Peripheral Inflammatory Blood Markers in Diagnosis of Glioma and IDH Status

外周血炎症标志物在胶质瘤诊断和IDH状态中的应用

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Abstract

Objective  Gliomas are the most common intracranial tumors. Histopathology and neuroimaging are the main modalities used for diagnosis and treatment response monitoring. However, both are expensive and insensitive methods and can cause neurological deterioration. This study aimed to develop a minimally invasive peripheral inflammatory biomarker for diagnosis of glioma, its grade, and isocitrate dehydrogenase (IDH) status. Materials and Methods  Patients undergoing surgery for glioma, acoustic neuroma, and meningioma between January 2019 and December 2019 were included. Preoperative neutrophil/lymphocyte ratio (NLR), derived NLR (dNLR), platelet/lymphocyte ratio (PLR), lymphocyte/monocyte ratio (LMR), eosinophil/lymphocyte ratio (ELR), and prognostic nutritional index (PNI) were calculated. Histopathology and immunohistochemistry (IHC) staining were done postoperatively. Results  A total of 154 patients of glioma, 36 patients of acoustic neuroma, 58 patients of meningioma, and 107 healthy controls were included. dNLR showed the maximum area under the curve (AUC) (0.656639) for diagnosis of glioma from other tumors and among combinations. dNLR +NLR showed the maximum AUC (0.647865). Maximum AUC for glioblastoma multiforme (GBM) versus other grades and among combinations was shown by NLR (0.83926). NLR + dNLR had the maximum AUC (0.764794). NLR showed significant p value in differentiating IDH wild from IDH mutant GBM. Conclusion  dNLR has the maximum diagnostic value in diagnosing glioma from other tumors. NLR (AUC = 0.83926) showed the highest accuracy for GBM diagnosis and may be a parameter in predicting the grade of glioma; also, it has maximum diagnostic value in differentiating IDH wild GBM from IDH mutant GBM. These peripheral inflammatory parameters may prove to be sensitive and cost-effective markers for glioma diagnosis, predicting grade of glioma, monitoring of treatment response, and in predicting recurrence.

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