Optimizing Atherosclerotic Cardiovascular Disease Risk Estimation for Veterans With Diabetes Mellitus.

Autor:	Raghavan S; Veterans Affairs Eastern Colorado Healthcare System, Aurora, CO (S.R.).; Division of Hospital Medicine, University of Colorado School of Medicine, Aurora, CO (S.R.).; Colorado Cardiovascular Outcomes Research Consortium, Aurora, CO (S.R.)., Ho YL; Veterans Affairs Boston Healthcare System, MA (Y.-L.H., J.L.V., D.P., J.H., L.C., D.R.G., K.C.)., Vassy JL; Veterans Affairs Boston Healthcare System, MA (Y.-L.H., J.L.V., D.P., J.H., L.C., D.R.G., K.C.).; Department of Medicine, Harvard Medical School, Boston, MA (J.L.V., K.C.).; Division of General Internal Medicine and Primary Care (J.L.V.), Brigham and Women's Hospital, Boston, MA., Posner D; Veterans Affairs Boston Healthcare System, MA (Y.-L.H., J.L.V., D.P., J.H., L.C., D.R.G., K.C.)., Honerlaw J; Veterans Affairs Boston Healthcare System, MA (Y.-L.H., J.L.V., D.P., J.H., L.C., D.R.G., K.C.)., Costa L; Veterans Affairs Boston Healthcare System, MA (Y.-L.H., J.L.V., D.P., J.H., L.C., D.R.G., K.C.)., Phillips LS; Atlanta Veterans Affairs Medical Center, Decatur, GA (L.S.P., P.W.F.W.).; Division of Endocrinology (L.S.P.), Emory University School of Medicine, Atlanta, GA., Gagnon DR; Veterans Affairs Boston Healthcare System, MA (Y.-L.H., J.L.V., D.P., J.H., L.C., D.R.G., K.C.).; Department of Biostatistics, Boston University School of Public Health, MA (D.R.G.)., Wilson PWF; Atlanta Veterans Affairs Medical Center, Decatur, GA (L.S.P., P.W.F.W.).; Division of Cardiology (P.W.F.W.), Emory University School of Medicine, Atlanta, GA., Cho K; Veterans Affairs Boston Healthcare System, MA (Y.-L.H., J.L.V., D.P., J.H., L.C., D.R.G., K.C.).; Department of Medicine, Harvard Medical School, Boston, MA (J.L.V., K.C.).; Division of Aging (K.C.), Brigham and Women's Hospital, Boston, MA.
Jazyk:	angličtina
Zdroj:	Circulation. Cardiovascular quality and outcomes [Circ Cardiovasc Qual Outcomes] 2020 Sep; Vol. 13 (9), pp. e006528. Date of Electronic Publication: 2020 Aug 31.
DOI:	10.1161/CIRCOUTCOMES.120.006528
Abstrakt:	Background: Estimated 10-year atherosclerotic cardiovascular disease (ASCVD) risk in diabetes mellitus patients is used to guide primary prevention, but the performance of risk estimators (2013 Pooled Cohort Equations [PCE] and Risk Equations for Complications of Diabetes [RECODe]) varies across populations. Data from electronic health records could be used to improve risk estimation for a health system's patients. We aimed to evaluate risk equations for initial ASCVD events in US veterans with diabetes mellitus and improve model performance in this population. Methods and Results: We studied 183 096 adults with diabetes mellitus and without prior ASCVD who received care in the Veterans Affairs Healthcare System (VA) from 2002 to 2016 with mean follow-up of 4.6 years. We evaluated model discrimination, using Harrell's C statistic, and calibration, using the reclassification χ 2 test, of the PCE and RECODe equations to predict fatal or nonfatal myocardial infarction or stroke and cardiovascular mortality. We then tested whether model performance was affected by deriving VA-specific β-coefficients. Discrimination of ASCVD events by the PCE was improved by deriving VA-specific β-coefficients (C statistic increased from 0.560 to 0.597) and improved further by including measures of glycemia, renal function, and diabetes mellitus treatment (C statistic, 0.632). Discrimination by the RECODe equations was improved by substituting VA-specific coefficients (C statistic increased from 0.604 to 0.621). Absolute risk estimation by PCE and RECODe equations also improved with VA-specific coefficients; the calibration P increased from <0.001 to 0.08 for PCE and from <0.001 to 0.005 for RECODe, where higher P indicates better calibration. Approximately two-thirds of veterans would meet a guideline indication for high-intensity statin therapy based on the PCE versus only 10% to 15% using VA-fitted models. Conclusions: Existing ASCVD risk equations overestimate risk in veterans with diabetes mellitus, potentially impacting guideline-indicated statin therapy. Prediction model performance can be improved for a health system's patients using readily available electronic health record data.
Databáze:	MEDLINE
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