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Pan-cancer analysis of prognostic metastatic phenotypes

Pan-cancer analysis of prognostic metastatic phenotypes

Authors :
Nicholas G. Zaorsky
Amar U. Kishan
Ming Wang
Timothy N. Showalter
Daniel M. Trifiletti
J.T. Yang
Vernon M. Chinchilli
David J. DeGraff
Eric J. Lehrer
Henry S. Park
Xi Wang
Christine Lin
Sara M Garrett
Daniel E. Spratt
Source :
Int J Cancer
Publication Year :
2021

Abstract

Although cancer is highly heterogeneous, all metastatic cancer is considered American Joint Committee on Cancer (AJCC) Stage IV disease. The purpose of this project was to redefine staging of metastatic cancer. Internal validation of nationally representative patient data from the National Cancer Database (n = 461 357; 2010-2013), and external validation using the Surveillance, Epidemiology and End Results database (n = 106 595; 2014-2015) were assessed using the concordance index for evaluation of survival prediction. A Cox proportional hazards model was used for overall survival by considering identified phenotypes (latent classes) and other confounding variables. Latent class analysis was performed for phenotype identification, where Bayesian information criterion (BIC) and sample-size-adjusted BIC were used to select the optimal number of distinct clusters. Kappa coefficients assessed external cluster validation. Latent class analysis identified five metastatic phenotypes with differences in overall survival (P

Details

ISSN :
10970215
Volume :
150
Issue :
1
Database :
OpenAIRE
Journal :
International journal of cancer
Accession number :
edsair.doi.dedup.....0fb27b303ad80a6952ec0dff3cf28f2b