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Risk Prediction Model for Colorectal Cancer: National Health Insurance Corporation Study, Korea

PURPOSE: Incidence and mortality rates of colorectal cancer have been rapidly increasing in Korea during last few decades. Development of risk prediction models for colorectal cancer in Korean men and women is urgently needed to enhance its prevention and early detection. METHODS: Gender specific fi...

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Autores principales: Shin, Aesun, Joo, Jungnam, Yang, Hye-Ryung, Bak, Jeongin, Park, Yunjin, Kim, Jeongseon, Oh, Jae Hwan, Nam, Byung-Ho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922771/
https://www.ncbi.nlm.nih.gov/pubmed/24533067
http://dx.doi.org/10.1371/journal.pone.0088079
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author Shin, Aesun
Joo, Jungnam
Yang, Hye-Ryung
Bak, Jeongin
Park, Yunjin
Kim, Jeongseon
Oh, Jae Hwan
Nam, Byung-Ho
author_facet Shin, Aesun
Joo, Jungnam
Yang, Hye-Ryung
Bak, Jeongin
Park, Yunjin
Kim, Jeongseon
Oh, Jae Hwan
Nam, Byung-Ho
author_sort Shin, Aesun
collection PubMed
description PURPOSE: Incidence and mortality rates of colorectal cancer have been rapidly increasing in Korea during last few decades. Development of risk prediction models for colorectal cancer in Korean men and women is urgently needed to enhance its prevention and early detection. METHODS: Gender specific five-year risk prediction models were developed for overall colorectal cancer, proximal colon cancer, distal colon cancer, colon cancer and rectal cancer. The model was developed using data from a population of 846,559 men and 479,449 women who participated in health examinations by the National Health Insurance Corporation. Examinees were 30–80 years old and free of cancer in the baseline years of 1996 and 1997. An independent population of 547,874 men and 415,875 women who participated in 1998 and 1999 examinations was used to validate the model. Model validation was done by evaluating its performance in terms of discrimination and calibration ability using the C-statistic and Hosmer-Lemeshow-type chi-square statistics. RESULTS: Age, body mass index, serum cholesterol, family history of cancer, and alcohol consumption were included in all models for men, whereas age, height, and meat intake frequency were included in all models for women. Models showed moderately good discrimination ability with C-statistics between 0.69 and 0.78. The C-statistics were generally higher in the models for men, whereas the calibration abilities were generally better in the models for women. CONCLUSIONS: Colorectal cancer risk prediction models were developed from large-scale, population-based data. Those models can be used for identifying high risk groups and developing preventive intervention strategies for colorectal cancer.
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spelling pubmed-39227712014-02-14 Risk Prediction Model for Colorectal Cancer: National Health Insurance Corporation Study, Korea Shin, Aesun Joo, Jungnam Yang, Hye-Ryung Bak, Jeongin Park, Yunjin Kim, Jeongseon Oh, Jae Hwan Nam, Byung-Ho PLoS One Research Article PURPOSE: Incidence and mortality rates of colorectal cancer have been rapidly increasing in Korea during last few decades. Development of risk prediction models for colorectal cancer in Korean men and women is urgently needed to enhance its prevention and early detection. METHODS: Gender specific five-year risk prediction models were developed for overall colorectal cancer, proximal colon cancer, distal colon cancer, colon cancer and rectal cancer. The model was developed using data from a population of 846,559 men and 479,449 women who participated in health examinations by the National Health Insurance Corporation. Examinees were 30–80 years old and free of cancer in the baseline years of 1996 and 1997. An independent population of 547,874 men and 415,875 women who participated in 1998 and 1999 examinations was used to validate the model. Model validation was done by evaluating its performance in terms of discrimination and calibration ability using the C-statistic and Hosmer-Lemeshow-type chi-square statistics. RESULTS: Age, body mass index, serum cholesterol, family history of cancer, and alcohol consumption were included in all models for men, whereas age, height, and meat intake frequency were included in all models for women. Models showed moderately good discrimination ability with C-statistics between 0.69 and 0.78. The C-statistics were generally higher in the models for men, whereas the calibration abilities were generally better in the models for women. CONCLUSIONS: Colorectal cancer risk prediction models were developed from large-scale, population-based data. Those models can be used for identifying high risk groups and developing preventive intervention strategies for colorectal cancer. Public Library of Science 2014-02-12 /pmc/articles/PMC3922771/ /pubmed/24533067 http://dx.doi.org/10.1371/journal.pone.0088079 Text en © 2014 Shin et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Shin, Aesun
Joo, Jungnam
Yang, Hye-Ryung
Bak, Jeongin
Park, Yunjin
Kim, Jeongseon
Oh, Jae Hwan
Nam, Byung-Ho
Risk Prediction Model for Colorectal Cancer: National Health Insurance Corporation Study, Korea
title Risk Prediction Model for Colorectal Cancer: National Health Insurance Corporation Study, Korea
title_full Risk Prediction Model for Colorectal Cancer: National Health Insurance Corporation Study, Korea
title_fullStr Risk Prediction Model for Colorectal Cancer: National Health Insurance Corporation Study, Korea
title_full_unstemmed Risk Prediction Model for Colorectal Cancer: National Health Insurance Corporation Study, Korea
title_short Risk Prediction Model for Colorectal Cancer: National Health Insurance Corporation Study, Korea
title_sort risk prediction model for colorectal cancer: national health insurance corporation study, korea
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922771/
https://www.ncbi.nlm.nih.gov/pubmed/24533067
http://dx.doi.org/10.1371/journal.pone.0088079
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