Department of Health Sciences, University of Leicester, UK.
Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden.
Cancer Epidemiol. 2020 Aug;67:101745. doi: 10.1016/j.canep.2020.101745. Epub 2020 Jun 15.
Age-standardization is vital in international comparison studies of cancer patient survival, but standard approaches can fail to produce estimates in the case of sparsity.
The purpose of this paper is to demonstrate that using a standardization pre-weighting approach is a viable alternative approach for external age-standardization in population-based cancer data and performs well in cases of sparsity. We further de;1;scribe how the pre-weighting approach to age-standardization can be coupled with the Pohar Perme estimator in both a cohort and period analysis setting. For period analysis, we compare approaches for defining the internal age distribution. We use SEER public use data to illustrate our approach and estimate survival for Connecticut and by race to create a scenario with sufficient sparsity.
The pre-weighting approach gives comparable estimates to traditional age-standardization in cases with sufficient data and produces estimates throughout follow-up in cases of sparsity when a traditional approach would fail.
International comparison studies and other national population-based survival studies that need to age-standardize estimates for comparability purposes should adopt the Pohar Perme estimator with pre-weighting. This approach avoids issues of non-estimation in the case of sparsity and will allow more consistent comparisons across the produced estimates.
在癌症患者生存的国际比较研究中,年龄标准化至关重要,但在稀疏的情况下,标准方法可能无法产生估计。
本文旨在证明,在基于人群的癌症数据中,使用标准化预加权方法进行外部年龄标准化是一种可行的替代方法,并且在稀疏的情况下表现良好。我们进一步描述了如何在队列和时期分析设置中将预加权方法与 Pohar Perme 估计器结合使用。对于时期分析,我们比较了定义内部年龄分布的方法。我们使用 SEER 公共使用数据来说明我们的方法,并估计康涅狄格州和按种族划分的生存情况,以创建一个具有足够稀疏性的场景。
在数据充足的情况下,预加权方法与传统年龄标准化方法给出的估计值相当,并在传统方法失败的情况下在稀疏情况下产生整个随访期间的估计值。
需要为可比性而对估计值进行年龄标准化的国际比较研究和其他国家基于人群的生存研究应采用 Pohar Perme 估计器和预加权。这种方法避免了稀疏情况下无法估计的问题,并将允许在生成的估计值之间进行更一致的比较。