On standardized relative survival
On standardized relative survival
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DOI：
10.1111/biom.12578
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发表时间：
2017-06-01
期刊：
影响因子：
1.9
通讯作者：
Brentnall, Adam R.
中科院分区：
文献类型：
--
作者：
Sasieni, Peter;Brentnall, Adam R.
队列之间的癌症存活率比较通常通过估计相对或净存活率来评估。这些指标衡量了被诊断患有这种疾病的人与普通人群之间的死亡率差异。对于这种比较，需要标准化队列结构（包括诊断时的年龄）和一般人群的全因死亡率的方法。通过确定标准化非参数相对生存测量（i）确保正确的秩排序，（ii）允许协变量分布的差异，以及（iii）具有稳健性和最大估计精度，对标准化非参数相对生存测量进行评价。两个相对生存的家庭，subadherent的Ederer-I，Ederer-II，和Pohar-Perme统计进行了评估。上述统计量不符合我们的标准，并且在协变量分布的变化下不是不变的。现有的标准化这些统计数据的方法不是对一般人口死亡率的变化保持不变，就是不够稳健。标准化的统计数据和估计，以解决不足之处。他们使用年龄等协变量的参考分布，以及参考人群死亡率生存分布，该分布建议随着年龄的增长接近零，与预期寿命最差的队列一样快。估计比较使用乳腺癌生存的例子和计算机模拟。这些建议是不变的和强大的，并优于目前的方法，以标准化的Ederer-II和Pohar-Perme估计在模拟，特别是延长后续。
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.