Brookmeyer R, Day N E
Johns Hopkins University, Department of Biostatistics, Baltimore, Maryland 21205.
Biometrics. 1987 Sep;43(3):657-69.
Methods are proposed for the analysis of the natural history of disease from screening data when it cannot be assumed that untreated preclinical disease always progresses to clinical disease. The methodology is based on a two-stage model for preclinical disease in which stage 1 lesions may or may not progress to stage 2, but all stage 2 lesions progress to clinical disease. The focus is on joint estimation of the total preclinical duration and the sensitivity of the screening test. A partial likelihood is proposed for the analysis of prospectively collected screening data, and an analogous conditional likelihood is proposed for retrospective data. Some special cases for the joint sojourn distribution of the two stages are considered, including the independent model and limiting models where the duration of stage 2 is short relative to stage 1. The methods are applied to a case-control study of cervical cancer screening in Northeast Scotland.
当无法假定未经治疗的临床前疾病总会进展为临床疾病时，本文提出了从筛查数据中分析疾病自然史的方法。该方法基于临床前疾病的两阶段模型，其中1期病变可能进展也可能不进展至2期，但所有2期病变都会进展为临床疾病。重点在于联合估计临床前疾病的总持续时间和筛查试验的敏感性。本文提出了一个部分似然函数用于分析前瞻性收集的筛查数据，并针对回顾性数据提出了一个类似的条件似然函数。文中考虑了两阶段联合停留分布的一些特殊情况，包括独立模型以及2期持续时间相对于1期较短的极限模型。这些方法应用于苏格兰东北部宫颈癌筛查的病例对照研究。
