Sasieni Peter, Brentnall Adam R
Centre for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, U.K.
Biometrics. 2017 Jun;73(2):473-482. doi: 10.1111/biom.12578. Epub 2016 Aug 23.
Cancer survival comparisons between cohorts are often assessed by estimates of relative or net survival. These measure the difference in mortality between those diagnosed with the disease and the general population. For such comparisons methods are needed to standardize cohort structure (including age at diagnosis) and all-cause mortality rates in the general population. Standardized non-parametric relative survival measures are evaluated by determining how well they (i) ensure the correct rank ordering, (ii) allow for differences in covariate distributions, and (iii) possess robustness and maximal estimation precision. Two relative survival families that subsume the Ederer-I, Ederer-II, and Pohar-Perme statistics are assessed. The aforementioned statistics do not meet our criteria, and are not invariant under a change of covariate distribution. Existing methods for standardization of these statistics are either not invariant to changes in the general population mortality or are not robust. Standardized statistics and estimators are developed to address the deficiencies. They use a reference distribution for covariates such as age, and a reference population mortality survival distribution that is recommended to approach zero with increasing age as fast as the cohort with the worst life expectancy. Estimators are compared using a breast-cancer survival example and computer simulation. The proposals are invariant and robust, and out-perform current methods to standardize the Ederer-II and Pohar-Perme estimators in simulations, particularly for extended follow-up.
不同队列之间的癌症生存率比较通常通过相对生存或净生存估计来评估。这些方法衡量了患该疾病者与一般人群之间的死亡率差异。对于此类比较，需要采用方法来标准化队列结构（包括诊断时的年龄）以及一般人群的全因死亡率。通过确定标准化非参数相对生存指标在以下方面的表现来对其进行评估：（i）确保正确的排名顺序；（ii）考虑协变量分布的差异；（iii）具备稳健性和最大估计精度。对包含埃德勒-I、埃德勒-II和波哈尔-佩尔梅统计量的两个相对生存族进行了评估。上述统计量不符合我们的标准，并且在协变量分布变化时不具有不变性。现有的这些统计量标准化方法要么对一般人群死亡率的变化不具有不变性，要么不稳健。为解决这些缺陷，开发了标准化统计量和估计量。它们使用年龄等协变量的参考分布，以及一个参考人群死亡率生存分布，建议该分布随着年龄增长以与预期寿命最差的队列相同的速度趋近于零。使用乳腺癌生存实例和计算机模拟对估计量进行了比较。所提出的方法具有不变性和稳健性，并且在模拟中优于当前用于标准化埃德勒-II和波哈尔-佩尔梅估计量的方法，尤其是在长期随访中。
