ArticleFrontiers in neurology2022
A Multielement Prognostic Nomogram Based on a Peripheral Blood Test, Conventional MRI and Clinical Factors for Glioblastoma.
Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed, 11 citations in OpenAlex.
- Diagnostic lncRNA biomarkers and immune-related ceRNA networks for osteonecrosis of the femoral head in metabolic syndrome identified by plasma RNA sequencing and machine learning.Frontiers in immunology · 2025Article
- Blood-Based Prognostic Prediction Model for Glioblastoma: Construction and Validation.Cancer management and research · 2025Article
- Article
- Prognostic nomogram model based on quantitative metrics of subregions surrounding residual cavity in glioblastoma patients.Journal of cancer research and clinical oncology · 2024Article
- Article
- Review
- The diagnostic value of neutrophil to lymphocyte ratio, albumin to fibrinogen ratio, and lymphocyte to monocyte ratio in Parkinson's disease: a retrospective study.Frontiers in neurology · 2024Article
- Identification of immune-associated genes in diagnosing osteoarthritis with metabolic syndrome by integrated bioinformatics analysis and machine learning.Frontiers in immunology · 2023Article
- The role of angiogenic growth factors in the immune microenvironment of glioma.Frontiers in oncology · 2023Review
- The Prognostic Value of Preoperative Inflammatory Markers for Pathological Grading of Glioma Patients.Technology in cancer research & treatmentArticle
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9 authors at 2 institutions in 1 country.
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Abstract
backgroundGlioblastoma (GBM) is one of the most malignant types of tumors in the central nervous system, and the 5-year survival remains low. Several studies have shown that preoperative peripheral blood tests and preoperative conventional Magnetic Resonance Imaging (MRI) examinations affect the prognosis of GBM patients. Therefore, it is necessary to construct a risk score based on a preoperative peripheral blood test and conventional MRI and develop a multielement prognostic nomogram for GBM.
methodsThis study retrospectively analyzed 131 GBM patients. Determination of the association between peripheral blood test variables and conventional MRI variables and prognosis was performed by univariate Cox regression. The nomogram model, which was internally validated using a cohort of 56 GBM patients, was constructed by multivariate Cox regression. RNA sequencing data from Gene Expression Omnibus (GEO) and Chinese Glioma Genome Atlas (CGGA datasets were used to determine peripheral blood test-related genes based on GBM prognosis.
resultsThe constructed risk score included the neutrophil/lymphocyte ratio (NLR), lymphocyte/monocyte ratio (LMR), albumin/fibrinogen (AFR), platelet/lymphocyte ratio (PLR), and center point-to-ventricle distance (CPVD). A final nomogram was developed using factors associated with prognosis, including age, sex, the extent of tumor resection, IDH mutation status, radiotherapy status, chemotherapy status, and risk. The Area Under Curve (AUC) values of the receiver operating characteristic curve (ROC) curve were 0.876 (12-month ROC), 0.834 (24-month ROC) and 0.803 (36-month ROC) in the training set and 0.906 (12-month ROC), 0.800 (18-month ROC) and 0.776 (24-month ROC) in the validation set. In addition, vascular endothelial growth factor A (VEGFA) was closely associated with NLR and LMR and identified as the most central negative gene related to the immune microenvironment and influencing immune activities.
conclusionThe risk score was established as an independent predictor of GBM prognosis, and the nomogram model exhibit appropriate predictive power. In addition, VEGFA is the key peripheral blood test-related gene that is significantly associated with poor prognosis.
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