by Richard R. Winkelmann, DO; Jane Yoo, MD, MPP; Natlie Tucker, BS; Richard White, MS; Darrell S. Rigel, MD, MS
Richard R. Winkelmann, DO, is from Rigel Dermatology, New York, New York; Jane Yoo, MD, MPP, is from Department of Dermatology, Yale School of Medicine, Yale University, New Haven, Connecticut; Natalie Tucker, BS, MELA Sciences Inc., Irvington, New York; Richard White, MS, Iris Interactive System, Cody, Wyoming; Darrell S. Rigel, MD, MS, is from the Department of Dermatology, New York University School of Medicine, New York, New York
ABSTRACT
Objective: Risk prediction models for primary malignant melanoma thus far have relied on qualitative patient information. The authors propose a quantitative diagnostic predictive probability model using Multispectral Digital Skin Lesion Analysis for melanoma and other high-risk pigmented lesions and evaluate its effectiveness optimizing biopsy decisions by dermatologists. Design: Data from 1,632 pigmented lesions analyzed by a Multispectral Digital Skin Lesion Analysis device were used to perform a logistic regression analysis. This new quantitative melanoma or melanoma/atypical melanocytic hyperplasia/high-grade dysplastic nevus probability model was then evaluated to determine its impact on dermatologist decisions to biopsy pigmented lesions clinically suggestive of melanoma. Participants were given an electronic keypad and answered “yes” or “no” if they would biopsy each of 12 pigmented lesions when presented first with patient history, clinical images, and dermoscopic images and again when subsequently shown Multispectral Digital Skin Lesion Analysis data. Setting/participants: Study of 191 dermatologists at a medical conference. Measurements: Sensitivity, specificity, biopsy accuracy, overall biopsy rate, and percentage dermatologists biopsying all five melanomas. Results: Dermatologists were significantly more sensitive, specific, and accurate while decreasing overall biopsy rates with Multispectral Digital Skin Lesion Analysis probability information. Conclusion: Integration of Multispectral Digital Skin Lesion Analysis probability information in the biopsy evaluation and selection process of pigmented lesions has the potential to improve melanoma sensitivity of dermatologists without the concomitant costs associated with additional biopsies being performed. (J Clin Aesthet Dermatol. 2014;7(12):16–18.)