Liu Xiaofei, Shen Peng, Zhang Dudan, Sun Yexiang, Chen Yi, Liang Jingyuan, Wu Jinguo, Zhang Jingyi, Lu Ping, Lin Hongbo, Tang Xun, Gao Pei
Department of Epidemiology and Biostatistics, Peking University Health Science Center, Beijing, China.
Center for Real-world Evidence Evaluation, Peking University Clinical Research Institute, Beijing, China.
JACC Asia. 2022 Jan 4;2(1):33-43. doi: 10.1016/j.jacasi.2021.10.007. eCollection 2022 Feb.
Updated American or Chinese guidelines recommended calculating atherosclerotic cardiovascular disease (ASCVD) risk using the Pooled Cohort Equations (PCE) or Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR) models; however, evidence on performance of both models in Asian populations is limited.
The authors aimed to evaluate the accuracy of the PCE or China-PAR models in a Chinese contemporary cohort.
Data were extracted from the CHERRY (CHinese Electronic health Records Research in Yinzhou) study. Participants aged 40 to 79 years without prior ASCVD at baseline from 2010 to 2016 were included. ASCVD was defined as nonfatal or fatal stroke, nonfatal myocardial infarction, and cardiovascular death. Models were assessed for discrimination and calibration.
Among 226,406 participants, 5362 (2.37%) adults developed a first ASCVD event during a median of 4.60 years of follow-up. Both models had good discrimination: -statistics in men were 0.763 (95% confidence interval [CI]: 0.754-0.773) for PCE and 0.758 (95% CI: 0.749-0.767) for China-PAR; -statistics in women were 0.820 (95% CI: 0.812-0.829) for PCE and 0.811 (95% CI: 0.802-0.819) for China-PAR. The China-PAR model underpredicted risk by 20% in men and by 40% in women, especially in the highest-risk groups. However, PCE overestimated by 63% in men and inversely underestimated the risk by 34% in women with poor calibration (both < 0.001). After recalibration, observed and predicted risks by recalibrated PCE were better aligned.
In this large-scale population-based study, both PCE and China-PAR had good discrimination in 5-year ASCVD risk prediction. China-PAR outperformed PCE in calibration, whereas recalibration equalized the performance of PCE and China-PAR. Further specific models are needed to improve accuracy in the highest-risk groups.
更新后的美国或中国指南推荐使用合并队列方程（PCE）或中国动脉粥样硬化性心血管疾病风险预测模型（China-PAR）来计算动脉粥样硬化性心血管疾病（ASCVD）风险；然而，这两种模型在亚洲人群中的性能证据有限。
作者旨在评估PCE或China-PAR模型在中国当代队列中的准确性。
数据来自CHERRY（鄞州中国电子健康记录研究）研究。纳入2010年至2016年基线时年龄在40至79岁且无既往ASCVD的参与者。ASCVD定义为非致死性或致死性卒中、非致死性心肌梗死和心血管死亡。对模型进行区分度和校准评估。
在226,406名参与者中，5362名（2.37%）成年人在中位4.60年的随访期间发生了首次ASCVD事件。两种模型都有良好的区分度：PCE在男性中的C统计量为0.763（95%置信区间[CI]：0.754 - 0.773），China-PAR为0.758（95%CI：0.749 - 0.767）；PCE在女性中的C统计量为0.820（95%CI：0.812 - 0.829），China-PAR为0.811（95%CI：0.802 - 0.819）。China-PAR模型在男性中低估风险20%，在女性中低估40%，尤其是在最高风险组。然而，PCE在男性中高估63%，在校准不佳的女性中反而低估风险34%（两者P均<0.001）。重新校准后，重新校准的PCE观察到的风险和预测的风险更吻合。
在这项基于大规模人群的研究中，PCE和China-PAR在5年ASCVD风险预测中都有良好的区分度。China-PAR在校准方面优于PCE，而重新校准使PCE和China-PAR的性能趋于均衡。需要进一步的特定模型来提高最高风险组的准确性。
