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SYSTEMATIC REVIEW article
Front. Immunol.
Sec. Cancer Immunity and Immunotherapy
Volume 16 - 2025 | doi: 10.3389/fimmu.2025.1547506
Limitations of Nomogram Models in Predicting Survival Outcomes for Glioma Patients
Provisionally accepted- 1 Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China
- 2 Department of Urology or Nursing, Dazhou First People's Hospital, Dazhou, China
- 3 College of Nursing, Chongqing Medical University, Chongqing, China
- 4 Academician (Expert) Workstation of Sichuan Province, Luzhou, 646000, China, Luzhou, China
- 5 Neurological Diseases and Brain Function Laboratory, Luzhou, 646000, Sichuan Province, China., Luzhou, China
Glioma represents a prevalent and malignant tumor of the central nervous system (CNS), and it is essential to accurately predict the survival of glioma patients to optimize their subsequent treatment plans.This review outlines the most recent advancements and viewpoints regarding the application of nomograms in glioma prognosis research.With an emphasis on the precision and external applicability of predictive models, we carried out a comprehensive review of the literature on the application of nomograms in glioma and provided a stepby-step guide for developing and evaluating nomograms.A summary of thirty-nine articles was produced. The majority of nomogram-building research has used limited patient samples, disregarded the proportional hazards (PH) assumption in Cox regression models, and some of them have failed to incorporate external validation. Furthermore, the predictive capability of nomograms is influenced by the selection of incorporated risk factors. Overall, the current predictive accuracy of nomograms is moderately credible.The development and validation of nomogram models ought to adhere to a standardized set of criteria, thereby augmenting their worth in clinical decision-making and clinician-patient communication. Prior to the clinical application of a nomogram, it is imperative to thoroughly scrutinize its statistical foundation, rigorously evaluate its accuracy, and, whenever feasible, assess its external applicability utilizing multicenter databases.
Keywords: Glioma, nomogram, proportional hazards (PH) assumption, cox regression model, prediction
Received: 18 Dec 2024; Accepted: 28 Feb 2025.
Copyright: © 2025 Xue, Liu, Yin, Chen and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ligang Chen, Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China
Ming Wang, Department of Neurosurgery, The Affiliated Hospital of Southwest Medical University, Luzhou, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.