Statistical Framework in Support of a Revised Children's Oncology Group Neuroblastoma Risk Classification System.

Abstract

The International Neuroblastoma Risk Group (INRG) Staging System (INRGSS) was developed through international consensus to provide a presurgical staging system that uses clinical and imaging data at diagnosis. A revised Children's Oncology Group (COG) neuroblastoma (NB) risk classification system is needed to incorporate the INRGSS and within the context of modern therapy. Herein, we provide statistical support for the clinical validity of a revised COG risk classification system. Nine factors were tested for potential statistical and clinical significance in 4,569 patients diagnosed with NB who were enrolled in the COG biology/banking study ANBL00B1 (2006-2016). Recursive partitioning was performed to create a survival-tree regression (STR) analysis of event-free survival (EFS), generating a split by selecting the strongest prognostic factor among those that were statistically significant. The least absolute shrinkage and selection operator (LASSO) was applied to obtain the most parsimonious model for EFS. COG patients were risk classified using STR, LASSO, and per the 2009 INRG classification (generated using an STR analysis of INRG data). Results were descriptively compared among the three classification approaches. The 3-year EFS and overall survival (± SE) were 72.9% ± 0.9% and 84.5% ± 0.7%, respectively (N = 4,569). In each approach, the most statistically and clinically significant factors were diagnostic category (eg, NB, ganglioneuroblastoma), INRGSS, MYCN status, International Neuroblastoma Pathology Classification, ploidy, and 1p/11q status. The results of the STR analysis were more concordant with those of the INRG classification system than with LASSO, although both methods showed moderate agreement with the INRG system. These analyses provide a framework to develop a new COG risk classification incorporating the INRGSS. There is statistical evidence to support the clinical validity of each of the three classifications: STR, LASSO, and INRG.