A Clinical Prognostic Model Based on Preoperative Hematological and Clinical Parameters Predicts the Progression of Primary WHO Grade II Meningioma

Abstract

PurposeThe purpose was to explore the correlation between hematological parameters and the progression of WHO grade II meningioma, and establish a clinical prognostic model based on hematological parameters and clinical prognostic factors to predict the progression-free survival (PFS) of patients.MethodsA total of 274 patients with WHO grade II meningiomas were included. Patients were randomly divided into a training cohort (192, 70%) and a test cohort (82, 30%). In the training cohort, the least absolute shrinkage and selection operator Cox regression analysis were used to screen for hematological parameters with prognostic value, and the hematological risk model (HRM) was constructed based on these parameters; univariate and multivariate Cox regression analyses were utilized to screen for clinical prognostic factors, and a clinical prognostic model was constructed based on clinical prognostic factors and HRM. The prognostic stability and accuracy of the HRM and clinical prognostic model were verified in the test cohort. Subgroup analysis was performed according to the patients’ different clinical characteristics.ResultsPreoperative neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, albumin-to-globulin ratio, D-dimer, fibrinogen, and lactate dehydrogenase were associated with the PFS of patients. The areas under curve of the HRM were 0.773 (95% confidence interval [CI] 0.707–0.839) and 0.745 (95% CI 0.637–0.852) in the training cohort and test cohort, respectively. The progression risk was higher in the high-risk group than that in the low-risk group categorized by the optimal cutoff value (2.05) of hematological risk scores. The HRM, age, tumor location, tumor size, peritumoral edema, extent of resection, Ki-67 index, and postoperative radiotherapy were the prognostic factors for the progression of meningiomas. The corrected C-index of the clinical prognosis model was 0.79 in the training cohort. Clinical decision analysis showed that the clinical prognostic model could be used to obtain favorable clinical benefits. In the subgroup analysis, the HRM displayed excellent prognostic stability and general applicability in different subgroups.ConclusionsPreoperative hematological parameters are associated with the postoperative progression of WHO grade II meningiomas. The clinical prognosis model constructed based on hematological parameters and clinical prognostic factors has favorable predictive accuracy and clinical benefits.

MRI features and tumor-infiltrating CD8 + T cells-based nomogram for predicting meningioma recurrence risk

“…Our model serves as an intuitive visual tool with demonstrable reliability and accuracy, while being an improvement to previous attempts. For example, a prior nomogram was built from clinical data to predict grade 2–3 meningiomas and measure meningioma prognosis [ 29 , 30 ]. Similarly, Mo et al [ 31 ] constructed a nomogram using independent predictors such as tumor size, Ki-67 index, and resection extent to stratify the recurrence risk of meningiomas.…”

Neutrophil-to-lymphocyte Ratio as an Effective Biomarker for Meningioma: A Systematic Review and Meta-analysis

“…The efficacy of NLR in estimating patient outcomes, including progression-free survival (PFS) and tumor recurrence, was explored in five studies. [24][25][26][27][28] In a retrospective analysis in 2020, Kuranari et al investigated the predictive importance of preoperative NLR in 160 meningioma patients in Japan. 24 According to the receiver operating characteristic (ROC) curve, the NLR cutoff value was 2.6 as a predictor of tumor recurrence, with an area under the curve (AUC) of 0.55, a sensitivity of 34.1%, and a specificity of 81.9%.…”

“…26 In another study in 2021 in China, Gao et al used the clinical data of 274 patients with primary grade II meningioma to make a clinical predictive model relying on preoperative hematological and clinical parameters. 27 According to the ROC analysis, 1.79 was the best cutoff value for NLR to predict patient PFS. When the hematological parameters were integrated into the LASSO Cox regression model, an increased level of NLR was an independent predictor for progression (weighting coefficient: 0.833, p = 0.701).…”

“…This study concluded that the postoperative development of grade II meningioma is linked to preoperative hematological markers like NLR. 27 Also in 2021, Yuksel et al performed a retrospective study in Turkey in 23 patients with grade 1 meningioma to see if regular blood indicators could be used to predict prognosis in these patients. 28 This study did not recognize NLR as a predictor of short-term prognosis (p > 0.05).…”