Department of Health Sciences, University of Leicester, UK.
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden.
Cancer Epidemiol. 2019 Jun;60:168-173. doi: 10.1016/j.canep.2019.04.005. Epub 2019 May 1.
There are a broad range of survival-based metrics that are available to report from cancer survival studies, with varying advantages and disadvantages. A combination of metrics should be considered to improve comprehensibility and give a fuller understanding of the impact of cancer. In this article, we discuss the utility of loss in life expectancy and gain in life years as measures of cancer impact, and to quantify differences across population groups. These measures are simple to interpret, have a real-world meaning, and evaluate impact over a life-time horizon. We illustrate the use of the loss in life expectancy measures through a range of examples using data on women diagnosed with cancer in England. We use four different examples across a number of tumour types to illustrate different uses of the metrics, and highlight how they can be interpreted and used in practice in population-based oncology studies. Extensions of the measures conditional on survival to specific times after diagnosis can be used to give updated prognosis for cancer patients. Furthermore, we show how the measures can be used to understand the impact of population differences seen across patient groups. We believe that these under-used, and relatively easy to calculate, measures of overall impact can supplement reporting of cancer survival metrics and improve the comprehensibility compared to the metrics typically reported.
有广泛的基于生存的指标可用于报告癌症生存研究，它们具有不同的优缺点。应考虑结合使用多种指标，以提高理解能力，并更全面地了解癌症的影响。在本文中，我们讨论了预期寿命损失和寿命年增加作为衡量癌症影响的指标的效用，并定量比较了不同人群的差异。这些指标易于解释，具有现实意义，并在一生中评估影响。我们通过使用英格兰癌症诊断女性的数据，展示了预期寿命损失指标的使用范围。我们使用了四种不同的肿瘤类型的例子来说明指标的不同用途，并强调了如何在基于人群的肿瘤学研究中实际解释和使用这些指标。在特定的诊断后时间条件下对生存的扩展指标可用于为癌症患者提供更新的预后。此外，我们展示了如何使用这些指标来了解患者群体之间存在的人群差异的影响。我们认为，这些使用较少且相对易于计算的总体影响指标可以补充癌症生存指标的报告，并与通常报告的指标相比，提高了可理解性。
