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Construction and validation a Nomogram for Predicting Cancer-Specific Survival for patients with Ependymoma: An Analysis of the Surveillance, Epidemiology, and End Results Database
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  • Zhizheng Liu,
  • Kang Chen,
  • Zhenyan Shi,
  • Yun Chen,
  • Zhigao Tong,
  • Xuanyong Yang
Zhizheng Liu
Zhujiang Hospital

Corresponding Author:liuzhizheng1996@126.com

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Kang Chen
First Affiliated Hospital of Nanchang University Department of Neurosurgery
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Zhenyan Shi
First Affiliated Hospital of Nanchang University
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Yun Chen
First Affiliated Hospital of Nanchang University
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Zhigao Tong
First Affiliated Hospital of Nanchang University
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Xuanyong Yang
First Affiliated Hospital of Nanchang University
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Abstract

Background: Despite ongoing debate about reliable prognostic factors, this study aimed to develop and validate a novel nomogram for predicting cancer-specific survival (CSS) in patients with ependymoma. Methods: Clinical data from the Surveillance, Epidemiology, and End Results database spanning 2000 to 2018 were used for the analysis. Data were randomly categorized into development and validation groups in a 7:3 ratio. Univariate and multivariate Cox regression analyses and LASSO regression were conducted to identify independent risk factors for CSS. Predictive models were evaluated using calibration plots,  concordance index (C-index),  and area under the receiver operating characteristic curve (AUC). Additionally, decision curve analysis and clinical impact curves were conducted. Results: The final sample comprised 2,340 patients. Multivariate analysis identified race, age, histological type, surgery, and tumor site as independent predictors of CSS. A nomogram incorporating these risk factors was developed to predict CSS  in patients with ependymomas. Calibration plots demonstrated a high level of consistency between predicted and actual values. The C-index for the training cohort was 0.746 (95% CI: 0.715–0.777), and for the validation cohort, it was 0.743 (95% CI: 0.698–0.788). Additionally, both AUC and decision curve analysis analyses indicated robust performance and clinical significance benefits. Kaplan–Meier curves further demonstrated the nomogram’s strong ability to predict patient outcomes. Conclusions: Our nomogram has the potential to offer significant value in predicting the outcomes of patients with ependymomas aged > 1, 5, and 8 years. This predictive model will assist doctors and patients in devising effective clinical strategies.
Submitted to Cancer Reports
06 Jun 2024Submission Checks Completed
06 Jun 2024Assigned to Editor
06 Jun 2024Review(s) Completed, Editorial Evaluation Pending
14 Jun 2024Reviewer(s) Assigned
02 Sep 2024Editorial Decision: Revise Major
19 Sep 20241st Revision Received
30 Sep 2024Assigned to Editor
30 Sep 2024Submission Checks Completed
30 Sep 2024Review(s) Completed, Editorial Evaluation Pending
30 Sep 2024Reviewer(s) Assigned