Preoperative growth dynamics of untreated glioblastoma: Description of an exponential growth type, correlating factors, and association with postoperative survival

Author:

Feucht Daniel12ORCID,Haas Patrick12,Skardelly Marco13,Behling Felix1245,Rieger David14,Bombach Paula14,Paulsen Frank1,Hoffmann Elgin15,Hauser Till-Karsten6,Bender Benjamin167,Renovanz Mirjam124ORCID,Niyazi Maximilian15,Tabatabai Ghazaleh147ORCID,Tatagiba Marcos12,Roder Constantin12ORCID

Affiliation:

1. Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen , Tübingen , Germany

2. Department of Neurosurgery, University Hospital Tübingen, Eberhard Karls University Tübingen , Tübingen , Germany

3. Department of Neurosurgery, Klinikum am Steinenberg , Reutlingen , Germany

4. Department of Neurology and Interdisciplinary Neuro-Oncology, Hertie Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University Tübingen , Tübingen , Germany

5. Department of Radiation Oncology, University Hospital Tübingen, Eberhard Karls University Tübingen , Tübingen , Germany

6. Department of Diagnostic and Interventional Neuroradiology, Department of Radiology, University Hospital Tübingen, Eberhard Karls University Tübingen , Tübingen ,  Germany

7. German Cancer Consortium (DKTK), DKFZ partner site Tübingen , Tübingen , Germany

Abstract

Abstract Background 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. Methods 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. Results 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, P < .001). Growth rates were dichotomized according to the median SGR.OS was significantly longer in the group with slow growth (log-rank: P = .010). Slower preoperative growth was independently associated with longer overall survival in a multivariable Cox regression model for patients after tumor resection. Conclusions 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.

Publisher

Oxford University Press (OUP)

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