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Prediction Model for Gastric Cancer Incidence in Korean Population
BACKGROUND: Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort i...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4506054/ https://www.ncbi.nlm.nih.gov/pubmed/26186332 http://dx.doi.org/10.1371/journal.pone.0132613 |
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author | Eom, Bang Wool Joo, Jungnam Kim, Sohee Shin, Aesun Yang, Hye-Ryung Park, Junghyun Choi, Il Ju Kim, Young-Woo Kim, Jeongseon Nam, Byung-Ho |
author_facet | Eom, Bang Wool Joo, Jungnam Kim, Sohee Shin, Aesun Yang, Hye-Ryung Park, Junghyun Choi, Il Ju Kim, Young-Woo Kim, Jeongseon Nam, Byung-Ho |
author_sort | Eom, Bang Wool |
collection | PubMed |
description | BACKGROUND: Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea. METHOD: Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell’s C-statistics, and the calibration was evaluated using a calibration plot and slope. RESULTS: During a median of 11.4 years of follow-up, 19,465 (1.4%) and 5,579 (0.7%) newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women). CONCLUSIONS: In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance. |
format | Online Article Text |
id | pubmed-4506054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-45060542015-07-23 Prediction Model for Gastric Cancer Incidence in Korean Population Eom, Bang Wool Joo, Jungnam Kim, Sohee Shin, Aesun Yang, Hye-Ryung Park, Junghyun Choi, Il Ju Kim, Young-Woo Kim, Jeongseon Nam, Byung-Ho PLoS One Research Article BACKGROUND: Predicting high risk groups for gastric cancer and motivating these groups to receive regular checkups is required for the early detection of gastric cancer. The aim of this study is was to develop a prediction model for gastric cancer incidence based on a large population-based cohort in Korea. METHOD: Based on the National Health Insurance Corporation data, we analyzed 10 major risk factors for gastric cancer. The Cox proportional hazards model was used to develop gender specific prediction models for gastric cancer development, and the performance of the developed model in terms of discrimination and calibration was also validated using an independent cohort. Discrimination ability was evaluated using Harrell’s C-statistics, and the calibration was evaluated using a calibration plot and slope. RESULTS: During a median of 11.4 years of follow-up, 19,465 (1.4%) and 5,579 (0.7%) newly developed gastric cancer cases were observed among 1,372,424 men and 804,077 women, respectively. The prediction models included age, BMI, family history, meal regularity, salt preference, alcohol consumption, smoking and physical activity for men, and age, BMI, family history, salt preference, alcohol consumption, and smoking for women. This prediction model showed good accuracy and predictability in both the developing and validation cohorts (C-statistics: 0.764 for men, 0.706 for women). CONCLUSIONS: In this study, a prediction model for gastric cancer incidence was developed that displayed a good performance. Public Library of Science 2015-07-17 /pmc/articles/PMC4506054/ /pubmed/26186332 http://dx.doi.org/10.1371/journal.pone.0132613 Text en © 2015 Eom 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 Eom, Bang Wool Joo, Jungnam Kim, Sohee Shin, Aesun Yang, Hye-Ryung Park, Junghyun Choi, Il Ju Kim, Young-Woo Kim, Jeongseon Nam, Byung-Ho Prediction Model for Gastric Cancer Incidence in Korean Population |
title | Prediction Model for Gastric Cancer Incidence in Korean Population |
title_full | Prediction Model for Gastric Cancer Incidence in Korean Population |
title_fullStr | Prediction Model for Gastric Cancer Incidence in Korean Population |
title_full_unstemmed | Prediction Model for Gastric Cancer Incidence in Korean Population |
title_short | Prediction Model for Gastric Cancer Incidence in Korean Population |
title_sort | prediction model for gastric cancer incidence in korean population |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4506054/ https://www.ncbi.nlm.nih.gov/pubmed/26186332 http://dx.doi.org/10.1371/journal.pone.0132613 |
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