Framingham Risk Score and Alternatives for Prediction of Coronary Heart Disease in Older Adults

BackgroundGuidelines for the prevention of coronary heart disease (CHD) recommend use of Framingham-based risk scores that were developed in white middle-aged populations. It remains unclear whether and how CHD risk prediction might be improved among older adults. We aimed to compare the prognostic performance of the Framingham risk score (FRS), directly and after recalibration, with refit functions derived from the present cohort, as well as to assess the utility of adding other routinely available risk parameters to FRS. MethodsAmong 2193 black and white older adults (mean age, 73.5 years) without pre-existing cardiovascular disease from the Health ABC cohort, we examined adjudicated CHD events, defined as incident myocardial infarction, CHD death, and hospitalization for angina or coronary revascularization. ResultsDuring 8-year follow-up, 351 participants experienced CHD events. The FRS poorly discriminated between persons who experienced CHD events vs. not (C-index: 0.577 in women; 0.583 in men) and underestimated absolute risk prediction by 51% in women and 8% in men. Recalibration of the FRS improved absolute risk prediction, particulary for women. For both genders, refitting these functions substantially improved absolute risk prediction, with similar discrimination to the FRS. Results did not differ between whites and blacks. The addition of lifestyle variables, waist circumference and creatinine did not improve risk prediction beyond risk factors of the FRS. ConclusionsThe FRS underestimates CHD risk in older adults, particularly in women, although traditional risk factors remain the best predictors of CHD. Re-estimated risk functions using these factors improve accurate estimation of absolute risk.

背景：冠心病（coronary heart disease, CHD）的预防指南推荐使用基于弗雷明汉队列开发的风险评分，此类评分最初是在白人中年人群中构建的。目前尚不清楚在老年人群中是否可以优化冠心病风险预测效果，以及具体的优化路径。

研究目的：本研究旨在对比弗雷明汉风险评分（Framingham Risk Score, FRS）未经调整、经重新校正后，与本研究队列衍生的重新拟合模型的预后性能；同时评估在FRS基础上添加其他常规可获取的风险参数的应用价值。

研究方法：本研究纳入来自Health ABC队列的2193名黑人和白人老年受试者（平均年龄73.5岁），所有受试者均无基础心血管疾病。我们评估了经裁定确认的冠心病事件，包括新发心肌梗死、冠心病死亡，以及因心绞痛或冠状动脉血运重建住院的病例。

研究结果：在8年随访期间，共计351名受试者发生冠心病事件。原FRS对发生与未发生冠心病事件的受试者区分能力较差（C指数：女性0.577，男性0.583），且对绝对风险的预测值分别低估了女性群体51%、男性群体8%。对FRS进行重新校正可改善绝对风险预测效果，尤其在女性受试者中。针对两种性别，基于本队列重新拟合的模型均显著提升了绝对风险预测性能，其区分能力与原FRS相当。白人与黑人受试者的研究结果无显著差异。在FRS原有危险因素的基础上添加生活方式变量、腰围与肌酐，并未能进一步改善风险预测效果。

研究结论：尽管传统危险因素仍是冠心病最佳的预测因子，但原FRS会低估老年人群的冠心病风险，尤其在女性群体中。基于本队列重新拟合的风险模型可提升绝对风险的精准预测能力。