Development and Validation of Prognostic Nomograms Based on Lymph Node Ratio for Young Patients with Gastric Cancer: A SEER-Based Study
| Autor: | Yi-Ru Chen MD, Zhen-Yi Tian MD, Mei-Qian Wang MD, Mei-Ling Sun MD, Jin-Zhen Wu MM, Xin-Ying Wang PhD |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Technology in Cancer Research & Treatment, Vol 22 (2023) |
| Druh dokumentu: | article |
| ISSN: | 1533-0338 15330338 |
| DOI: | 10.1177/15330338231157923 |
| Popis: | Purpose To investigate the role of lymph node ratio (LNR) in young patients with gastric cancer (GC) and develop nomograms to predict the survival of young GC patients. Methods This retrospective study enrolled stage I-III GC patients before the age of 40 between 2010 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database. Cox proportional hazards models were used to determine the prognosticators and create the nomograms incorporating LNR to predict overall survival (OS) and cancer-specific survival (CSS). The discriminating superiority of the nomograms was examined using calibration curves, C-index, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and integrated discrimination improvement (IDI) by comparing with the TNM staging. The performance of the nomograms for risk stratification was analyzed by the Kaplan–Meier method. Results Based on the significant prognosticators identified in multivariate survival analysis, the nomograms were established and showed LNR as the third strongest predictor. The C-index of the nomograms for OS and CSS were higher than those of the TNM staging (OS: 0.773 vs 0.665; CSS: 0.769 vs 0.666). The ROC curves for the nomograms to predict survival exhibited superior sensitivity and specificity when compared with the TNM staging. The calibration plots, DCA curves, and IDI values of the nomograms also demonstrated adequate fit and ideal net benefit in prediction and clinical utility. The Kaplan–Meier analysis observed remarkable differences in patients divided into different risk subgroups ( P |
| Databáze: | Directory of Open Access Journals |
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