Evidence map›Paper›PMID 28803840›Full record

ArticleThe lancet. Diabetes & endocrinology2017

Development and validation of Risk Equations for Complications Of type 2 Diabetes (RECODe) using individual participant data from randomised trials.

Sanjay Basu, Jeremy B Sussman, Seth A Berkowitz, Rodney A Hayward, John S Yudkin

Abstract readValidation Study
PubMed Full text at PMC Publisher
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 113 papers, 16 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
113citing papers in PubMed, 16 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.

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

113 citing papers in PubMed, 16 syntheses or guidelines pooled it.

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  19. Type 1 diabetes and cardiovascular medicine.Cardiovascular diabetology. Endocrinology reports · 2026
    Review
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53 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Sanjay BasuCenter for Population Health Sciences, Center for Primary Care and Outcomes Research, and Departments of Medicine and of Health Research and Policy, Stanford University, Palo Alto, CA, USA; Center for Primary Care, Massachusetts General Hospital, Boston, MA, USA. Electronic address: basus@stanford.edu.
Jeremy B SussmanDivision of General Medicine, University of Michigan, and Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare, Ann Arbor, MI, USA.
Seth A BerkowitzDepartment of Medicine, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, and Division of General Internal Medicine and Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA.
Rodney A HaywardDivision of General Medicine, University of Michigan, and Center for Clinical Management Research, Veterans Affairs Ann Arbor Healthcare, Ann Arbor, MI, USA.
John S YudkinInstitute of Cardiovascular Science, Division of Medicine, University College London, London, UK.

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 CULLEN, MARK RICHARD · 2016 to 2021
$16.3M
Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Designing Food Voucher Programs to Reduce Disparities in Healthy DietsR01HL132814 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SELIGMAN, HILARY KESSLER · 2016 to 2020
$3.3M
Cohort filtering models to identify social program effects on health disparitiesDP2MD010478 · NIMHD · STANFORD UNIVERSITY · PI BASU, SANJAY · 2015 to 2015
$2.4M
Understanding & Overcoming Food Insecurity in Diabetes PatientsK23DK109200 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BERKOWITZ, SETH A · 2016 to 2020
$973k
Studying social factors in sodium consumption to reduce hypertension disparitiesK08HL121056 · NHLBI · STANFORD UNIVERSITY · PI BASU, SANJAY · 2014 to 2017
$599k
NHLBI NIH HHS K08 HL121056NHLBI NIH HHS R01 HL132814NIDDK NIH HHS K23 DK109200NIDDK NIH HHS L30 DK103291NIDDK NIH HHS P30 DK092926NIDDK NIH HHS P60 DK020572NIMHD NIH HHS DP2 MD010478NIMHD NIH HHS U54 MD010724
6 · The paper itself

Abstract

backgroundIn view of substantial mis-estimation of risks of diabetes complications using existing equations, we sought to develop updated Risk Equations for Complications Of type 2 Diabetes (RECODe).

methodsTo develop and validate these risk equations, we used data from the Action to Control Cardiovascular Risk in Diabetes study (ACCORD, n=9635; 2001-09) and validated the equations for microvascular events using data from the Diabetes Prevention Program Outcomes Study (DPPOS, n=1018; 1996-2001), and for cardiovascular events using data from the Action for Health in Diabetes (Look AHEAD, n=4760; 2001-12). Microvascular outcomes were nephropathy, retinopathy, and neuropathy. Cardiovascular outcomes were myocardial infarction, stroke, congestive heart failure, and cardiovascular mortality. We also included all-cause mortality as an outcome. We used a cross-validating machine learning method to select predictor variables from demographic characteristics, clinical variables, comorbidities, medications, and biomarkers into Cox proportional hazards models for each outcome. The new equations were compared to older risk equations by assessing model discrimination, calibration, and the net reclassification index.

findingsAll equations had moderate internal and external discrimination (C-statistics 0·55-0·84 internally, 0·57-0·79 externally) and high internal and external calibration (slopes 0·71-1·31 between observed and estimated risk). Our equations had better discrimination and calibration than the UK Prospective Diabetes Study Outcomes Model 2 (for microvascular and cardiovascular outcomes, C-statistics 0·54-0·62, slopes 0·06-1·12) and the American College of Cardiology/American Heart Association Pooled Cohort Equations (for fatal or non-fatal myocardial infarction or stroke, C-statistics 0·61-0·66, slopes 0·30-0·39).

interpretationRECODe might improve estimation of risk of complications for patients with type 2 diabetes.

fundingNational Institute for Diabetes and Digestive and Kidney Disease, National Heart, Lung and Blood Institute, and National Institute on Minority Health and Health Disparities, National Institutes of Health, and US Department of Veterans Affairs.

Indexed as

Risk AssessmentAgedCardiovascular DiseasesDiabetes Mellitus, Type 2Diabetic AngiopathiesFemaleHumansMaleMiddle AgedRandomized Controlled Trials as TopicRisk Factors

Identifiers

PMID28803840
PMCPMC5769867

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.