{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["13(1)"],"submitter":["Shao Y"],"pubmed_abstract":["At present, no study has established a survival prediction model for non-metastatic primary malignant bone tumors of the spine (PMBS) patients. The clinical features and prognostic limitations of PMBS patients still require further exploration. Data on patients with non-metastatic PBMS from 2004 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate regression analysis using Cox, Best-subset and Lasso regression methods was performed to identify the best combination of independent predictors. Then two nomograms were structured based on these factors for overall survival (OS) and cancer-specific survival (CSS). The accuracy and applicability of the nomograms were assessed by area under the curve (AUC) values, calibration curves and decision curve analysis (DCA). Results: The C-index indicated that the nomograms of OS (C-index 0.753) and CSS (C-index 0.812) had good discriminative power. The calibration curve displays a great match between the model's predictions and actual observations. DCA curves show our models for OS (range: 0.09-0.741) and CSS (range: 0.075-0.580) have clinical value within a specific threshold probability range compared with the two extreme cases. Two nomograms and web-based survival calculators based on established clinical characteristics was developed for OS and CSS. These can provide a reference for clinicians to formulate treatment plans for patients."],"journal":["Scientific reports"],"pagination":["3503"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9977926"],"repository":["biostudies-literature"],"pubmed_title":["Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients."],"pmcid":["PMC9977926"],"pubmed_authors":["Shao Y","Wang Y","Wang Z","Shi X"],"additional_accession":[]},"is_claimable":false,"name":"Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients.","description":"At present, no study has established a survival prediction model for non-metastatic primary malignant bone tumors of the spine (PMBS) patients. The clinical features and prognostic limitations of PMBS patients still require further exploration. Data on patients with non-metastatic PBMS from 2004 to 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Multivariate regression analysis using Cox, Best-subset and Lasso regression methods was performed to identify the best combination of independent predictors. Then two nomograms were structured based on these factors for overall survival (OS) and cancer-specific survival (CSS). The accuracy and applicability of the nomograms were assessed by area under the curve (AUC) values, calibration curves and decision curve analysis (DCA). Results: The C-index indicated that the nomograms of OS (C-index 0.753) and CSS (C-index 0.812) had good discriminative power. The calibration curve displays a great match between the model's predictions and actual observations. DCA curves show our models for OS (range: 0.09-0.741) and CSS (range: 0.075-0.580) have clinical value within a specific threshold probability range compared with the two extreme cases. Two nomograms and web-based survival calculators based on established clinical characteristics was developed for OS and CSS. These can provide a reference for clinicians to formulate treatment plans for patients.","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Mar","modification":"2026-06-20T03:15:49.804Z","creation":"2025-04-19T09:20:46.399Z"},"accession":"S-EPMC9977926","cross_references":{"pubmed":["36859465"],"doi":["10.1038/s41598-023-30509-y"]}}