Predicting Major Adverse Cardiovascular Events in Asian Type 2 Diabetes Patients With Lasso-Cox Regression

Abstract

Background: South-East Asia has seen a dramatic increase in type 2 diabetes (T2D). Risk prediction models for Major adverse cardiovascular events (MACE) identify patients who may benefit most from intensive prevention strategies. Existing risk prediction models for T2D were developed mainly in Caucasian populations, limiting their generalizability to Asian populations. We developed a Lasso-Cox regression model to predict the 5-year risk of incident MACE in Asian patients with T2DM using data from the largest diabetes registry in Singapore. Methodology: The diabetes registry contained public healthcare data from 9 primary healthcare centers, 4 hospitals and 3 national specialty centers. Data from 120,131 T2D subjects without MACE at baseline, from 2008 to 2018, were used for model development and validation. Patients with less than 5 years of follow-up data were excluded. Lasso-Cox, a semi-parametric variant of the Cox Proportional Hazard Model with l1-regularization, was used to predict individual survival distribution of incident MACE. A total of 69 features within electronic health records, including demographic data, vital signs, laboratory tests, and prescriptions for blood pressure, lipid and glucose-lowering medication were supplied to the model. Regression shrinkage and selection via the lasso method was used to identify variables associated with incident MACE. Identified variables were used to generate individual survival probability curves. Incident MACE was defined as the first occurrence of nonfatal myocardial infarction, nonfatal stroke, and CV disease-related death. Results: A total of 12,535 (10.4%) subjects developed MACE between 2008 and 2018. Model performance was evaluated by time-dependent concordance index and Brier score at 1, 2 and 5 years. The results of 5-fold cross validation shows that the model displayed good discrimination, achieving time-dependent C-statistics of 0.746±0.005, 0.742±0.003 and 0.738±0.002 at 1, 2 and 5 years respectively. The model demonstrated low Brier scores of 0.0355±0.0004, 0.0601±0.0011, 0.104±0.004 at 1, 2 and 5 years respectively, indicating good calibration. Factors most predictive of MACE were age and a history of hypertension and hyperlipidemia. Conclusions: We have developed a risk prediction model for MACE in Asian T2D using a large Singaporean T2D cohort, which can be used to support clinical decision-making. The individual survival probability estimates achieve an average C-statistics of 0.742 and are well-calibrated at 1, 2 and 5 years.