Data set for reporting of paediatric rhabdomyosarcoma: recommendations from the International Collaboration on Cancer Reporting (ICCR).

Aims: Rhabdomyosarcoma (RMS) is rare, but it is the most common sarcoma in childhood. The World Health Organisation classifies RMS into four main categories, sharing the same terminology of RMS, but the subtypes have different morphology, clinical behaviour and underlying molecular characterisation. Although the main diagnostic categories have remained the same there have been changes in the histological criteria, together with integration of both immunohistochemical and molecular data in the reporting of RMS. Integrated histology reporting provides valuable information for the management of children with RMS, is important for patients enrolled into clinical trials, supports tissue-based biological research and contributes to data required in cancer registries. Consistent, comprehensive and reproducible reporting of RMS is imperative.

Methods and results: In this article we provide the International Collaboration on Cancer Reporting (ICCR) process for the development of the first international Paediatric RMS data set for the reporting of biopsy and resection specimens. An international expert panel consisting of pathologists and paediatric oncologists produced a set of core and non-core elements to be included in the histopathology reporting of paediatric RMS, inclusive of clinical, macroscopic, microscopic and ancillary testing required for a comprehensive report. The selection of data items was based on review of current evidence, taking into account items that are recognised as essential for patient treatment stratification and that are currently in use in the clinical trial setting. Commentary was provided for each data item to detail the rationale for selecting it as core or non-core element, and to highlight their clinical relevance.

Conclusions: The first international data set for the reporting of paediatric RMS aims to promote standardised, high-quality reporting and supports uniform data collection, which is critical for clinical data comparison on a global level, ultimately improving patient outcome.