Belot Aurélien, Ndiaye Aminata, Luque-Fernandez Miguel-Angel, Kipourou Dimitra-Kleio, Maringe Camille, Rubio Francisco Javier, Rachet Bernard
Cancer Survival Group, Department of Non-Communicable DiseaseEpidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK,
Clin Epidemiol. 2019 Jan 3;11:53-65. doi: 10.2147/CLEP.S173523. eCollection 2019.
Survival data analysis results are usually communicated through the overall survival probability. Alternative measures provide additional insights and may help in communicating the results to a wider audience. We describe these alternative measures in two data settings, the overall survival setting and the relative survival setting, the latter corresponding to the particular competing risk setting in which the cause of death is unavailable or unreliable. In the overall survival setting, we describe the overall survival probability, the conditional survival probability and the restricted mean survival time (restricted to a prespecified time window). In the relative survival setting, we describe the net survival probability, the conditional net survival probability, the restricted mean net survival time, the crude probability of death due to each cause and the number of life years lost due to each cause over a prespecified time window. These measures describe survival data either on a probability scale or on a timescale. The clinical or population health purpose of each measure is detailed, and their advantages and drawbacks are discussed. We then illustrate their use analyzing England population-based registry data of men 15-80 years old diagnosed with colon cancer in 2001-2003, aiming to describe the deprivation disparities in survival. We believe that both the provision of a detailed example of the interpretation of each measure and the software implementation will help in generalizing their use.
生存数据分析结果通常通过总体生存概率来传达。其他指标能提供更多见解，并可能有助于将结果传达给更广泛的受众。我们在两种数据设定下描述这些替代指标，即总体生存设定和相对生存设定，后者对应于死亡原因不可用或不可靠的特定竞争风险设定。在总体生存设定中，我们描述总体生存概率、条件生存概率和受限平均生存时间（限制在预先指定的时间窗口内）。在相对生存设定中，我们描述净生存概率、条件净生存概率、受限平均净生存时间、每种原因导致的粗死亡概率以及在预先指定的时间窗口内每种原因导致的生命年损失数。这些指标要么在概率尺度上，要么在时间尺度上描述生存数据。详细阐述了每种指标的临床或人群健康目的，并讨论了它们的优缺点。然后，我们通过分析2001 - 2003年诊断为结肠癌的15 - 80岁英格兰男性基于人群登记数据来说明它们的用途，旨在描述生存方面的贫困差异。我们相信，提供每种指标解释的详细示例以及软件实现将有助于推广它们的使用。
