Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction?
Does Information on Blood Heavy Metals Improve Cardiovascular Mortality Prediction?
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DOI：
10.1161/jaha.119.013571
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发表时间：
2019-10
期刊：
影响因子：
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通讯作者：
Xin Wang;B. Mukherjee;S. Park
中科院分区：
文献类型：
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作者：
Xin Wang;B. Mukherjee;S. Park
背景：评价铅、镉和汞的血液标志物单独、联合或作为综合指标/环境风险评分（ERS），在具有既定危险因素的模型中，是否可以改善心血管疾病（CVD）死亡率的预测。方法与结果我们的研究样本包括16 028名年龄≥40岁的成年人，他们参加了1999-2012年全国健康与营养调查，并随访至2015年12月31日。研究样本随机分为ERS构建训练组（n=8043）和预测性能评价测试组（n=7985）。ERS采用弹性网惩罚Cox模型计算，该模型基于预测心血管疾病死亡率的选定金属预测因子。在中位随访7.2年期间，517人死于心血管疾病。在训练集中，镉和汞的线性项，铅和汞的平方项，以及所有3个成对相互作用被弹性网选择用于ERS构建。在测试集中，C‐统计量从仅纳入已建立的心血管疾病危险因素时的0.845增加到加入ERS时的0.854。将血金属的所有线性、平方和两两相互作用项添加到Cox模型中，将C -统计量从0.845提高到0.857。当以净重分类改善和综合歧视改善来评估时，改善仍然显着。结论有毒金属的血液标记物可以改善心血管疾病风险预测，并强调其在心血管疾病风险评估、预防和精准健康方面的潜在应用。
Background To evaluate whether blood markers of lead, cadmium, and mercury can improve prediction for cardiovascular disease (CVD) mortality when added individually, jointly, or as an integrative index/Environmental Risk Score (ERS), in a model with established risk factors. Methods and Results Our study sample comprised 16 028 adults aged ≥40 years who were enrolled in the National Health and Nutrition Examination Survey 1999–2012 and followed up through December 31, 2015. The study sample was randomly split into training for the ERS construction (n=8043) and testing for the evaluation of prediction performance (n=7985). ERS was computed using elastic‐net penalized Cox's model based on the selected metal predictors predicting CVD mortality. During median follow‐up of 7.2 years, 517 died from CVD. In the training set, linear terms of cadmium and mercury, squared terms of lead and mercury, and all 3 pairwise interactions were selected by elastic‐net for ERS construction. In the testing set, the C‐statistic increased from 0.845 when only established CVD risk factors were in the model to 0.854 when the ERS was additionally added to the model. Addition of all linear, squared, and pairwise interaction terms of blood metals to the Cox's models improved C‐statistic from 0.845 to 0.857. The improvement remained significant when it was assessed by net reclassification improvement and integrated discrimination improvement. Conclusions Our findings suggest that blood markers of toxic metals can improve CVD risk prediction over the established risk factors and highlight their potential utility for CVD risk assessment, prevention, and precision health.