Albakr Abdulrahman, Baghdadi Amir, Karmur Brij S, Lama Sanju, Sutherland Garnette R
Department of Clinical Neurosciences, Project neuroArm, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.
Surg Neurol Int. 2024 May 10;15:155. doi: 10.25259/SNI_43_2024. eCollection 2024.
Meningioma, the most common brain tumor, traditionally considered benign, has a relatively high risk of recurrence over a patient's lifespan. In addition, with the emergence of several clinical, radiological, and molecular variables, it is becoming evident that existing grading criteria, including Simpson's and World Health Organization classification, may not be sufficient or accurate. As web-based tools for widespread accessibility and usage become commonplace, such as those for gene identification or other cancers, it is timely for meningioma care to take advantage of evolving new markers to help advance patient care.
A scoping review of the meningioma literature was undertaken using the MEDLINE and Embase databases. We reviewed original studies and review articles from September 2022 to December 2023 that provided the most updated information on the demographic, clinical, radiographic, histopathological, molecular genetics, and management of meningiomas in the adult population.
Our scoping review reveals a large body of meningioma literature that has evaluated the determinants for recurrence and aggressive tumor biology, including older age, female sex, genetic abnormalities such as telomerase reverse transcriptase promoter mutation, deletion, subtotal resection, and higher grade. Despite a large body of evidence on meningiomas, however, we noted a lack of tools to aid the clinician in decision-making. We identified the need for an online, self-updating, and machine-learning-based dynamic model that can incorporate demographic, clinical, radiographic, histopathological, and genetic variables to predict the recurrence risk of meningiomas.
Although a challenging endeavor, a recurrence prediction tool for meningioma would provide critical information for the meningioma patient and the clinician making decisions on long-term surveillance and management of meningiomas.
脑膜瘤是最常见的脑肿瘤,传统上被认为是良性的,但在患者的一生中复发风险相对较高。此外,随着一些临床、放射学和分子变量的出现,现有的分级标准,包括辛普森分级和世界卫生组织分类,可能并不充分或准确,这一点越来越明显。随着基于网络的广泛可及和使用的工具变得普遍,比如用于基因识别或其他癌症的工具,脑膜瘤治疗利用不断发展的新标志物来推进患者护理恰逢其时。
使用MEDLINE和Embase数据库对脑膜瘤文献进行了范围综述。我们回顾了2022年9月至2023年12月的原始研究和综述文章,这些文章提供了关于成年人群脑膜瘤的人口统计学、临床、影像学、组织病理学、分子遗传学和治疗的最新信息。
我们的范围综述揭示了大量评估复发和侵袭性肿瘤生物学决定因素的脑膜瘤文献,这些因素包括年龄较大、女性、端粒酶逆转录酶启动子突变等基因异常、缺失、次全切除以及更高分级。然而,尽管有大量关于脑膜瘤的证据,但我们注意到缺乏帮助临床医生进行决策的工具。我们确定需要一个基于网络、自我更新且基于机器学习的动态模型,该模型可以纳入人口统计学、临床、影像学、组织病理学和基因变量,以预测脑膜瘤的复发风险。
尽管是一项具有挑战性的工作,但脑膜瘤复发预测工具将为脑膜瘤患者以及就脑膜瘤的长期监测和管理做出决策的临床医生提供关键信息。