A Predictive Nomogram for Early Death of Metastatic Gastric Cancer: A Retrospective Study in the SEER Database and China.

Abstract:

:Background: To identify associated risk factors and develop a predictive nomogram for the early death of metastatic gastric cancer patients. Methods: A total of 4575 patients in the SEER cohort and 220 patients in the Chinese cohort diagnosed with metastatic gastric cancer in our Cancer Center were obtained. Univariate and multivariate logistic regression models were used to identify independent risk variables for early death. A predictive nomogram and a web-based probability calculator were developed and then validated by receiver operating characteristics (ROCs) curve and calibration plot in a Chinese cohort. Results: Eight independent variables, including race, grade, surgery, chemotherapy, and metastases of bone, brain, liver, lung were recognized by using univariate and multivariate logistic regression models for identifying independent risk variables of early death about metastatic gastric cancer patients. By comprising these variables, a predictive nomogram and a web-based probability calculator were constructed in the SEER cohort. Then, it could be validated well in the Chinese cohort by receiver operating characteristics (ROCs) curve and calibration plot. Conclusion: Using this nomogram model provided an insightful and applicable tool to distinguish the early death of metastatic gastric cancer patients.

journal_name

J Cancer

journal_title

Journal of Cancer

authors

Zhu Y,Fang X,Wang L,Zhang T,Yu D

doi

10.7150/jca.46563

subject

Has Abstract

pub_date

2020-07-14 00:00:00

pages

5527-5535

issue

18

issn

1837-9664

pii

jcav11p5527

journal_volume

11

pub_type

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