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Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case–Control Study

OBJECTIVE: To identify people with high-risk early colorectal neoplasm is highly desirable for pre-selection in colorectal cancer (CRC) screening in low-resource countries. We aim to build and validate a risk-based model so as to improve compliance and increase the benefits of screening. PATIENTS AN...

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Autores principales: Shen, Jie, Wu, Yiling, Feng, Xiaoshuang, Liang, Fei, Mo, Miao, Cai, Binxin, Zhou, Changming, Wang, Zezhou, Zhu, Meiying, Cai, Guoxiang, Zheng, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126801/
https://www.ncbi.nlm.nih.gov/pubmed/34012295
http://dx.doi.org/10.2147/CMAR.S301185
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author Shen, Jie
Wu, Yiling
Feng, Xiaoshuang
Liang, Fei
Mo, Miao
Cai, Binxin
Zhou, Changming
Wang, Zezhou
Zhu, Meiying
Cai, Guoxiang
Zheng, Ying
author_facet Shen, Jie
Wu, Yiling
Feng, Xiaoshuang
Liang, Fei
Mo, Miao
Cai, Binxin
Zhou, Changming
Wang, Zezhou
Zhu, Meiying
Cai, Guoxiang
Zheng, Ying
author_sort Shen, Jie
collection PubMed
description OBJECTIVE: To identify people with high-risk early colorectal neoplasm is highly desirable for pre-selection in colorectal cancer (CRC) screening in low-resource countries. We aim to build and validate a risk-based model so as to improve compliance and increase the benefits of screening. PATIENTS AND METHODS: Using data from the Shanghai CRC screening cohort, we conducted a population-based nested case–control study to build a risk-based model. Cases of early colorectal neoplasm were extracted as colorectal adenomas and stage 0-I CRC. Each case was matched with five individuals without neoplasm (controls) by the screening site and year of enrollment. Cases and controls were then randomly divided into two groups, with two thirds for building the risk prediction model and the other one third for model validation. Known risk factors were included for risk prediction models using logistic regressions. The area under the receiver operating characteristic curve (AUC) and Hosmer–Lemeshow chi-square statistics were used to evaluate model discrimination and calibration. The predicted individual risk probability was calculated under the risk regression equation. RESULTS: The model incorporating age, sex, family history and lifestyle factors including body mass index (BMI), smoking status, alcohol, regular moderate-to-intensity physical activity showed good calibration and discrimination. When the risk cutoff threshold was defined as 17%, the sensitivity and specificity of the model were 63.99% and 53.82%, respectively. The validation data analysis also showed well discrimination. CONCLUSION: A risk prediction model combining personal and lifestyle factors was developed and validated for high-risk early colorectal neoplasm among the Chinese population. This risk-based model could improve the pre-selection for screening and contribute a lot to efficient population-based screening in low-resource countries.
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spelling pubmed-81268012021-05-18 Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case–Control Study Shen, Jie Wu, Yiling Feng, Xiaoshuang Liang, Fei Mo, Miao Cai, Binxin Zhou, Changming Wang, Zezhou Zhu, Meiying Cai, Guoxiang Zheng, Ying Cancer Manag Res Original Research OBJECTIVE: To identify people with high-risk early colorectal neoplasm is highly desirable for pre-selection in colorectal cancer (CRC) screening in low-resource countries. We aim to build and validate a risk-based model so as to improve compliance and increase the benefits of screening. PATIENTS AND METHODS: Using data from the Shanghai CRC screening cohort, we conducted a population-based nested case–control study to build a risk-based model. Cases of early colorectal neoplasm were extracted as colorectal adenomas and stage 0-I CRC. Each case was matched with five individuals without neoplasm (controls) by the screening site and year of enrollment. Cases and controls were then randomly divided into two groups, with two thirds for building the risk prediction model and the other one third for model validation. Known risk factors were included for risk prediction models using logistic regressions. The area under the receiver operating characteristic curve (AUC) and Hosmer–Lemeshow chi-square statistics were used to evaluate model discrimination and calibration. The predicted individual risk probability was calculated under the risk regression equation. RESULTS: The model incorporating age, sex, family history and lifestyle factors including body mass index (BMI), smoking status, alcohol, regular moderate-to-intensity physical activity showed good calibration and discrimination. When the risk cutoff threshold was defined as 17%, the sensitivity and specificity of the model were 63.99% and 53.82%, respectively. The validation data analysis also showed well discrimination. CONCLUSION: A risk prediction model combining personal and lifestyle factors was developed and validated for high-risk early colorectal neoplasm among the Chinese population. This risk-based model could improve the pre-selection for screening and contribute a lot to efficient population-based screening in low-resource countries. Dove 2021-05-12 /pmc/articles/PMC8126801/ /pubmed/34012295 http://dx.doi.org/10.2147/CMAR.S301185 Text en © 2021 Shen et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Shen, Jie
Wu, Yiling
Feng, Xiaoshuang
Liang, Fei
Mo, Miao
Cai, Binxin
Zhou, Changming
Wang, Zezhou
Zhu, Meiying
Cai, Guoxiang
Zheng, Ying
Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case–Control Study
title Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case–Control Study
title_full Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case–Control Study
title_fullStr Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case–Control Study
title_full_unstemmed Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case–Control Study
title_short Assessing Individual Risk for High-Risk Early Colorectal Neoplasm for Pre-Selection of Screening in Shanghai, China: A Population-Based Nested Case–Control Study
title_sort assessing individual risk for high-risk early colorectal neoplasm for pre-selection of screening in shanghai, china: a population-based nested case–control study
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126801/
https://www.ncbi.nlm.nih.gov/pubmed/34012295
http://dx.doi.org/10.2147/CMAR.S301185
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