A prognostic nomogram to predict the cancer-specific survival of patients with initially diagnosed metastatic gastric cancer: a validation study in a Chinese cohort

Author:

Zhao Ziming,Dai Erxun,Jin Bao,Deng Ping,Salehebieke Zulihaer,Han Bin,Wu Rongfan,Yu Zhaowu,Ren JunORCID

Abstract

Abstract Background Few studies have been designed to predict the survival of Chinese patients initially diagnosed with metastatic gastric cancer (mGC). Therefore, the objective of this study was to construct and validate a new nomogram model to predict cancer-specific survival (CSS) in Chinese patients. Methods We collected 328 patients with mGC from Northern Jiangsu People’s Hospital as the training cohort and 60 patients from Xinyuan County People’s Hospital as the external validation cohort. Multivariate Cox regression was used to identify risk factors, and a nomogram was created to predict CSS. The predictive performance of the nomogram was evaluated using the consistency index (C-index), the calibration curve, and the decision curve analysis (DCA) in the training cohort and the validation cohort. Results Multivariate Cox regression identified differentiation grade (P < 0.001), T-stage (P < 0.05), N-stage (P < 0.001), surgery (P < 0.05), and chemotherapy (P < 0.001) as independent predictors of CSS. Nomogram of chemotherapy regimens and cycles was also designed by us for the prediction of mGC. Thus, these factors are integrated into the nomogram model: the C-index value was 0.72 (95% CI 0.70–0.85) for the nomogram model and 0.82 (95% CI 0.79–0.89) and 0.73 (95% CI 0.70–0.86) for the internal and external validation cohorts, respectively. Calibration curves and DCA also demonstrated adequate fit and ideal net benefit in prediction and clinical applications. Conclusions We established a practical nomogram to predict CSS in Chinese patients initially diagnosed with mGC. Nomograms can be used to individualize survival predictions and guide clinicians in making therapeutic decisions.

Publisher

Springer Science and Business Media LLC

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3