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Gouveia BM, Carlos G, Wadell A, Sinz C, Ahmed T, Lo SN, Rawson RV, Ferguson PM, Scolyer RA, Guitera P. In vivo reflectance confocal microscopy can detect the invasive component of lentigo maligna melanoma: Prospective analysis and case-control study. J Eur Acad Dermatol Venereol 2023; 37:1293-1301. [PMID: 36855833 PMCID: PMC10946995 DOI: 10.1111/jdv.18998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2022] [Accepted: 02/08/2023] [Indexed: 03/02/2023]
Abstract
BACKGROUND Lentigo maligna (LM), a form of melanoma in situ, has no risk of causing metastasis unless dermal invasive melanoma (LMM) supervenes. Furthermore, the detection of invasion impacts prognosis and management. OBJECTIVE To assess the accuracy of RCM for the detection of invasion component on LM/LMM lesions. METHODS In the initial case-control study, the performance of one expert in detecting LMM at the time of initial RCM assessment of LM/LMM lesions was recorded prospectively (n = 229). The cases were assessed on RCM-histopathology correlation sessions and a panel with nine RCM features was proposed to identify LMM, which was subsequently tested in a subset of initial cohort (n = 93) in the matched case-control study by two blinded observers. Univariable and multivariable logistic regression models were performed to evaluate RCM features predictive of LMM. Reproducibility of assessment of the nine RCM features was also evaluated. RESULTS A total of 229 LM/LMM cases evaluated by histopathology were assessed blindly and prospectively by an expert confocalist. On histopathology, 210 were LM and 19 were LMM cases. Correct identification of an invasive component was achieved for 17 of 19 LMM cases (89%) and the absence of a dermal component was correctly diagnosed in 190 of 210 LM cases (90%). In the matched case-control (LMM n = 35, LM n = 58), epidermal and junctional disarray, large size of melanocytes and nests of melanocytes were independent predictors of LMM on multivariate analysis. The interobserver analysis demonstrated that these three features had a fair reproducibility between the two investigators (K = 0.4). The multivariable model including those three features showed a high predictive performance AUC = 74% (CI 95% 64-85%), with sensitivity of 63% (95% CI 52-78%) and specificity of 79% (CI 95% 74-88%), and likelihood ratio of 18 (p-value 0.0026). CONCLUSION Three RCM features were predictive for identifying invasive melanoma in the background of LM.
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Grants
- Melanoma Institute Australia
- N/A MetaOptima Technology Incl., Hoffmann-La Roche Ltd, Evaxion, Provectus Biopharmaceuticals Australia, Qbiotics, Novartis, Merck Sharp & Dohme, NeraCare, AMGEN Inc., Bristol-Myers Squibb, Myriad Genetics, GlaxoSmithKline.
- APP1141295 NHMRC Practitioner Fellowship
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Affiliation(s)
- Bruna Melhoranse Gouveia
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Giuliana Carlos
- Sydney Melanoma Diagnostic Centre, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
| | - Andreanne Wadell
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- CHUS - Hôtel-Dieu, Sherbrooke, Québec, Canada
| | - Christoph Sinz
- Sydney Melanoma Diagnostic Centre, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Tasnia Ahmed
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
| | - Serigne N Lo
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Robert V Rawson
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, New South Wales, Australia
| | - Peter M Ferguson
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, New South Wales, Australia
| | - Richard A Scolyer
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital and NSW Health Pathology, Sydney, New South Wales, Australia
- Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Pascale Guitera
- Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- Sydney Melanoma Diagnostic Centre, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
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