Estimating net survival: the importance of allowing for informative censoring
Estimating net survival: the importance of allowing for informative censoring
复制标题
DOI：
10.1002/sim.4464
复制
发表时间：
2012-04-13
影响因子：
2
通讯作者：
Belot, Aurelien
中科院分区：
文献类型：
--
作者：
Danieli, Coraline;Remontet, Laurent;Belot, Aurelien
净生存率（如果癌症是唯一死因则观察到的净生存率）是比较地区或国家之间癌症死亡率的最合适指标。已经开发了几种参数和非参数方法来估计净生存率，特别是在死因未知的情况下。这些方法基于相对生存率或基于附加超额风险模型，后者使用一般人群死亡风险来估计超额死亡风险（与净生存相关的风险）。目前的工作使用模拟来比较估计器在不同环境下估计净生存的能力，例如是否存在年龄对超额死亡风险或潜在随访时间的影响，因为知道该协变量也对一般人群死亡风险有影响。研究表明，当年龄影响超额死亡风险时，大多数估计值（包括特定生存率）都会出现偏差。只有两个估计量适合估计净生存率。第一个基于多变量超额风险模型，其中包括年龄作为协变量。第二种是非参数的，基于逆概率加权。这些估计者以不同的方式考虑预期死亡率过程引起的信息审查。前者提供了很大的灵活性，而后者既不需要假设特定的分布，也不需要模型构建策略。由于非参数估计量在常用软件中简单且可用，癌症登记处应考虑将非参数估计量用于基于人群的研究。版权所有 (c) 2012 John Wiley & Sons, Ltd.
Net survival, the one that would be observed if cancer were the only cause of death, is the most appropriate indicator to compare cancer mortality between areas or countries. Several parametric and non-parametric methods have been developed to estimate net survival, particularly when the cause of death is unknown. These methods are based either on the relative survival ratio or on the additive excess hazard model, the latter using the general population mortality hazard to estimate the excess mortality hazard (the hazard related to net survival). The present work used simulations to compare estimator abilities to estimate net survival in different settings such as the presence/absence of an age effect on the excess mortality hazard or on the potential time of follow-up, knowing that this covariate has an effect on the general population mortality hazard too. It showed that when age affected the excess mortality hazard, most estimators, including specific survival, were biased. Only two estimators were appropriate to estimate net survival. The first is based on a multivariable excess hazard model that includes age as covariate. The second is non-parametric and is based on the inverse probability weighting. These estimators take differently into account the informative censoring induced by the expected mortality process. The former offers great flexibility whereas the latter requires neither the assumption of a specific distribution nor a model-building strategy. Because of its simplicity and availability in commonly used software, the nonparametric estimator should be considered by cancer registries for population-based studies. Copyright (c) 2012 John Wiley & Sons, Ltd.