BACKGROUND: The aim of this study was to construct a nomogram to predict the survival of patients with metastatic Siewert Type II adenocarcinomas of the esophagogastric junction (AEG). METHODS: Patients were identified using the Surveillance, Epidemiology, and End Results (SEER) database. Cox regression analysis was performed to assess the prognostic factors. A nomogram comprising independent prognostic factors was established and evaluated using C-indexes, calibration curves, and decision curve analyses. RESULTS: In total 1616 eligible patients were enrolled. Race, age, bone metastasis, liver metastasis, lung metastasis, other metastasis sites, and distant lymph nodes metastasis were independent prognostic factors and were integrated to construct the nomogram. The nomogram had a C-index of 0.590 (95% CI: 0.569-0.611) in the training cohort and 0.569 (95% CI: 0.532-0.606) in the validation cohort. The calibration plots for the probabilities of 6-month and 1-year overall survival demonstrated there was an optimum between nomogram prediction and actual observation. CONCLUSION: We developed and validated a nomogram to predict individual prognosis for patients with metastatic Siewert Type II AEG, and the risk stratification system based on the nomogram could effectively stratify the patients into two risk subgroups, which can help clinicians accurately predict mortality risk and recommend personalized treatment modalities.
BACKGROUND: The aim of this study was to construct a nomogram to predict the survival of patients with metastatic Siewert Type II adenocarcinomas of the esophagogastric junction (AEG). METHODS:Patients were identified using the Surveillance, Epidemiology, and End Results (SEER) database. Cox regression analysis was performed to assess the prognostic factors. A nomogram comprising independent prognostic factors was established and evaluated using C-indexes, calibration curves, and decision curve analyses. RESULTS: In total 1616 eligible patients were enrolled. Race, age, bone metastasis, liver metastasis, lung metastasis, other metastasis sites, and distant lymph nodes metastasis were independent prognostic factors and were integrated to construct the nomogram. The nomogram had a C-index of 0.590 (95% CI: 0.569-0.611) in the training cohort and 0.569 (95% CI: 0.532-0.606) in the validation cohort. The calibration plots for the probabilities of 6-month and 1-year overall survival demonstrated there was an optimum between nomogram prediction and actual observation. CONCLUSION: We developed and validated a nomogram to predict individual prognosis for patients with metastatic Siewert Type II AEG, and the risk stratification system based on the nomogram could effectively stratify the patients into two risk subgroups, which can help clinicians accurately predict mortality risk and recommend personalized treatment modalities.