Position statement on classification of basal cell carcinomas. Part 2: EADO proposal for new operational staging system adapted to basal cell carcinomas
Autor: | Bernard Fertil, Claus Garbe, J.-J. Grob, Luca Tagliaferri, Iris Zalaudek, B Bertrand, Pablo Fernandez-Penas, Ketty Peris, Joseph Malvehy, Roland Kaufmann, M C Fargnoli, Nicole Basset-Seguin, Alexander Guminski, Alexandros Stratigos, V. Del Marmol, Caroline Gaudy-Marqueste |
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Přispěvatelé: | Grob, J J, Gaudy-Marqueste, C, Guminski, A, Malvehy, J, Basset-Seguin, N, Bertrand, B, Fernandez-Penas, P, Kaufmann, R, Zalaudek, I, Fargnoli, M C, Tagliaferri, L, Fertil, B, Del Marmol, V, Stratigos, A, Garbe, C, Peris, K |
Rok vydání: | 2021 |
Předmět: |
Cluster Analysis
Humans Prognosis Carcinoma Basal Cell Skin Neoplasms Position statement Decision tool Prognosi Basal Cell Guidelines and Position Statements Dermatology computer.software_genre Medicine Basal cell ddc:610 Position Statement Staging system Method testing Cluster Analysi business.industry Carcinoma Infectious Diseases Pattern recognition (psychology) Artificial intelligence Tumour classification Settore MED/35 - MALATTIE CUTANEE E VENEREE business Unsupervised clustering computer Natural language processing Human |
Zdroj: | Journal of the European Academy of Dermatology and Venereology |
ISSN: | 1468-3083 0926-9959 |
Popis: | Background No simple staging system has emerged for basal cell carcinomas (BCCs), since they do not follow the TNM process, and practitioners failed to agree on simple clinical or pathological criteria as a basis for a classification. Operational classification of BCCs is required for decision‐making, trials and guidelines. Unsupervised clustering of real cases of difficult‐to‐treat BCCs (DTT‐BCCs; part 1) has demonstrated that experts could blindly agree on a five groups classification of DTT‐BCCs based on five patterns of clinical situations. Objective Using this five patterns to generate an operational and comprehensive classification of BCCs. Method Testing practitioner's agreement, when using the five patterns classification to ensure that it is robust enough to be used in the practice. Generating the first version of a staging system of BCCs based on pattern recognition. Results Sixty‐two physicians, including 48 practitioners and the 14 experts who participated in the generation of the five different patterns of DTT‐BCCs, agreed on 90% of cases when classifying 199 DTT‐BCCs cases using the five patterns classification (part 1) attesting that this classification is understandable and usable in practice. In order to cover the whole field of BCCs, these five groups of DTT‐BCCs were added a group representing the huge number of easy‐to‐treat BCCs, for which sub‐classification has little interest, and a group of very rare metastatic cases, resulting in a four‐stage and seven‐substage staging system of BCCs. Conclusion A practical classification adapted to the specificities of BCCs is proposed. It is the first tumour classification based on pattern recognition of clinical situations, which proves to be consistent and usable. This EADO staging system version 1 will be improved step by step and tested as a decision tool and a prognostic instrument. |
Databáze: | OpenAIRE |
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