Development and validation of a nomogram to predict the prognosis of patients with gastric cardia cancer

Abstract

Abstract Our goal was to develop a prognostic nomogram to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric cardia cancer (GCC). Patients diagnosed with GCC from 2004 to 2015 were screened from the surveillance, epidemiology, and end results (SEER) database. A nomogram was developed based on the variables associated with OS and CSS using multivariate Cox analysis regression models, which predicted 3- and 5-year OS and CSS. The predictive performance of the nomogram was evaluated using the consistency index (C-index), calibration curve and decision curve analysis (DCA), and the nomogram was calibrated for 3- and 5-year OS and CSS. A total of 7,332 GCC patients were identified and randomized into a training cohort (5,231, 70%) and a validation cohort (2,200, 30%). Multivariate Cox regression analysis showed that marital status, race, SEER stage, grade, T stage, N stage, M stage, tumor size, and surgery were independent risk factors for OS and CSS in GCC patients. Based on the multivariate Cox regression results, we constructed prognostic nomograms of OS and CSS. In the training cohort, the C-index for the OS nomogram was 0.714 (95% CI = 0.705–0.723), and the C-index for the CSS nomogram was 0.759 (95% CI = 0.746–0.772). In the validation cohort, the C-index for the OS nomogram was 0.734 (95% CI = 0.721–0.747), while the C-index for the CSS nomogram was 0.780 (95% CI = 0.759–0.801). Our nomogram has better prediction than the nomogram based on TNM stage. In addition, in the training and external validation cohorts, the calibration curves of the nomogram showed good consistency between the predicted and actual 3- and 5-year OS and CSS rates. The nomogram can effectively predict OS and CSS in GCC patients, which may help clinicians personalize prognostic assessments and clinical decisions.