Zhiyu Chen
1
Yong Yu
2*
LI DAI
1*The final, formatted version of the article will be published soon.
ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Epidemiology and Prevention
Volume 14 - 2024 |
doi: 10.3389/fonc.2024.1431124
This article is part of the Research Topic The Future of Cancer Surveillance Research View all 25 articles
Markov model analysis of esophageal cancer transition probabilities in high-risk Chinese populations
Provisionally accepted- 1 West China Second University Hospital, Sichuan University, Chengdu, China
- 2 Chengdu Shuangliu District Center for Disease Control and Prevention, Chengdu, China
- 3 West China School of Public Health, Sichuan University, Chengdu, Sichuan Province, China
Purpose: Predicating state transition probabilities in esophageal cancer (EC) progression is significant for deciding reasonable screening and follow-up intervals.This study aims to estimate these probabilities using a Markov model for EC and its precancerous lesions.The transition probabilities among health states of EC were estimated by employing Markov models for the natural history of EC based on the project of Early Diagnosis and Treatment of EC, "early detection of EC" program, Linzhou County Cancer Registry, and published literature in China. We calibrated the Markov models by comparing the modeled incidence and distributions of pathological stages (alone or combined) with epidemiological and screening data.The annual transition probabilities were 0.024, 0.05, 0.12 from health state progressing to mild dysplasia (mD), mD to moderate dysplasia (MD), and MD to severe dysplasia/carcinoma in situ (SD/CIS), respectively. Age-specific transition probabilities were 0.08~0.18 for SD/CIS progressing to intramucosal carcinoma(IC), 0.4~0.87 for IC to submucosal carcinoma (SC), and 0.2~0.85 for SC to invasive carcinoma. The progression probabilities increased with age and disease severity. The model's predictions of EC incidence and pathological stage distributions were corroborated by epidemiological and screening data, respectively, thereby confirming the reproducibility of the transition probabilities.Conclusions: An EC transition model in high-risk areas of China had been established and confirmed by real-world data. It represents the first attempt at developing models that can potentially be used for further economic evaluation and policy formulation of EC screening in China.
Keywords: esophageal cancer, Precancerous lesions, transition probabilities, Markov models, China
Received: 11 May 2024; Accepted: 30 Dec 2024.
Copyright: © 2024 Chen, Yu, Zhao, Wang, Yang and DAI. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Yong Yu, Chengdu Shuangliu District Center for Disease Control and Prevention, Chengdu, China
Fei Zhao, West China Second University Hospital, Sichuan University, Chengdu, China
Jingxuan Wang, Chengdu Shuangliu District Center for Disease Control and Prevention, Chengdu, China
Chunxia Yang, West China School of Public Health, Sichuan University, Chengdu, 610000, Sichuan Province, China
LI DAI, West China Second University Hospital, Sichuan University, Chengdu, China
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