Evidence map›Paper›PMID 31152807›Full record

ArticleDiabetes research and clinical practice2020

The Estimating effectiveness from efficacy taxonomy (EFFECT): A tool to estimate the real-world impact of health interventions.

Karla I Galaviz, Mohammed K Ali, Jeehea Sonya Haw, Matthew James Magee, Alysse Kowalski, Jingkai Wei, Audrey Straus, Mary Beth Weber, Theo Vos, Christopher Murray and 1 more

Abstract read
In one paragraph

Article in Diabetes research and clinical practice, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Karla I GalavizHubert Department of Global Health, Emory University, Atlanta, GA 30322, USA. Electronic address: kgalavi@emory.edu.
Mohammed K AliHubert Department of Global Health, Emory University, Atlanta, GA 30322, USA. Electronic address: mkali@emory.edu.
Jeehea Sonya HawDepartment of Endocrinology and Metabolism, Emory University School of Medicine, Atlanta, GA 30307, USA. Electronic address: jeehea.sonya.haw@emory.edu.
Matthew James MageeSchool of Public Health, Georgia State University, Atlanta, GA 30302, USA. Electronic address: mjmagee@gsu.edu.
Alysse KowalskiHubert Department of Global Health, Emory University, Atlanta, GA 30322, USA. Electronic address: alysse.kowalski@emory.edu.
Jingkai WeiDepartment of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Electronic address: jingkai@live.unc.edu.
Audrey StrausCommUnityCare Health Centers, Austin, TX 78758, USA. Electronic address: audrey.straus@communitycaretx.org.
Mary Beth WeberHubert Department of Global Health, Emory University, Atlanta, GA 30322, USA. Electronic address: mbweber@emory.edu.
Theo VosInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA. Electronic address: tvos@uw.edu.
Christopher MurrayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA. Electronic address: cjlm@uw.edu.
K M V NarayanHubert Department of Global Health, Emory University, Atlanta, GA 30322, USA. Electronic address: KNARAYA@emory.edu.

Funding

Translational Research Core - Engagement and Behavior ChangeP30DK111024 · NIDDK · EMORY UNIVERSITY · PI Mohammed Kumail Ali · 2016 to 2026
$13.4M
NIDDK NIH HHS P30 DK111024
6 · The paper itself

Abstract

aimsTo develop and pilot test a taxonomy that empirically estimates health intervention effectiveness from efficacy data.

methodsWe developed a taxonomy to score health interventions across 11 items on a scale from 0-100. The taxonomy was pilot-tested in efficacy and effectiveness diabetes prevention studies identified in two separate systematic reviews; here, the face validity, inter-rater reliability and factor structure of the taxonomy were established. Random effects meta-analyses were used to obtain weight loss and diabetes incidence pooled effects across studies. These effects and taxonomy scores were used to down calibrate efficacy estimates to effectiveness estimates as follows: Efficacy effect*[Efficacy score/highest possible score].

resultsWe scored 82 effectiveness lifestyle modification studies (mean score 49.2), 32 efficacy lifestyle modification studies (mean score 69.8) and 20 efficacy studies testing medications (mean score 77.4). The taxonomy had face validity and good inter-rater reliability (ICC = 0.9 [0.87, 0.93]). The between-groups down calibrated weight loss estimate was similar to that observed in the effectiveness meta-analysis (1.7 and 1.8 kg, respectively). The down calibrated diabetes relative risk reduction was also similar to that observed in the effectiveness meta-analysis (30.6% over 2.7 years and 29% over 2 years, respectively).

conclusionsThe taxonomy is a promising tool to estimate the real-world impact of health interventions.

Indexed as

Life StyleClassificationFemaleGlobal HealthHumansMaleReproducibility of ResultsEffectiveness metricsGlobal healthImplementation science

Identifiers

PMID31152807
PMCPMC6883153

What OpenQuestion holds

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LicenceTDM
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Registered trials

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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.