Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index.
Performance of the Pooled Cohort Equations to Estimate Atherosclerotic Cardiovascular Disease Risk by Body Mass Index.
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DOI：
10.1001/jamanetworkopen.2020.23242
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发表时间：
2020-10-01
影响因子：
13.8
通讯作者：
Neeland IJ
中科院分区：
文献类型：
--
作者：
Khera R;Pandey A;Ayers CR;Carnethon MR;Greenland P;Ndumele CE;Nambi V;Seliger SL;Chaves PHM;Safford MM;Cushman M;Xanthakis V;Vasan RS;Mentz RJ;Correa A;Lloyd-Jones DM;Berry JD;de Lemos JA;Neeland IJ
本队列研究评估了通过体重指数范围估计动脉粥样硬化性心血管疾病风险的合并队列方程的性能。用体重指数估算动脉粥样硬化性心血管疾病（ASCVD）风险的合并队列方程（PCE）的性能如何？在这项包括37311名成年人的8项纵向队列研究的汇总分析中，PCE显示出可接受的模型歧视，但在体重指数较高的个体中，PCE明显高估了动脉粥样硬化性心血管疾病的风险，在接近临床决策阈值的校准中，PCE的校准效果更好，而在最高风险组中，PCE的校准效果较差。与标准PCE相比，纳入常规的肥胖临床测量并没有得到更准确的风险估计。这些研究结果表明，PCE可以作为一种风险估计工具，指导临床BMI类别的成人预防和治疗策略，但可能高估了超重和肥胖类别个体的ASCVD风险。肥胖是一个全球性的健康挑战，也是动脉粥样硬化性心血管疾病（ASVCD）的危险因素。以体重指数（BMI，以体重（公斤）除以身高（米）的平方计算）衡量ASCVD风险的合并队列方程（PCE）的性能尚不清楚。评估PCE在不同临床BMI类别中的表现。该队列研究汇集了8项基于社区的前瞻性纵向队列研究的个人水平数据，这些研究对1996年至2016年的ASCVD事件进行了10年随访。我们纳入了所有年龄在40至79岁之间，基线无ASCVD或他汀类药物使用的成年人，样本量为37311名参与者。数据分析时间为2017年8月至2020年7月。参与者BMI类别：体重过轻（<18.5）、体重正常（18.5 ~ <25）、体重超重（25 ~ <30）、轻度肥胖（30 ~ <35）、中度至重度肥胖（≥35）。不同BMI类别间PCE的判别（Harrell C统计）和校正（Nam-D'Agostino χ2拟合优度检验）。在PCE中加入BMI、腰围和高敏c反应蛋白（hsCRP），可改善区分和净重分类。在37311名参与者中（平均[SD]年龄58.6[11.8]岁；21897[58.7%]名女性），进行了380604人年的随访。平均（SD）基线BMI为29.0(6.2)，体重不足360人（1.0%），正常体重9937人（26.6%），超重13 601人（36.4%），轻度肥胖7783人（20.9%），中度至重度肥胖5630人（15.1%）。10年ASCVD估计风险中位数（四分位间距[IQR]）为7.1%(2.5%-15.4%)，3709人（9.9%）在中位数（IQR） 10.8（8.5-12.6）年期间发展为ASCVD。PCE在整个队列中高估了ASCVD风险（估计/观察[E/O]风险比，1.22;95% CI, 1.18-1.26），除体重过轻类别外，所有BMI类别均高估了ASCVD风险。在所有BMI组中，校准在临床决策阈值附近更好，但在中度或重度肥胖个体（E/O风险比，1.36;95% CI, 1.25-1.47）和ASCVD最高估计风险≥20%的个体中更差。整体PCE C统计量为0.760 (95% CI, 0.753-0.767)，与正常范围BMI组（C统计量，0.742;95% CI, 0.721-0.763）相比，中度或重度肥胖组的歧视程度较低（C统计量，0.785;95% CI, 0.772-0.798）。腰围（风险比，1.07 / 1-SD增加；95% CI, 1.03-1.11）和hsCRP（风险比，1.07 / 1-SD增加；95% CI, 1.05-1.09）与PCE增加时ASCVD风险增加相关，但BMI无关。然而，无论是否添加指标，这些因素都没有改善模型的性能（C统计量，0.760;95% CI, 0.753-0.767）。这些发现表明PCE具有可接受的模型歧视，并且在临床决策阈值上进行了很好的校准，但对于超重和肥胖类别的个体，特别是具有高估计风险的个体，高估了ASCVD的风险。纳入常规的肥胖临床指标并没有改善PCE的风险估计，需要进一步的研究来确定将其他高危肥胖指标（如体重轨迹或内脏或异位脂肪测量）纳入PCE是否可以改善风险预测。
This cohort study evaluates the performance of the pooled cohort equations in estimating the risk of atherosclerotic cardiovascular disease risk by body mass index range. What is the performance of the pooled cohort equations (PCE) for estimation of atherosclerotic cardiovascular disease (ASCVD) risk by body mass index? In this pooled analysis of 8 longitudinal cohort studies that included 37 311 adults, the PCE demonstrated acceptable model discrimination but significantly overestimated risk of atherosclerotic cardiovascular disease in individuals with higher body mass index, with better calibration near clinical decision thresholds and less optimal calibration for the groups at highest risk. Incorporation of usual clinical measures of obesity did not result in more accurate risk estimation compared with standard PCE. These findings suggest that the PCE could be used as a risk-estimation tool to guide prevention and treatment strategies in adults across clinical BMI categories, but may overestimate risk of ASCVD for individuals in overweight and obese categories. Obesity is a global health challenge and a risk factor for atherosclerotic cardiovascular disease (ASVCD). Performance of the pooled cohort equations (PCE) for ASCVD risk by body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) is