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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
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.
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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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