Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
German Center for Diabetes Research (DZD), Munich Neuherberg, Germany.
Sci Rep. 2021 Oct 4;11(1):19609. doi: 10.1038/s41598-021-99103-4.
Inclusion of clinical parameters limits the application of most cardiovascular disease (CVD) prediction models to clinical settings. We developed and externally validated a non-clinical CVD risk score with a clinical extension and compared the performance to established CVD risk scores. We derived the scores predicting CVD (non-fatal and fatal myocardial infarction and stroke) in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort (n = 25,992, cases = 683) using competing risk models and externally validated in EPIC-Heidelberg (n = 23,529, cases = 692). Performance was assessed by C-indices, calibration plots, and expected-to-observed ratios and compared to a non-clinical model, the Pooled Cohort Equation, Framingham CVD Risk Scores (FRS), PROCAM scores, and the Systematic Coronary Risk Evaluation (SCORE). Our non-clinical score included age, gender, waist circumference, smoking, hypertension, type 2 diabetes, CVD family history, and dietary parameters. C-indices consistently indicated good discrimination (EPIC-Potsdam 0.786, EPIC-Heidelberg 0.762) comparable to established clinical scores (thereof highest, FRS: EPIC-Potsdam 0.781, EPIC-Heidelberg 0.764). Additional clinical parameters slightly improved discrimination (EPIC-Potsdam 0.796, EPIC-Heidelberg 0.769). Calibration plots indicated very good calibration with minor overestimation in the highest decile of predicted risk. The developed non-clinical 10-year CVD risk score shows comparable discrimination to established clinical scores, allowing assessment of individual CVD risk in physician-independent settings.
纳入临床参数限制了大多数心血管疾病 (CVD) 预测模型在临床环境中的应用。我们开发并外部验证了一种非临床 CVD 风险评分,该评分具有临床扩展,并将其性能与已建立的 CVD 风险评分进行了比较。我们使用竞争风险模型预测了欧洲前瞻性癌症与营养研究 (EPIC)-波茨坦队列 (n=25992,病例=683) 中的 CVD(非致命和致命性心肌梗死和中风),并在 EPIC-海德堡队列 (n=23529,病例=692) 中进行了外部验证。通过 C 指数、校准图和期望与观察比来评估性能,并与非临床模型、Pooled Cohort Equation、Framingham CVD Risk Scores (FRS)、PROCAM 评分和 Systematic Coronary Risk Evaluation (SCORE) 进行比较。我们的非临床评分包括年龄、性别、腰围、吸烟、高血压、2 型糖尿病、CVD 家族史和饮食参数。C 指数始终表明具有良好的区分度(EPIC-Potsdam 0.786,EPIC-Heidelberg 0.762),与已建立的临床评分相当(其中最高的是 FRS:EPIC-Potsdam 0.781,EPIC-Heidelberg 0.764)。额外的临床参数略有改善了区分度(EPIC-Potsdam 0.796,EPIC-Heidelberg 0.769)。校准图表明具有非常好的校准度,在预测风险最高的十分位数中存在轻微高估。开发的非临床 10 年 CVD 风险评分与已建立的临床评分具有相当的区分度,允许在医生独立的环境中评估个体 CVD 风险。