Faculty Bibliography

Mohs micrographic surgery (MMS) is a tissue-sparing surgical technique that is the standard of care for treatment of several cutaneous malignancies. Current US and international guidelines recommend wide local excision as the first-line surgical therapy for noninvasive melanoma, and use of MMS may be appropriate for melanoma-in-situ, lentigo maligna, and potentially thin invasive malignant melanoma. Based on available literature, MMS can potentially result in lower recurrence rates of melanoma, especially when using immunostaining. This chapter explores the existing evidence supporting MMS for treatment of melanoma as well as its challenges.

Metastatic melanoma is an aggressive and treatment-resistant skin cancer with a low 5-year survival rate of 27%. Historically considered radioresistant, melanoma's response to radiation therapy (RT) has evolved, especially when integrated with systemic therapies like immune checkpoint inhibitors (ICIs). RT is now recognized for its utility in local control, palliative care, and brain metastasis management. Emerging evidence shows RT's synergy with ICIs through mechanisms like the abscopal effect. This article explores RT's evolving role in metastatic melanoma treatment, focusing on integration with modern therapies and ongoing research into optimizing outcomes.

Melanoma is a type of cutaneous malignancy responsible for thousands of deaths every year. Despite improvements in therapuetics and identification, incidence rate and the total number of associated deaths for melanoma continue to increase annually. Melanoma outcomes are impacted by numerous variables, and sex, age, race, socioeconomic status, and tanning bed use have been studied extensively as they relate to melanoma. Additionally, this article explores the trends in the changing melanoma incidence and mortality rates per modifiable variable and subpopulation.

Melanoma, an aggressive skin cancer, requires timely diagnostics for improved patient outcomes. The ABCDE criteria-assessing asymmetry, borders, color, diameter, and evolution-serve as foundational guidelines for early detection. Non-invasive tools like dermoscopy, total body photography, and advanced imaging techniques enhance visualization of skin lesions, while artificial intelligence-driven algorithms improve diagnostic accuracy. Despite these advancements, biopsy remains the gold standard for definitive diagnosis. This multifaceted approach highlights the need for integrating traditional methods with innovative technologies to optimize melanoma evaluation and management, ultimately leading to better patient outcomes.

Genomic advancements have transformed melanoma prognosis by identifying key genetic alterations that influence disease progression and treatment outcomes. Gene expression profiling (GEP) tests, including the 31-GEP, 11-GEP, and 8-GEP + CP, refine traditional staging by stratifying patients based on recurrence and metastasis risk. These tests enhance clinical decision-making by guiding sentinel lymph node biopsy selection, surveillance intensity, and adjuvant therapy use. Studies confirm their prognostic accuracy, linking GEP results to survival outcomes. Despite their potential, challenges like cost and validation limit widespread adoption. As research progresses, integrating genomic data with traditional staging could further personalize melanoma management.

BACKGROUND:Hedgehog inhibitors (HHIs) can be used to treat patients with locally advanced basal cell carcinoma (laBCC) who are not candidates for surgery or radiation or whose tumors have recurred following radiation or surgery. The purpose of this expert consensus panel is to guide HHI usage, thereby informing clinical decision-making and optimizing patient care. METHODS:A comprehensive literature search was completed on May 1, 2024, using the keywords "basal cell carcinoma," "hedgehog inhibitor," "sonidegib," and "vismodegib". A panel of eight dermatologists with significant expertise in the treatment of BCC gathered to review the articles and create consensus statements. A modified Delphi process was used to approve each statement and a strength of recommendation was assigned. RESULTS:The literature search produced 200 articles. A screening of the studies resulted in 19 articles that met the criteria. The panel unanimously voted to adopt 8 consensus statements and recommendations, two were given a strength of "A", three were given a strength of "B", and three were given a strength of "C". CONCLUSION/CONCLUSIONS:Sonidegib and vismodegib are FDA-approved HHIs that can decrease the size of laBCC tumors prior to surgical intervention or be used as primary therapy in certain circumstances. The most common adverse events include muscle spasms, alopecia, and taste alterations. CITATION/BACKGROUND:Burshtein J, Shah M, Zakria D, et al. Efficacy and safety of hedgehog inhibitors for advanced basal cell carcinoma: an expert consensus panel. J Drugs Dermatol. 2025;24(5):465-471. doi:10.36849/JDD.8827.

BACKGROUND:Patients with skin lesions suspicious for skin cancer or atypical melanocytic nevi of uncertain malignant potential often present to dermatologists, who may have variable dermoscopy triage clinical experience. OBJECTIVE:To evaluate the clinical utility of a digital dermoscopy image-based artificial intelligence algorithm (DDI-AI device) on the diagnosis and management of skin cancers by dermatologists. METHODS:Thirty-six United States board-certified dermatologists evaluated 50 clinical images and 50 digital dermoscopy images of the same skin lesions (25 malignant and 25 benign), first without and then with knowledge of the DDI-AI device output. Participants indicated whether they thought the lesion was likely benign (unremarkable) or malignant (suspicious). RESULTS:The management sensitivity of dermatologists using the DDI-AI device was 91.1%, compared to 84.3% with DDI, and 70.0% with clinical images. The management specificity was 71.0%, compared to 68.4% and 64.9%, respectively. The diagnostic sensitivity of dermatologists using the DDI-AI device was 86.1%, compared to 78.8% with DDI, and 63.4% with clinical images. Diagnostic specificity using the DDI-AI device increased to 80.7%, compared to 75.9% and 73.6%, respectively. CONCLUSION/CONCLUSIONS:The use of the DDI-AI device may quickly, safely, and effectively improve dermoscopy performance, skin cancer diagnosis, and management when used by dermatologists, independent of training and experience.