Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study

Background Gastric signet ring cell carcinoma (GSRCC) is a rare disease associated with poor prognosis. A prognostic nomogram was developed and validated in this study to assess GSRCC patients' overall survival (OS). Methods Patients diagnosed with GSRCC from the Surveillance, Epidemiology, and End Results (SEER) database (2004-2016) and the First Hospital of China Medical University (CMU1h) were enrolled in this retrospective cohort study. Univariate and multivariate COX analysis was used to determine independent prognostic factors to construct the prognostic nomogram. Predictions were evaluated by the C-index and calibration curve. In addition, the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and Kaplan-Meier analysis were employed to assess the clinical utility of the survival prediction model. Results Patients were classified into two cohorts. We randomly divided patients in the SEER database and CMU1h cohort into a training group (n=3068, 80%) and a validation group (n=764, 20%). Age, race, T stage, N stage, M stage, therapy, and tumor size were significantly associated with the prognosis of GSRCC patients. On this basis, a nomogram was constructed, with a C-index in the training and the validation cohorts at 0.772 (95% CI: 0.762-0.782) and 0.774 (95% CI: 0.752-0.796), respectively. The accuracy of the generated nomogram was verified through calibration plots. Similarly, compared with the traditional AJCC staging system, the results of the area under curve (AUC) calculated by ROC, DCA, and Kaplan-Meier curves, demonstrated a good predictive value of the constructed nomogram, compared to the traditional AJCC staging system. Conclusion In the present study, seven independent prognostic factors of GSRCC were screened out. The established nomogram models based on seven variables provided a visualization of each prognostic factor's risk and assisted clinicians in predicting the 1-, 3-, and 5-year OS of GSRCC.

Automated summary

This study identified seven independent prognostic factors of GSRCC and established corresponding nomogram models to help clinicians predict survival, showing good predictive value in comparison to the traditional AJCC staging system.