Comparative performance of diabetes-specific and general population-based cardiovascular risk assessment models in people with diabetes mellitus.
OBJECTIVE
Multivariable models for estimating cardiovascular disease (CVD) risk in people with diabetes comprise general population-based models and those from diabetic cohorts. Whether one set of models should receive preference is unclear. We evaluated the evidence on direct comparisons of the performance of general population vs diabetes-specific CVD risk models in people with diabetes.


METHODS
MEDLINE and EMBASE databases were searched up to March 2013. Two reviewers independently identified studies that compared the performance of general CVD models vs diabetes-specific ones in the same group of people with diabetes. Independent, dual data extraction on study design, risk models, outcomes; and measures of performance was conducted.


RESULTS
Eleven articles reporting on 22 pair wise comparisons of a diabetes-specific model (UKPDS, ADVANCE and DCS risk models) to a general population model (three variants of the Framingham model, Prospective Cardiovascular Münster [PROCAM] score, CardioRisk Manager [CRM], Joint British Societies Coronary Risk Chart [JBSRC], Progetto Cuore algorithm and the CHD-Riskard algorithm) were eligible. Absolute differences in C-statistic of diabetes-specific vs general population-based models varied from -0.13 to 0.09. Comparisons for other performance measures were unusual. Outcomes definitions were congruent with those applied during model development. In 14 comparisons, the UKPDS, ADVANCE or DCS diabetes-specific models were superior to the general population CVD risk models. Authors reported better C-statistic for models they developed.


CONCLUSIONS
The limited existing evidence suggests a possible discriminatory advantage of diabetes-specific over general population-based models for CVD risk stratification in diabetes. More robust head-to-head comparisons are needed to confirm this trend and strengthen recommendations.
Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA.
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Echouffo-Tcheugui
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Kengne
D000465:Algorithms; D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000209:etiology / Q000517:prevention & control; D003924:Diabetes Mellitus, Type 2 / Q000150:complications* / Q000453:epidemiology / Q000517:prevention & control; D003925:Diabetic Angiopathies / Q000453:epidemiology* / Q000209:etiology / Q000517:prevention & control; D005260:Female; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D017410:Practice Guidelines as Topic; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors
Cardiovascular disease; Diabetes mellitus; Diabète sucré; Malade cardiovasculaire; Modèles de risque; Performance; Risk models