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Data set for reporting of paediatric rhabdomyosarcoma: recommendations from the International Collaboration on Cancer
Anna Kelsey1, Rita Alaggio2,3, Fleur Webster4
1Department of Diagnostic Paediatric Histopathology, Royal Manchester Children's Hospital, Manchester, UK.
Insights
A new international data set standardizes reporting for paediatric rhabdomyosarcoma (RMS), a rare childhood cancer. This promotes consistent data collection for improved patient outcomes globally.
Area of Science:
- Oncology
- Pathology
- Paediatric Medicine
Background:
- Rhabdomyosarcoma (RMS) is the most common childhood sarcoma, with subtypes exhibiting diverse characteristics.
- Histological criteria for RMS diagnosis have evolved, integrating immunohistochemical and molecular data for comprehensive reporting.
- Standardized reporting is crucial for patient management, clinical trials, research, and cancer registries.
Purpose of the Study:
- To introduce the International Collaboration on Cancer Reporting (ICCR) process for developing the first international paediatric RMS data set.
- To establish core and non-core reporting elements for biopsy and resection specimens of paediatric RMS.
- To ensure comprehensive histopathology reports incorporating clinical, macroscopic, microscopic, and ancillary testing data.
Main Methods:
- An international expert panel of pathologists and paediatric oncologists developed the data set.
- Data item selection was based on evidence review, focusing on elements essential for treatment stratification and clinical trials.
- Commentary was provided for each data item, detailing rationale and clinical relevance.
Main Results:
- The ICCR developed the first international data set for paediatric RMS reporting.
- The data set includes core and non-core elements for comprehensive histopathology reports.
- Elements cover clinical, macroscopic, microscopic, and ancillary testing data.
Conclusions:
- The international data set promotes standardized, high-quality reporting of paediatric RMS.
- It facilitates uniform data collection for global clinical data comparison.
- Ultimately, this aims to improve patient outcomes for childhood rhabdomyosarcoma.
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.
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