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

Jason L. Hornick, Fleur Webster, Angelo Paolo Dei Tos, Chris Hemmings, Markku Miettinen, Yoshinao Oda, Chandrajit P. Raut, Brian P. Rubin, Margaret Von Mehren, Eva Wardelmann, Christopher D.M. Fletcher

Research output: Contribution to journalReview articlepeer-review


Gastrointestinal stromal tumours (GISTs) are the most common mesenchymal tumours of the gastrointestinal tract and are among the most frequent sarcomas. Accurate diagnosis, classification, and reporting are critical for prognostication and patient management, including selection of appropriate targeted therapy. Here we report on international consensus-based datasets for the pathology reporting of biopsy and resection specimens of GIST. The datasets were produced under the auspices of the International Collaboration on Cancer Reporting (ICCR), a global alliance of major international pathology and cancer organizations. An international expert panel consisting of pathologists, a surgical oncologist, and a medical oncologist produced a set of core and noncore data items for biopsy and resection specimens based on a critical review and discussion of current evidence. All professionals involved were subspecialized soft tissue tumour experts and affiliated with tertiary referral centres. Commentary was provided for each data item to explain its clinical relevance and the rationale for selection as a core or noncore element. Following international public consultation, the datasets, which include synoptic reporting guides, were finalized and ratified, and published on the ICCR website. These first international datasets for GIST are intended to promote high-quality, standardised pathology reporting. Their widespread adoption will improve consistency of reporting, facilitate multidisciplinary communication, and enhance comparability of data, all of which will ultimately help to improve the management of patients with GIST. All the ICCR datasets, including these on GIST, are freely available worldwide on the ICCR website (

Original languageEnglish
Pages (from-to)376-384
Number of pages9
Issue number3
Publication statusPublished - Feb 2023

All Science Journal Classification (ASJC) codes

  • Pathology and Forensic Medicine
  • Histology


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