Department of Registration, Cancer Registry Norway, Oslo, Norway.
Department of Research and Innovation, Møre and Romsdal Hospital Trust, Ålesund, Norway.
Br J Cancer. 2023 Sep;129(5):819-828. doi: 10.1038/s41416-023-02360-5. Epub 2023 Jul 11.
Routine reporting of cancer patient survival is important, both to monitor the effectiveness of health care and to inform about prognosis following a cancer diagnosis. A range of different survival measures exist, each serving different purposes and targeting different audiences. It is important that routine publications expand on current practice and provide estimates on a wider range of survival measures. We examine the feasibility of automated production of such statistics.
We used data on 23 cancer sites obtained from the Cancer Registry of Norway (CRN). We propose an automated way of estimating flexible parametric relative survival models and calculating estimates of net survival, crude probabilities, and loss in life expectancy across many cancer sites and subgroups of patients.
For 21 of 23 cancer sites, we were able to estimate survival models without assuming proportional hazards. Reliable estimates of all desired measures were obtained for all cancer sites.
It may be challenging to implement new survival measures in routine publications as it can require the application of modeling techniques. We propose a way of automating the production of such statistics and show that we can obtain reliable estimates across a range of measures and subgroups of patients.
癌症患者生存情况的常规报告非常重要，这不仅有助于监测医疗保健的效果，还能为癌症诊断后的预后提供信息。目前存在多种不同的生存测量方法，每种方法都有不同的用途和针对的受众。重要的是，常规出版物应扩展当前的实践，并提供更广泛的生存测量估计值。我们研究了自动生成此类统计数据的可行性。
我们使用了从挪威癌症登记处（CRN）获得的 23 个癌症部位的数据。我们提出了一种自动估计灵活参数相对生存模型的方法，并计算了许多癌症部位和患者亚组的净生存、粗概率和预期寿命损失的估计值。
对于 23 个癌症部位中的 21 个，我们能够在不假设比例风险的情况下估计生存模型。对于所有癌症部位，都获得了所有所需测量值的可靠估计值。
在常规出版物中实施新的生存措施可能具有挑战性，因为这可能需要应用建模技术。我们提出了一种自动化生成此类统计数据的方法，并证明我们可以在一系列措施和患者亚组中获得可靠的估计值。
