Background The presence of peripheral globules is associated with enlarging melanocytic lesions; however, there are numerous patterns of peripheral globules distribution and it remains unknown whether specific patterns can help differentiate enlarging naevi from melanoma. Objective To investigate whether morphological differences exist between the peripheral globules seen in different subsets of naevi and in melanoma. Methods A cross‐sectional study of clinical notes that mentioned peripheral globules, in addition to all melanoma images with peripheral globules on the International Skin Imaging Collaboration archive. Dermoscopic images were reviewed and annotated. Associations between diagnosis and categorical features were measured with odds ratios. Non‐parametric tests were used for continuous factors. Results 184 lesions with peripheral globules from our clinic were included in the analysis; only 6 of these proved to be melanoma. 109 melanomas with peripheral globules from the International Skin Imaging Collaboration archive were added to the analysis. Melanomas were more common on the extremities and among older individuals. Melanomas were more likely to display atypical, tiered and/or focal peripheral globules. Only 5% of melanomas lacked dermoscopic melanoma‐specific structures compared to 48% of naevi. Conclusions Melanocytic lesions with atypical or asymmetrically distributed peripheral globules, especially when located on the extremities, should raise suspicion for malignancy. Melanocytic lesions with typical and symmetrically distributed peripheral globules, and with no other concerning dermoscopic features, are unlikely to be malignant.
IMPORTANCEThe performance of prognostic gene expression profile (GEP) tests for cutaneous melanoma is poorly characterized. OBJECTIVE To systematically assess the performance of commercially available GEP tests in patients with American Joint Committee on Cancer (AJCC) stage I or stage II disease.DATA SOURCES For this systematic review and meta-analysis, comprehensive searches of PubMed/MEDLINE, Embase, and Web of Science were conducted on December 12, 2019, for English-language studies of humans without date restrictions.STUDY SELECTION Two reviewers identified GEP external validation studies of patients with localized melanoma. After exclusion criteria were applied, 7 studies (8%; 5 assessing DecisionDx-Melanoma and 2 assessing MelaGenix) were included.DATA EXTRACTION AND SYNTHESIS Data were extracted using an adaptation of the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS-PF). When feasible, meta-analysis using random-effects models was performed. Risk of bias and level of evidence were assessed with the Quality in Prognosis Studies tool and an adaptation of Grading of Recommendations Assessment, Development, and Evaluation.MAIN OUTCOMES AND MEASURES Proportion of patients with or without melanoma recurrence correctly classified by the GEP test as being at high or low risk. RESULTSIn the 7 included studies, a total of 1450 study participants contributed data (age and sex unknown). The performance of both GEP tests varied by AJCC stage. Of patients tested with DecisionDx-Melanoma, 623 had stage I disease (6 true-positive [TP], 15 false-negative, 61 false-positive, and 541 true-negative [TN] results) and 212 had stage II disease (59 TP, 13 FN, 78 FP, and 62 TN results). Among patients with recurrence, DecisionDx-Melanoma correctly classified 29% with stage I disease and 82% with stage II disease. Among patients without recurrence, the test correctly classified 90% with stage I disease and 44% with stage II disease. Of patients tested with MelaGenix, 88 had stage I disease (7 TP, 15 FN, 15 FP, and 51 TN results) and 245 had stage II disease (59 TP, 19 FN, 95 FP, and 72 TN results). Among patients with recurrence, MelaGenix correctly classified 32% with stage I disease and 76% with stage II disease. Among patients without recurrence, the test correctly classified 77% with stage I disease and 43% with stage II disease. CONCLUSIONS AND RELEVANCEThe prognostic ability of GEP tests among patients with localized melanoma varied by AJCC stage and appeared to be poor at correctly identifying recurrence in patients with stage I disease, suggesting limited potential for clinical utility in these patients.
Background Nevus-associated melanomas (NAM) account for 30% of all melanomas and are associated with younger age and with thinner Breslow thickness. Previous studies of NAM dermoscopy found conflicting results.Objective To compare the clinical and dermoscopic features of NAM and de novo melanomas (DNM), stratified by melanoma thickness, in a relatively large cohort of patients.Methods A cross-sectional study of all melanomas biopsied between 2004 and 2019 at a large cancer centre. Lesions were categorized as in situ and invasive NAM or DNM. Dermoscopic images were reviewed and annotated. Associations between melanoma subtype and dermoscopic features were analysed via logistic regression modelling. Bivariate analyses were conducted using non-parametric bootstrap and chi-squared methods. ResultsThe study included 160 NAM (86 in situ and 74 invasive) and 218 DNM (109 in situ and 109 invasive). NAM were associated with younger age, greater likelihood of being present on the torso, and thinner Breslow thickness. NAM were 2.5 times more likely to show a negative pigment network than DNM. In situ NAM were 2.1 and two times more likely to display dermoscopic area without definable structures and tan structureless areas than DNM, respectively. In situ melanomas were more likely to present a pigment network, and invasive melanomas more commonly presented scar-like depigmentation and shiny white structures. Streaks, blotches and shiny white structures were associated with deeper Breslow depth.Conclusions Even though the nevus component of NAM could not be identified dermoscopically in the current series, negative pigment network, tan structureless areas and areas without definable structures are dermoscopic clues for NAM.
Background Existing artificial intelligence for melanoma detection has relied on analysing images of lesions of clinical interest, which may lead to missed melanomas. Tools analysing the entire skin surface are lacking. Objectives To determine if melanoma can be distinguished from other skin lesions using data from automated analysis of 3D‐images. Methods Single‐centre, retrospective, observational convenience sample of patients diagnosed with melanoma at a tertiary care cancer hospital. Eligible participants were those with a whole‐body 3D‐image captured within 90 days prior to the diagnostic skin biopsy. 3D‐images were obtained as standard of care using VECTRA WB360 Whole Body 3‐dimensional Imaging System (Canfield Scientific). Automated data from image processing (i.e. lesion size, colour, border) for all eligible participants were exported from VECTRA DermaGraphix research software for analysis. The main outcome was the area under the receiver operating characteristic curve (AUC). Results A total of 35 patients contributed 23,538 automatically identified skin lesions >2 mm in largest diameter (102–3021 lesions per participant). All were White patients and 23 (66%) were males. The median (range) age was 64 years (26–89). There were 49 lesions of melanoma and 22,489 lesions that were not melanoma. The AUC for the prediction model was 0.94 (95% CI: 0.92–0.96). Considering all lesions in a patient‐level analysis, 14 (28%) melanoma lesions had the highest predicted score or were in the 99th percentile among all lesions for an individual patient. Conclusions In this proof‐of‐concept pilot study, we demonstrated that automated analysis of whole‐body 3D‐images using simple image processing techniques can discriminate melanoma from other skin lesions with high accuracy. Further studies with larger, higher quality, and more representative 3D‐imaging datasets would be needed to improve and validate these results.
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