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通过临床和非临床生物标志物预测死亡率。

Predicting mortality from clinical and nonclinical biomarkers.

作者信息

Goldman Noreen, Turra Cassio M, Glei Dana A, Seplaki Christopher L, Lin Yu-Hsuan, Weinstein Maxine

机构信息

DSc, Office of Population Research, Princeton University, 243 Wallace Hall, Princeton, New Jersey 08544-2091, USA.

出版信息

J Gerontol A Biol Sci Med Sci. 2006 Oct;61(10):1070-4. doi: 10.1093/gerona/61.10.1070.

Abstract

BACKGROUND

Few studies focus on "preclinical" warning signs associated with mortality. In this article, we investigate associations between all-cause mortality and two clusters of biological risk factors: (i) standard clinical measures related to cardiovascular disease and metabolic function; and (ii) nonclinical measures pertaining to hypothalamic-pituitary-adrenal axis activity, sympathetic nervous system activity, and inflammatory response.

METHODS

Data come from the 2000 Social Environment and Biomarkers of Aging Study, a national sample of Taiwanese persons aged 54 years or older; 1497 persons were interviewed in their homes, and 1023 participated in a hospital examination. The analysis is based on 927 respondents with complete information. Logistic regression models describe the association between biomarkers and the 3-year probability of dying.

RESULTS

Although both groups of biomarkers are significantly associated with mortality, the model with neuroendocrine and immune biomarkers has better explanatory and discriminatory power than the one with clinical measures. The association between these nonclinical measures and mortality remains strong after adjustment for the clinical markers, suggesting that the physiological effects of the nonclinical biomarkers are broader than those captured by the cardiovascular and metabolic system measures included here.

CONCLUSIONS

Nonclinical markers are likely to provide warning signs of deteriorating health and function beyond what can be learned from conventional markers. Our findings are consistent with those of recent studies that (i) demonstrate the importance of neuroendocrine and immune system markers for survival, and (ii) indicate that standard clinical variables are less predictive of mortality in older than in younger populations.

摘要

背景

很少有研究关注与死亡率相关的“临床前”警示信号。在本文中,我们调查全因死亡率与两类生物风险因素之间的关联:(i)与心血管疾病和代谢功能相关的标准临床指标;以及(ii)与下丘脑 - 垂体 - 肾上腺轴活动、交感神经系统活动和炎症反应相关的非临床指标。

方法

数据来自2000年社会环境与衰老生物标志物研究,这是一项对54岁及以上台湾人群的全国性抽样调查;1497人在家中接受了访谈,1023人参加了医院检查。分析基于927名拥有完整信息的受访者。逻辑回归模型描述了生物标志物与3年死亡概率之间的关联。

结果

尽管两组生物标志物均与死亡率显著相关,但包含神经内分泌和免疫生物标志物的模型比包含临床指标的模型具有更好的解释力和区分力。在对临床标志物进行调整后,这些非临床指标与死亡率之间的关联仍然很强,这表明非临床生物标志物的生理效应比此处纳入的心血管和代谢系统指标所反映的效应更为广泛。

结论

非临床标志物可能会提供超出传统标志物所能反映的健康和功能恶化的警示信号。我们的研究结果与近期研究结果一致,这些研究(i)证明了神经内分泌和免疫系统标志物对生存的重要性,以及(ii)表明标准临床变量对老年人死亡率的预测能力低于年轻人。

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