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The Prognostic Value of a Nomogram Model Based on Tumor Immune Markers and Clinical Factors for Adult Primary Glioma

  • 0Department of Radiation Oncology, The Fourth Hospital of Hebei Medical University, 12 Jiankang Road, Shijiazhuang 050011, China.
Cancers +

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September 27, 2025

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September 27, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

A new nomogram model predicts survival in adult glioma patients using age, WHO grade, treatment, and tumor markers like ATRX and IDH1. This tool offers a practical alternative to molecular testing for forecasting overall survival (OS).

Area Of Science

  • Neuro-oncology
  • Medical Statistics
  • Biomarker Research

Background

  • Primary gliomas are aggressive brain tumors with variable prognoses.
  • Accurate prediction of overall survival (OS) is crucial for guiding treatment decisions in adult glioma patients.

Purpose Of The Study

  • To identify independent prognostic factors for OS in adult primary glioma patients.
  • To develop and validate a nomogram prediction model for OS.
  • To evaluate the clinical utility of the nomogram.

Main Methods

  • Retrospective collection of clinical data from 257 adult glioma patients.
  • Multivariate Cox regression analysis to identify prognostic factors.
  • Construction and validation of a nomogram using internal and external datasets (CGGA).

Main Results

  • Identified age, Karnofsky Performance Status (KPS), tumor diameter, WHO grade, radiotherapy, chemotherapy, and expression of ATRX, IDH1, and Ki-67 as independent prognostic factors.
  • The developed nomogram demonstrated excellent discrimination and calibration for predicting 1-, 2-, and 3-year survival rates.
  • The model showed strong predictive performance in both internal and external validation cohorts.

Conclusions

  • A nomogram integrating clinical, treatment, and molecular markers (ATRX, IDH1, Ki-67) effectively predicts survival in adult glioma patients.
  • This nomogram serves as a practical and potentially more accessible alternative to extensive molecular testing for prognostic assessment.
  • The findings support the use of this nomogram for improved patient management and clinical trial stratification.

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