Two novel clinical tools to predict the risk of bone metastasis and overall survival in esophageal cancer patients: a large population-based retrospective cohort study.

Background: The aim of this study was to construct two web-based nomograms to predict the probability of bone metastasis (BM) in esophageal cancer (EC) patients and the prognostic of EC patients with BM (ECBM).
Methods: We collected the data of EC and ECBM patients in the Surveillance, Epidemiology and End Results (SEER) database from 2010 to 2015. Independent risk variables for the development of BM in EC patients were identified using univariate and multivariate logistic regression analyses. Univariate and multivariate Cox regression analyses were used to assess independent prognostic variables in ECBM patients. And then, constructed two nomograms to predict the risk of bone metastases and overall survival (OS) of ECBM patients. Survival differences were studied by Kaplan-Meier (K-M) survival analysis. The predictive efficacy and clinical applicability of these two nomograms were assessed by using receiver operating characteristic (ROC) curve, the area under curve (AUC), calibration curve and decision curve analysis (DCA).
Results: We selected a total of 6839 patients with EC, of which 326 (4.77%) had BM at the time of initial diagnosis. The results of K-M survival and Cox regression analysis showed significant effects of BM on the OS in EC patients. Age, N stage, tumor size and brain/liver/lung organ metastasis were identified as BM-related risk variables. Chemotherapy and brain/liver organ metastasis were identified as ECBM-related prognostic variables. The ROC, AUC, calibration curves and DCA of two nomograms all showed excellent predictive efficacy and clinical applicability.
Conclusions: These two nomograms were constructed and validated, which could objectively predict the risk of BM in EC patients and the prognostic in ECBM patients. These tools are expected to make valuable contributions in clinical work, informing surgeons in making decisions about patient care.
(© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)