Individualizing life expectancy estimates for older adults using the Gompertz Law of Human Mortality.
Individualizing life expectancy estimates for older adults using the Gompertz Law of Human Mortality.
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DOI：
10.1371/journal.pone.0108540
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Covinsky KE
中科院分区：
文献类型：
--
作者：
Lee SJ;Boscardin WJ;Kirby KA;Covinsky KE
指南建议将预期寿命 (LE) 纳入癌症筛查等预防性干预措施的临床决策中。之前的研究主要集中在死亡风险（例如 4 年死亡风险为 28%），这对于患者和临床医生来说比 LE（例如 7.3 年）更难以解释。我们的目标是利用 Gompertz 人类死亡率定律（该定律规定死亡风险在固定时间间隔内加倍）将 Lee 死亡率指数转换为 LE 计算器。我们调查了参加 1998 年全国代表性健康与退休研究或 HRS 浪潮的 50 岁及以上的社区老年人（答复率为 81%），将研究受访者分为发展组 (n = 11701) 和验证组 (n = 8009)。在开发队列中，我们为 Lee 死亡率指数定义的每个风险组拟合了比例风险 Gompertz 生存函数。我们通过将预测的 LE 与 HRS 验证队列和来自 2004 年英国纵向研究或 ELSA 的外部验证队列中观察到的生存率进行比较来验证我们的 LE 估计值 (n = 7042)。与我们的 HRS 开发组 (23%) 和验证组 (25%) 相比，ELSA 组的 8 年死亡率风险较低 (14%)。我们的模型在验证队列中具有良好的区分度（Harrell’s c 在 HRS 中为 0.78，在 ELSA 中为 0.80）。我们预测的 LE 与 HRS 验证队列中观察到的生存率相似，没有校准错误的证据（Hosmer-Lemeshow，8 年时 p = 0.2）。然而，我们预测的 LE 比 ELSA 队列中观察到的生存期长，有校准错误的证据（Hosmer-Lemeshow，8 年时 p<0.001），反映了 ELSA 中死亡率较低。我们将之前验证的死亡率指数转化为包含患者水平风险因素的 LE 计算器。我们的 LE 计算器可以帮助临床医生确定哪些预防干预措施最适合美国老年人。
Guidelines recommend incorporating life expectancy (LE) into clinical decision-making for preventive interventions such as cancer screening. Previous research focused on mortality risk (e.g. 28% at 4 years) which is more difficult to interpret than LE (e.g. 7.3 years) for both patients and clinicians. Our objective was to utilize the Gompertz Law of Human Mortality which states that mortality risk doubles in a fixed time interval to transform the Lee mortality index into a LE calculator. We examined community-dwelling older adults age 50 and over enrolled in the nationally representative 1998 wave of the Health and Retirement Study or HRS (response rate 81%), dividing study respondents into development (n = 11701) and validation (n = 8009) cohorts. In the development cohort, we fit proportional hazards Gompertz survival functions for each of the risk groups defined by the Lee mortality index. We validated our LE estimates by comparing our predicted LE with observed survival in the HRS validation cohort and an external validation cohort from the 2004 wave of the English Longitudinal Study on Ageing or ELSA (n = 7042). The ELSA cohort had a lower 8-year mortality risk (14%) compared to our HRS development (23%) and validation cohorts (25%). Our model had good discrimination in the validation cohorts (Harrell’s c 0.78 in HRS and 0.80 in the ELSA). Our predicted LE’s were similar to observed survival in the HRS validation cohort without evidence of miscalibration (Hosmer-Lemeshow, p = 0.2 at 8 years). However, our predicted LE’s were longer than observed survival in the ELSA cohort with evidence of miscalibration (Hosmer-Lemeshow, p<0.001 at 8 years) reflecting the lower mortality rate in ELSA. We transformed a previously validated mortality index into a LE calculator that incorporated patient-level risk factors. Our LE calculator may help clinicians determine which preventive interventions are most appropriate for older US adults.
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影响因子：
105.7
作者：
Lee, Sei J.;Boscardin, W. John;Walter, Louise C.
通讯作者：
Walter, Louise C.
影响因子：
50.5
作者：
Schmidt, M.;Victor, A.;Thomssen, C.
通讯作者：
Thomssen, C.
影响因子：
3.5
作者：
Hayes, A. J.;Leal, J.;Clarke, P. M.
通讯作者：
Clarke, P. M.
影响因子：
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作者：
Celli, BR;Cote, CG;Cabral, HJ
通讯作者：
Cabral, HJ
影响因子：
39.2
作者：
KNAUS, WA;HARRELL, FE;WAGNER, DP
通讯作者：
WAGNER, DP