesignRisk FactorsAntihypertensive Agents

Identifiers

PMID28055048
PMCPMC5815372

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.