BACKGROUND In population-based cancer survival studies, the event of interest is usually death due to cancer. However, other competing events may be present. Relative survival is a commonly used measure in cancer studies that circumvents problems caused by the inaccuracy of the cause of death information. A summary of the prognosis of the cancer population and potential differences between subgroups can be obtained using marginal estimates of relative survival. METHODS We utilize regression standardization to obtain marginal estimates of interest in a relative survival framework. Such measures include the standardized relative survival, standardized all-cause survival and standardized crude probabilities of death. Contrasts of these can be formed to explore differences between exposure groups and under certain assumptions are interpreted as causal effects. The difference in standardized all-cause survival can also provide an estimate for the impact of eliminating cancer-related differences between exposure groups. The potential avoidable deaths after such hypothetical scenarios can also be estimated. To illustrate the methods we use the example of survival differences across socio-economic groups for colon cancer. RESULTS Using relative survival, a range of marginal measures and contrasts were estimated. For these measures we either focused on cancer-related differences only or chose to incorporate both cancer and other cause differences. The impact of eliminating differences between groups was also estimated. Another useful way for quantifying that impact is the avoidable deaths under hypothetical scenarios. CONCLUSIONS Marginal estimates within the relative survival framework provide useful summary measures and can be applied to better understand differences across exposure groups.

中文翻译：

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使用相对生存框架的边际度量和因果效应。

背景技术在基于人群的癌症生存研究中，感兴趣的事件通常是由于癌症导致的死亡。但是，可能会出现其他竞争事件。相对存活率是癌症研究中常用的一种度量标准，可以规避由死因信息不准确引起的问题。癌症人群的预后和亚组之间的潜在差异的总结可使用相对存活率的边际估算得出。方法我们利用回归标准化来获得相对生存框架中感兴趣的边缘估计。这些措施包括标准化的相对生存，标准化的全因生存和标准化的死亡率。可以形成这些对比以探索暴露组之间的差异，在某些假设下，这些差异可以解释为因果关系。标准化全因生存率的差异还可以为消除暴露人群之间与癌症相关的差异所带来的影响进行估算。在这种假设情况下，也可以估计潜在的可避免的死亡。为了说明这些方法，我们以不同社会经济群体的结肠癌生存差异为例。结果使用相对生存率，估计了一系列边缘测量和对比。对于这些措施，我们要么只关注与癌症相关的差异，要么选择合并癌症和其他原因差异。还估计了消除群体之间差异的影响。量化影响的另一种有用方法是在假设情况下可避免的死亡。结论相对生存框架内的边际估计值提供了有用的汇总指标，可用于更好地理解暴露人群之间的差异。