Service de Biostatistique-Bioinformatique, Pôle Santé Publique, Hospices Civils de Lyon, Lyon, France.
Equipe Biostatistique-Santé, Laboratoire de Biométrie et Biologie Évolutive, CNRS UMR 5558, Villeurbanne, France.
Int J Epidemiol. 2024 Feb 14;53(2). doi: 10.1093/ije/dyae033.
In descriptive epidemiology, there are strong similarities between incidence and survival analyses. Because of the success of multidimensional penalized splines (MPSs) in incidence analysis, we propose in this pedagogical paper to show that MPSs are also very suitable for survival or net survival studies.
The use of MPSs is illustrated in cancer epidemiology in the context of survival trends studies that require specific statistical modelling. We focus on two examples (cervical and colon cancers) using survival data from the French cancer registries (cases 1990-2015). The dynamic of the excess mortality hazard according to time since diagnosis was modelled using an MPS of time since diagnosis, age at diagnosis and year of diagnosis. Multidimensional splines bring the flexibility necessary to capture any trend patterns while penalization ensures selecting only the complexities necessary to describe the data.
For cervical cancer, the dynamic of the excess mortality hazard changed with the year of diagnosis in opposite ways according to age: this led to a net survival that improved in young women and worsened in older women. For colon cancer, regardless of age, excess mortality decreases with the year of diagnosis but this only concerns mortality at the start of follow-up.
MPSs make it possible to describe the dynamic of the mortality hazard and how this dynamic changes with the year of diagnosis, or more generally with any covariates of interest: this gives essential epidemiological insights for interpreting results. We use the R package survPen to do this type of analysis.
在描述性流行病学中,发病率分析和生存分析之间存在很强的相似性。由于多维惩罚样条(MPSs)在发病率分析中的成功,我们在这篇教学论文中提出,MPSs 也非常适合生存或净生存研究。
在癌症流行病学中,MPSs 的使用在需要特定统计建模的生存趋势研究中得到了说明。我们关注了两个示例(宫颈癌和结肠癌),使用了来自法国癌症登记处的生存数据(1990-2015 年病例)。通过诊断后时间、诊断时年龄和诊断年份的 MPS 来模拟根据诊断后时间的超额死亡危险的动态。多维样条具有捕捉任何趋势模式的灵活性,而惩罚则确保仅选择描述数据所需的复杂性。
对于宫颈癌,根据年龄,超额死亡危险的动态随诊断年份以相反的方式变化:这导致年轻女性的净生存率提高,而老年女性的净生存率恶化。对于结肠癌,无论年龄大小,超额死亡率随诊断年份的增加而降低,但这仅与随访开始时的死亡率有关。
MPSs 使得描述死亡危险的动态及其随诊断年份或更一般地随任何感兴趣的协变量的变化成为可能:这为解释结果提供了重要的流行病学见解。我们使用 R 包 survPen 进行这种类型的分析。