Original Article
Development and validation of prognostic nomogram for young patients with gastric cancer
Abstract
Background: This study was to establish nomogram models for prognostic evaluation of early-onset gastric cancer (EOGC) in both overall survival (OS) and cancer-specific survival (CSS).
Methods: EOGC patients from 2004 to 2015 were retrieved from the surveillance, epidemiology and end results (SEER) and further randomly assigned to training and validation sets. Univariate and multivariate cox analysis was used to screen out significant variables for construction of nomogram. Nomogram models were assessed by concordance index (C-index), calibration plot, receiver operating characteristics (ROCs) curve and decision curve analysis (DCA).
Results: A total of 549 EOGC were selected in this process. OS nomogram was constructed based on tumor size and tumor site. CSS nomogram was constructed based on tumor size, SEER stage and tumor site. In training set, C-index for the OS nomogram was 0.688 [95% confidence intervals (95% CI): 0.629–0.747], CSS nomogram 0.785 (95% CI: 0.735–0.835). In the external validation, the C-index for the OS nomogram was 0.633 (95% CI: 0.579–0.687), while for the CSS nomogram 0.733 (95% CI: 0.686–0.780). High quality of calibration plots both in OS and OS nomogram models was noticed. Nomograms displayed a comparable result to tumor-node-metastasis (TNM) stage and SEER stage for EOGC based on DCA.
Conclusions: The nomogram models provided an insightful and applicable tool to evaluate the prognosis of EOGC both in OS and CSS.
Methods: EOGC patients from 2004 to 2015 were retrieved from the surveillance, epidemiology and end results (SEER) and further randomly assigned to training and validation sets. Univariate and multivariate cox analysis was used to screen out significant variables for construction of nomogram. Nomogram models were assessed by concordance index (C-index), calibration plot, receiver operating characteristics (ROCs) curve and decision curve analysis (DCA).
Results: A total of 549 EOGC were selected in this process. OS nomogram was constructed based on tumor size and tumor site. CSS nomogram was constructed based on tumor size, SEER stage and tumor site. In training set, C-index for the OS nomogram was 0.688 [95% confidence intervals (95% CI): 0.629–0.747], CSS nomogram 0.785 (95% CI: 0.735–0.835). In the external validation, the C-index for the OS nomogram was 0.633 (95% CI: 0.579–0.687), while for the CSS nomogram 0.733 (95% CI: 0.686–0.780). High quality of calibration plots both in OS and OS nomogram models was noticed. Nomograms displayed a comparable result to tumor-node-metastasis (TNM) stage and SEER stage for EOGC based on DCA.
Conclusions: The nomogram models provided an insightful and applicable tool to evaluate the prognosis of EOGC both in OS and CSS.
