A Prevalence Analysis that Adjusts for Survival and Tumour Lethality
本文提出一种回归分析方法，在不需要死因数据的情况下调整生存差异，适用于致死性肿瘤的患病率比较，并以ED01研究的肝肿瘤数据为例进行说明。
If animals with or without the tumour of interest die at a common rate, the tumour is typically referred to as non‐lethal and survival‐adjusted prevalence comparisons can be based on mortality and tumour response data alone. If these death rates differ, however, most analyses also require cause‐of‐death data or sacrifice data. This paper describes a regression analysis that adjusts for survival and allows different conditional death rates but does not require any data on cause of death and often is practical with few sacrifices. The interval analysis of Hoel and Walburg and the logistic regression analysis of Dinse and Lagakos, both of which are appropriate for non‐lethal tumours, are special cases of the analysis presented here. The methods proposed provide a framework for incorporating covariates, as well as for estimating the tumour's relative risk, and are illustrated with liver tumour data from the ED01 study.