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A risk scoring system to predict the individual incidence of early-onset colorectal cancer
BACKGROUND: The incidence of early-onset colorectal cancer (EOCRC) is increasing at an alarming rate and further studies are needed to identify risk factors and to develop prevention strategies. METHODS: Risk factors significantly associated with EOCRC were identified using meta-analysis. An individ...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8801093/ https://www.ncbi.nlm.nih.gov/pubmed/35093005 http://dx.doi.org/10.1186/s12885-022-09238-4 |
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author | Gu, Jialin Li, Yan Yu, Jialin Hu, Miao Ji, Yi Li, Lingchang Hu, Canhong Wei, Guoli Huo, Jiege |
author_facet | Gu, Jialin Li, Yan Yu, Jialin Hu, Miao Ji, Yi Li, Lingchang Hu, Canhong Wei, Guoli Huo, Jiege |
author_sort | Gu, Jialin |
collection | PubMed |
description | BACKGROUND: The incidence of early-onset colorectal cancer (EOCRC) is increasing at an alarming rate and further studies are needed to identify risk factors and to develop prevention strategies. METHODS: Risk factors significantly associated with EOCRC were identified using meta-analysis. An individual risk appraisal model was constructed using the Rothman–Keller model. Next, a group of random data sets was generated using the binomial distribution function method, to determine nodes of risk assessment levels and to identify low, medium, and high risk populations. RESULTS: A total of 32,843 EOCRC patients were identified in this study, and nine significant risk factors were identified using meta-analysis, including male sex, Caucasian ethnicity, sedentary lifestyle, inflammatory bowel disease, and high intake of red meat and processed meat. After simulating the risk assessment data of 10,000 subjects, scores of 0 to 0.0018, 0.0018 to 0.0036, and 0.0036 or more were respectively considered as low-, moderate-, and high-risk populations for the EOCRC population based on risk trends from the Rothman–Keller model. CONCLUSION: This model can be used for screening of young adults to predict high risk of EOCRC and will contribute to the primary prevention strategies and the reduction of risk of developing EOCRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09238-4. |
format | Online Article Text |
id | pubmed-8801093 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88010932022-02-02 A risk scoring system to predict the individual incidence of early-onset colorectal cancer Gu, Jialin Li, Yan Yu, Jialin Hu, Miao Ji, Yi Li, Lingchang Hu, Canhong Wei, Guoli Huo, Jiege BMC Cancer Research BACKGROUND: The incidence of early-onset colorectal cancer (EOCRC) is increasing at an alarming rate and further studies are needed to identify risk factors and to develop prevention strategies. METHODS: Risk factors significantly associated with EOCRC were identified using meta-analysis. An individual risk appraisal model was constructed using the Rothman–Keller model. Next, a group of random data sets was generated using the binomial distribution function method, to determine nodes of risk assessment levels and to identify low, medium, and high risk populations. RESULTS: A total of 32,843 EOCRC patients were identified in this study, and nine significant risk factors were identified using meta-analysis, including male sex, Caucasian ethnicity, sedentary lifestyle, inflammatory bowel disease, and high intake of red meat and processed meat. After simulating the risk assessment data of 10,000 subjects, scores of 0 to 0.0018, 0.0018 to 0.0036, and 0.0036 or more were respectively considered as low-, moderate-, and high-risk populations for the EOCRC population based on risk trends from the Rothman–Keller model. CONCLUSION: This model can be used for screening of young adults to predict high risk of EOCRC and will contribute to the primary prevention strategies and the reduction of risk of developing EOCRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12885-022-09238-4. BioMed Central 2022-01-29 /pmc/articles/PMC8801093/ /pubmed/35093005 http://dx.doi.org/10.1186/s12885-022-09238-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Gu, Jialin Li, Yan Yu, Jialin Hu, Miao Ji, Yi Li, Lingchang Hu, Canhong Wei, Guoli Huo, Jiege A risk scoring system to predict the individual incidence of early-onset colorectal cancer |
title | A risk scoring system to predict the individual incidence of early-onset colorectal cancer |
title_full | A risk scoring system to predict the individual incidence of early-onset colorectal cancer |
title_fullStr | A risk scoring system to predict the individual incidence of early-onset colorectal cancer |
title_full_unstemmed | A risk scoring system to predict the individual incidence of early-onset colorectal cancer |
title_short | A risk scoring system to predict the individual incidence of early-onset colorectal cancer |
title_sort | risk scoring system to predict the individual incidence of early-onset colorectal cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8801093/ https://www.ncbi.nlm.nih.gov/pubmed/35093005 http://dx.doi.org/10.1186/s12885-022-09238-4 |
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