Assessment of Chemo-Immunotherapy Regimens in Patients with Refractory or Relapsed Neuroblastoma: A Systematic Review...

Background: Neuroblastoma is a highly aggressive pediatric cancer, particularly in children with refractory or relapsed disease, where survival outcomes remain poor despite advancements in treatment. Combining anti-GD2 antibodies, such as dinutixumab beta, dinutixumab, and naxitanab, with conventional chemotherapy has emerged as a promising approach to improve clinical outcomes in this high-risk population. This chemo-immunotherapy regimen meta-analysis aimed to investigate the efficacy of these combination regimens by analyzing objective response rate (ORR), overall survival (OS), and event-free survival (EFS) outcomes across multiple studies. Methods: A systematic review and meta-analysis were conducted following PRISMA guidelines. PubMed, Web of Science, and Scopus databases were searched, yielding studies comprising the related reports. Both randomized controlled trials and non-randomized studies were included. The primary outcome of interest was ORR, and the secondary outcome of interest was EFS. A random-effects model using the DerSimonian-Laird method and Knapp-Hartung-Sidik-Jonkman adjustments was employed to pool effect sizes, and heterogeneity was assessed using I² statistics. Results: A total of ten reports from eight studies were deemed eligible and included in the meta-analysis. The pooled ORR across the studies was 0.45 (95% CI: 0.35-0.54, p < 0.001), indicating that approximately 45% of patients showed a favorable treatment response, with moderate heterogeneity (I² = 52.78%). The pooled analysis showed an OS of 75% (95% CI: 53-96, p < 0.001), and the pooled EFS effect size was 0.59 (95% CI: 0.45-0.73, p < 0.001), despite substantial heterogeneity (I² = 60.54%). Conclusions: anti-GD2 antibodies combined with conventional chemotherapy may significantly improve response rates and event-free survival in children with refractory or relapsed neuroblastoma. Future research should focus on identifying predictive biomarkers to tailor therapies to individual patients, enhancing both efficacy and safety in this vulnerable population.