Evidence map›Paper›PMID 23651763›Full record

ReviewJournal of clinical epidemiology2013

A framework for the analysis of heterogeneity of treatment effect in patient-centered outcomes research.

Ravi Varadhan, Jodi B Segal, Cynthia M Boyd, Albert W Wu, Carlos O Weiss

Registry-linked trialAbstract readReview
In one paragraph

Review in Journal of clinical epidemiology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04251208 (MOms in REcovery), which is not on this map. Cited by 70 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed, 8 pooled it
–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.

NCT04251208 completednot on this mapstarted 2019, after this paper: background citation

MOms in REcovery (MORE): Defining Optimal Care for Pregnant Women and Infants

TypeobservationalSponsorTrustees of Dartmouth CollegeRan2019 to 2024Enrolled444ConditionsOpioid-Related Disorders, NAS, Substance Use DisordersArmsObservational Study
3 · Its place in the literature

Who cites it

70 citing papers in PubMed, 8 syntheses or guidelines pooled it.

  1. Pooled it
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  3. Effectiveness of telemedicine-based psychosocial intervention for breast cancer patients: a systematic review and meta-analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023
    Pooled it
  4. Multimorbidity in randomized controlled trials of behavioral interventions: A systematic review.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2019
    Pooled it
  5. Smoking Cessation Pharmacotherapy Based on Genetically-Informed Biomarkers: What is the Evidence?Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco · 2019
    Pooled it
  6. A systematic review of randomised controlled trials evaluating the use of patient-reported outcome measures (PROMs).Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2019
    Pooled it
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  14. Practical guidance on modeling choices for the virtual twins method.Journal of biopharmaceutical statistics · 2023
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10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Ravi VaradhanDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA. rvaradhan@jhmi.edu
Jodi B Segal
Cynthia M Boyd
Albert W Wu
Carlos O Weiss

Funding

Treatment Burden in Older Adults with Diabetes and MultimorbidityK23AG032910 · NIA · JOHNS HOPKINS UNIVERSITY · PI BOYD, CYNTHIA MELINDA · 2009 to 2013
$533k
NIA NIH HHS K23 AG032910NIA NIH HHS K23AG032910
6 · The paper itself

Abstract

Individuals vary in their response to a treatment. Understanding this heterogeneity of treatment effect is critical for evaluating how well a treatment can be expected to work for an individual or a subgroup of individuals. An overemphasis on hypothesis testing has resulted in a dichotomy of all heterogeneity of treatment effect analyses into confirmatory (hypothesis testing) and exploratory (hypothesis finding) analyses. This limited view of heterogeneity of treatment effect is inadequate for creating evidence that is useful for informing patient-centered decisions. An expanded framework for heterogeneity of treatment effect assessment is proposed. It recognizes four distinct goals of heterogeneity of treatment effect analyses: hypothesis testing, hypothesis finding, reporting subgroup effects for meta-analysis, and individual-level prediction. Accordingly, two new types of heterogeneity of treatment effect analyses are proposed: descriptive and predictive. Descriptive heterogeneity of treatment effect analyses report treatment effects for prespecified subgroups in accordance with prospectively specified analytic strategy. They need not be powered to detect heterogeneity of treatment effect. They emphasize estimation and reporting of subgroup effects rather than hypothesis testing. Sampling properties (e.g., standard error) of descriptive analysis can be characterized, thus facilitating meta-analysis of subgroup effects. Predictive heterogeneity of treatment effect analyses estimate probabilities of beneficial and adverse responses of individuals to treatments and facilitates optimal treatment decisions for different types of individuals. Procedures are also suggested to improve reliability of heterogeneity of treatment effect assessment from observational studies. Heterogeneity of treatment effect analysis should be identified as confirmatory, descriptive, exploratory, or predictive analysis. Evidence should be interpreted in a manner consistent with the analytic goal.

Indexed as

Data Interpretation, StatisticalRandomized Controlled Trials as TopicComparative Effectiveness ResearchHumansMeta-Analysis as TopicOutcome Assessment, Health CareReproducibility of Results

Identifiers

PMID23651763
PMCPMC4450361

What OpenQuestion holds

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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.