NIMG-54. DIFFUSION MRI PHENOTYPES PREDICT OVERALL SURVIVAL BENEFIT FROM BEVACIZUMAB IN RECURRENT GLIOBLASTOMA WITH A LARGE TUMOR BURDEN: EVIDENCE FROM CLINICAL PRACTICE AND A MULTICENTER PHASE 3 TRIAL. (11th November 2019)

• Record Type: Journal Article
• Authors: Patel, Kunal; Raymond, Catalina; Yao, Jingwen; Tsung, Joseph; Goldman, Jodi; Schlossman, Jacob; Tran, Caleb; Brenner, Andrew; Butowski, Nicholas; Wen, Patrick; Pope, Whitney; Ji, Matthew; Lai, Albert; Leia Nghiemphu, P; Rachmilewitz Minei, Tamar; Cohen, Yael; Harats, Dror; Cloughesy, Timothy; Ellingson, Benjamin
• Is Part Of: Neuro-oncology. Volume 21(2019)Supplement 6
• Page Start: vi173
• Page End: vi173
• Publication Date: 2019-11-11
• Subjects: Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/noz175.723
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: We have previously shown that diffusion MR characteristics are a predictive imaging biomarker for survival benefit in recurrent glioblastoma treated with anti-VEGF therapy; however, contemporary clinical use of bevacizumab is often limited to patients with very large tumors and/or after multiple recurrences. We hypothesize that diffusion MR characteristics can be used to predict long-term survival benefit in these patients, which may be beneficial for clinical decision-making. The current study identified 83 recurrent glioblastoma patients from our institution who were treated with bevacizumab over the past 5 years with high quality anatomic and diffusion MRI data. Of these 83 patients, 35 had large contrast enhancing tumors (>20cc or >3.4cm diameter, group average). Additionally, we identified 37 recurrent glioblastoma patients from the bevacizumab treated control arm of a recent multicenter phase III trial (NCT02511405) with high quality data and large enhancing tumors for validation. Pre-treatment tumor volume was quantified using T1 subtraction maps and apparent diffusion coefficient (ADC) histogram analysis was used to phenotype patients as having high (> 1.24 um2/ms) or low (< 1.24 um2/ms) ADCL, the mean value of the lower peak using a double Gaussian mixed model. Median overall survival in patients with large volume recurrent glioblastoma was ~5.7 months. High ADCL was associated with significantly longer overall survival (OS) compared with low ADCL in both single center (P=0.0271, HR=0.486, mOS=5.5 vs. 2.8mo) and multicenter phase III data (P=0.0457, HR=0.507, mOS=7.9 vs. 5.7mo). Accounting for absolute tumor volume and age, both cohorts showed that ADCL was an independent prognostic factor for OS (Cox, P< 0.01). In summary, pre-treatment diffusion MR imaging is an independent predictive biomarker for OS in recurrent glioblastoma with a large tumor burden.