An aspect of interest in surveillance of diseases is whether the survival time distribution changes over time. By following data in health registries over time, this can be monitored, either in real time or retrospectively. With relevant risk factors registered, these can be taken into account in the monitoring as well. A challenge in monitoring survival times based on registry data is that data on cause of death might either be missing or uncertain. To quantify the burden of disease in such cases, excess hazard methods can be used, where the total hazard is modelled as the population hazard plus the excess hazard due to the disease. We propose a CUSUM procedure for monitoring for changes in the survival time distribution in cases where use of excess hazard models is relevant. The procedure is based on a survival log-likelihood ratio and extends previously suggested methods for monitoring of time to event to the excess hazard setting. The procedure takes into account changes in the population risk over time, as well as changes in the excess hazard which is explained by observed covariates. Properties, challenges and an application to cancer registry data will be presented.

翻译：疾病监测的一个重要方面是生存时间分布是否随时间发生变化。通过长期追踪健康注册数据，可以实时或回顾性地进行监测。若相关风险因素已登记，监测过程中亦可将其纳入考量。基于注册数据监测生存时间的一个挑战在于，死亡原因数据可能缺失或不确定。为量化此类情况下的疾病负担，可采用超额风险方法，即将总风险建模为人群风险与疾病导致的超额风险之和。本文提出一种CUSUM（累积和控制）程序，用于在适用超额风险模型的情况下监测生存时间分布的变化。该程序基于生存对数似然比，将先前提出的事件发生时间监测方法扩展至超额风险框架。该程序同时考虑了人群风险随时间的变化，以及由观测协变量解释的超额风险变化。本文将阐述该方法的性质、挑战，并展示其在癌症注册数据中的应用实例。