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Validation of Risk Equations for Complications of Type 2 Diabetes (RECODe) Using Individual Participant Data From
Sanjay Basu1,2, Jeremy B Sussman3,4, Seth A Berkowitz5,6
1Center for Primary Care and Outcomes Research, Center for Population Health Sciences, Departments of Medicine and Health Research and Policy, Stanford University, Stanford, CA basus@stanford.edu.
Objective:
We sought to validate Risk Equations for Complications of Type 2 Diabetes (RECODe) among diverse populations.
Research Design And Methods:
We compared risk predictions from RECODe equations and from two alternative risk models (UK Prospective Diabetes Study Outcomes Model 2 [UKPDS OM2] and American College of Cardiology/American Heart Association Pooled Cohort Equations) to observed outcomes in two studies: the Multi-Ethnic Study of Atherosclerosis (MESA, n = 1,555 adults with type 2 diabetes, median follow-up 9.1 years) and the Jackson Heart Study (JHS, n = 1,746 adults with type 2 diabetes, median follow-up 8.0 years). Outcomes included nephropathy by multiple measures (microalbuminuria, macroalbuminuria, renal failure, end-stage renal disease, and reduction in glomerular filtration rate), moderate to severe diabetic retinopathy by Airlie House classification, fatal or nonfatal myocardial infarction, fatal or nonfatal stroke, congestive heart failure, and all-cause mortality.
Results:
RECODe equations for microvascular and cardiovascular outcomes had C-statistics for discrimination ranging from 0.71 to 0.85 in MESA and 0.64 to 0.91 in JHS for alternative outcomes. Calibration slopes in MESA ranged from 0.62 for a composite nephropathy outcome, 0.83-1.04 for individual nephropathy outcomes, 1.07 for retinopathy, 1.00-1.05 for cardiovascular outcomes, and 1.03 for all-cause mortality. Slopes in JHS ranged from 0.47 for retinopathy, 0.97-1.16 for nephropathy, 0.72-1.05 for cardiovascular outcomes, and 1.01 for all-cause mortality. The alternative models had C-statistics 0.50-0.72 and calibration slopes 0.07-0.60.
Conclusions:
RECODe equations improved risk estimation for diverse patients with type 2 diabetes, as compared with two commonly used alternatives.
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