Namgung Hyun Kyung, Woo Hye Won, Shin Jinho, Shin Min-Ho, Koh Sang Baek, Kim Hyeon Chang, Kim Yu-Mi, Kim Mi Kyung
Department of Epidemiology and Health Statistics, Graduate School of Public Health, Hanyang University, Seoul, Korea.
Institute for Health and Society, Hanyang University, Seoul, Korea.
J Hum Hypertens. 2023 Mar;37(3):205-212. doi: 10.1038/s41371-021-00645-x. Epub 2022 Feb 18.
This study aimed to develop and validate the hypertension risk prediction models of the CArdioVascular disease Association Study (CAVAS). Overall, 6,186 participants without hypertension at baseline were randomly divided into derivation and internal validation sets in a 6:4 ratio. We derived two prediction models: the first used the Framingham hypertension risk prediction factors (F-CAVAS-HTN); the second considered additional risk factors identified using stepwise Weibull regression analysis (CAVAS-HTN). These models were externally evaluated among Ansan and Ansung (A&A) participants, and the external validity of the Framingham and A&A prediction models (F-HTN and A&A-HTN) were assessed using the internal validation set of CAVAS. The discrimination, calibration, and net reclassification were determined. During the 4-year follow-up, 777 new cases of hypertension were diagnosed. All four models showed good discrimination (C-statistic ≥ 0.7). Internal calibrations were good for both the coefficient-based and the risk score-based F-CAVAS-HTN models, respectively (Hosmer-Lemeshow chi-square, H-L χ < 20, P ≥ 0.05). However, the two CAVAS models (H-L χ ≥ 20, P < 0.05, both) as well as the F-HTN and the A&A-HTN prediction models (H-L χ = 155.39, P < 0.0001; H-L χ = 209.72, P < 0.0001, respectively) were not externally calibrated. The F-CAVAS-HTN may be better than models with additional risk factors or derived for another population in the view of the findings of the internal validation in the present study, although future studies to improve the external validity of the F-CAVAS-HTN are needed.
本研究旨在开发并验证心血管疾病协会研究（CAVAS）的高血压风险预测模型。总体而言，6186名基线时无高血压的参与者按6:4的比例随机分为推导集和内部验证集。我们推导了两个预测模型：第一个使用弗雷明汉高血压风险预测因素（F-CAVAS-HTN）；第二个考虑了通过逐步威布尔回归分析确定的额外风险因素（CAVAS-HTN）。这些模型在安山和安城（A&A）参与者中进行了外部评估，并使用CAVAS的内部验证集评估了弗雷明汉和A&A预测模型（F-HTN和A&A-HTN）的外部有效性。确定了区分度、校准度和净重新分类。在4年的随访期间，诊断出777例新的高血压病例。所有四个模型均显示出良好的区分度（C统计量≥0.7）。基于系数的F-CAVAS-HTN模型和基于风险评分的F-CAVAS-HTN模型的内部校准效果均良好（Hosmer-Lemeshow卡方检验，H-L χ<20，P≥0.05）。然而，两个CAVAS模型（均为H-L χ≥20，P<0.05）以及F-HTN和A&A-HTN预测模型（分别为H-L χ=155.39，P<0.0001；H-L χ=209.72，P<0.0001）未进行外部校准。根据本研究内部验证的结果，F-CAVAS-HTN可能优于包含额外风险因素的模型或为其他人群推导的模型，尽管未来需要开展研究以提高F-CAVAS-HTN的外部有效性。
