Feucht Daniel, Haas Patrick, Skardelly Marco, Behling Felix, Rieger David, Bombach Paula, Paulsen Frank, Hoffmann Elgin, Hauser Till-Karsten, Bender Benjamin, Renovanz Mirjam, Niyazi Maximilian, Tabatabai Ghazaleh, Tatagiba Marcos, Roder Constantin
Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Tübingen, Germany.
Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany.
Neurooncol Adv. 2024 Apr 3;6(1):vdae053. doi: 10.1093/noajnl/vdae053. eCollection 2024 Jan-Dec.
Little is known about the growth dynamics of untreated glioblastoma and its possible influence on postoperative survival. Our aim was to analyze a possible association of preoperative growth dynamics with postoperative survival.
We performed a retrospective analysis of all adult patients surgically treated for newly diagnosed glioblastoma at our center between 2010 and 2020. By volumetric analysis of data of patients with availability of ≥3 preoperative sequential MRI, a growth pattern was aimed to be identified. Main inclusion criterion for further analysis was the availability of two preoperative MRI scans with a slice thickness of 1 mm, at least 7 days apart. Individual growth rates were calculated. Association with overall survival (OS) was examined by multivariable.
Out of 749 patients screened, 13 had ≥3 preoperative MRI, 70 had 2 MRI and met the inclusion criteria. A curve estimation regression model showed the best fit for exponential tumor growth. Median tumor volume doubling time (VDT) was 31 days, median specific growth rate (SGR) was 2.2% growth per day. SGR showed negative correlation with tumor size (rho = -0.59, < .001). Growth rates were dichotomized according to the median SGR.OS was significantly longer in the group with slow growth (log-rank: = .010). Slower preoperative growth was independently associated with longer overall survival in a multivariable Cox regression model for patients after tumor resection.
Especially small lesions suggestive of glioblastoma showed exponential tumor growth with variable growth rates and a median VDT of 31 days. SGR was significantly associated with OS in patients with tumor resection in our sample.
关于未经治疗的胶质母细胞瘤的生长动力学及其对术后生存的可能影响，人们了解甚少。我们的目的是分析术前生长动力学与术后生存之间的可能关联。
我们对2010年至2020年间在本中心接受手术治疗的所有新诊断胶质母细胞瘤成年患者进行了回顾性分析。通过对有≥3次术前连续MRI数据的患者进行体积分析，旨在确定生长模式。进一步分析的主要纳入标准是有两次术前MRI扫描，层厚1毫米，间隔至少7天。计算个体生长率。通过多变量分析检查与总生存期（OS）的关联。
在筛查的749例患者中，13例有≥3次术前MRI，70例有2次MRI且符合纳入标准。曲线估计回归模型显示最适合指数型肿瘤生长。中位肿瘤体积倍增时间（VDT）为31天，中位比生长率（SGR）为每天2.2%的生长率。SGR与肿瘤大小呈负相关（rho = -0.59，P <.001）。根据中位SGR将生长率进行二分法划分。生长缓慢组的OS明显更长（对数秩检验：P =.010）。在肿瘤切除术后患者的多变量Cox回归模型中，术前生长较慢与更长的总生存期独立相关。
尤其是提示为胶质母细胞瘤的小病灶显示出指数型肿瘤生长，生长率各异，中位VDT为31天。在我们的样本中，SGR与肿瘤切除患者的OS显著相关。
