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Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review
Objective: The risk prediction model is an effective tool for risk stratification and is expected to play an important role in the early detection and prevention of esophageal cancer. This study sought to summarize the available evidence of esophageal cancer risk predictions models and provide refer...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671165/ https://www.ncbi.nlm.nih.gov/pubmed/34926362 http://dx.doi.org/10.3389/fpubh.2021.680967 |
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author | Chen, Ru Zheng, Rongshou Zhou, Jiachen Li, Minjuan Shao, Dantong Li, Xinqing Wang, Shengfeng Wei, Wenqiang |
author_facet | Chen, Ru Zheng, Rongshou Zhou, Jiachen Li, Minjuan Shao, Dantong Li, Xinqing Wang, Shengfeng Wei, Wenqiang |
author_sort | Chen, Ru |
collection | PubMed |
description | Objective: The risk prediction model is an effective tool for risk stratification and is expected to play an important role in the early detection and prevention of esophageal cancer. This study sought to summarize the available evidence of esophageal cancer risk predictions models and provide references for their development, validation, and application. Methods: We searched PubMed, EMBASE, and Cochrane Library databases for original articles published in English up to October 22, 2021. Studies that developed or validated a risk prediction model of esophageal cancer and its precancerous lesions were included. Two reviewers independently extracted study characteristics including predictors, model performance and methodology, and assessed risk of bias and applicability with PROBAST (Prediction model Risk Of Bias Assessment Tool). Results: A total of 20 studies including 30 original models were identified. The median area under the receiver operating characteristic curve of risk prediction models was 0.78, ranging from 0.68 to 0.94. Age, smoking, body mass index, sex, upper gastrointestinal symptoms, and family history were the most commonly included predictors. None of the models were assessed as low risk of bias based on PROBST. The major methodological deficiencies were inappropriate date sources, inconsistent definition of predictors and outcomes, and the insufficient number of participants with the outcome. Conclusions: This study systematically reviewed available evidence on risk prediction models for esophageal cancer in general populations. The findings indicate a high risk of bias due to several methodological pitfalls in model development and validation, which limit their application in practice. |
format | Online Article Text |
id | pubmed-8671165 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86711652021-12-16 Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review Chen, Ru Zheng, Rongshou Zhou, Jiachen Li, Minjuan Shao, Dantong Li, Xinqing Wang, Shengfeng Wei, Wenqiang Front Public Health Public Health Objective: The risk prediction model is an effective tool for risk stratification and is expected to play an important role in the early detection and prevention of esophageal cancer. This study sought to summarize the available evidence of esophageal cancer risk predictions models and provide references for their development, validation, and application. Methods: We searched PubMed, EMBASE, and Cochrane Library databases for original articles published in English up to October 22, 2021. Studies that developed or validated a risk prediction model of esophageal cancer and its precancerous lesions were included. Two reviewers independently extracted study characteristics including predictors, model performance and methodology, and assessed risk of bias and applicability with PROBAST (Prediction model Risk Of Bias Assessment Tool). Results: A total of 20 studies including 30 original models were identified. The median area under the receiver operating characteristic curve of risk prediction models was 0.78, ranging from 0.68 to 0.94. Age, smoking, body mass index, sex, upper gastrointestinal symptoms, and family history were the most commonly included predictors. None of the models were assessed as low risk of bias based on PROBST. The major methodological deficiencies were inappropriate date sources, inconsistent definition of predictors and outcomes, and the insufficient number of participants with the outcome. Conclusions: This study systematically reviewed available evidence on risk prediction models for esophageal cancer in general populations. The findings indicate a high risk of bias due to several methodological pitfalls in model development and validation, which limit their application in practice. Frontiers Media S.A. 2021-12-01 /pmc/articles/PMC8671165/ /pubmed/34926362 http://dx.doi.org/10.3389/fpubh.2021.680967 Text en Copyright © 2021 Chen, Zheng, Zhou, Li, Shao, Li, Wang and Wei. https://creativecommons.org/licenses/by/4.0/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) and the copyright owner(s) 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. |
spellingShingle | Public Health Chen, Ru Zheng, Rongshou Zhou, Jiachen Li, Minjuan Shao, Dantong Li, Xinqing Wang, Shengfeng Wei, Wenqiang Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review |
title | Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review |
title_full | Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review |
title_fullStr | Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review |
title_full_unstemmed | Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review |
title_short | Risk Prediction Model for Esophageal Cancer Among General Population: A Systematic Review |
title_sort | risk prediction model for esophageal cancer among general population: a systematic review |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8671165/ https://www.ncbi.nlm.nih.gov/pubmed/34926362 http://dx.doi.org/10.3389/fpubh.2021.680967 |
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