Datasets for reporting of soft‐tissue sarcoma: recommendations from the International Collaboration on Cancer Reporting (ICCR). Issue 5 (20th January 2023) - Dei Tos, Angelo Paolo; Webster, Fleur; Agaimy, Abbas; Bovée, Judith; Dickson, Brendan; Doyle, Leona; Dry, Sarah; Gronchi, Alessandro; Hameed, Meera; Hemmings, Chris; Liegl‐Atzwanger, Bernadette; Thway, Khin; et al.
Abstract : Aims: Soft‐tissue tumours are rare and both accurate diagnosis and proper treatment represent a global challenge. Current treatment guidelines also recommend review by specialised pathologists. Here we report on international consensus‐based datasets for the pathology reporting of biopsy and resection specimens of soft‐tissue sarcomas. The datasets were produced under the auspices of the International Collaboration on Cancer Reporting (ICCR), a global alliance of international pathology and cancer organisations. Methods and results: According to the ICCR's guidelines for dataset development, 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 subspecialised soft‐tissue sarcoma experts and affiliated with tertiary referral centres. Commentary was provided for each data item to explain the rationale for selecting it as a core or noncore element, its clinical relevance, and to highlight potential areas of disagreement or lack of evidence, in which case a consensus position was formulated. Following international public consultation, the documents were finalised and ratified, and the datasets, which included a synoptic reporting guide, were published on the ICCR website. Conclusion: These first international datasets for soft‐tissue sarcomas are aimed to promote high‐quality, standardised pathology reporting. Their adoption will improve consistency of reporting, facilitate multidisciplinary communication, and enhance comparability of data, all of which will help to improve patient's management. Abstract :