Development and Validation a nomogram to predict the risk of pulmonary metastasis in pediatric osteosarcoma Article Swipe
Haiping Ouyang
,
Jinkui Wang
,
Zhongliang Wang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-2432677/v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-2432677/v1
Background Most malignant bone tumors in children and adolescents are osteosarcomas. Pediatric osteosarcoma has a high mortality rate due to pulmonary metastasis, which occurs in a short period of time. We would like to establish a nomogram to predict the risk of pulmonary metastasis of pediatric osteosarcoma to help doctors conduct early intervention and and improve their survival rate. Methods The clinicopathological information of patients was downloaded from SEER to identify pediatric osteosarcoma from 2004 to 2018. We analyzed the independent risk factors for pulmonary metastasis of pediatric osteosarcoma in the training cohort using univariate and multivariate logistic regression. Using these risk factors, we established a Nomogram prediction for pulmonary metastasis of pediatric osteosarcoma. We used three indicators to evaluate the accuracy of the nomogram. These three were calibration curve, c-index and area under the receiver operating curve (AUC). The clinical value of this nomogram was evaluated using Decision curve analysis (DCA). Results A sum of 1362 pediatric patients with osteosarcoma were involved in this research. They were randomly divided into the training cohort (N = 965) and the validation cohort (N = 397). In training cohort, univariate and multivariate logistic regression analysis showed that there were four independent risk factors, namely T stage, N stage, surgery, and radiotherapy. We constructed a new Nomogram to predict the risk of pulmonary metastasis in pediatric osteosarcoma. In the training cohorts and validation cohorts, the C-index was 0.699 (95% CI, 0.656–0.741) and 0.736 (95% CI, 0.675–0.797),respectively, indicating that the nomogram had good accuracy. The AUC of training group and validation group showed good predictive ability. Conclusion This study constructed a new nomogram to predict the risk of pulmonary metastasis in pediatric osteosarcoma. Our nomogram can help doctors provide accurate assessment of individual risk, active monitoring and follow-up of patients, and prevent pulmonary metastasis in pediatric osteosarcoma.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-2432677/v1
- https://www.researchsquare.com/article/rs-2432677/latest.pdf
- OA Status
- green
- References
- 35
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4313561084
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4313561084Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-2432677/v1Digital Object Identifier
- Title
-
Development and Validation a nomogram to predict the risk of pulmonary metastasis in pediatric osteosarcomaWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-05Full publication date if available
- Authors
-
Haiping Ouyang, Jinkui Wang, Zhongliang WangList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-2432677/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-2432677/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.researchsquare.com/article/rs-2432677/latest.pdfDirect OA link when available
- Concepts
-
Nomogram, Medicine, Osteosarcoma, Logistic regression, Receiver operating characteristic, Cohort, Univariate, Univariate analysis, Internal medicine, Oncology, Multivariate analysis, Stage (stratigraphy), Metastasis, Multivariate statistics, Cancer, Pathology, Statistics, Mathematics, Biology, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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35Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| publication_date | 2023-01-05 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W4205538905, https://openalex.org/W1988325237, https://openalex.org/W1992018116, https://openalex.org/W2127748864, https://openalex.org/W1954845453, https://openalex.org/W181426613, https://openalex.org/W1648254607, https://openalex.org/W1867002980, https://openalex.org/W1963728338, https://openalex.org/W2095885225, https://openalex.org/W2029788516, https://openalex.org/W2078055837, https://openalex.org/W1967204277, https://openalex.org/W2014516834, https://openalex.org/W2239924772, https://openalex.org/W2015639618, https://openalex.org/W2254989877, https://openalex.org/W1998191384, https://openalex.org/W2011551652, https://openalex.org/W2013239147, https://openalex.org/W2104070754, https://openalex.org/W2141788705, https://openalex.org/W2155196704, https://openalex.org/W2921544782, https://openalex.org/W2168606082, https://openalex.org/W2914447356, https://openalex.org/W1857092002, https://openalex.org/W2100289672, https://openalex.org/W3205919348, https://openalex.org/W2039791295, https://openalex.org/W4246742253, https://openalex.org/W2124074911, https://openalex.org/W2144744111, https://openalex.org/W2107905762, https://openalex.org/W2159889625 |
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