Which treatment is best? A systematic review and Bayesian network meta-analysis of adjuvant treatments for low-grade glioma.
Abstract
2057 Background: The standard of care for low-grade glioma (LGG) includes resection with or without adjuvant treatment. It is currently unknown which adjuvant strategy is best. Methods: A systematic review of PubMed and EMBASE for randomized controlled trials (RCTs) evaluating adjuvant treatment for LGG published on or before 6/2/2025 was conducted as pre-registered (CRD420251072899). Study eligibility and data extraction were reviewed by two authors independently, and risk of bias was assessed via Cochrane RoB2. Two Bayesian network meta-analyses profiling de novo LGG were conducted with uninformative priors adjusting for baseline characteristics of each trial cohort. The pre-specified outcome measure was the distribution of posterior HR PFS (primary meta-analysis) and HR OS (secondary meta-analysis) for each identified treatment against observation. Posterior distributions were summarized with the posterior median hazard ratio (HR), and 95% equal-tailed credible interval (CrI). Further the probability of major benefit (HR≤0.6) and any magnitude harm (HR>1.0) were reported for each meta-analysis. Results: Six RCTs (all with low risk of bias) profiling 1,757 participants were identified for the primary meta-analysis (PFS). Seven RCTs (6 with low risk of bias 1 with high risk of bias) profiling 1,392 patients were identified for the secondary meta-analysis (OS). In total, six adjuvant treatment strategies were identified: radiotherapy (RT) + procarbazine/CCNU/vincristine (PCV), RT + temozolomide (TMZ), RT + CCNU alone, high-dose RT (HDRT, >54Gy), low-dose RT (LDRT; ≤54Gy), and TMZ. The posterior median HRs and 95% CrIs are reported in Table 1. For all profiled treatments, the probability of any benefit (HR<1.0) on the endpoint of PFS was >98% and >76% for OS. Additionally, the probability of major benefit (P1) and any magnitude harm (P2) were reported as clinically significant summary measures of all posterior distributions (Table 1). Conclusions: Based on the identified RCTs, RT+PCV was found to have the most favorable probability efficacy and RT+TMZ a similar distribution of treatment effect. RT+PCV and RT+TMZ had a >98% probability of any benefit for both endpoints. The probability of major benefit for RT+PCV and RT+TMZ was >99.9% and 84.8% for PFS and 71.3% and 63.3% for OS. Probability of benefit/harm of adjuvant therapy for low-grade glioma. PFS P1 PFS P2 PFS OS P1 OS P2 OS PT+PCV 0.29 (0.19-0.43) >99.9% <0.1% 0.53 (0.32-0.84) 71.3% 0.4% RT+TMZ 0.45 (0.27-0.76) 84.8% 0.2% 0.55 (0.33-0.91) 63.3% 1.1% RT+CCNU - - 0.63 (0.28-1.42) 46.0% 13.4% HDRT 0.59 (0.41-0.83) 55.0% 0.2% 0.86 (0.57-1.30) 4.4% 23.0% LDRT 0.58 (0.44-0.76) 59.0% <0.1% 0.89 (0.63-1.24) 1.4% 23.4% TMZ 0.67 (0.47-0.97) 26.9% 1.4% - - - Observation 1 (Ref.) - - 1 (Ref.) - - P1, probability HR≤0.6; P2, probability HR>1.0.
Article Details
Journal Info
Journal of Clinical Oncology
Lippincott Williams & Wilkins
Authors (6)
Amit Kumar Chowdhry
AdventHealth Cancer Institute, Orlando, FL
Mame Daro Faye
McGill University Health Centre, Montréal, QC, Canada
Huma Chaudhry
National Cancer Institute, National Institutes of Health, Bethesda, MD
John Parel
George Washington University, Washington, DC
Erich Huang
National Cancer Institute, National Institutes of Health, Rockville, MD
Krishnan R. Patel
Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD