Evidence map›Paper›PMID 28711469›Full record

ArticleThe lancet. Diabetes & endocrinology2017

Targeting weight loss interventions to reduce cardiovascular complications of type 2 diabetes: a machine learning-based post-hoc analysis of heterogeneous treatment effects in the Look AHEAD trial.

Aaron Baum, Joseph Scarpa, Emilie Bruzelius, Ronald Tamler, Sanjay Basu, James Faghmous

Abstract read
In one paragraph

Article in The lancet. Diabetes & endocrinology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 2 pooled it
10.4field-weighted citation impact, top 1% of its field
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

57 citing papers in PubMed, 2 syntheses or guidelines pooled it, 115 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 4 institutions in 1 country.

Aaron BaumDepartment of Health System Design and Global Health, Arnhold Institute for Global Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address: aaron.baum@mssm.edu.
Joseph ScarpaDepartment of Health System Design and Global Health, Arnhold Institute for Global Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Emilie BruzeliusDepartment of Health System Design and Global Health, Arnhold Institute for Global Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Epidemiology, Joseph L Mailman School of Public Health, Columbia University, New York, NY, USA.
Ronald TamlerDivision of Endocrinology, Diabetes, and Bone Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Sanjay BasuDepartment of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
James FaghmousDepartment of Health System Design and Global Health, Arnhold Institute for Global Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Icahn School of Medicine at Mount Sinai · USColumbia University · USMount Sinai Health System · USStanford University · US

Funding

Trial of strategies to communicate genetic information to different ethnic and racial subpopulationsU54MD010724 · NIMHD · STANFORD UNIVERSITY · PI CULLEN, MARK RICHARD · 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
Probing networks underlying sleep and stress with multiscale dataF30MH106293 · NIMH · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI SCARPA, JOSEPH · 2014 to 2018
$157k
NHLBI NIH HHS K08 HL121056NIMHD NIH HHS DP2 MD010478NIMHD NIH HHS U54 MD010724NIMH NIH HHS F30 MH106293
6 · The paper itself

Abstract

backgroundThe Action for Health in Diabetes (Look AHEAD) trial investigated whether long-term cardiovascular disease morbidity and mortality could be reduced through a weight loss intervention among people with type 2 diabetes. Despite finding no significant reduction in cardiovascular events on average, it is possible that some subpopulations might have derived benefit. In this post-hoc analysis, we test the hypothesis that the overall neutral average treatment effect in the trial masked important heterogeneous treatment effects (HTEs) from intensive weight loss interventions.

methodsWe used causal forest modelling, which identifies HTEs, using a random half of the trial data (the training set). We applied Cox proportional hazards models to test the potential HTEs on the remaining half of the data (the testing set). The analysis was deemed exempt from review by the Columbia University Institutional Review Board, Protocol ID# AAAO3003.

findingsBetween Aug 22, 2001, and April 30, 2004, 5145 patients with type 2 diabetes were enrolled in the Look AHEAD randomised controlled trial, of whom 4901 were included in the The National Institute of Diabetes and Digestive and Kidney Diseases Repository and included in our analyses: 2450 for model development and 2451 in the testing dataset. Baseline HbA

interpretationLook AHEAD participants with moderately or poorly controlled diabetes (HbA

fundingNone.

Indexed as

Weight Reduction ProgramsCardiovascular DiseasesDiabetes Mellitus, Type 2Disease ManagementFemaleHumansMachine LearningMaleMiddle AgedRandomized Controlled Trials as TopicTreatment OutcomeWeight Loss

Identifiers

PMID28711469
PMCPMC5815373
OpenAlexW2734626658

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.