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Beyond Self-Reports: Changes in Biomarkers as Predictors of Mortality

机译:超越自我报告:生物标志物的变化可预测死亡率

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The proliferation of biosocial surveys has increased the importance of weighing the costs and benefits of adding biomarker collection to population-based surveys. A crucial question is whether biomarkers offer incremental value beyond self-reported measures, which are easier to collect and impose less respondent burden. We use longitudinal data from a nationally representative sample of older Taiwanese (aged 54+ in 2000, examined in 2000 and 2006 with mortality follow-up through 2011) to address that question with respect to predicting all-cause mortality. A summary measure of biomarkers improves mortality prediction (as measured by the area under the receiver operating characteristic curve) compared with self-reports alone, but individual biomarkers perform better than the summary score. We find that incorporating change in biomarkers over a six-year period yields a small improvement in mortality prediction compared with one-time measurement. But, is the incremental value worth the costs?
机译:生物社会调查的激增增加了权衡将生物标志物收集添加到基于人口的调查中的成本和收益的重要性。一个关键的问题是,生物标志物是否能提供比自我报告的措施更有价值的价值,而自我报告的措施更易​​于收集且减轻了受访者的负担。我们使用全国有代表性的台湾老年人样本(2000年年龄在54岁以上,在2000年和2006年进行检查,并在2011年之前进行了死亡率随访)的纵向数据来解决有关预测全因死亡率的问题。与单独的自我报告相比,对生物标志物进行的总结指标可以提高死亡率预测(通过接受者工作特征曲线下的面积衡量),但单个生物标志物的表现要好于总结指标。我们发现,与一次性测量相比,在六年内纳入生物标志物的变化对死亡率的预测影响不大。但是,增量值值得吗?

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