Predicting the Probability of Tumor-Specific Survival in Patients Diagnosed With Primary Tumors in the Spinal Cord Using Nomogram Models Article Swipe
Chao Huang
,
Tingting Tang
,
Zichuan Ding
,
Haoyang Wang
,
Zongke Zhou
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1177/21925682241235894
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1177/21925682241235894
Study Design A retrospective cohort study. Objective The goal of this study was to develop a useful clinical prediction nomogram to accurately predict the cancer-specific survival (CSS) of patients with primary spinal cord tumor (SCT), thereby formulating scientific prevention and aiding clinical decision-making. Methods In this study, patients with SCT diagnoses from the surveillance, epidemiology, and end results (SEER) database (2000-2018) were taken into account. Initially, a nomogram was created using the CSS-associated independent factors that were determined from both univariate and multivariable Cox regression analyses. Furthermore, the nomogram’s capacity for calibration, ability to discriminate, and actual clinical effectiveness were assessed through calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA), respectively. Finally, a strategy for categorizing SCT patients’ risk was developed. Results This study included 909 SCT individuals. A novel nomogram was developed to forecast SCT patients’ CSS, taking into account age, histological type, tumor grade, tumor stage, and radiotherapy. These factors were identified as independent prognostic indicators for CSS in SCT patients. Elderly SCT patients with distant metastasis, advanced tumor grade, received radiotherapy, and confirmed lymphoma have a poor prognosis. Meanwhile, the risk classification system could differentiate SCT patients and realize targeted management. Conclusions The developed nomogram has the ability to accurately forecast the CSS in SCT individuals, aiding in precise decision-making during clinical practice, enhancing health planning, maximizing treatment advantages, and ultimately improving patient prognosis.
Related Topics
Concepts
Medicine
Nomogram
Spinal cord
Primary tumor
Surgery
Oncology
Internal medicine
Cancer
Metastasis
Psychiatry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1177/21925682241235894
- https://journals.sagepub.com/doi/pdf/10.1177/21925682241235894
- OA Status
- gold
- Cited By
- 1
- References
- 25
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392168071
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4392168071Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1177/21925682241235894Digital Object Identifier
- Title
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Predicting the Probability of Tumor-Specific Survival in Patients Diagnosed With Primary Tumors in the Spinal Cord Using Nomogram ModelsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-26Full publication date if available
- Authors
-
Chao Huang, Tingting Tang, Zichuan Ding, Haoyang Wang, Zongke ZhouList of authors in order
- Landing page
-
https://doi.org/10.1177/21925682241235894Publisher landing page
- PDF URL
-
https://journals.sagepub.com/doi/pdf/10.1177/21925682241235894Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://journals.sagepub.com/doi/pdf/10.1177/21925682241235894Direct OA link when available
- Concepts
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Medicine, Nomogram, Spinal cord, Primary tumor, Surgery, Oncology, Internal medicine, Cancer, Metastasis, PsychiatryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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25Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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