Using the Neosoma AI technology for neuro-oncology, a group of prominent researchers at UCLA have demonstrated a correlation between alterations in tumor growth rate (TGR) and overall survival in patients with recurrent glioblastoma (rGBM) undergoing chemotherapy, with or without radiation therapy.
Their study, involving 61 rGBM patients at 1st or 2nd recurrence, meticulously analyzed pre- and post-treatment contrast enhancing tumor volumes. Patients with progression-free survival at 6 months (PFS6) and a decrease in TGR post-treatment were categorized as 'responders,' while those who didn't reach PFS6 or saw an increase in TGR were categorized as 'non-responders.'
In a significant development, the study highlighted that stratification based on PFS6 and TGR significantly impacted overall survival rates. A decrease in TGR, smaller initial tumor volume, O6-methylguanine-DNA methyltransferase promoter methylation, and fewer recurrences were all found to correlate with longer overall survival rates, after adjusting for age, sex, and concurrent radiation therapy.
Regardless of the treatment type, the study reveals that a decrease in TGR in patients achieving PFS6 and having smaller baseline tumor volume considerably improves overall survival in rGBM patients. Notably, all patients who reached PFS6 also exhibited a quantifiable decrease in TGR, thus presenting a new benchmark for predicting treatment efficacy, which can be accurately and consistently measured by the Neosoma Glioma AI technology.
The Neosoma Glioma AI-based quantitative biomarker technology can be used in clinical practice to support neurosurgical planning, post operative extent of resection assessment, radiation treatment planning and assessment, and to help guide medical therapy decisions throughout the course of clinical care.
To read the complete paper, please click here.