Detection of Primary Melanoma in Individuals at Extreme High Risk

Moloney, Fergal J.; Guitera, Pascale; Coates, E. Osborne; Haass, Nikolas K.; Ho, Kenneth; Khoury, R.; O’Connell, Rachel; Raudonikis, Leo; Schmid, Helen; Mann, Graham J.; Menzies, Scott W.

doi:10.1001/jamadermatol.2014.514

Cited by 128 publications

(144 citation statements)

References 30 publications

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“…We too are of the opinion that this new technology can be useful for, above all, high-risk patients with many equivocal PSL, but obviously in the hands of specialists. Moreover, we believe that i-DDA can be added to the methods recently suggested by Moloney et al [28].…”

Section: Discussionmentioning

confidence: 89%

Computer-assisted melanoma diagnosis

et al. 2015

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In dermatology, attempts at synergy between man and machine have mainly been made to improve melanoma diagnosis. The aim of the present study was to test an 'integrated digital dermoscopy analysis' (i-DDA) system with a series of melanocytic lesions that were benign and malignant in nature, and to evaluate its discriminating power with respect to histological diagnosis. In a retrospective study we used an i-DDA system to evaluate a series of 856 excised, clinically atypical pigmented skin lesions (584 benign and 272 malignant). The system evaluated 48 parameters to be studied as possible discriminant variables, grouped into four categories (geometries, colours, textures and islands of colour) integrated with three personal metadata items (sex, age and site of lesion) and presence/absence of three dermoscopic patterns (regression structures, blue-white veil and polymorphic vascular structures). Stepwise multivariate logistic regression of i-DDA data selected nine variables with the highest possible discriminant power. At the end of the stepwise procedure the percentage of cases correctly classified by i-DDA was 89.2% (100% sensitivity and 40.8% specificity). The limitations of the study included those associated with a retrospective design and the 'a priori' exclusion of nonmelanocytic skin lesions. By incorporating numerical digital features with personal data and some dermoscopic patterns into the learning process, the proposed i-DDA improved the performance of assisted melanoma diagnosis, with the advantage that our results can be objectively repeated in any other clinical setting. Melanoma Res 25:537-542

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Section: Discussionmentioning

confidence: 89%

Computer-assisted melanoma diagnosis

et al. 2015

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“…16 The strategy used for surveillance in the Sydney HRC has been described previously. 12 In brief, this strategy involves regular extended-length consultations once every 6 months, which include a full-body skin examination augmented with dermoscopy and the use of total body photography plus dermoscopy when indicated. When a suspected lesion is identified, the lesion is excised or sequential digital dermoscopic imaging 17 of the lesion is commenced and the patient returns for nevus monitoring in 3 months.…”

Section: Study Samplementioning

confidence: 99%

“…10 Microcosting techniques are preferred for interventions that contain a large component of labor costs and in which interpatient variation in costs is likely, making a mean cost difficult to predict. 11 The treatment of patients at high risk for melanoma in a specialized surveillance clinic has been evaluated in only a few countries, [12][13][14][15] and, to our knowledge, no studies have reviewed or evaluated the costs of the health care service or the societal costs.…”

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confidence: 99%

Specialized Surveillance for Individuals at High Risk for Melanoma

et al. 2015

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“…This advice is particularly relevant to people already diagnosed with melanoma, who are at 5-to 10-fold increased risk of a subsequent primary melanoma (11,12). Targeted high-risk screening and surveillance programs have been shown to assist with early diagnosis of melanoma and are deemed more cost-effective than a population-wide screening program (13)(14)(15)). …”

Section: Introductionmentioning

confidence: 99%