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- Errichetti, E., et al.
(author)
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Standardization of dermoscopic terminology and basic dermoscopic parameters to evaluate in general dermatology (non-neoplastic dermatoses): an expert consensus on behalf of the International Dermoscopy Society
- 2020
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In: British Journal of Dermatology. - : Oxford University Press (OUP). - 0007-0963 .- 1365-2133. ; 182:2, s. 454-467
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Journal article (peer-reviewed)abstract
- Background Over the last few years, several articles on dermoscopy of non-neoplastic dermatoses have been published, yet there is poor consistency in the terminology among different studies. Objectives We aimed to standardize the dermoscopic terminology and identify basic parameters to evaluate in non-neoplastic dermatoses through an expert consensus. Methods The modified Delphi method was followed, with two phases: (i) identification of a list of possible items based on a systematic literature review and (ii) selection of parameters by a panel of experts through a three-step iterative procedure (blinded e-mail interaction in rounds 1 and 3 and a face-to-face meeting in round 2). Initial panellists were recruited via e-mail from all over the world based on their expertise on dermoscopy of non-neoplastic dermatoses. Results Twenty-four international experts took part in all rounds of the consensus and 13 further international participants were also involved in round 2. Five standardized basic parameters were identified: (i) vessels (including morphology and distribution); (ii) scales (including colour and distribution); (iii) follicular findings; (iv) 'other structures' (including colour and morphology); and (v) 'specific clues'. For each of them, possible variables were selected, with a total of 31 different subitems reaching agreement at the end of the consensus (all of the 29 proposed initially plus two more added in the course of the consensus procedure). Conclusions This expert consensus provides a set of standardized basic dermoscopic parameters to follow when evaluating inflammatory, infiltrative and infectious dermatoses. This tool, if adopted by clinicians and researchers in this field, is likely to enhance the reproducibility and comparability of existing and future research findings and uniformly expand the universal knowledge on dermoscopy in general dermatology.
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- Horgan, D, et al.
(author)
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How Can the EU Beating Cancer Plan Help in Tackling Lung Cancer, Colorectal Cancer, Breast Cancer and Melanoma?
- 2022
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In: Healthcare (Basel, Switzerland). - : MDPI AG. - 2227-9032. ; 10:9
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Journal article (peer-reviewed)abstract
- Cancer is the second leading cause of mortality in EU countries, and the needs to tackle cancer are obvious. New scientific understanding, techniques and methodologies are opening up horizons for significant improvements in diagnosis and care. However, take-up is uneven, research needs and potential outstrip currently available resources, manifestly beneficial practices—such as population-level screening for lung cancer—are still not generalised, and the quality of life of patients and survivors is only beginning to be given attention it merits. This paper, mainly based on a series of multistakeholder expert workshops organised by the European Alliance for Personalised Medicine (EAPM), looks at some of those specifics in the interest of planning a way forward. Part of this exercise also involves taking account of the specific nature of Europe and its constituent countries, where the complexities of planning a way forward are redoubled by the wide variations in national and regional approaches to cancer, local epidemiology and the wide disparities in health systems. Despite all the differences between cancers and national and regional resources and approaches to cancer care, there is a common objective in pursuing broader and more equal access to the best available care for all European citizens.
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- Tschandl, P., et al.
(author)
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Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study
- 2019
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In: The Lancet Oncology. - 1470-2045 .- 1474-5488. ; 20:7, s. 938-947
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Journal article (peer-reviewed)abstract
- Background: Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human experts is unclear. The aim of this study was to compare the diagnostic accuracy of state-of-the-art machine-learning algorithms with human readers for all clinically relevant types of benign and malignant pigmented skin lesions. Methods: For this open, web-based, international, diagnostic study, human readers were asked to diagnose dermatoscopic images selected randomly in 30-image batches from a test set of 1511 images. The diagnoses from human readers were compared with those of 139 algorithms created by 77 machine-learning labs, who participated in the International Skin Imaging Collaboration 2018 challenge and received a training set of 10 015 images in advance. The ground truth of each lesion fell into one of seven predefined disease categories: intraepithelial carcinoma including actinic keratoses and Bowen's disease; basal cell carcinoma; benign keratinocytic lesions including solar lentigo, seborrheic keratosis and lichen planus-like keratosis; dermatofibroma; melanoma; melanocytic nevus; and vascular lesions. The two main outcomes were the differences in the number of correct specific diagnoses per batch between all human readers and the top three algorithms, and between human experts and the top three algorithms. Findings: Between Aug 4, 2018, and Sept 30, 2018, 511 human readers from 63 countries had at least one attempt in the reader study. 283 (55·4%) of 511 human readers were board-certified dermatologists, 118 (23·1%) were dermatology residents, and 83 (16·2%) were general practitioners. When comparing all human readers with all machine-learning algorithms, the algorithms achieved a mean of 2·01 (95% CI 1·97 to 2·04; p<0·0001) more correct diagnoses (17·91 [SD 3·42] vs 19·92 [4·27]). 27 human experts with more than 10 years of experience achieved a mean of 18·78 (SD 3·15) correct answers, compared with 25·43 (1·95) correct answers for the top three machine algorithms (mean difference 6·65, 95% CI 6·06–7·25; p<0·0001). The difference between human experts and the top three algorithms was significantly lower for images in the test set that were collected from sources not included in the training set (human underperformance of 11·4%, 95% CI 9·9–12·9 vs 3·6%, 0·8–6·3; p<0·0001). Interpretation: State-of-the-art machine-learning classifiers outperformed human experts in the diagnosis of pigmented skin lesions and should have a more important role in clinical practice. However, a possible limitation of these algorithms is their decreased performance for out-of-distribution images, which should be addressed in future research. Funding: None. © 2019 Elsevier Ltd
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- Barrett, Jennifer H., et al.
