Predicting outcomes for children with neuroblastoma

One of the main challenges in clinical cancer research remains to be accurate outcome prediction at the time of diagnosis. Although not frequent in absolute terms, neuroblastoma represents an important clinical challenge, as it is fatal in almost half of the patients despite advances in multimodal anti-cancer therapies. Four major risk stratification systems for neuroblastoma patients are currently being used in various parts of the world. Systems are based on a combination of various clinical, histopathological, and biological factors. Accordingly, different therapeutic schemes exist ranging from wait-and-see approaches to intensive multimodal therapies. Clinical experience with the currently used risk stratification systems suggests that the stratification of patients for treatment is useful, but patients with the same clinico-pathological parameters, receiving the same treatment, can have markedly different clinical courses. Therefore, the challenge remains to identify additional tumor-specific and sensitive prognostic markers for improved risk estimation at the time of diagnosis and to improve the choice of risk-related therapy. Various studies have put forward new prognostic markers, including copy number aberrations, gene expression signatures, and epigenetic markers.

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