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Update and validation of a diagnostic model to identify prevalent malignant lesions in esophagus in general population.

作者信息

Liu Mengfei, Zhou Ren, Liu Zhen, Guo Chuanhai, Xu Ruiping, Zhou Fuyou, Liu Anxiang, Yang Haijun, Li Fenglei, Duan Liping, Shen Lin, Wu Qi, Zheng Hongchen, Tian Hongrui, Liu Fangfang, Liu Ying, Pan Yaqi, Chen Huanyu, Hu Zhe, Cai Hong, He Zhonghu, Ke Yang

机构信息

Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Laboratory of Genetics, Peking University Cancer Hospital and Institute, #52 Fucheng Rd, Beijing 100142, China.

Anyang Cancer Hospital, Anyang, Henan Province, China.

出版信息

EClinicalMedicine. 2022 Apr 16;47:101394. doi: 10.1016/j.eclinm.2022.101394. eCollection 2022 May.


DOI:10.1016/j.eclinm.2022.101394
PMID:35480078
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9035729/
Abstract

BACKGROUND: Previous risk prediction models taking esophageal malignant lesions detected during endoscopy as the primary outcome are not always sufficient to identify prevalent cases which are "overlooked" at screening. We aimed to update and externally validate our previous risk prediction model for malignant esophageal lesions by redefining the predicted outcome. METHODS: 15,192 individuals from the Endoscopic Screening for Esophageal Cancer in China randomized controlled trial (ESECC trial, NCT01688908) were included as the training set, and 4576 participants from another population-based esophageal squamous cell carcinoma (ESCC) screening cohort (Anyang Esophageal Cancer Cohort Study, AECCS) served as the external validation set. Lesions with severe dysplasia or worse diagnosed at chromoendoscopy or identified via follow-up within 1 year after screening were defined as main outcome. Logistic regressions were applied to reconstruct the questionnaire-based prediction model using information collected before screening, with Akaike Information Criterion to determine the model structure. FINDINGS: The final prediction model included age and its quadratic term, family history of ESCC, low body mass index (≤22 kg/m), use of coal or wood as main fuel for cooking, eating rapidly, and ingestion of leftover food. The area under the curve was 0·77 (95% CI: 0·73-0·80) and 0·71 (95% CI: 0·65-0·78) in the training and validation set. When screening the top 50% or 10% of high-risk individuals within population, the detection rates can be increased in both cohorts, as compared to universal screening. INTERPRETATION: The described tool may promote the efficiency of current national screening programs for ESCC and contribute to a precision screening strategy in high-risk regions in China. FUNDING: This work was supported by the National Natural Science Foundation of China (82073626, 81773501), the National Science & Technology Fundamental Resources Investigation Program of China (2019FY101102), the National Key R&D Program of China (2021YFC2500405), the Beijing-Tianjin-Hebei Basic Research Cooperation Project (J200016), the Digestive Medical Coordinated Development Center of Beijing Hospitals Authority (XXZ0204) and the Beijing Nova Program (Z201100006820093). Sponsors had no role in the study design, data collection, analysis, and interpretation of data.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9c8/9035729/bc717b248603/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9c8/9035729/bc717b248603/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9c8/9035729/bc717b248603/gr1.jpg

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Update and validation of a diagnostic model to identify prevalent malignant lesions in esophagus in general population.

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引用本文的文献

[1]
Diagnostic Risk Prediction Models for Upper Gastrointestinal Cancers: A Systematic Review.

Cancer Epidemiol Biomarkers Prev. 2025-8-1

[2]
An Image-Based Model for Assisting in Diagnosing Malignant Esophageal Lesions During Lugol Chromoendoscopic Examination.

Clin Transl Gastroenterol. 2025-5-1

[3]
Microfluidic biosensors for biomarker detection in body fluids: a key approach for early cancer diagnosis.

Biomark Res. 2024-12-5

[4]
Construction and validation of serum Metabolic Risk Score for early warning of malignancy in esophagus.

iScience. 2024-5-11

[5]
Challenge and future of cancer screening in China: Insights from esophageal cancer screening practice.

Chin J Cancer Res. 2023-12-30

[6]
The landscape of cancer research and cancer care in China.

Nat Med. 2023-12

本文引用的文献

[1]
Esophageal cancer: Epidemiology, risk factors and screening.

Chin J Cancer Res. 2021-10-31

[2]
Precision screening for esophageal squamous cell carcinoma in China.

Chin J Cancer Res. 2020-12-31

[3]
Initial results from a multi-center population-based cluster randomized trial of esophageal and gastric cancer screening in China.

BMC Gastroenterol. 2020-11-24

[4]
Selection of high-risk individuals for esophageal cancer screening: A prediction model of esophageal squamous cell carcinoma based on a multicenter screening cohort in rural China.

Int J Cancer. 2021-1-15

[5]
Esophageal Histological Precursor Lesions and Subsequent 8.5-Year Cancer Risk in a Population-Based Prospective Study in China.

Am J Gastroenterol. 2020-7

[6]
Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China.

EClinicalMedicine. 2020-3-20

[7]
Identification of cancer patients using claims data from health insurance systems: A real-world comparative study.

Chin J Cancer Res. 2019-8

[8]
Mortality Risk of Nonoperative Papillary Thyroid Carcinoma: A Corollary for Active Surveillance.

Thyroid. 2019-9-24

[9]
Quantifying the relationship between age at diagnosis and breast cancer-specific mortality.

Breast Cancer Res Treat. 2019-7-11

[10]
Age at Menopause and Risk of Developing Endometrial Cancer: A Meta-Analysis.

Biomed Res Int. 2019-5-29

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