Risk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, <i>Helicobacter pylori</i> Infection and Lifestyle-Related Risk Factors in a Japanese Population
Background: As part of our efforts to develop practical intervention applications for cancer prevention, we investigated a risk prediction model for gastric cancer based on genetic, biological, and lifestyle-related risk factors. Methods: We conducted two independent age- and sex-matched case–contro...
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2021
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oai:doaj.org-article:ddaf54aa838e41fc90f3c40fe5cd73b02021-11-11T15:33:53ZRisk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, <i>Helicobacter pylori</i> Infection and Lifestyle-Related Risk Factors in a Japanese Population10.3390/cancers132155252072-6694https://doaj.org/article/ddaf54aa838e41fc90f3c40fe5cd73b02021-11-01T00:00:00Zhttps://www.mdpi.com/2072-6694/13/21/5525https://doaj.org/toc/2072-6694Background: As part of our efforts to develop practical intervention applications for cancer prevention, we investigated a risk prediction model for gastric cancer based on genetic, biological, and lifestyle-related risk factors. Methods: We conducted two independent age- and sex-matched case–control studies, the first for model derivation (696 cases and 1392 controls) and the second (795 and 795) for external validation. Using the derivation study data, we developed a prediction model by fitting a conditional logistic regression model using the predictors age, ABCD classification defined by <i>H. pylori</i> infection and gastric atrophy, smoking, alcohol consumption, fruit and vegetable intake, and 3 GWAS-identified polymorphisms. Performance was assessed with regard to discrimination (area under the curve (AUC)) and calibration (calibration plots and Hosmer–Lemeshow test). Results: A combination of selected GWAS-identified polymorphisms and the other predictors provided high discriminatory accuracy and good calibration in both the derivation and validation studies, with AUCs of 0.77 (95% confidence intervals: 0.75–0.79) and 0.78 (0.77–0.81), respectively. The calibration plots of both studies stayed close to the ideal calibration line. In the validation study, the environmental model (nongenetic model) was significantly more discriminative than the inclusive model, with an AUC value of 0.80 (0.77–0.82). Conclusion: The contribution of genetic factors to risk prediction was limited, and the ABCD classification (<i>H. pylori</i> infection-related factor) contributes most to risk prediction of gastric cancer.Naoyo IshikuraHidemi ItoIsao OzeYuriko N. KoyanagiYumiko KasugaiYukari TaniyamaYukino KawakatsuTsutomu TanakaSeiji ItoMasahiro TajikaYasuhiro ShimizuYasumasa NiwaKeitaro MatsuoMDPI AGarticlegastric cancerrisk predictiongenetic variantslifestyle factors<i>Helicobacter pylori</i> infectionNeoplasms. Tumors. Oncology. Including cancer and carcinogensRC254-282ENCancers, Vol 13, Iss 5525, p 5525 (2021) |
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DOAJ |
language |
EN |
topic |
gastric cancer risk prediction genetic variants lifestyle factors <i>Helicobacter pylori</i> infection Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 |
spellingShingle |
gastric cancer risk prediction genetic variants lifestyle factors <i>Helicobacter pylori</i> infection Neoplasms. Tumors. Oncology. Including cancer and carcinogens RC254-282 Naoyo Ishikura Hidemi Ito Isao Oze Yuriko N. Koyanagi Yumiko Kasugai Yukari Taniyama Yukino Kawakatsu Tsutomu Tanaka Seiji Ito Masahiro Tajika Yasuhiro Shimizu Yasumasa Niwa Keitaro Matsuo Risk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, <i>Helicobacter pylori</i> Infection and Lifestyle-Related Risk Factors in a Japanese Population |
description |
Background: As part of our efforts to develop practical intervention applications for cancer prevention, we investigated a risk prediction model for gastric cancer based on genetic, biological, and lifestyle-related risk factors. Methods: We conducted two independent age- and sex-matched case–control studies, the first for model derivation (696 cases and 1392 controls) and the second (795 and 795) for external validation. Using the derivation study data, we developed a prediction model by fitting a conditional logistic regression model using the predictors age, ABCD classification defined by <i>H. pylori</i> infection and gastric atrophy, smoking, alcohol consumption, fruit and vegetable intake, and 3 GWAS-identified polymorphisms. Performance was assessed with regard to discrimination (area under the curve (AUC)) and calibration (calibration plots and Hosmer–Lemeshow test). Results: A combination of selected GWAS-identified polymorphisms and the other predictors provided high discriminatory accuracy and good calibration in both the derivation and validation studies, with AUCs of 0.77 (95% confidence intervals: 0.75–0.79) and 0.78 (0.77–0.81), respectively. The calibration plots of both studies stayed close to the ideal calibration line. In the validation study, the environmental model (nongenetic model) was significantly more discriminative than the inclusive model, with an AUC value of 0.80 (0.77–0.82). Conclusion: The contribution of genetic factors to risk prediction was limited, and the ABCD classification (<i>H. pylori</i> infection-related factor) contributes most to risk prediction of gastric cancer. |
format |
article |
author |
Naoyo Ishikura Hidemi Ito Isao Oze Yuriko N. Koyanagi Yumiko Kasugai Yukari Taniyama Yukino Kawakatsu Tsutomu Tanaka Seiji Ito Masahiro Tajika Yasuhiro Shimizu Yasumasa Niwa Keitaro Matsuo |
author_facet |
Naoyo Ishikura Hidemi Ito Isao Oze Yuriko N. Koyanagi Yumiko Kasugai Yukari Taniyama Yukino Kawakatsu Tsutomu Tanaka Seiji Ito Masahiro Tajika Yasuhiro Shimizu Yasumasa Niwa Keitaro Matsuo |
author_sort |
Naoyo Ishikura |
title |
Risk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, <i>Helicobacter pylori</i> Infection and Lifestyle-Related Risk Factors in a Japanese Population |
title_short |
Risk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, <i>Helicobacter pylori</i> Infection and Lifestyle-Related Risk Factors in a Japanese Population |
title_full |
Risk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, <i>Helicobacter pylori</i> Infection and Lifestyle-Related Risk Factors in a Japanese Population |
title_fullStr |
Risk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, <i>Helicobacter pylori</i> Infection and Lifestyle-Related Risk Factors in a Japanese Population |
title_full_unstemmed |
Risk Prediction for Gastric Cancer Using GWAS-Identifie Polymorphisms, <i>Helicobacter pylori</i> Infection and Lifestyle-Related Risk Factors in a Japanese Population |
title_sort |
risk prediction for gastric cancer using gwas-identifie polymorphisms, <i>helicobacter pylori</i> infection and lifestyle-related risk factors in a japanese population |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/ddaf54aa838e41fc90f3c40fe5cd73b0 |
work_keys_str_mv |
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