Literature DB >> 31564475

Nomogram for predicting gastric cancer recurrence using biomarker gene expression.

Sang-Ho Jeong1, Rock Bum Kim2, Sun Yi Park1, Jiho Park1, Eun-Jung Jung1, Young-Tae Ju1, Chi-Young Jeong1, Miyeong Park3, Gyung Hyuck Ko4, Dae Hyun Song4, Hyun Min Koh4, Woo-Ho Kim5, Han-Kwang Yang6, Young-Joon Lee7, Soon-Chan Hong8.   

Abstract

BACKGROUND: Recently, researchers have tried to predict patient prognosis using biomarker expression in cancer patients. The aim of this study was to develop a nomogram predicting the 5-year recurrence-free probability (RFP) of gastric cancer patients using prognostic biomarker gene expression.
METHODS: We enrolled 360 patients in the training data set to develop the predictive model and nomogram. We analyzed the patients' general variables and the gene expression levels of 10 prognostic biomarker candidates between the nonrecurrence and recurrence groups. We also performed external validation using 420 patients from the validation data set.
RESULTS: The final nomogram was composed of age, sex, and the expression levels of CAPZA, PPase, OCT-1, PRDX4, gamma-enolase, and c-Myc. The five-year RFPs were 89%, 75%, 54% and 32% for the patients in the low-risk, intermediate-risk, high-risk and very-high-risk groups in the development cohort, respectively. In the external validation cohort, the 5-year RFPs were 89%, 75%, 63% and 60%, respectively. The areas under the curve were 0.718 (95% CI, 0.65-0.78) and 0.640 (95% CI, 0.57-0.70) for the training and validation data sets, respectively. The RFP Kaplan-Meier curves were significantly different among the 4 groups in the training and validation data sets (p < 0.0001).
CONCLUSION: This newly developed nomogram using gene expression can predict the 5-year RFP for gastric cancer patients after surgical treatment. We hope that this nomogram will help in the therapeutic decision between endoscopic treatment and gastrectomy.
Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Biomarkers; Gastric neoplasm; Gene expression; Nomograms

Year:  2019        PMID: 31564475     DOI: 10.1016/j.ejso.2019.09.143

Source DB:  PubMed          Journal:  Eur J Surg Oncol        ISSN: 0748-7983            Impact factor:   4.424


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