Barbara Hero

PURPOSE: Because current approaches to risk classification and treatment stratification for children with neuroblastoma (NB) vary greatly throughout the world, it is difficult to directly compare risk-based clinical trials. The International Neuroblastoma Risk Group (INRG) classification system was developed to establish a consensus approach for pretreatment risk stratification. PATIENTS AND METHODS: The statistical and clinical significance of 13 potential prognostic factors were analyzed in a cohort of 8,800 children diagnosed with NB between 1990 and 2002 from North America and Australia (Children's Oncology Group), Europe (International Society of Pediatric Oncology Europe Neuroblastoma Group and German Pediatric Oncology and Hematology Group), and Japan. Survival tree regression analyses using event-free survival (EFS) as the primary end point were performed to test the prognostic significance of the 13 factors. RESULTS: Stage, age, histologic category, grade of tumor differentiation, the status of the MYCN oncogene, chromosome 11q status, and DNA ploidy were the most highly statistically significant and clinically relevant factors. A new staging system (INRG Staging System) based on clinical criteria and tumor imaging was developed for the INRG Classification System. The optimal age cutoff was determined to be between 15 and 19 months, and 18 months was selected for the classification system. Sixteen pretreatment groups were defined on the basis of clinical criteria and statistically significantly different EFS of the cohort stratified by the INRG criteria. Patients with 5-year EFS more than 85%, more than 75% to < or = 85%, > or = 50% to < or = 75%, or less than 50% were classified as very low risk, low risk, intermediate risk, or high risk, respectively. CONCLUSION: By defining homogenous pretreatment patient cohorts, the INRG classification system will greatly facilitate the comparison of risk-based clinical trials conducted in different regions of the world and the development of international collaborative studies.

Neuroblastoma is an enigmatic disease entity; some tumors disappear spontaneously without any therapy, while others progress with a fatal outcome despite the implementation of maximal modern therapy. However, strong prognostic factors can accurately predict whether children have "good" or "bad" disease at diagnosis, and the clinical stage is currently the most significant and clinically relevant prognostic factor. Therefore, for an individual patient, proper staging is of paramount importance for risk assessment and selection of optimal treatment. In 2009, the International Neuroblastoma Risk Group (INRG) Project proposed a new staging system designed for tumor staging before any treatment, including surgery. Compared with the focus of the International Neuroblastoma Staging System, which is currently the most used, the focus has now shifted from surgicopathologic findings to imaging findings. The new INRG Staging System includes two stages of localized disease, which are dependent on whether image-defined risk factors (IDRFs) are or are not present. IDRFs are features detected with imaging at the time of diagnosis. The present consensus report was written by the INRG Imaging Committee to optimize imaging and staging and reduce interobserver variability. The rationales for using imaging methods (ultrasonography, magnetic resonance imaging, computed tomography, and scintigraphy), as well as technical guidelines, are described. Definitions of the terms recommended for assessing IDRFs are provided with examples. It is anticipated that the use of standardized nomenclature will contribute substantially to more uniform staging and thereby facilitate comparisons of clinical trials conducted in different parts of the world.

BACKGROUND: Neuroblastoma is the second most common type of childhood tumor. It is not known whether screening for neuroblastoma at one year of age reduces the incidence of metastatic disease or mortality due to neuroblastoma. METHODS: We offered urine screening for neuroblastoma at approximately one year of age to 2,581,188 children in 6 of 16 German states from 1995 to 2000. A total of 2,117,600 eligible children in the remaining states served as controls. We compared the two groups in terms of the incidence of disseminated disease and mortality from neuroblastoma. RESULTS: A total of 1,475,773 children (61.2 percent of those who were born between July 1, 1994, and October 31, 1999) underwent screening. In this group, neuroblastoma was detected by screening in 149 children, of whom 3 have died. Fifty-five children who had negative screening tests were subsequently given a diagnosis of neuroblastoma; 14 of these children have died. The screened group and children in the control area had a similar incidence of stage 4 neuroblastoma (3.7 cases per 100,000 screened children [95 percent confidence interval, 2.7 to 4.7] and 3.8 per 100,000 controls [95 percent confidence interval, 2.9 to 4.6]) and a similar rate of death among children with neuroblastoma (1.3 deaths per 100,000 screened children [95 percent confidence interval, 0.7 to 1.8] and 1.2 per 100,000 controls [95 percent confidence interval, 0.7 to 1.7]). Comparison of the screened group and the children in the control area revealed substantial overdiagnosis in the former group (an estimated rate of 7 cases per 100,000 children [95 percent confidence interval, 4.6 to 9.2]); the overdiagnosis rate represents children who had neuroblastoma that was diagnosed by screening but who would not benefit from earlier diagnosis and treatment. CONCLUSIONS: The present findings do not support the usefulness of general screening for neuroblastoma at one year of age.

BACKGROUND: Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. RESULTS: We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. CONCLUSIONS: We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.