Andrew G Nicholson1, Frank Detterbeck2, Alexander Marx3, Anja C Roden4, Alberto M Marchevsky5, Kiyoshi Mukai6, Gang Chen7, Mirella Marino8, Michael A den Bakker9, Woo-Ick Yang10, Meagan Judge11, Lynn Hirschowitz12. 1. Department of Histopathology, Royal Brompton and Harefield NHS Foundation Trust and National Heart and Lung Division, Imperial College, London, UK. 2. Division of Thoracic Surgery, Department of Surgery, Yale University, New Haven, CN, USA. 3. Department of Pathology, University Medical Centre Mannheim, University of Heidelberg, Mannheim, Germany. 4. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA. 5. Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA. 6. Department of Diagnostic Pathology, Saiseikai Central Hospital, Tokyo, Japan. 7. Department of Pathology, Zhongshan Hospital Fudan University, Shanghai, China. 8. Department of Pathology, Regina Elena National Cancer Institute, Rome, Italy. 9. Department of Pathology, Maasstad Hospital and Department of Pathology of the Erasmus MC, Rotterdam, the Netherlands. 10. Department of Pathology, Yonsei University College of Medicine, Seoul, Korea. 11. Royal College of Pathologists of Australasia, Sydney, Australia. 12. Department of Cellular Pathology, Birmingham Women's Hospital, Birmingham, UK.
Abstract
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.
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.
Authors: Prerna Guleria; Rajinder Parshad; Prabhat Singh Malik; Ruma Ray; R M Pandey; Deepali Jain Journal: Indian J Med Res Date: 2019-08 Impact factor: 2.375