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验证一种评分系统,以评估神经纤维瘤病 2 型患者颅内脑膜瘤快速生长的风险。

Validation of a scoring system to evaluate the risk of rapid growth of intracranial meningiomas in neurofibromatosis type 2 patients.

机构信息

1Department of Neurosurgery and.

2Sorbonne Universités, Paris.

出版信息

J Neurosurg. 2020 May 22;134(5):1377-1385. doi: 10.3171/2020.3.JNS192382. Print 2021 May 1.

Abstract

OBJECTIVE

Intracranial meningiomas occur in about half of neurofibromatosis type 2 (NF2) patients and are very frequently multiple. Thus, estimating individual meningiomas' growth rates is of great interest to tailor therapeutic interventions. The Asan Intracranial Meningioma Scoring System (AIMSS) has recently been published to estimate the risk of tumor growth in sporadic meningiomas. The current study aimed to determine predictors of rapid meningioma growth in NF2 patients and to evaluate the AIMSS score in a specific NF2 cohort.

METHODS

The authors performed a retrospective analysis of 92 NF2 patients with 358 measured intracranial meningiomas that had been observed prospectively between 2012 and 2018. Tumor volumes were measured at diagnosis and at each follow-up visit. The growth rates were determined and evaluated with respect to the clinicoradiological parameters. Predictors of rapid tumor growth (defined as growth ≥ 2 cm3/yr) were analyzed using univariate followed by multivariate logistic regression to build a dedicated predicting model. Receiver operating characteristic (ROC) curves to predict the risk of rapid tumor growth with the AIMSS versus the authors' multivariate model were compared.

RESULTS

Sixty tumors (16.76%) showed rapid growth. After multivariate analysis, a larger tumor volume at diagnosis (p < 0.0001), presence of peritumoral edema (p = 0.022), absence of calcifications (p < 0.0001), and hyperintense or isointense signal on T2-weighted MRI (p < 0.005) were statistically significantly associated with rapid tumor growth. It is particularly notable that the genetic severity score did not seem to influence the growth rate of NF2 meningiomas. In comparison with the AIMSS, the authors' multivariate model's prediction did not show a statistically significant difference (area under the curve [AUC] 0.82 [95% CI 0.76-0.88] for the AIMSS vs AUC 0.86 [95% CI 0.81-0.91] for the authors' model, p = 0.1).

CONCLUSIONS

The AIMSS score is valid in the authors' cohort of NF2-related meningiomas. It adequately predicted risk of rapid meningioma growth and could aid in decision-making in NF2 patients.

摘要

目的

神经纤维瘤病 2 型(NF2)患者约有一半会发生颅内脑膜瘤,且通常为多发性。因此,评估单个脑膜瘤的生长速度对于制定治疗干预措施非常重要。最近发表的 Asan 颅内脑膜瘤评分系统(AIMSS)用于估计散发脑膜瘤的肿瘤生长风险。本研究旨在确定 NF2 患者脑膜瘤快速生长的预测因素,并在特定的 NF2 队列中评估 AIMSS 评分。

方法

作者对 92 例 NF2 患者的 358 个经测量的颅内脑膜瘤进行了回顾性分析,这些脑膜瘤在 2012 年至 2018 年期间进行了前瞻性观察。在诊断时和每次随访时测量肿瘤体积。根据临床和影像学参数评估生长率,并确定快速肿瘤生长(定义为生长≥2cm3/yr)的预测因素。使用单变量和多变量逻辑回归分析快速肿瘤生长的预测因素,以建立专门的预测模型。比较 AIMSS 与作者的多变量模型预测快速肿瘤生长风险的受试者工作特征(ROC)曲线。

结果

60 个肿瘤(16.76%)生长较快。多变量分析后,诊断时肿瘤体积较大(p<0.0001)、存在瘤周水肿(p=0.022)、无钙化(p<0.0001)和 T2 加权 MRI 上呈高信号或等信号(p<0.005)与肿瘤快速生长有统计学显著相关性。值得注意的是,遗传严重程度评分似乎并不影响 NF2 脑膜瘤的生长速度。与 AIMSS 相比,作者的多变量模型的预测没有统计学显著差异(AIMSS 的曲线下面积 [AUC] 为 0.82[95%CI 0.76-0.88],作者模型的 AUC 为 0.86[95%CI 0.81-0.91],p=0.1)。

结论

AIMSS 评分在作者的 NF2 相关脑膜瘤队列中是有效的。它充分预测了脑膜瘤快速生长的风险,并有助于 NF2 患者的决策。

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