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基于胶质母细胞瘤生长的最小模型的反应分类对临床结局具有预后价值,并可区分进展和假性进展。

Response classification based on a minimal model of glioblastoma growth is prognostic for clinical outcomes and distinguishes progression from pseudoprogression.

机构信息

Department of Pathology, University of Washington, Seattle, WA 98195, USA.

出版信息

Cancer Res. 2013 May 15;73(10):2976-86. doi: 10.1158/0008-5472.CAN-12-3588. Epub 2013 Feb 11.

Abstract

Glioblastoma multiforme is the most aggressive type of primary brain tumor. Glioblastoma growth dynamics vary widely across patients, making it difficult to accurately gauge their response to treatment. We developed a model-based metric of therapy response called Days Gained that accounts for this heterogeneity. Here, we show in 63 newly diagnosed patients with glioblastoma that Days Gained scores from a simple glioblastoma growth model computed at the time of the first postradiotherapy MRI scan are prognostic for time to tumor recurrence and overall patient survival. After radiation treatment, Days Gained also distinguished patients with pseudoprogression from those with true progression. Because Days Gained scores can be easily computed with routinely available clinical imaging devices, this model offers immediate potential to be used in ongoing prospective studies.

摘要

多形性胶质母细胞瘤是最具侵袭性的原发性脑肿瘤。胶质母细胞瘤的生长动态在患者之间差异很大,这使得准确评估他们对治疗的反应变得困难。我们开发了一种基于模型的治疗反应度量方法,称为获得的天数,该方法考虑了这种异质性。在这里,我们在 63 名新诊断的胶质母细胞瘤患者中显示,在首次放疗后 MRI 扫描时计算的简单胶质母细胞瘤生长模型的获得天数评分可预测肿瘤复发时间和患者总生存时间。在放射治疗后,获得的天数还可以区分假性进展和真性进展的患者。由于获得的天数评分可以使用常规临床成像设备轻松计算,因此该模型具有立即在正在进行的前瞻性研究中使用的潜力。

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