Individualized assessment of risk and overall survival in patients newly diagnosed with primary osseous spinal neoplasms with synchronous distant metastasis - Tong, Yuexin; Huang, Zhangheng; Jiang, Liming; Pi, Yangwei; Gong, Yan; Zhao, Dongxu (Frontiers in Public Health, 2022)
Background: The prognosis of primary osseous spinal neoplasms (POSNs) patients presented with distant metastases (DM) was still poor. This study aimed to evaluate the independent risk and prognostic factors in this population and then develop two web-based models to predict the probability of DM in patients with POSNs and overall survival (OS) rate of patients with DM. Methods: The data of POSNs patients diagnosed between 2004 and 2017 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistics regression analysis were used to study the risk factors of DM. Based on independent DM-related variable, we developed a diagnostic nomogram to estimate the risk of DM in POSNs patients. Among all POSNs patients, those had synchronous DM were used to constitute the prognostic cohort for investigating the prognostic factors by Cox regress analysis, then, a nomogram incorporating predictors was developed to predict the OS for POSNs patients with DM. Kaplan–Meier (K-M) survival analysis was conducted to study the survival difference. Besides, validation of these nomograms were performed by receiver operating characteristic (ROC) curves, the area under curves (AUC), calibration curves and decision curve analysis (DCA). Results: There were 1345 patients with POSNs included in the study, of which 238 cases (17.70%) had synchronous DM at the initial diagnosis. Kaplan–Meier (K-M) survival analysis and multivariate Cox regression analysis showed that patients with DM had poorer prognosis. Grade, T stage, N stage and histological type were found to be significantly associated with DM in patients with POSNs. And age, surgery and histological type were identified as independent prognostic factors of POSNs patients with DM. Subsequently, two nomogram and their online versions (https://yxyx.shinyapps.io/RiskofDMin/ and https://yxyx.shinyapps.io/SurvivalPOSNs/) were developed. The results of ROC curves, calibration curves, DCA and K-M survival analysis together showed the excellent predictive accuracy and clinical utility of these newly proposed nomograms. Conclusion: We developed two well-validated nomograms to accurately quantify the probability of DM in patients with POSNs and predict the OS rate in patients with DM, which were expected to be useful tool to facilitate individualized clinical management for these patients.