Trent Cancer Registry, Sheffield S10 3TG, England, United Kingdom.
Eur J Cancer. 2009 Dec;45(18):3298-302. doi: 10.1016/j.ejca.2009.06.013. Epub 2009 Aug 3.
A high proportion of cancer registrations solely based on a death certificate (DCOs) indicates poor data quality and biases cancer survival estimates. Intensive trace-back of registrations initiated after death (DCIs) can reduce the proportion of DCOs to an acceptable level and also improve data quality in other areas (such as increasing the information on disease extent, morphology and treatment) but is expensive in staff time. Our approach - based on a proportional hazards model for DCOs relative to all other cases - can be used to predict what the likely effect of the trace-back will be on survival and to justify the extra work involved. It can also be used to correct results from other sources (including historical data) especially when these sources contain high percentages of DCOs. Of course, the ability to make this correction is no excuse for omitting trace-back of DCI cases when resources permit. With our model the true survival tends ultimately to (1-p) *S where p is the proportion of DCOs and S is the observed survival, which is a simple correction noted by others. The worse the assumed survival of DCOs is relative to all other cases, the earlier is the time for the maximum difference between observed and true survival. Correction to the later part of survival curves is easy and an example is shown using EUROCARE data. This paper shows why the simple method works and suggests that researchers should always think about adjusting their survival estimates with regard to the percentage of DCOs. This paper also shows when the simple correction can (on 5-year survival estimates) and cannot (on 1-year survival estimates, generally) be used to adjust survival figures when comparisons are made across regions or countries with differing percentages of DCOs. We also present examples of some hazard ratios found in practice.
高比例的癌症登记仅基于死亡证明（DCO）表明数据质量差，并会影响癌症生存估计的偏差。对死亡后发起的登记（DCI）进行密集追溯，可以将 DCO 的比例降低到可接受的水平，并改善其他领域的数据质量（例如，增加疾病程度、形态和治疗的信息），但会耗费大量的人力成本。我们的方法——基于 DCO 与所有其他病例的比例风险模型——可用于预测追溯对生存的可能影响，并证明所涉及的额外工作是合理的。它还可用于校正来自其他来源（包括历史数据）的数据，尤其是当这些来源包含高比例的 DCO 时。当然，有能力进行这种校正并不能成为在资源允许的情况下省略 DCI 病例追溯的借口。使用我们的模型，真实生存趋势最终为（1-p）*S，其中 p 是 DCO 的比例，S 是观察到的生存，这是其他人注意到的简单校正。DCO 相对于所有其他病例的假设生存越差，观察到的和真实生存之间的最大差异出现的时间越早。对生存曲线后期的校正很容易，使用 EUROCARE 数据展示了一个示例。本文说明了为什么简单的方法有效，并建议研究人员应始终考虑根据 DCO 的百分比调整其生存估计。本文还说明了在比较具有不同 DCO 比例的地区或国家时，简单校正何时可以（在 5 年生存率估计中）和何时不能（在 1 年生存率估计中，通常情况下）用于调整生存数据。我们还展示了实践中发现的一些危险比示例。
