Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg, Stockholm, Sweden.
Biostatistics Research Group, Department of Health Sciences, University of Leicester, University Road, Leicester, UK.
Biom J. 2022 Oct;64(7):1161-1177. doi: 10.1002/bimj.202100254. Epub 2022 Jun 16.
In competing risks settings where the events are death due to cancer and death due to other causes, it is common practice to use time since diagnosis as the timescale for all competing events. However, attained age has been proposed as a more natural choice of timescale for modeling other cause mortality. We examine the choice of using time since diagnosis versus attained age as the timescale when modeling other cause mortality, assuming that the hazard rate is a function of attained age, and how this choice can influence the cumulative incidence functions ( s) derived using flexible parametric survival models. An initial analysis on the colon cancer data from the population-based Swedish Cancer Register indicates such an influence. A simulation study is conducted in order to assess the impact of the choice of timescale for other cause mortality on the bias of the estimated and how different factors may influence the bias. We also use regression standardization methods in order to obtain marginal estimates. Using time since diagnosis as the timescale for all competing events leads to a low degree of bias in for cancer mortality ( ) under all approaches. It also leads to a low degree of bias in for other cause mortality ( ), provided that the effect of age at diagnosis is included in the model with sufficient flexibility, with higher bias under scenarios where a covariate has a time-varying effect on the hazard rate for other cause mortality on the attained age scale.
在存在癌症相关死亡和其他原因相关死亡竞争风险的情况下，通常使用从诊断到所有竞争事件的时间作为时间尺度。然而，已有人提出，获得年龄（ attained age）作为其他原因死亡率建模的时间尺度更为自然。我们考察了在假设风险率是获得年龄的函数的情况下，使用从诊断到时间作为其他原因死亡率建模的时间尺度的选择，以及这种选择如何影响使用灵活参数生存模型得出的累积发生率函数（ cumulative incidence functions，CIFs）。对来自基于人群的瑞典癌症登记处的结肠癌数据的初步分析表明存在这种影响。进行了一项模拟研究，以评估其他原因死亡率的时间尺度选择对估计值 的偏差的影响，以及不同因素可能如何影响偏差。我们还使用回归标准化方法获得边缘 估计值。对于所有竞争事件，将从诊断到时间作为时间尺度，会导致癌症死亡率（ cancer mortality）的 估计值（ ）出现低度偏差（ ），所有方法都是如此。如果在模型中以足够的灵活性包含诊断时的年龄效应，那么对于其他原因死亡率（ other cause mortality）的 也会出现低度偏差（ ），前提是在获得年龄尺度上，协变量对其他原因死亡率的风险率有随时间变化的影响。
