In epidemiology research with cancer registry data, it is often of primary interest to make inference on cancer death, not overall survival. Since cause of death is not easy to collect or is not necessarily reliable in cancer registries, some special methodologies have been introduced and widely used by using the concepts of the relative survival ratio and the net survival. In making inference of those measures, external life tables of the general population are utilized to adjust the impact of non-cancer death on overall survival. The validity of this adjustment relies on the assumption that mortality in the external life table approximates non-cancer mortality of cancer patients. However, the population used to calculate a life table may include cancer death and cancer patients. Sensitivity analysis proposed by Talb\"{a}ck and Dickman to address it requires additional information which is often not easily available. We propose a method to make inference on the net survival accounting for potential presence of cancer patients and cancer death in the life table for the general population. The idea of adjustment is to consider correspondence of cancer mortality in the life table and that in the cancer registry. We realize a novel method to adjust cancer mortality in the cancer registry without any additional information to the standard analyses of cancer registries. Our simulation study revealed that the proposed method successfully removed the bias. We illustrate the proposed method with the cancer registry data in England.

翻译：在利用癌症登记数据进行流行病学研究时，首要关注点通常是对癌症死亡而非总生存率进行推断。由于死因在癌症登记中难以收集或未必可靠，因此引入并广泛使用了一些基于相对生存比和净生存概念的特殊方法。在推断这些指标时，需借助一般人群的外部生命表来调整非癌症死亡对总生存率的影响。该调整的有效性依赖于一个假设：外部生命表中的死亡率近似于癌症患者的非癌症死亡率。然而，用于计算生命表的人群可能包含癌症死亡和癌症患者。Talbäck和Dickman提出的敏感性分析需额外信息，但这些信息通常难以获取。我们提出了一种方法，用于在一般人群生命表中可能存在癌症患者和癌症死亡的情况下推断净生存率。调整思路是考虑生命表中的癌症死亡率与癌症登记中的癌症死亡率之间的对应关系。我们实现了一种新颖的方法，无需任何超出标准癌症登记分析所需的信息即可调整癌症登记中的癌症死亡率。模拟研究表明，我们的方法成功消除了偏差。我们以英格兰的癌症登记数据为例展示了该方法的应用。