Division of Cardiology, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas.
Division of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia.
JAMA Cardiol. 2021 Jun 1;6(6):690-696. doi: 10.1001/jamacardio.2021.0948.
The American Heart Association/American College of Cardiology pooled cohort equations (PCEs) are used for predicting 10-year atherosclerotic cardiovascular disease (ASCVD) risk. Pooled cohort equation risk prediction capabilities across self-reported leisure-time physical activity (LTPA) levels and the change in model performance with addition of LTPA to the PCE are unclear.
To evaluate PCE risk prediction performance across self-reported LTPA levels and the change in model performance by adding LTPA to the existing PCE model.
DESIGN, SETTING, AND PARTICIPANTS: Individual-level pooling of data from 3 longitudinal cohort studies-Atherosclerosis Risk in Communities, Multi-Ethnic Study of Atherosclerosis, and Cardiovascular Health Study-was performed. A total of 18 824 participants were stratified into 4 groups based on self-reported LTPA levels: inactive (0 metabolic equivalent of task [MET]-min/wk), less than guideline-recommended (<500 MET-min/wk), guideline-recommended (500-1000 MET-min/week), and greater than guideline-recommended (>1000 MET-min/wk). Pooled cohort equation risk discrimination was studied using the C statistic and reclassification capabilities were studied using the Greenwood Nam-D'Agostino χ2 goodness-of-fit test. Change in risk discrimination and reclassification on adding LTPA to PCEs was evaluated using change in C statistic, integrated discrimination index, and categorical net reclassification index.
Adjudicated ASCVD events during 10-year follow-up.
Among 18 824 participants studied, 10 302 were women (54.7%); mean (SD) age was 57.6 (8.2) years. A total of 5868 participants (31.2%) were inactive, 3849 (20.4%) had less than guideline-recommended LTPA, 3372 (17.9%) had guideline-recommended LTPA, and 5735 (30.5%) had greater than guideline-recommended LTPA level. Higher LTPA levels were associated with a lower risk of ASCVD after adjustment for risk factors (hazard ratio [HR] per 1-SD higher LTPA, 0.91; 95% CI, 0.86-0.96). Across LTPA groups, PCE risk discrimination (C statistic, 0.76-0.78) and risk calibration (all χ2 P > .10) was similar. Addition of LTPA to the PCE model resulted in no significant change in the C statistic (0.0005; 95% CI, -0.0004 to 0.0015; P = .28) and categorical net reclassification index (-0.003; 95% CI, -0.010 to 0.010; P = .95), but a minimal improvement in the integrated discrimination index (0.0008; 95% CI, 0.0002-0.0013; P = .005) was observed. Similar results were noted when cohort-specific coefficients were used for creating the baseline model.
Higher self-reported LTPA levels appear to be associated with lower ASCVD risk and increasing LTPA promotes cardiovascular wellness. These findings suggest the American Heart Association/American College of Cardiology PCEs are accurate at estimating the probability of 10-year ASCVD risk regardless of LTPA level. The addition of self-reported LTPA to PCEs does not appear to be associated with improvement in risk prediction model performance.
美国心脏协会/美国心脏病学会的汇总队列方程（PCE）用于预测 10 年动脉粥样硬化性心血管疾病（ASCVD）风险。目前尚不清楚 PCE 风险预测能力在自我报告的闲暇时间体力活动（LTPA）水平上的差异，以及在 PCE 中加入 LTPA 后模型性能的变化。
评估 PCE 风险预测性能在自我报告的 LTPA 水平上的差异，以及通过将 LTPA 添加到现有 PCE 模型中对模型性能的变化。
设计、地点和参与者：对来自 3 项纵向队列研究（社区动脉粥样硬化风险研究、多民族动脉粥样硬化研究和心血管健康研究）的数据进行个体水平汇总。共有 18824 名参与者根据自我报告的 LTPA 水平分为 4 组：不活动（0 代谢当量任务[MET]-min/wk）、低于指南推荐量（<500 MET-min/wk）、指南推荐量（500-1000 MET-min/week）和高于指南推荐量（>1000 MET-min/wk）。使用 C 统计量研究 PCE 风险区分能力，使用 Greenwood-Nam-D'Agostino χ2 拟合优度检验研究再分类能力。通过 C 统计量、综合鉴别指数和分类净再分类指数的变化评估在 PCE 中添加 LTPA 对风险区分和再分类的变化。
10 年随访期间的 ASCVD 事件。
在 18824 名参与者中，有 10302 名女性（54.7%）；平均（SD）年龄为 57.6（8.2）岁。共有 5868 名参与者（31.2%）不活动，3849 名（20.4%）的 LTPA 低于指南推荐量，3372 名（17.9%）的 LTPA 符合指南推荐量，5735 名（30.5%）的 LTPA 超过了指南推荐量。在调整了危险因素后，较高的 LTPA 水平与 ASCVD 风险降低相关（每 1-SD 更高 LTPA 的 HR，0.91；95%CI，0.86-0.96）。在 LTPA 组中，PCE 风险区分（C 统计量，0.76-0.78）和风险校准（所有 χ2 P 值均>0.10）相似。在 PCE 模型中加入 LTPA 后，C 统计量没有显著变化（0.0005；95%CI，-0.0004 至 0.0015；P=0.28）和分类净再分类指数（-0.003；95%CI，-0.010 至 0.010；P=0.95），但综合鉴别指数略有改善（0.0008；95%CI，0.0002-0.0013；P=0.005）。当使用队列特定系数为基线模型创建时，也观察到了类似的结果。
较高的自我报告的 LTPA 水平似乎与较低的 ASCVD 风险相关，而增加 LTPA 则促进心血管健康。这些发现表明，美国心脏协会/美国心脏病学会的 PCE 能够准确估计 10 年 ASCVD 风险的概率，无论 LTPA 水平如何。在 PCE 中加入自我报告的 LTPA 似乎不会改善风险预测模型的性能。
