Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Harvard-MIT Program in Health Science Technology, MD-PhD Program, Harvard Medical School, Boston, Massachusetts, USA.
Neuro Oncol. 2022 May 4;24(5):796-808. doi: 10.1093/neuonc/noab213.
Meningiomas are the most common primary intracranial tumor in adults. Clinical care is currently guided by the World Health Organization (WHO) grade assigned to meningiomas, a 3-tiered grading system based on histopathology features, as well as extent of surgical resection. Clinical behavior, however, often fails to conform to the WHO grade. Additional prognostic information is needed to optimize patient management.
We evaluated whether chromosomal copy-number data improved prediction of time-to-recurrence for patients with meningioma who were treated with surgery, relative to the WHO schema. The models were developed using Cox proportional hazards, random survival forest, and gradient boosting in a discovery cohort of 527 meningioma patients and validated in 2 independent cohorts of 172 meningioma patients characterized by orthogonal genomic platforms.
We developed a 3-tiered grading scheme (Integrated Grades 1-3), which incorporated mitotic count and loss of chromosome 1p, 3p, 4, 6, 10, 14q, 18, 19, or CDKN2A. 32% of meningiomas reclassified to either a lower-risk or higher-risk Integrated Grade compared to their assigned WHO grade. The Integrated Grade more accurately identified meningioma patients at risk for recurrence, relative to the WHO grade, as determined by time-dependent area under the curve, average precision, and the Brier score.
We propose a molecularly integrated grading scheme for meningiomas that significantly improves upon the current WHO grading system in prediction of progression-free survival. This framework can be broadly adopted by clinicians with relative ease using widely available genomic technologies and presents an advance in the care of meningioma patients.
脑膜瘤是成年人中最常见的原发性颅内肿瘤。目前,临床治疗主要依据世界卫生组织(WHO)对脑膜瘤的分级,这是一种基于组织病理学特征和手术切除范围的三级分级系统。然而,临床行为往往与 WHO 分级不符。需要额外的预后信息来优化患者管理。
我们评估了染色体拷贝数数据是否可以改善手术治疗的脑膜瘤患者的复发时间预测,相对于 WHO 方案。该模型是在一个包含 527 名脑膜瘤患者的发现队列中使用 Cox 比例风险、随机生存森林和梯度提升方法进行开发的,并在两个具有正交基因组平台的 172 名脑膜瘤患者的独立队列中进行了验证。
我们开发了一种三级分级方案(综合分级 1-3),其中纳入了有丝分裂计数和染色体 1p、3p、4、6、10、14q、18、19 或 CDKN2A 的缺失。与 WHO 分级相比,32%的脑膜瘤重新分类为风险较低或较高的综合分级。综合分级比 WHO 分级更准确地识别出有复发风险的脑膜瘤患者,这通过时间依赖性曲线下面积、平均精度和 Brier 评分来确定。
我们提出了一种脑膜瘤的分子综合分级方案,该方案在预测无进展生存率方面显著优于目前的 WHO 分级系统。该框架可以通过相对容易地使用广泛可用的基因组技术被临床医生广泛采用,并为脑膜瘤患者的治疗提供了进展。