Risk Prediction Scores for Mortality, Cerebrovascular, and Heart Disease Among Chinese People With Type 2 Diabetes

Abstract

Abstract Context Risk scores for cardiovascular and mortality outcomes have not been commonly applied in Chinese populations. Objective To develop and externally validate a set of parsimonious risk scores [University of Hong Kong-Singapore (HKU-SG)] to predict the risk of mortality, cerebrovascular disease, and ischemic heart disease among Chinese people with type 2 diabetes and compare HKU-SG risk scores to other existing ones. Design Retrospective population-based cohorts drawn from Hong Kong Hospital Authority health records from 2006 to 2014 for development and Singapore Ministry of Health records from 2008 to 2016 for validation. Separate five-year risk scores were derived using Cox proportional hazards models for each outcome. Setting Study participants were adults with type 2 diabetes aged 20 years or over, consisting of 678,750 participants from Hong Kong and 386,425 participants from Singapore. Main Outcome Measures Performance was evaluated by discrimination (Harrell C-index), and calibration plots comparing predicted against observed risks. Results All models had fair external discrimination. Among the risk scores for the diabetes population, ethnic-specific risk scores (HKU-SG and Joint Asia Diabetes Evaluation) performed better than UK Prospective Diabetes Study and Risk Equations for Complications Of type 2 Diabetes models. External validation of the HKU-SG risk scores for mortality, cerebrovascular disease, and ischemic heart disease had corresponding C-indices of 0.778, 0.695, and 0.644. The HKU-SG models appeared well calibrated on visual plots, with predicted risks closely matching observed risks. Conclusions The HKU-SG risk scores were developed and externally validated in two large Chinese population-based cohorts. The parsimonious use of clinical predictors compared with previous risk scores could allow wider implementation of risk estimation in diverse Chinese settings.