Development and validation of a Surveillance, Epidemiology, and End Results (SEER)-based prognostic nomogram for predicting survival in gastric cancer with multi-organ metastases

Abstract

Background Nomogram can be used to accurately predict the prognosis of patients and guide treatment according to the individual situation of patients. This study is to investigate the independent prognostic factors for multi-organ metastases in gastric cancer (GC) patients, and construct and validate prognostic nomograms for overall survival (OS) and cancer-specific survival (CSS). Methods The clinical data of GC patients with multi-organ metastases from 2010 to 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. The independent prognostic factors affecting the OS and CSS of the patients were screened using univariate and multivariate Cox’s proportional hazards model and the Fine-Gray competing risk model. Corresponding nomogram models were constructed to predict the OS and CSS of the patients. The reliability and accuracy of the prediction model were evaluated by consistency index (C-index), area under receiver operating characteristic (ROC) curve (AUC) and calibration curve. Results A total of 1,386 patients were included and randomly divided into a training group (972 cases) and a validation group (414 cases) in a 7:3 ratio. Cox proportional hazards analysis showed that age [P<0.001, hazard ratio (HR) =1.29 (1.11–1.49)], race (P=0.018, HR =0.79 (0.65–0.96)], metastases [P=0.036, HR =1.96 (1.05–3.67)], tumor size [P=0.045, HR =1.35 (1.01–1.82)], degree of differentiation [P=0.002, HR =1.99 (1.30–3.06)] and metastasis surgery (P=0.005, HR =0.52 (0.33–0.82)] were independent prognostic factors for OS in GC patients with multi-organ metastases. The Fine-Gray competing risk analysis showed that age [P=0.006, HR =1.23 (1.06–1.42)], histological type [P=0.037, HR =1.53 (1.03–2.27)], metastases [P=0.009, HR =2.02 (1.19–3.41)], tumor size [P=0.028, HR =1.33 (1.03–1.70)], degree of differentiation [P=0.009, HR =1.65 (1.13–2.40)] and metastasis surgery [P=0.001, HR =0.50 (0.32–0.76)] were independent prognostic factors for CSS in GC patients with multi-organ metastases. The above factors were used to construct nomogram models for predicting OS and CSS. Both C-index and AUC of the training group and the validation group showed that the models had an acceptable predictive performance. The calibration curve showed that the predicted and ideal curves fit well, indicating that the constructed models were well-calibrated. Conclusions Using data from the SEER database, this study established and validated nomogram models for OS and CSS in GC patients with multi-organ metastases, to help clinicians formulate accurate and individualized treatment plans.

Artificial intelligence annotated clinical-pathologic risk model to predict outcomes of advanced gastric cancer

“…Although several studies had proposed their nomograms for evaluation of prognosis in metastatic GC, they only focused on patients with liver metastases, or multi-organ metastases, or metachronous metastases, or palliative gastrectomy, which was different from our study (32)(33)(34)(35). Furthermore, these studies only provided prognostic models, and lacked in-depth exploration of treatment options for advanced GC.…”