Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcoma
Abstract The present work aimed to establish a new model to accurately estimate overall survival (OS) as well as cancer-specific survival (CSS) of osteosarcoma. Osteosarcoma cases were collected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2017 and randomized...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-06-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-37391-8 |
| _version_ | 1797795692553437184 |
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| author | Yali Yu Shaohua Wang Jia Liu Jiejie Ge Hongya Guan |
| author_facet | Yali Yu Shaohua Wang Jia Liu Jiejie Ge Hongya Guan |
| author_sort | Yali Yu |
| collection | DOAJ |
| description | Abstract The present work aimed to establish a new model to accurately estimate overall survival (OS) as well as cancer-specific survival (CSS) of osteosarcoma. Osteosarcoma cases were collected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2017 and randomized as training or validation sets. Then, the OS- and CSS-related variables were discovered through multivariate Cox regression analysis to develop new nomograms to predict the 1-, 3- and 5-year OS and CSS. Besides, consistency index (C-index), decision curve analysis (DCA), along with calibration curve were adopted for assessing the predicting ability of our constructed nomograms after calibrating for 1-, 3- and 5-year OS and CSS. Altogether, 1727 osteosarcoma cases were enrolled in the present study and randomly divided as training (n = 1149, 70%) or validation (n = 576, 30%) set. As shown by univariate as well as multivariate Cox regression analyses, age, grade, T stage, M stage, surgery, chemotherapy, and histological type were identified to be the adverse factors to independently predict OS and CSS among the osteosarcoma cases. Besides, based on results of multivariate Cox regression analysis, we constructed the OS and CSS prediction nomograms. The C-index in training set was 0.806 (95% CI 0.769–0.836) for OS nomogram and 0.807 (95% CI 0.769–0.836) for CSS nomogram. In the meantime, C-index value in validation set was 0.818 (95% CI 0.789–0.847) for OS nomogram, while 0.804 (95% CI 0.773–0.835) for CSS nomogram. Besides, those calibration curves regarding the 3- and 5-year CSS of our constructed nomogram were highly consistent between the predicted values and the measurements in the training set as well as the external validation set. Our constructed nomogram outperformed the TNM stage in prediction. Our constructed nomogram is facile, creditable, and feasible; it efficiently predicts OS and CSS for osteosarcoma cases and can assist clinicians in assessing the prognosis for individuals and making decisions. |
| first_indexed | 2024-03-13T03:21:51Z |
| format | Article |
| id | doaj.art-172d87a5aa864565aecf1f7155bef2c9 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-13T03:21:51Z |
| publishDate | 2023-06-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-172d87a5aa864565aecf1f7155bef2c92023-06-25T11:15:28ZengNature PortfolioScientific Reports2045-23222023-06-0113111110.1038/s41598-023-37391-8Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcomaYali Yu0Shaohua Wang1Jia Liu2Jiejie Ge3Hongya Guan4Department of Clinical Laboratory, Zhengzhou Orthopaedics HospitalDepartment of Joint Surgery, Zhengzhou Orthopaedics HospitalDepartment of Translational Medicine Center, Zhengzhou Central Hospital Affiliated to Zhengzhou UniversityDepartment of Clinical Laboratory, Zhengzhou Central Hospital Affiliated to Zhengzhou UniversityDepartment of Translational Medicine Center, Zhengzhou Central Hospital Affiliated to Zhengzhou UniversityAbstract The present work aimed to establish a new model to accurately estimate overall survival (OS) as well as cancer-specific survival (CSS) of osteosarcoma. Osteosarcoma cases were collected from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2017 and randomized as training or validation sets. Then, the OS- and CSS-related variables were discovered through multivariate Cox regression analysis to develop new nomograms to predict the 1-, 3- and 5-year OS and CSS. Besides, consistency index (C-index), decision curve analysis (DCA), along with calibration curve were adopted for assessing the predicting ability of our constructed nomograms after calibrating for 1-, 3- and 5-year OS and CSS. Altogether, 1727 osteosarcoma cases were enrolled in the present study and randomly divided as training (n = 1149, 70%) or validation (n = 576, 30%) set. As shown by univariate as well as multivariate Cox regression analyses, age, grade, T stage, M stage, surgery, chemotherapy, and histological type were identified to be the adverse factors to independently predict OS and CSS among the osteosarcoma cases. Besides, based on results of multivariate Cox regression analysis, we constructed the OS and CSS prediction nomograms. The C-index in training set was 0.806 (95% CI 0.769–0.836) for OS nomogram and 0.807 (95% CI 0.769–0.836) for CSS nomogram. In the meantime, C-index value in validation set was 0.818 (95% CI 0.789–0.847) for OS nomogram, while 0.804 (95% CI 0.773–0.835) for CSS nomogram. Besides, those calibration curves regarding the 3- and 5-year CSS of our constructed nomogram were highly consistent between the predicted values and the measurements in the training set as well as the external validation set. Our constructed nomogram outperformed the TNM stage in prediction. Our constructed nomogram is facile, creditable, and feasible; it efficiently predicts OS and CSS for osteosarcoma cases and can assist clinicians in assessing the prognosis for individuals and making decisions.https://doi.org/10.1038/s41598-023-37391-8 |
| spellingShingle | Yali Yu Shaohua Wang Jia Liu Jiejie Ge Hongya Guan Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcoma Scientific Reports |
| title | Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcoma |
| title_full | Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcoma |
| title_fullStr | Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcoma |
| title_full_unstemmed | Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcoma |
| title_short | Development and validation of a nomogram to predict long-term cancer-specific survival for patients with osteosarcoma |
| title_sort | development and validation of a nomogram to predict long term cancer specific survival for patients with osteosarcoma |
| url | https://doi.org/10.1038/s41598-023-37391-8 |
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