(author)
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Genome-wide association study identifies three new melanoma susceptibility loci
- 2011
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 43:11, s. 1108-1113
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Journal article (peer-reviewed)abstract
- We report a genome-wide association study for melanoma that was conducted by the GenoMEL Consortium. Our discovery phase included 2,981 individuals with melanoma and 1,982 study-specific control individuals of European ancestry, as well as an additional 6,426 control subjects from French or British populations, all of whom were genotyped for 317,000 or 610,000 single-nucleotide polymorphisms (SNPs). Our analysis replicated previously known melanoma susceptibility loci. Seven new regions with at least one SNP with P < 10(-5) and further local imputed or genotyped support were selected for replication using two other genome-wide studies (from Australia and Texas, USA). Additional replication came from case-control series from the UK and The Netherlands. Variants at three of the seven loci replicated at P < 10(-3): an SNP in ATM (rs1801516, overall P = 3.4 x 10(-9)), an SNP in MX2 (rs45430, P = 2.9 x 10-9) and an SNP adjacent to CASP8 (rs13016963, P = 8.6 x 10(-10)). A fourth locus near CCND1 remains of potential interest, showing suggestive but inconclusive evidence of replication (rs1485993, overall P = 4.6 x 10(-7) under a fixed-effects model and P = 1.2 x 10(-3) under a random-effects model). These newly associated variants showed no association with nevus or pigmentation phenotypes in a large British case-control series.
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- Bishop, D. Timothy, et al.
(author)
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Genome-wide association study identifies three loci associated with melanoma risk
- 2009
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 41:8, s. 920-925
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Journal article (peer-reviewed)abstract
- We report a genome-wide association study of melanoma conducted by the GenoMEL consortium based on 317K tagging SNPs for 1,650 selected cases and 4,336 controls, with replication in an additional two cohorts (1,149 selected cases and 964 controls from GenoMEL, and a population-based case-control study in Leeds of 1,163 cases and 903 controls). The genome-wide screen identified five loci with genotyped or imputed SNPs reaching P < 5 x 10(-7). Three of these loci were replicated: 16q24 encompassing MC1R (combined P = 2.54 x 10(-27) for rs258322), 11q14-q21 encompassing TYR (P = 2.41 x 10(-14) for rs1393350) and 9p21 adjacent to MTAP and flanking CDKN2A (P = 4.03 x 10(-7) for rs7023329). MC1R and TYR are associated with pigmentation, freckling and cutaneous sun sensitivity, well-recognized melanoma risk factors. Common variants within the 9p21 locus have not previously been associated with melanoma. Despite wide variation in allele frequency, these genetic variants show notable homogeneity of effect across populations of European ancestry living at different latitudes and show independent association to disease risk.
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- Liopyris, Konstantinos, et al.
(author)
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Expert agreement on the presence and spatial localization of melanocytic features in dermoscopy.
- 2023
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In: The Journal of investigative dermatology. - 1523-1747. ; 144:3
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Journal article (peer-reviewed)abstract
- Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. Herein we attempted to evaluate agreement among experts on 'exemplar images' not only for the presence of melanocytic-specific features but also for spatial localization. This was a cross-sectional, multicenter, observational study. Dermoscopy images exhibiting at least one of 31 melanocytic-specific features were submitted by 25 world experts as 'exemplars'. Using a web-based platform that allows for image mark-up of specific contrast-defined regions (superpixels), 20 expert readers annotated 248 dermoscopic images in collections of 62 images. Each collection was reviewed by five independent readers. A total of 4,507 feature observations were performed. Good-to-excellent agreement was found for 14 of 31 features (45.2%), with 8 achieving excellent agreement (Gwet's AC >0.75) and 7 of them being melanoma-specific features. These features were: 'Peppering /Granularity' (0.91); 'Shiny White Streaks' (0.89); 'Typical Pigment network' (0.83); 'Blotch Irregular' (0.82); 'Negative Network' (0.81); 'Irregular Globules' (0.78); 'Dotted Vessels' (0.77) and 'Blue Whitish Veil' (0.76). By utilizing an exemplar dataset, good-to-excellent agreement was found for 14 features that have previously been shown useful in discriminating nevi from melanoma. All images are public (www.isic-archive.com) and can be used for education, scientific communication and machine learning experiments.
