Development and Validation of a Risk Assessment Tool for Gastric Cancer in a General Japanese Population

Overview

Journal Gastric Cancer

Specialties Gastroenterology
Oncology

Date 2017 Oct 19

PMID 29043529

Citations 21

Authors

Masahiro Iida

Fumie Ikeda

Jun Hata

Yoichiro Hirakawa

Tomoyuki Ohara

Naoko Mukai

Daigo Yoshida

Koji Yonemoto

Motohiro Esaki

Takanari Kitazono

Yutaka Kiyohara

Toshiharu Ninomiya

Affiliations

Soon will be listed here.

Abstract

Background: There have been very few reports of risk score models for the development of gastric cancer. The aim of this study was to develop and validate a risk assessment tool for discerning future gastric cancer risk in Japanese.

Methods: A total of 2444 subjects aged 40 years or over were followed up for 14 years from 1988 (derivation cohort), and 3204 subjects of the same age group were followed up for 5 years from 2002 (validation cohort). The weighting (risk score) of each risk factor for predicting future gastric cancer in the risk assessment tool was determined based on the coefficients of a Cox proportional hazards model in the derivation cohort. The goodness of fit of the established risk assessment tool was assessed using the c-statistic and the Hosmer-Lemeshow test in the validation cohort.

Results: During the follow-up, gastric cancer developed in 90 subjects in the derivation cohort and 35 subjects in the validation cohort. In the derivation cohort, the risk prediction model for gastric cancer was established using significant risk factors: age, sex, the combination of Helicobacter pylori antibody and pepsinogen status, hemoglobin A1c level, and smoking status. The incidence of gastric cancer increased significantly as the sum of risk scores increased (P trend < 0.001). The risk assessment tool was validated internally and showed good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test P = 0.43) in the validation cohort.

Conclusions: We developed a risk assessment tool for gastric cancer that provides a useful guide for stratifying an individual's risk of future gastric cancer.

Citing Articles

Using the Electronic Health Record to Develop a Gastric Cancer Risk Prediction Model.

Kim M, Rouphael C, Wehbe S, Yoon J, Wisnivesky J, McMichael J Gastro Hep Adv. 2024; 3(7):910-916.

PMID: 39286619 PMC: 11402285. DOI: 10.1016/j.gastha.2024.07.001.

Risk Prediction Models for Gastric Cancer: A Scoping Review.

Xu L, Lyu J, Zheng X, Wang A J Multidiscip Healthc. 2024; 17:4337-4352.

PMID: 39257385 PMC: 11385365. DOI: 10.2147/JMDH.S479699.

Hotspots and trends of risk factors in gastric cancer: A visualization and bibliometric analysis.

Li M, Gao N, Wang S, Guo Y, Liu Z World J Gastrointest Oncol. 2024; 16(5):2200-2218.

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Prediction algorithm for gastric cancer in a general population: A validation study.

Wong M, Leung E, Yau S, Chan S, Xie S, Xu W Cancer Med. 2023; 12(21):20544-20553.

PMID: 37855240 PMC: 10660462. DOI: 10.1002/cam4.6629.

A Model for Gastric Cancer Risk Prediction Based on Polymorphisms and Health-risk Behaviors in a Vietnamese Population.

Nguyen N, Dang N, Vu Q, Dang A, Ta T In Vivo. 2023; 37(5):2347-2356.

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