unknown. To assess performance of the PCE across clinical BMI categories. This cohort study used pooled individual-level data from 8 community-based, prospective, longitudinal cohort studies with 10-year ASCVD event follow-up from 1996 to 2016. We included all adults ages 40 to 79 years without baseline ASCVD or statin use, resulting in a sample size of 37 311 participants. Data were analyzed from August 2017 to July 2020. Participant BMI category: underweight (<18.5), normal weight (18.5 to <25), overweight (25 to <30), mild obesity (30 to <35), and moderate to severe obesity (≥35). Discrimination (Harrell C statistic) and calibration (Nam-D'Agostino χ2 goodness-of-fit test) of the PCE across BMI categories. Improvement in discrimination and net reclassification with addition of BMI, waist circumference, and high-sensitivity C-reactive protein (hsCRP) to the PCE. Among 37 311 participants (mean [SD] age, 58.6 [11.8] years; 21 897 [58.7%] women), 380 604 person-years of follow-up were conducted. Mean (SD) baseline BMI was 29.0 (6.2), and 360 individuals (1.0%) were in the underweight category, 9937 individuals (26.6%) were in the normal weight category, 13 601 individuals (36.4%) were in the overweight category, 7783 individuals (20.9%) were in the mild obesity category, and 5630 individuals (15.1%) were in the moderate to severe obesity category. Median (interquartile range [IQR]) 10-year estimated ASCVD risk was 7.1% (2.5%-15.4%), and 3709 individuals (9.9%) developed ASCVD over a median (IQR) 10.8 [8.5-12.6] years. The PCE overestimated ASCVD risk in the overall cohort (estimated/observed [E/O] risk ratio, 1.22; 95% CI, 1.18-1.26) and across all BMI categories except the underweight category. Calibration was better near the clinical decision threshold in all BMI groups but worse among individuals with moderate or severe obesity (E/O risk ratio, 1.36; 95% CI, 1.25-1.47) and among those with the highest estimated ASCVD risk ≥20%. The PCE C statistic overall was 0.760 (95% CI, 0.753-0.767), with lower discrimination in the moderate or severe obesity group (C statistic, 0.742; 95% CI, 0.721-0.763) compared with the normal-range BMI group (C statistic, 0.785; 95% CI, 0.772-0.798). Waist circumference (hazard ratio, 1.07 per 1-SD increase; 95% CI, 1.03-1.11) and hsCRP (hazard ratio, 1.07 per 1-SD increase; 95% CI, 1.05-1.09), but not BMI, were associated with increased ASCVD risk when added to the PCE. However, these factors did not improve model performance (C statistic, 0.760; 95% CI, 0.753-0.767) with or without added metrics. These findings suggest that the PCE had acceptable model discrimination and were well calibrated at clinical decision thresholds but overestimated risk of ASCVD for individuals in overweight and obese categories, particularly individuals with high estimated risk. Incorporation of the usual clinical measures of obesity did not improve risk estimation of the PCE. Future research is needed to determine whether incorporation of alternative high-risk obesity markers (eg, weight trajectory or measures of visceral or ectopic fat) into the PCE may improve risk prediction.
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DOI：
10.1001/jama.2014.732
发表时间：
2014-02-26
期刊：
JAMA
影响因子：
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作者：
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通讯作者：
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影响因子：
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影响因子：
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