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Cutaneous melanoma (CM) is potentially the most dangerous form of skin tumor and causes 90% of skin cancer mortality. A unique collaboration of multi-disciplinary experts from the European Dermatology Forum (EDF), the European Association of Dermato-Oncology (EADO) and the European Organization for Research and Treatment of Cancer (EORTC) was formed to make recommendations on CM diagnosis and treatment, based on systematic literature reviews and the experts' experience. The diagnosis of melanoma can be made clinically and shall always be confirmed with dermatoscopy. If a melanoma is suspected, a histopathological examination is always required. Sequential digital dermatoscopy and full body photography can be used in high-risk patients to improve the detection of early melanoma. Where available, confocal reflectance microscopy can also improve clinical diagnosis in special cases. Melanoma shall be classified according to the 8th version of the American Joint Committee on Cancer classification. Thin melanomas up to 0.8 mm tumor thickness do not require further imaging diagnostics. From stage IB onwards, examinations with lymph node sonography are recommended, but no further imaging examinations. From stage IIC onwards whole-body examinations with computed tomography (CT) or positron emission tomography CT (PET-CT) in combination with brain magnetic resonance imaging are recommended. From stage III and higher, mutation testing is recommended, particularly for BRAF V600 mutation. It is important to provide a structured follow-up to detect relapses and secondary primary melanomas as early as possible. There is no evidence to define the frequency and extent of examinations. A stage-based follow-up scheme is proposed which, according to the experience of the guideline group, covers the optimal requirements, but further studies may be considered. This guideline is valid until the end of 2024. © 2022 Elsevier Ltd

Background No simple classification system has emerged for `advanced basal cell carcinomas', and more generally for all difficult-to-treat BCCs (DTT-BCCs), due to the heterogeneity of situations, TNM inappropriateness to BCCs, and different approaches of different specialists. Objective To generate an operational classification, using the unconscious ability of experts to simplify the great heterogeneity of the clinical situations into a few relevant groups, which drive their treatment decisions. Method Non-supervised independent and blinded clustering of real clinical cases of DTT-BCCs was used. Fourteen international experts from different specialties independently partitioned 199 patient cases considered `difficult to treat' into as many clusters they want (

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.

Hedgehog pathway inhibitors (HPI) inactivating SMO 1, have become first line treatment for patients with locally advanced BCC (laBCC). HPI safety and efficacy have been shown in clinical trials2,3. Nevertheless, common adverse events lead to treatment discontinuation.