Predicting Macro- and Microvascular Complications in Type 2 Diabetes

• DOI: 10.2337/dc12-0958
• Publication Date: 2013-02-13T05:09:16Z
• Authors: Shiro Tanaka; Sachiko Tanaka; Satoshi Iimuro; Hidetoshi Yamashita; Shigehiro Katayama; Yasuo Akanuma; Nobuhiro Yamada; Atsushi Araki; Hideki Ito; Hirohito Sone; Yasuo Ohashi
• Keywords: Macro

OBJECTIVE To develop and validate a risk engine that calculates the risks of macro- microvascular complications in type 2 diabetes. RESEARCH DESIGN AND METHODS We analyzed pooled data from two clinical trials on 1,748 Japanese diabetic patients without diabetes other than mild retinopathy with median follow-up 7.2 years. End points were coronary heart disease (CHD), stroke, noncardiovascular mortality, overt nephropathy defined by persistent proteinuria, progression retinopathy. fit multistate Cox regression model to derive an algorithm for prediction. The predictive accuracy calculated 5-year was cross-validated. RESULTS Sex, age, HbA1c, years after diagnosis, BMI, systolic blood pressure, non-HDL cholesterol, albumin-to-creatinine ratio, atrial fibrillation, current smoker, leisure-time physical activity factors incorporated into engine. observed-to-predicted (O/P) ratios each event between 0.93 1.08, Hosmer-Lemeshow tests showed no significant deviations observed predicted events. In contrast, UK Prospective Diabetes Study (UKPDS) overestimated CHD (O/P ratios: 0.30 0.72 stroke). C statistics our high CHD, (0.725, 0.696, 0.767) but moderate stroke (0.636 0.614). By combining risks, classification low- high-risk improved net reclassification improvement 5.7% (P = 0.02). CONCLUSIONS accurately predicts would provide helpful information health economic simulations.