A BAYESIAN ACCELERATED FAILURE TIME MODEL FOR INTERVAL

• 成果类型: Article
• 署名作者: Klausch, Thomas; Akwiwu, Eddymurphy U.; van de Wiel, Mark A.; Coupe, Veerle M. H.; Berkhof, Johannes
• 署名单位: University of Amsterdam
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/22-AOAS1669
• 发表日期: 2023
• 页码: 1285-1306
• 关键词: semi-markov models; censored-data; panel-data; multistate; package; risks

摘要

Women infected by the human papillomavirus are at an increased risk to develop cervical intraepithelial neoplasia lesions (CIN). CIN are classified into three grades of increasing severity (CIN-1, CIN-2, and CIN-3) and can eventually develop into cervical cancer. The main purpose of screening is detecting CIN-2 and CIN-3 cases which are usually removed surgically. Screening data from the POBASCAM trial involving 1454 HPV-positive women are analyzed with two objectives, estimate: (a) the transition time from HPV diagnosis to CIN-3 and (b) the transition time from CIN-2 to CIN-3. The screening data have two key characteristics. First, the CIN state is monitored in an interval censored sequence of screening times. Second, a woman's progression to CIN-3 is only observed if the woman progresses to, both, CIN2 and from CIN-2 to CIN-3 in the same screening interval. We propose a Bayesian accelerated failure time model for the two transition times in this three-state model. To deal with the unusual censoring structure of the screening data, we develop a Metropolis-within-Gibbs algorithm with data augmentation from the truncated transition time distributions.