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Tailoring Therapy for Children With Neuroblastoma on the Basis of Risk Group Classification: Past, Present, and Future

Authors :
Susan L. Cohn
Wayne H. Liang
Wendy B. London
Arlene Naranjo
Meredith S. Irwin
Sara M. Federico
Samuel L. Volchenboum
Source :
JCO Clin Cancer Inform
Publication Year :
2020

Abstract

For children with neuroblastoma, the likelihood of cure varies widely according to age at diagnosis, disease stage, and tumor biology. Treatments are tailored for children with this clinically heterogeneous malignancy on the basis of a combination of markers that are predictive of risk of relapse and death. Sequential risk-based, cooperative-group clinical trials conducted during the past 4 decades have led to improved outcome for children with neuroblastoma. Increasingly accurate risk classification and refinements in treatment stratification strategies have been achieved with the more recent discovery of robust genomic and molecular biomarkers. In this review, we discuss the history of neuroblastoma risk classification in North America and Europe and highlight efforts by the International Neuroblastoma Risk Group (INRG) Task Force to develop a consensus approach for pretreatment stratification using seven risk criteria including an image-based staging system—the INRG Staging System. We also update readers on the current Children’s Oncology Group risk classifier and outline plans for the development of a revised 2021 Children’s Oncology Group classifier that will incorporate INRG Staging System criteria to facilitate harmonization of risk-based frontline treatment strategies conducted around the globe. In addition, we discuss new approaches to establish increasingly robust, future risk classification algorithms that will further refine treatment stratification using machine learning tools and expanded data from electronic health records and the INRG Data Commons.

Details

ISSN :
24734276
Volume :
4
Database :
OpenAIRE
Journal :
JCO clinical cancer informatics
Accession number :
edsair.doi.dedup.....7e212a1739c462ca43dfa0c829b9a6a4