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Types of Shade Vary in Protection Just Like Sunscreens-Reply
Ou-Yang, Hao; Farberg, Aaron S; Rigel, Darrell S
PMID: 28854311
ISSN: 2168-6084
CID: 2679792
Integrating Skin Cancer-Related Technologies into Clinical Practice
Winkelmann, Richard R; Farberg, Aaron S; Glazer, Alex M; Cockerell, Clay J; Sober, Arthur J; Siegel, Daniel M; Leachman, Sancy A; High, Whitney A; Markowitz, Orit; Berman, Brian; Pariser, David M; Goldenberg, Gary; Rosen, Theodore; Rigel, Darrell S
Early diagnosis and treatment of melanoma improve survival. New technologies are emerging that may augment the diagnosis, assessment, and management of melanoma but penetrance into everyday practice is low. In the current health care climate, greater emphasis will be placed on the incorporation of technology for clinically suspicious pigmented lesions to facilitate better, more cost-effective management.
PMID: 28886814
ISSN: 1558-0520
CID: 2688482
Noninvasive Technologies for the Diagnosis of Cutaneous Melanoma
Winkelmann, Richard R; Farberg, Aaron S; Glazer, Alex M; Rigel, Darrell S
Multispectral analysis devices assess pigmented lesion disorganization at different levels using variable wavelengths of light. Computerized algorithms measure morphologic disorganization of the pigmented skin lesion. Aggregated data of 855 participants investigating the influence of multispectral digital skin lesion analysis (MSDSLA) on practitioner decisions to biopsy pigmented skin lesions revealed the overall sensitivity for detection of melanoma improved from 70% to 88%. Participant specificity increased from 52% to 58% after MSDSLA. Five studies using spectrophotometric intracutaneous analysis scope to evaluate suspicious pigmented skin lesions demonstrated an overall sensitivity and specificity of 85% and 81%, respectively, for the detection of melanoma.
PMID: 28886801
ISSN: 1558-0520
CID: 2688502
Assessing Genetic Expression Profiles in Melanoma Prognosis
Farberg, Aaron S; Glazer, Alex M; Winkelmann, Richard R; Rigel, Darrell S
A 31-genetic expression profile (31-GEP) test (DecisionDx-Melanoma, Castle Biosciences Inc, Friendswood, TX, USA) was developed as a diagnostic test to assist physicians in the management of cutaneous malignant melanoma. Based on a patient's primary tumor expression levels of a panel of genes (28 discriminating genes and 3 control genes), a lesion is classified as "low risk" (class 1) or "high risk" (class 2) for metastasis. Studies evaluating the clinical utility and impact of the 31-GEP test showed it positively influenced clinical management and patient care, as clinicians incorporated the additional data to modify their clinical recommendations in a risk-appropriate manner.
PMID: 28886811
ISSN: 1558-0520
CID: 2688492
The Importance of Early Recognition of Skin Cancer [Editorial]
Farberg, Aaron S; Rigel, Darrell S
PMID: 28886816
ISSN: 1558-0520
CID: 2688472
Clinical Diagnosis of Skin Cancer: Enhancing Inspection and Early Recognition
Glazer, Alex M; Rigel, Darrell S; Winkelmann, Richard R; Farberg, Aaron S
The annual incidence rate for melanoma and nonmelanoma skin cancer continues to rise and morbidity and deaths from skin cancer are increasing. Despite advances in therapeutics, the factors that most impact prognosis remain early recognition and removal of neoplasms before deep invasion or metastatic disease can occur. There are numerous public health and screening initiatives that have been introduced to help recognize disease earlier and to increase patients' awareness of signs or changes of lesions that may represent skin cancers. Early recognition and removal of suspicious lesions remains critical in significantly reducing morbidity and mortality associated with skin cancers.
PMID: 28886797
ISSN: 1558-0520
CID: 2688522
The Impact of Quantitative Data Provided by a Multi-spectral Digital Skin Lesion Analysis Device on Dermatologists'Decisions to Biopsy Pigmented Lesions
Farberg, Aaron S; Winkelmann, Richard R; Tucker, Natalie; White, Richard; Rigel, Darrell S
BACKGROUND: Early diagnosis of melanoma is critical to survival. New technologies, such as a multi-spectral digital skin lesion analysis (MSDSLA) device [MelaFind, STRATA Skin Sciences, Horsham, Pennsylvania] may be useful to enhance clinician evaluation of concerning pigmented skin lesions. Previous studies evaluated the effect of only the binary output. OBJECTIVE: The objective of this study was to determine how decisions dermatologists make regarding pigmented lesion biopsies are impacted by providing both the underlying classifier score (CS) and associated probability risk provided by multi-spectral digital skin lesion analysis. This outcome was also compared against the improvement reported with the provision of only the binary output. METHODS: Dermatologists attending an educational conference evaluated 50 pigmented lesions (25 melanomas and 25 benign lesions). Participants were asked if they would biopsy the lesion based on clinical images, and were asked this question again after being shown multi-spectral digital skin lesion analysis data that included the probability graphs and classifier score. RESULTS: Data were analyzed from a total of 160 United States board-certified dermatologists. Biopsy sensitivity for melanoma improved from 76 percent following clinical evaluation to 92 percent after quantitative multi-spectral digital skin lesion analysis information was provided (p<0.0001). Specificity improved from 52 percent to 79 percent (p<0.0001). The positive predictive value increased from 61 percent to 81 percent (p<0.01) when the quantitative data were provided. Negative predictive value also increased (68% vs. 91%, p<0.01), and overall biopsy accuracy was greater with multi-spectral digital skin lesion analysis (64% vs. 86%, p<0.001). Interrater reliability improved (intraclass correlation 0.466 before, 0.559 after). CONCLUSION: Incorporating the classifier score and probability data into physician evaluation of pigmented lesions led to both increased sensitivity and specificity, thereby resulting in more accurate biopsy decisions.
PMCID:5749615
PMID: 29344323
ISSN: 1941-2789
CID: 2915452
Increasing Diversity in Dermatology Residencies
Kailas, Ajay; Rigel, Darrell S
PMID: 28467523
ISSN: 2168-6084
CID: 2546572
Analysis of US dermatology physician assistant density
Glazer, Alex M; Holyoak, Keri; Cheever, Eileen; Rigel, Darrell S
PMID: 28522049
ISSN: 1097-6787
CID: 2563022
Analysis of Trends in Geographic Distribution of US Dermatology Workforce Density
Glazer, Alex M; Rigel, Darrell S
PMCID:5470415
PMID: 28296988
ISSN: 2168-6084
CID: 2490002