4.6 Article

Dataset for reporting of thymic epithelial tumours: recommendations from the International Collaboration on Cancer Reporting (ICCR)

Journal

HISTOPATHOLOGY
Volume 70, Issue 4, Pages 522-538

Publisher

WILEY
DOI: 10.1111/his.13099

Keywords

checklist; dataset; protocol; structured report; synoptic report; thymic carcinoma; thymic epithelial tumours; thymoma; thymus

Funding

  1. National Institute of Health Research Respiratory Disease Biomedical Research Unit at the Royal Brompton Hospital and Harefield Foundation NHS Trust
  2. Imperial College London

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Aims: The International Collaboration on Cancer Reporting (ICCR) is a not-for-profit organization formed by the Royal Colleges of Pathologists of Australasia and the United Kingdom, the College of American Pathologists, the Canadian Association of Pathologists-Association Canadienne des Pathologists in association with the Canadian Partnership Against Cancer, and the European Society of Pathology. Its goal is to produce standardized, internationally agreed, evidence-based datasets for use throughout the world. Methods and results: This article describes the development of a cancer dataset by the multidisciplinary ICCR expert panel for the reporting of thymic epithelial tumours. The dataset includes required' (mandatory) and recommended' (non-mandatory) elements, which are validated by a review of current evidence and supported by explanatory text. Seven required elements and 12 recommended elements were agreed by the international dataset authoring committee to represent the essential information for the reporting of thymic epithelial tumours. Conclusions: The use of an internationally agreed, structured pathology dataset for reporting thymic tumours provides all of the necessary information for optimal patient management, facilitates consistent and accurate data collection, and provides valuable data for research and international benchmarking. The dataset also provides a valuable resource for those countries and institutions that are not in a position to develop their own datasets.

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