Related Experiment Video
Updated: Jan 26, 2026

Author Spotlight: Advancing Early Detection and Treatment of Gastrointestinal Tumors
Published on: February 16, 2024
Can Systemic Inflammatory Markers Be Used to Predict the Pathological Grade of Meningioma Before Surgery?
Minhua Lin1, Tingting Hu1, Ling Yan2
1Department of Neurosurgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Background:
We sought to determine whether systemic inflammatory markers (SIMs) can be used to predict the pathological grade of meningioma before surgery.
Methods:
Patients with histopathologically proven intracranial meningiomas who had undergone surgery from January 2014 to April 2018 were identified. The 14 most recent SIM levels measured before surgery were retrieved. The Mann-Whitney U test was used to determine the statistically significant differences between groups. Receiver operating characteristic curves were constructed, and the areas under the curve (AUC) were calculated to assess the diagnostic value of each biomarker. Predictive models built with biomarker pairs using logistic regression or support vector machine classifiers were used to assess their combined performance.
Results:
A total of 672 patients with 575 and 97 low-grade and high-grade meningiomas, respectively, were investigated. Of the 14 SIMS, 7 differed significantly between the 2 meningioma groups. However, receiver operating characteristic analysis showed that none of these 7 SIMs alone could predict for the meningioma grade; the highest AUC was 0.61. Two biomarkers (erythrocyte and neutrophil/lymphocyte ratio) were incorporated into the logistic regression model; the corresponding AUC was 0.64. Moreover, 21 biomarker pairs were used to train the support vector machine classifiers; the AUCs of 6 pairs were >0.55; the maximum AUC was 0.60.
Conclusions:
SIMs obtained from routine preoperative laboratory testing had a limited ability to differentiate low- and high-grade meningioma in our cohort of 672 patients. Further prospective, multicenter studies with larger sample sizes are warranted to confirm this finding.
Insights
Systemic inflammatory markers (SIMs) showed limited ability to predict meningioma grade in 672 patients. Further studies are needed to confirm these findings for predicting meningioma pathology.
Area of Science:
- Neurosurgery
- Oncology
- Pathology
Background:
- Meningiomas are the most common primary intracranial tumors.
- Accurate preoperative grading of meningioma is crucial for treatment planning.
Purpose of the Study:
- To evaluate the predictive value of systemic inflammatory markers (SIMs) for differentiating low-grade from high-grade meningiomas before surgery.
- To assess the diagnostic performance of individual SIMs and their combinations.
Main Methods:
- Retrospective analysis of 672 patients with histopathologically confirmed meningiomas.
- Analysis of 14 systemic inflammatory markers measured preoperatively.
- Statistical analysis using Mann-Whitney U test, ROC curves, logistic regression, and support vector machine classifiers.
Main Results:
- Seven of 14 SIMs showed significant differences between low- and high-grade meningiomas.
- No single SIM could reliably predict meningioma grade (highest AUC 0.61).
- Combined biomarkers in logistic regression (AUC 0.64) and SVM models (max AUC 0.60) showed limited predictive performance.
Conclusions:
- Systemic inflammatory markers have limited utility in predicting meningioma grade preoperatively.
- Larger, prospective, multicenter studies are required to validate these findings.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
Related Concept Videos
Graded Potential
Graded potentials fall into two categories: depolarizing and hyperpolarizing. Depolarizing graded potentials typically occur when sodium (Na+) or...
Predicting Molecular Geometry
Types of Aggregate Grading
Well-graded aggregates include a complete range of necessary size fractions that fit together to create a dense matrix with minimal voids, represented by a smooth, continuous gradation curve. This type of grading ensures good...
Inflammatory Response
Inflammation can be triggered by various stimuli, such as impact, abrasion, chemical irritation, infections, and extreme hot or cold temperatures. These can damage cells and connective tissue fibers,...
Inflammatory Response II: Inflammatory Exudate and Tissue Repair
The typical wound exudate is odorless, transparent, straw-colored, thin, and watery. Exudate, however, can differ depending on the state of wound healing. Likewise, the...
Sieve Analysis and Grading Curves