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提供更及时的患者生存估计:使用生命表方法和比例风险模型的标准生存分析与时期分析的比较

Providing more up-to-date estimates of patient survival: a comparison of standard survival analysis with period analysis using life-table methods and proportional hazards models.

作者信息

Smith Lucy K, Lambert Paul C, Botha Johannes L, Jones David R

机构信息

Department of Health Sciences, University of Leicester, 22-28 Princess Road West, Leicester, LE1 6TP, UK.

出版信息

J Clin Epidemiol. 2004 Jan;57(1):14-20. doi: 10.1016/S0895-4356(03)00253-1.

Abstract

OBJECTIVE

Standard survival methods can yield out-of-date estimates of long-term survival. Period analysis, based on life-table methodology, provides more up-to-date survival estimates by exploring survival during a restricted recent period of interest. It excludes the short-term survival of patients recruited at the start of the study. We use statistical models to further develop the method of period analysis, providing more up-to-date estimates of survival and the ability to explore differences in survival by covariates and adjust for case mix.

METHODS

We use cancer registry data for colorectal cancer in Leicestershire, UK, to illustrate the use of Cox proportional hazards (CPH) models to estimate period and standard survival. We compare these estimates with those obtained using life-table methodology.

RESULTS

Period estimates were slightly higher than the standard estimates as they reflect recent improvements in short-term survival. The results for period analysis using the life-table approach and using CPH models were similar. However, CPH models allowed further investigation of other risk factors and the ability to control for potential confounding variables.

CONCLUSION

Using period survival estimates, more up-to-date information is available to clinicians and others with an interest in monitoring survival. Period CHP models offer all the advantages of statistical modeling, and are straightforward to fit in standard statistical packages.

摘要

目的

标准生存方法可能会得出过时的长期生存估计值。基于生命表方法的时期分析,通过探索在感兴趣的受限近期内的生存情况,能提供更及时的生存估计值。它排除了研究开始时招募患者的短期生存情况。我们使用统计模型进一步完善时期分析方法,提供更及时的生存估计值,并能够通过协变量探索生存差异以及对病例组合进行调整。

方法

我们使用英国莱斯特郡结直肠癌的癌症登记数据,来说明使用Cox比例风险(CPH)模型估计时期生存和标准生存的方法。我们将这些估计值与使用生命表方法获得的估计值进行比较。

结果

时期估计值略高于标准估计值,因为它们反映了近期短期生存的改善情况。使用生命表方法和CPH模型进行时期分析的结果相似。然而,CPH模型允许进一步研究其他风险因素以及控制潜在混杂变量的能力。

结论

使用时期生存估计值,临床医生和其他关注监测生存情况的人员可获得更及时的信息。时期CPH模型具有统计建模的所有优点,并且易于在标准统计软件包中拟合。

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