Prognostic value of modified Lauren classification in gastric cancer

Fei-Long Ning; Nan-Nan Zhang; Jun Wang; Yi-Feng Jin; Hong-Guang Quan; Jun-Peng Pei; Yan Zhao; Xian-Tao Zeng; Masanobu Abe; Chun-Dong Zhang

doi:10.4251/wjgo.v13.i9.1184

Prognostic value of modified Lauren classification in gastric cancer

World J Gastrointest Oncol. 2021 Sep 15;13(9):1184-1195. doi: 10.4251/wjgo.v13.i9.1184.

Authors

Fei-Long Ning¹, Nan-Nan Zhang², Jun Wang¹, Yi-Feng Jin³, Hong-Guang Quan¹, Jun-Peng Pei⁴, Yan Zhao⁵, Xian-Tao Zeng⁶, Masanobu Abe⁷, Chun-Dong Zhang⁴

Affiliations

¹ Department of General Surgery, Xuzhou Hospital of Traditional Chinese Medicine, Xuzhou 221000, Jiangsu Province, China.
² State Key Laboratory of Cancer Biology and National Clinical Research Center for Digestive Diseases, Xijing Hospital of Digestive Diseases, The Fourth Military Medical University, Xi'an 710000, Shannxi Province, China.
³ Department of General Surgery, Jiading Hospital of Traditional Chinese Medicine, Shanghai 201800, China.
⁴ Department of Gastrointestinal Surgery, The Fourth Affiliated Hospital of China Medical University, Shenyang 110032, Liaoning Province, China.
⁵ Department of Stomach Surgery, Liaoning Cancer Hospital and Institute, Cancer Hospital of China Medical University, Shenyang 110042, Liaoning Province, China.
⁶ Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, Hubei Province, China.
⁷ Division for Health Service Promotion, The University of Tokyo, Tokyo 113-0033, Japan.

Abstract

Background: It remains controversial as to which pathological classification is most valuable in predicting the overall survival (OS) of patients with gastric cancer (GC).

Aim: To assess the prognostic performances of three pathological classifications in GC and develop a novel prognostic nomogram for individually predicting OS.

Methods: Patients were identified from the Surveillance, Epidemiology, and End Results program. Univariate and multivariate analyses were performed to identify the independent prognostic factors. Model discrimination and model fitting were evaluated by receiver operating characteristic curves and Akaike information criteria. Decision curve analysis was performed to assess clinical usefulness. The independent prognostic factors identified by multivariate analysis were further applied to develop a novel prognostic nomogram.

Results: A total of 2718 eligible GC patients were identified. The modified Lauren classification was identified as one of the independent prognostic factors for OS. It showed superior model discriminative ability and model-fitting performance over the other pathological classifications, and similar results were obtained in various patient settings. In addition, it showed superior net benefits over the Lauren classification and tumor differentiation grade in predicting 3- and 5-year OS. A novel prognostic nomogram incorporating the modified Lauren classification showed superior model discriminative ability, model-fitting performance, and net benefits over the American Joint Committee on Cancer 8^th edition tumor-node-metastasis classification.

Conclusion: The modified Lauren classification shows superior net benefits over the Lauren classification and tumor differentiation grade in predicting OS. A novel prognostic nomogram incorporating the modified Lauren classification shows good model discriminative ability, model-fitting performance, and net benefits.

Keywords: Gastric cancer; Pathological classification; Prognostic model; Survival outcome; Tumor-node-metastasis classification.