Lopez-Lopez Jose P, Garcia-Pena Angel A, Martinez-Bello Daniel, Gonzalez Ana M, Perez-Mayorga Maritza, Muñoz Velandia Oscar Mauricio, Ruiz-Uribe Gabriela, Campo Alfonso, Rangarajan Sumathy, Yusuf Salim, Lopez-Jaramillo Patricio
Masira Research Institute, Universidad de Santander (UDES), Bloque G, piso 6, Bucaramanga 680003, Colombia.
Department of Medicine, McMaster University, Hamilton, Canada.
Eur J Prev Cardiol. 2025 May 12;32(7):564-572. doi: 10.1093/eurjpc/zwae242.
To externally validate the SCORE2, AHA/ACC pooled cohort equation (PCE), Framingham Risk Score (FRS), Non-Laboratory INTERHEART Risk Score (NL-IHRS), Globorisk-LAC, and WHO prediction models and compare their discrimination and calibration capacity.
Validation in individuals aged 40-69 years with at least 10 years of follow-up and without baseline use of statins or cardiovascular diseases from the Prospective Urban Rural Epidemiology (PURE)-Colombia prospective cohort study. For discrimination, the C-statistic, and receiver operating characteristic curves with the integrated area under the curve (AUCi) were used and compared. For calibration, the smoothed time-to-event method was used, choosing a recalibration factor based on the integrated calibration index (ICI). In the NL-IHRS, linear regressions were used. In 3802 participants (59.1% women), baseline risk ranged from 4.8% (SCORE2 women) to 55.7% (NL-IHRS). After a mean follow-up of 13.2 years, 234 events were reported (4.8 cases per 1000 person-years). The C-statistic ranged between 0.637 (0.601-0.672) in NL-IHRS and 0.767 (0.657-0.877) in AHA/ACC PCE. Discrimination was similar between AUCi. In women, higher over-prediction was observed in the Globorisk-LAC (61%) and WHO (59%). In men, higher over-prediction was observed in FRS (72%) and AHA/ACC PCE (71%). Overestimations were corrected after multiplying by a factor derived from the ICI.
Six prediction models had a similar discrimination capacity, supporting their use after multiplying by a correction factor. If blood tests are unavailable, NL-IHRS is a reasonable option. Our results suggest that these models could be used in other countries of Latin America after correcting the overestimations with a multiplying factor.
对外验证SCORE2、美国心脏协会/美国心脏病学会汇总队列方程（PCE）、弗雷明汉风险评分（FRS）、非实验室国际心脏病风险评分（NL-IHRS）、全球风险-拉丁美洲（Globorisk-LAC）以及世界卫生组织（WHO）预测模型，并比较它们的区分度和校准能力。
在来自哥伦比亚城乡前瞻性流行病学（PURE）前瞻性队列研究的40至69岁个体中进行验证，这些个体至少有10年的随访时间，且基线时未使用他汀类药物或患有心血管疾病。对于区分度，使用C统计量以及带有曲线下综合面积（AUCi）的受试者工作特征曲线并进行比较。对于校准，使用平滑的事件发生时间方法，根据综合校准指数（ICI）选择重新校准因子。在NL-IHRS中，使用线性回归。在3802名参与者（59.1%为女性）中，基线风险范围从4.8%（SCORE2女性）到55.7%（NL-IHRS）。经过平均13.2年的随访，报告了234起事件（每1000人年4.8例）。C统计量在NL-IHRS中为0.637（0.601 - 0.672），在美国心脏协会/美国心脏病学会PCE中为0.767（0.657 - 0.877）。AUCi之间的区分度相似。在女性中，全球风险-拉丁美洲（61%）和世界卫生组织（59%）的预测过度情况较高。在男性中，弗雷明汉风险评分（72%）和美国心脏协会/美国心脏病学会PCE（71%）的预测过度情况较高。乘以从ICI得出的因子后，高估情况得到校正。
六个预测模型具有相似的区分能力，支持在乘以校正因子后使用它们。如果无法进行血液检测，NL-IHRS是一个合理的选择。我们的结果表明，在使用乘以因子校正高估情况后，这些模型可用于拉丁美洲的其他国家。