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- Longo, C., et al.
(author)
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Delphi Consensus Among International Experts on the Diagnosis, Management, and Surveillance for Lentigo Maligna
- 2023
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In: Dermatology Practical & Conceptual. - 2160-9381. ; 13:3
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Journal article (peer-reviewed)abstract
- Introduction: Melanoma of the lentigo maligna (LM) type is challenging. There is lack of consensus on the optimal diagnosis, treatment, and follow-up. Objectives: To obtain general consensus on the diagnosis, treatment, and follow-up for LM. Methods: A modified Delphi method was used. The invited participants were either members of the International Dermoscopy Society, academic experts, or authors of published articles relating to skin cancer and melanoma. Participants were required to respond across three rounds using a 4-point Likert scale). Consensus was defined as >75% of participants agreeing/strongly agreeing or disagreeing/strongly disagreeing. Results: Of the 31 experts invited to participate in this Delphi study, 29 participants completed Round 1 (89.9% response rate), 25/31 completed Round 2 (77.5% response rate), and 25/31 completed Round 3 (77.5% response rate). Experts agreed that LM diagnosis should be based on a clinical and dermatoscopic approach (92%) followed by a biopsy. The most appropriate primary treatment of LM was deemed to be margin-controlled surgery (83.3%), although non-surgical modalities, especially imiquimod, were commonly used either as alternative off-label primary treatment in selected patients or as adjuvant therapy following surgery; 62% participants responded life-long clinical follow-up was needed for LM. Conclusions: Clinical and histological diagnosis of LM is challenging and should be based on macroscopic, dermatoscopic, and RCM examination followed by a biopsy. Different treatment modalities and follow-up should be carefully discussed with the patient.
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- Menzies, Scott W, et al.
(author)
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Dermoscopic Evaluation of Nodular Melanoma.
- 2013
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In: JAMA dermatology (Chicago, Ill.). - : American Medical Association (AMA). - 2168-6084 .- 2168-6068. ; 149:6, s. 699-709
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Journal article (peer-reviewed)abstract
- IMPORTANCE Nodular melanoma (NM) is a rapidly progressing potentially lethal skin tumor for which early diagnosis is critical. OBJECTIVE To determine the dermoscopy features of NM. DESIGN Eighty-three cases of NM, 134 of invasive non-NM, 115 of nodular benign melanocytic tumors, and 135 of nodular nonmelanocytic tumors were scored for dermoscopy features using modified and previously described methods. Lesions were separated into amelanotic/hypomelanotic or pigmented to assess outcomes. SETTING Predominantly hospital-based clinics from 5 continents. MAIN OUTCOME MEASURES Sensitivity, specificity, and odds ratios for features/models for the diagnosis of melanoma. RESULTS Nodular melanoma occurred more frequently as amelanotic/hypomelanotic (37.3%) than did invasive non-NM (7.5%). Pigmented NM had a more frequent (compared with invasive non-NM; in descending order of odds ratio) symmetrical pigmentation pattern (5.8% vs 0.8%), large-diameter vessels, areas of homogeneous blue pigmentation, symmetrical shape, predominant peripheral vessels, blue-white veil, pink color, black color, and milky red/pink areas. Pigmented NM less frequently displayed an atypical broadened network, pigment network or pseudonetwork, multiple blue-gray dots, scarlike depigmentation, irregularly distributed and sized brown dots and globules, tan color, irregularly shaped depigmentation, and irregularly distributed and sized dots and globules of any color. The most important positive correlating features of pigmented NM vs nodular nonmelanoma were peripheral black dots/globules, multiple brown dots, irregular black dots/globules, blue-white veil, homogeneous blue pigmentation, 5 to 6 colors, and black color. A model to classify a lesion as melanocytic gave a high sensitivity (>98.0%) for both nodular pigmented and nonnodular pigmented melanoma but a lower sensitivity for amelanotic/hypomelanotic NM (84%). A method for diagnosing amelanotic/hypomelanotic malignant lesions (including basal cell carcinoma) gave a 93% sensitivity and 70% specificity for NM. CONCLUSIONS AND RELEVANCE When a progressively growing, symmetrically patterned melanocytic nodule is identified, NM needs to be excluded.
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