Can Systemic Inflammatory Markers Be Used to Predict the Pathological Grade of Meningioma Before Surgery?

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.