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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Autores principales: 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
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Publicado: MDPI AG 2021
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spelling 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)
institution DOAJ
collection 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
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