May Michaela, Sedlak Vojtech, Pecen Ladislav, Priban Vladimir, Buchvald Pavel, Fiedler Jiri, Vaverka Miroslav, Lipina Radim, Reguli Stefan, Malik Jozef, Cerny Martin, Netuka David, Benes Vladimir
Department of Neurosurgery and Neurooncology, First Faculty of Medicine, Charles University and Military University Hospital, U Vojenske nemocnice 1200, Prague, 169 02, Czech Republic.
First Faculty of Medicine, Charles University in Prague, Prague, Czech Republic.
Sci Rep. 2025 Jan 29;15(1):3715. doi: 10.1038/s41598-025-87882-z.
The histological grade is crucial for therapeutic management, and its reliable preoperative detection can significantly influence treatment approach. Lacking established risk factors, this study identifies preoperative predictors of high-grade skull base meningiomas and discusses the implications of non-invasive detection. A multicentric study was conducted on 552 patients with skull base meningiomas who underwent primary surgical resection between 2014 and 2019. Data were gathered from clinical, surgical and pathology records and radiological diagnostics. The predictive factors of higher WHO grade were analysed in univariate analysis and multivariate stepwise selection logistic regression analysis. Histological analysis revealed 511 grade 1 (92.6%) and 41 grade 2 (7.4%) meningiomas. A prognostic model predicting the probability of WHO grade 2 skull base meningioma (AUC 0.79; SE 0.04; 95% Wald Confidence Limits (0.71; 0.86)) based on meningioma diameter, presence of an arachnoid plane and cranial nerve palsy was built. Accurate preoperative detection of WHO grade in skull base meningiomas is essential for effective treatment planning. Our logistic regression model, based on diameter, cranial nerve palsy, and arachnoid plane, is tailored for detecting WHO grade 2 skull base meningiomas, even in outpatient settings.
组织学分级对于治疗管理至关重要,其可靠的术前检测可显著影响治疗方法。由于缺乏既定的风险因素,本研究确定了高级别颅底脑膜瘤的术前预测因素,并讨论了无创检测的意义。对2014年至2019年间接受初次手术切除的552例颅底脑膜瘤患者进行了一项多中心研究。数据收集自临床、手术和病理记录以及放射学诊断。在单因素分析和多因素逐步选择逻辑回归分析中分析了世界卫生组织(WHO)更高分级的预测因素。组织学分析显示有511例1级脑膜瘤(92.6%)和41例2级脑膜瘤(7.4%)。基于脑膜瘤直径、蛛网膜平面的存在和颅神经麻痹建立了一个预测WHO 2级颅底脑膜瘤概率的预后模型(曲线下面积0.79;标准误0.04;95% Wald置信区间(0.71;0.86))。准确术前检测颅底脑膜瘤的WHO分级对于有效的治疗计划至关重要。我们基于直径、颅神经麻痹和蛛网膜平面的逻辑回归模型,即使在门诊环境中也适用于检测WHO 2级颅底脑膜瘤。