Derivation and validation of a clinical prediction model for risks of venous thromboembolism in diabetic and general populations. Issue 39 (1st October 2021) - Lin, Cheng-Chieh; Chen, Ching-Chu; Li, Chia-Ing; Liu, Chiu-Shong; Lin, Wen-Yuan; Lin, Chih-Hsueh; Yang, Shing-Yu; Li, Tsai-Chung
Abstract : Supplemental Digital Content is available in the text Abstract : Abstract: Most studies on the prediction of venous thromboembolism (VTE) focused on hospitalized, surgery, and cancer patients or women receiving hormonal contraceptives or menopausal hormone therapy. No study considered diabetic and general populations to establish a VTE prediction model, especially in Asia. We developed a predictive model for VTE among type 2 diabetic patients and the general population. This study considered 2 nationwide retrospective cohort studies consisting of 52, 427 diabetic participants and 508, 664 participants from the general population aged 30 to 85 years during 2001 to 2004 in Taiwan. All participants were followed up until VTE event, death, or December 2011. The outcome event was VTE, including deep venous thrombosis and pulmonary embolism. Candidate predictors consisted of socio-demographic factors, diabetes-related factors and biomarkers, comorbidities, and medicine use. Our study followed the procedures proposed by the Framingham Heart Study to develop prediction models by using a Cox regression model. The predictive accuracy and performance characteristics were assessed using the area under curve of receiver operating characteristics curve and calibration of a risk score were performed by Hosmer–Lemeshow goodness-of-fit test. The common factors for persons with type 2 diabetes and general population included age, hospitalization status 1 year before the baseline, hypertension, chronic kidney disease, chronic obstructive pulmonary disease, and anti-diabetes medications; the specific factors for persons with type 2 diabetes consisted of body mass index, glycosylated hemoglobin A1C, and creatinine; and the factors for general population included gender, peripheral vascular disease, cancer, hypertension medication, cardiovascular medication, and non-steroidal anti-inflammatory drug. The area under curve of 3-, 5-, and 8-year VTE prediction models were 0.74, 0.71, and 0.69 in the diabetic population and 0.77, 0.76, and 0.75 in the general population, respectively. The new clinical prediction models can help identify a high risk of VTE and provide medical intervention in diabetic and general populations.