JAMA:心血管生物标志物在人群中的预后价值

2024-05-15 来源:JAMA

本文由小咖机器人翻译整理

期刊来源:JAMA

原文链接:https://doi.org/10.1001/jama.2024.5596

摘要内容如下:

重要性

在人群中识别动脉粥样硬化性心血管疾病的高危个体对于告知一级预防策略非常重要。

目的

评估常规可用的心血管生物标记物加入已确定的危险因素后的预后价值。

设计、设置和参与者

个体水平分析,包括来自12个国家和4个大洲的28个普通人群队列的心血管生物标志物数据,并按参与者年龄进行评估。中位随访时间为11.8年。

曝光

高敏心肌肌钙蛋白I、高敏心肌肌钙蛋白T、N末端B型利钠肽前体、B型利钠肽或高敏C反应蛋白的测定。

主要成果和措施

主要转归是动脉粥样硬化性心血管疾病事件,包括所有致命性和非致命性事件。次要转归为全因死亡率、心力衰竭、缺血性卒中和心肌梗死。在对已确定的危险因素进行调整后,计算生物标志物与结果之间的关联的亚分布风险比(HR)。使用C统计和重新分类分析评估生物标记物的额外预测价值。

结果

分析包括164054名个体(中位年龄53.1岁[IQR,42.7-62.9岁],52.4%为女性)。有17211例动脉粥样硬化性心血管疾病事件。所有生物标志物均与动脉粥样硬化性心血管疾病的发生显著相关(高敏心肌肌钙蛋白I的亚分布HR每1-SD变化,1.13[95%CI,1.11-1.16];高敏肌钙蛋白T为1.18[95%CI,1.12-1.23];N末端B型利钠肽前体为1.21[95%CI,1.18-1.24];B型利钠肽为1.14[95%CI,1.08-1.22];高敏C反应蛋白为1.14[95%CI,1.12-1.16])和所有次要结果。将每个单一生物标志物添加到包括已建立的风险因素的模型中,改善了C统计量。对于年轻人(年龄<65岁)10年发病的动脉粥样硬化性心血管疾病,高敏心肌肌钙蛋白I、N末端B型利钠肽前体和高敏C反应蛋白的组合导致C统计量从0.812(95%CI,0.8021-0.8208)改善至0.8 194(95%CI,0.8089-0.8277)。与传统模型相比,这些生物标记物的组合也改善了重新分类。对于心力衰竭和全因死亡率的次要结局,风险预测的改善最为显著。与年轻人相比,65岁或以上人群的生物标记物的增量价值更大。

结论和相关性

心血管生物标志物与致死性和非致死性心血管事件和死亡率密切相关。将生物标记物添加到已确定的危险因素中,仅对动脉粥样硬化性心血管疾病的风险预测指标有少量改善,但对心力衰竭和死亡率更有利。

英文原文如下:

Abstracts

Importance  Identification of individuals at high risk for atherosclerotic cardiovascular disease within the population is important to inform primary prevention strategies.

Objective  To evaluate the prognostic value of routinely available cardiovascular biomarkers when added to established risk factors.

Design, Setting, and Participants  Individual-level analysis including data on cardiovascular biomarkers from 28 general population-based cohorts from 12 countries and 4 continents with assessments by participant age. The median follow-up was 11.8 years.

Exposure  Measurement of high-sensitivity cardiac troponin I, high-sensitivity cardiac troponin T, N-terminal pro-B-type natriuretic peptide, B-type natriuretic peptide, or high-sensitivity C-reactive protein.

Main Outcomes and Measures  The primary outcome was incident atherosclerotic cardiovascular disease, which included all fatal and nonfatal events. The secondary outcomes were all-cause mortality, heart failure, ischemic stroke, and myocardial infarction. Subdistribution hazard ratios (HRs) for the association of biomarkers and outcomes were calculated after adjustment for established risk factors. The additional predictive value of the biomarkers was assessed using the C statistic and reclassification analyses.

Results  The analyses included 164 054 individuals (median age, 53.1 years [IQR, 42.7-62.9 years] and 52.4% were women). There were 17 211 incident atherosclerotic cardiovascular disease events. All biomarkers were significantly associated with incident atherosclerotic cardiovascular disease (subdistribution HR per 1-SD change, 1.13 [95% CI, 1.11-1.16] for high-sensitivity cardiac troponin I; 1.18 [95% CI, 1.12-1.23] for high-sensitivity cardiac troponin T; 1.21 [95% CI, 1.18-1.24] for N-terminal pro-B-type natriuretic peptide; 1.14 [95% CI, 1.08-1.22] for B-type natriuretic peptide; and 1.14 [95% CI, 1.12-1.16] for high-sensitivity C-reactive protein) and all secondary outcomes. The addition of each single biomarker to a model that included established risk factors improved the C statistic. For 10-year incident atherosclerotic cardiovascular disease in younger people (aged <65 years), the combination of high-sensitivity cardiac troponin I, N-terminal pro-B-type natriuretic peptide, and high-sensitivity C-reactive protein resulted in a C statistic improvement from 0.812 (95% CI, 0.8021-0.8208) to 0.8194 (95% CI, 0.8089-0.8277). The combination of these biomarkers also improved reclassification compared with the conventional model. Improvements in risk prediction were most pronounced for the secondary outcomes of heart failure and all-cause mortality. The incremental value of biomarkers was greater in people aged 65 years or older vs younger people.

Conclusions and Relevance  Cardiovascular biomarkers were strongly associated with fatal and nonfatal cardiovascular events and mortality. The addition of biomarkers to established risk factors led to only a small improvement in risk prediction metrics for atherosclerotic cardiovascular disease, but was more favorable for heart failure and mortality.

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