Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients
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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-03-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-30509-y |
| _version_ | 1797864778627022848 |
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| author | Yiming Shao Zhonghao Wang Xiaoya Shi Yexin Wang |
| author_facet | Yiming Shao Zhonghao Wang Xiaoya Shi Yexin Wang |
| author_sort | Yiming Shao |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-09T22:57:46Z |
| format | Article |
| id | doaj.art-d824dfe838ce418eb8db527b6264d844 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-09T22:57:46Z |
| publishDate | 2023-03-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-d824dfe838ce418eb8db527b6264d8442023-03-22T11:11:40ZengNature PortfolioScientific Reports2045-23222023-03-011311910.1038/s41598-023-30509-yDevelopment and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patientsYiming Shao0Zhonghao Wang1Xiaoya Shi2Yexin Wang3Department of Clinical Medicine, Jining Medical UniversityDepartment of Clinical Medicine, Jining Medical UniversityDepartment of Oncology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and TechnologyDepartment of Spine Surgery, Affiliated Hospital of Jining Medical UniversityAbstract 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.https://doi.org/10.1038/s41598-023-30509-y |
| spellingShingle | Yiming Shao Zhonghao Wang Xiaoya Shi Yexin Wang Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients Scientific Reports |
| title | Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients |
| title_full | Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients |
| title_fullStr | Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients |
| title_full_unstemmed | Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients |
| title_short | Development and validation of nomograms predicting overall and cancer-specific survival for non-metastatic primary malignant bone tumor of spine patients |
| title_sort | development and validation of nomograms predicting overall and cancer specific survival for non metastatic primary malignant bone tumor of spine patients |
| url | https://doi.org/10.1038/s41598-023-30509-y |
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