What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study.
What Matters Most for Predicting Survival? A Multinational Population-Based Cohort Study.
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DOI：
10.1371/journal.pone.0159273
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Weinstein M
中科院分区：
文献类型：
--
作者：
Goldman N;Glei DA;Weinstein M
尽管社会科学家、流行病学家和临床医生做出了无数努力来确定与死亡率有密切联系的变量，但很少有研究人员对一组全面的生存预测因子的相对强度进行统计评估。在这里，我们确定了四个国家，老年人的前瞻性研究中五年死亡率的最强预测因子。我们分析了具有相似预期寿命水平的四个国家的全国代表性老年人调查：英格兰（n = 6113，年龄52岁以上），美国（n = 2023，年龄50岁以上），哥斯达黎加（n = 2694，年龄60岁以上）和台湾（n = 1032，年龄53岁以上）。每项调查都包括一系列广泛的人口统计学、社会、健康和生物学变量，这些变量先前已被证明可以预测死亡率。我们对57个预测因素进行了排名，其中25个在所有四个国家都可用，年龄和性别。我们使用受试者工作特征曲线下的面积，并通过额外的鉴别措施评估稳健性。我们在四个具有不同文化传统、经济发展水平和流行病学转变的国家中展示了一致的发现。自我报告的工具性日常生活活动限制，行动能力限制和整体自我评估的健康措施是所有四个样本中最重要的预测因素。C-反应蛋白、其他炎症标志物、同型半胱氨酸、血清白蛋白、三项性能评估（步态速度、握力和椅子站立）和运动频率也能很好地区分死亡者和幸存者。我们确定了几个有前途的候选人，可以提高基于人群和临床人群的死亡率预测。更好的预后工具可能会为研究人员提供对健康社会分层的行为和生物学途径的新见解，并可能使医生与患者就临终治疗和优先事项进行更明智的讨论。
Despite myriad efforts among social scientists, epidemiologists, and clinicians to identify variables with strong linkages to mortality, few researchers have evaluated statistically the relative strength of a comprehensive set of predictors of survival. Here, we determine the strongest predictors of five-year mortality in four national, prospective studies of older adults. We analyze nationally representative surveys of older adults in four countries with similar levels of life expectancy: England (n = 6113, ages 52+), the US (n = 2023, ages 50+), Costa Rica (n = 2694, ages 60+), and Taiwan (n = 1032, ages 53+). Each survey includes a broad set of demographic, social, health, and biological variables that have been shown previously to predict mortality. We rank 57 predictors, 25 of which are available in all four countries, net of age and sex. We use the area under the receiver operating characteristic curve and assess robustness with additional discrimination measures. We demonstrate consistent findings across four countries with different cultural traditions, levels of economic development, and epidemiological transitions. Self-reported measures of instrumental activities of daily living limitations, mobility limitations, and overall self-assessed health are among the top predictors in all four samples. C-reactive protein, additional inflammatory markers, homocysteine, serum albumin, three performance assessments (gait speed, grip strength, and chair stands), and exercise frequency also discriminate well between decedents and survivors when these measures are available. We identify several promising candidates that could improve mortality prediction for both population-based and clinical populations. Better prognostic tools are likely to provide researchers with new insights into the behavioral and biological pathways that underlie social stratification in health and may allow physicians to have more informed discussions with patients about end-of-life treatment and priorities.