Oral minoxidil for late alopecia in cancer survivors.

PURPOSE: Late alopecia, defined as incomplete hair regrowth > 6 months following cytotoxic chemotherapy or > 6 months from initiation of endocrine therapy, negatively impacts quality of life and may affect dose intensity of adjuvant therapy. This study investigates the effect of oral minoxidil in women with chemotherapy and/or endocrine therapy-induced late alopecia. METHODS: The rate of clinical response was assessed by standardized photography and quantitated with trichoscopy. RESULTS: Two hundred and sixteen patients (mean age 57.8 ± 13.7) were included. The most common cancer diagnosis was breast, in 170 patients (79.1%). Alopecia developed after chemotherapy in 31 (14.4%) patients, endocrine monotherapy in 65 (30.1%) patients, and chemotherapy followed by endocrine therapy in 120 (55.6%) patients. In 119 patients, standardized photography assessments were used to determine clinical change in alopecia after a median of 105 (IQR = 70) days on oral minoxidil and revealed improvement in 88 (74%) patients. Forty-two patients received quantitative trichoscopic assessments at baseline and at follow-up after a median of 91 (IQR = 126) days on oral minoxidil. Patients had clinically and statistically significant increases in frontal hair shaft density (from 124.2 hairs/cm2 at initial to 153.2 hairs/cm2 at follow-up assessment, p = 0.008) and occipital shaft density (from 100.3 hairs/cm2 at initial to 123.5 hairs/cm2 at follow-up assessment. p = 0.004). No patients discontinued oral minoxidil due to adverse events. CONCLUSIONS: Overall, oral minoxidil was well tolerated by patients and may benefit both frontal and occipital late alopecia in cancer survivors treated with cytotoxic and/or endocrine therapy by increasing hair shaft and follicle density.

Prospective validation of dermoscopy-based open-source artificial intelligence for melanoma diagnosis (PROVE-AI study).

The use of artificial intelligence (AI) has the potential to improve the assessment of lesions suspicious of melanoma, but few clinical studies have been conducted. We validated the accuracy of an open-source, non-commercial AI algorithm for melanoma diagnosis and assessed its potential impact on dermatologist decision-making. We conducted a prospective, observational clinical study to assess the diagnostic accuracy of the AI algorithm (ADAE) in predicting melanoma from dermoscopy skin lesion images. The primary aim was to assess the reliability of ADAE's sensitivity at a predefined threshold of 95%. Patients who had consented for a skin biopsy to exclude melanoma were eligible. Dermatologists also estimated the probability of melanoma and indicated management choices before and after real-time exposure to ADAE scores. All lesions underwent biopsy. Four hundred thirty-five participants were enrolled and contributed 603 lesions (95 melanomas). Participants had a mean age of 59 years, 54% were female, and 96% were White individuals. At the predetermined 95% sensitivity threshold, ADAE had a sensitivity of 96.8% (95% CI: 91.1-98.9%) and specificity of 37.4% (95% CI: 33.3-41.7%). The dermatologists' ability to assess melanoma risk significantly improved after ADAE exposure (AUC 0.7798 vs. 0.8161, p = 0.042). Post-ADAE dermatologist decisions also had equivalent or higher net benefit compared to biopsying all lesions. We validated the accuracy of an open-source melanoma AI algorithm and showed its theoretical potential for improving dermatology experts' ability to evaluate lesions suspicious of melanoma. Larger randomized trials are needed to fully evaluate the potential of adopting this AI algorithm into clinical workflows.

Features of Skin Cancer in Black Individuals: A Single-Institution Retrospective Cohort Study.

Introduction: Minimal knowledge exists regarding skin cancers in Black individuals, which may adversely affect patient care. Objectives: To describe clinical features and risk factors of skin cancers in Black individuals. Methods: Retrospective study of Black individuals diagnosed with skin cancer between January 2000 and January 2020 at our institution. Results: 38,589 patients were diagnosed with skin cancer, of which 165 were Black individuals. One-hundred-thirteen of these Black individuals were diagnosed with melanoma, 35 with squamous cell carcinoma (SCC), and 17 with basal cell carcinoma (BCC). Most melanomas (80.0%, n = 90) were of the acral subtype; 75% (6 of 8 cases with dermoscopic images) displayed a parallel ridge pattern (PRP). The surrounding uninvolved background skin was visible in 7 cases, all demonstrating a PRP. This disappeared adjacent to most of the melanoma lesions (n = 4, 57.1%). creating a peripheral hypopigmented "halo". The nonmelanoma skin cancers were pigmented and had similar dermoscopic features as reported in predominantly White populations. Most SCCs (n = 5, 71.4%) had a hypopigmented "halo" and most BCCs (n = 10, 55.6%) had an accentuated reticular network adjacent to the lesions. Conclusions: Skin cancers are pigmented in Black individuals. In both acral melanomas and SCCs, we noted a peripheral rim of hypopigmentation between the lesions and the surrounding uninvolved background skin, while BCCs had accentuation of the background pigmentation adjacent to the lesions. Most acral melanomas displayed a PRP, which was also seen in surrounding uninvolved background skin.