AIMS Risk prediction models (RPMs) for coronary artery disease (CAD), using variables to calculate CAD risk, are potentially valuable tools in prevention strategies. However, their use in the clinical practice is limited by a lack of poor model description, external validation, and head-to-head comparisons. METHODS AND RESULTS CAD RPMs were identified through Tufts PACE CPM Registry and a systematic PubMed search. Every RPM was externally validated in the three cohorts (the UK Biobank, LifeLines, and PREVEND studies) for the primary endpoint myocardial infarction (MI) and secondary endpoint CAD, consisting of MI, percutaneous coronary intervention, and coronary artery bypass grafting. Model discrimination (C-index), calibration (intercept and regression slope), and accuracy (Brier score) were assessed and compared head-to-head between RPMs. Linear regression analysis was performed to evaluate predictive factors to estimate calibration ability of an RPM. Eleven articles containing 28 CAD RPMs were included. No single best-performing RPM could be identified across all cohorts and outcomes. Most RPMs yielded fair discrimination ability: mean C-index of RPMs was 0.706 ± 0.049, 0.778 ± 0.097, and 0.729 ± 0.074 (P < 0.01) for prediction of MI in UK Biobank, LifeLines, and PREVEND, respectively. Endpoint incidence in the original development cohorts was identified as a significant predictor for external validation performance. CONCLUSION Performance of CAD RPMs was comparable upon validation in three large cohorts, based on which no specific RPM can be recommended for predicting CAD risk.

中文翻译：

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28种冠状动脉疾病风险预测模型的验证和比较。

冠状动脉疾病 (CAD) 的 AIMS 风险预测模型 (RPM) 使用变量来计算 CAD 风险，是预防策略中潜在的有价值的工具。然而，由于缺乏糟糕的模型描述、外部验证和头对头比较，它们在临床实践中的使用受到限制。方法和结果 CAD RPM 是通过 Tufts PACE CPM Registry 和系统的 PubMed 搜索确定的。每个 RPM 在三个队列（UK Biobank、LifeLines 和 PREVEND 研究）中针对主要终点心肌梗死（MI）和次要终点 CAD（包括 MI、经皮冠状动脉介入治疗和冠状动脉旁路移植术）进行了外部验证。评估模型判别（C 指数）、校准（截距和回归斜率）和准确性（Brier 评分），并在 RPM 之间进行正面对比。进行线性回归分析以评估预测因素以估计 RPM 的校准能力。包括 11 篇包含 28 个 CAD RPM 的文章。无法在所有队列和结果中确定单一表现最佳的 RPM。大多数 RPM 产生了公平的辨别能力：在 UK Biobank、LifeLines 和 PREVEND 中，RPM 的平均 C 指数分别为 0.706 ± 0.049、0.778 ± 0.097 和 0.729 ± 0.074 (P < 0.01)，用于预测 MI。原始开发队列中的终点发生率被确定为外部验证性能的重要预测指标。结论 CAD RPM 的性能在三个大型队列中经过验证后具有可比性，在此基础上，无法推荐特定的 RPM 来预测 CAD 风险。