SynthesisFrontiers in immunology2025
Limitations of nomogram models in predicting survival outcomes for glioma patients.
Synthesis in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Prediction Models for Postoperative Delirium Among Cancer Patients: A Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- The specific linear or curved boundaries between WHO grade II-III insular gliomas and the basal ganglia indicate distinct biological features, survival outcomes, and surgical strategies: evidence from 330 cases.NeuroImage. Clinical · 2026Article
- Prediction of risk factors for postpartum stress urinary incontinence based on pelvic floor ultrasound combined with clinical information.SAGE open medicine · 2026Article
- Development and validation of nomograms to predict brain metastasis-free survival in lung and breast cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Development and Validation of a Prognostic Model for Lung Cancer Based on Machine Learning and Immune Microenvironment Analysis.Journal of cellular and molecular medicine · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: 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. Design: 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 step-by-step guide for developing and evaluating nomograms. Results: 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. Conclusion: 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.