Evidence map›Paper›PMID 36373783›Full record

ArticleClinical trials (London, England)2023

Randomized controlled trials of biomarker targets.

Margret Erlendsdottir, Forrest W Crawford

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Margret ErlendsdottirDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.ORCID 0000-0002-6413-7626
Forrest W CrawfordDepartment of Biostatistics, Yale School of Public Health, New Haven, CT, USA.

Funding

Network-based epidemiology for hidden and hard-to-reach populationsDP2HD091799 · NICHD · YALE UNIVERSITY · PI CRAWFORD, FORREST WRENN · 2016 to 2016
$2.5M
NICHD NIH HHS DP2 HD091799
6 · The paper itself

Abstract

introductionRandomized controlled trials are used to estimate the causal effect of a treatment on a health outcome of interest in a patient population. Often the specified treatment in a randomized controlled trial is a medical intervention-such as a drug or procedure-experienced directly by the patient. Sometimes the "treatment" in a randomized controlled trial is a target-such as a goal biomarker measurement-that the patient's physician attempts to reach using available medications or procedures. Large randomized controlled trials of biomarker targets are common in clinical research, and trials have been conducted to compare targets in the management of hypertension, diabetes, anemia, and acute respiratory distress syndrome. However, different randomized controlled trials intended to evaluate the same biomarker targets have produced conflicting recommendations, and meta-analyses that aggregate results of trials of biomarker targets have been inconclusive.

methodsWe use causal reasoning to explain why randomized controlled trials of biomarker targets can arrive at conflicting or misleading conclusions. We describe four key threats to the validity of trials of targets: (1) intention-to-treat analysis can be misleading when a direct effect of target assignment on the outcome exists due to lack of blinding; (2) incomparability in results across trials of targets; (3) time-varying adaptive treatment strategies; and (4) Goodhart's law, "when a measure becomes a target, it ceases to be a good measure."

resultsWe illustrate these findings using evidence from 15 randomized controlled trials of blood pressure targets for management of hypertension. Randomized trials of blood pressure targets exhibit substantial variation in the trial patient populations and antihypertensives used to achieve the blood pressure targets assigned in the trials. The trials did not compare or account for time-varying treatment strategies used to reach the randomized targets. Possible "off-target" effects of antihypertensive medications needed to reach lower blood pressure targets may explain the absence of a clear benefit from intensive blood pressure control. DISCUSSION: Researchers should critically assess meta-analyses of trials of targets for variation in the types, distributions, and off-target effects of therapies studied. Trial investigators should release detailed information about the biomarker targets compared in new randomized trials, as well as confounders, treatments delivered, and outcomes. New randomized controlled trials should experimentally compare treatment algorithms incorporating biomarkers, rather than targets alone. Causal inference methodology that adjusts for time-varying confounding should be used to compare time-varying treatment strategies in observational settings.

Indexed as

HypertensionBiomarkersBlood PressureHumansRandomized Controlled Trials as TopicBiomarkerscausal inferencehypertensionIntention-to-treatmeta-analysisrandomized controlled trial

Identifiers

PMID36373783
PMCPMC9974557

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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.