Image-based Re-evaluation of the JCOG0911 Study Focusing on Tumor Volume and Survival, Disease Progression Diagnosis, and Radiomic Prognostication for Newly Diagnosed Glioblastoma.

Purpose: To re-evaluate images recovered from JCOG0911, a randomized phase 2 trial for newly diagnosed glioblastoma (nGBM) conducted by the Japan Clinical Oncology Group (JCOG) Brain Tumor Study Group.
Methods: The correlation between tumor volumes and survival was evaluated, followed by progression-free survival (PFS) analysis by independent central review based on Response Assessment in Neuro-Oncology (RANO) criteria using MRI recovered from 118 nGBM patients enrolled in the JCOG0911 trial. A radiomic analysis was also performed to identify radiomic features predictive of nGBM prognosis.
Results: The distribution of the Gd-enhancing and T2-weighted image/fluid attenuated inversion recovery-high intensity lesions mainly occupied white matter. JCOG0911 consisted of more subjects with right-sided lesions. The median extent of resection of the Gd-enhancing lesions was 99%. The overall survival showed a nonsignificant negative trend with postoperative Gd-enhancing lesion volume (P = 0.22), with the hazard ratio increasing in parallel with its volume. The median PFS after registration was 302 and 308 days for local Response Evaluation Criteria in Solid Tumors (RECIST)-based and central RANO-based diagnoses. However, an apparent discrepancy was observed between the two in the early phase, presumably due to the misdiagnosis of pseudoprogression by local RECIST-based diagnosis. Radiomic analysis identified 28 radiomic features predictive of nGBM prognosis, 5 of which were those previously identified in a separate cohort. The constructed radiomics-based prognostic model stratified the cohort into high- and low-risk groups (P = 0.028).
Conclusion: Novel analytical methods that could be incorporated into future clinical trials were successfully tested. RANO and RECIST may not differ in progression calls if pseudoprogression is appropriately handled.