Non-biologic systemic treatments for atopic dermatitis: Current state of the art and future directions.

Atopic dermatitis (AD) is a prevalent chronic inflammatory skin condition with an unpredictable clinical course, associated with a significant impact on quality of life. The pathophysiology of AD involves a complex interplay between impaired skin barrier function, immune dysregulation, genetic susceptibility and environmental factors. Advances in understanding of the immunological mechanisms that underpin AD have heralded the recognition of multiple novel therapeutic targets to bolster the systemic treatment armamentarium for patients with severe AD. This review examines current and future directions of non-biologic systemic treatments for AD, with a focus on their mechanism of action, efficacy and safety, and the key considerations to help inform treatment decisions. We summarize new developments in small molecule systemic therapies which have the potential to further advance our management of AD in this new era of precision medicine.

Retinoid-induced skeletal hyperostosis in disorders of keratinization.

For disorders of keratinization, topical treatment alone may be ineffective, and systemic retinoid therapy may be indicated. Treatment with systemic retinoids (acitretin, isotretinoin and alitretinoin) has been shown to be effective in reducing disease severity; however, potentially rare adverse effects (AEs) may occur, including hyperostotic skeletal changes. The true prevalence of this AE in adult patients administered life-long therapy is unknown. We identified 3 of 127 (2.4%) patients (with ichthyosis or Darier disease) who had been prescribed isotretinoin with or without acitretin, and who developed radiological signs and clinical symptoms of hyperostosis and ligamentous ossification. This clinical review highlights the significance of retinoid-induced skeletal hyperostosis in patients prescribed long-term, high-dose retinoid therapy for disorders of keratinization. Patients commencing systemic retinoid therapy, particularly women of childbearing age, should be counselled about this important and potentially serious AE, especially if long-term treatment is indicated.

Systematic review of deep learning image analyses for the diagnosis and monitoring of skin disease.

Skin diseases affect one-third of the global population, posing a major healthcare burden. Deep learning may optimise healthcare workflows through processing skin images via neural networks to make predictions. A focus of deep learning research is skin lesion triage to detect cancer, but this may not translate to the wider scope of >2000 other skin diseases. We searched for studies applying deep learning to skin images, excluding benign/malignant lesions (1/1/2000-23/6/2022, PROSPERO CRD42022309935). The primary outcome was accuracy of deep learning algorithms in disease diagnosis or severity assessment. We modified QUADAS-2 for quality assessment. Of 13,857 references identified, 64 were included. The most studied diseases were acne, psoriasis, eczema, rosacea, vitiligo, urticaria. Deep learning algorithms had high specificity and variable sensitivity in diagnosing these conditions. Accuracy of algorithms in diagnosing acne (median 94%, IQR 86-98; n = 11), rosacea (94%, 90-97; n = 4), eczema (93%, 90-99; n = 9) and psoriasis (89%, 78-92; n = 8) was high. Accuracy for grading severity was highest for psoriasis (range 93-100%, n = 2), eczema (88%, n = 1), and acne (67-86%, n = 4). However, 59 (92%) studies had high risk-of-bias judgements and 62 (97%) had high-level applicability concerns. Only 12 (19%) reported participant ethnicity/skin type. Twenty-four (37.5%) evaluated the algorithm in an independent dataset, clinical setting or prospectively. These data indicate potential of deep learning image analysis in diagnosing and monitoring common skin diseases. Current research has important methodological/reporting limitations. Real-world, prospectively-acquired image datasets with external validation/testing will advance deep learning beyond the current experimental phase towards clinically-useful tools to mitigate rising health and cost impacts of skin disease.

Acne keloidalis nuchae: risk factors and associated disorders - a retrospective study.

BACKGROUND: Acne keloidalis nuchae (AKN) is a chronic scarring folliculitis which usually occurs in young adult males of African descent. Studies have suggested that AKN may be associated with other dermatologic conditions and even general medical disorders. The aim of this study was to identify cutaneous and extracutaneous associated disorders and to examine risk factors in our population for developing AKN. METHODS: The study was a retrospective, descriptive, and analytical study conducted at the Dermatology Outpatient department of the University Hospital of the West Indies. Data were obtained from the medical records of patients diagnosed over a 15-year period (2000-2014). RESULTS: There were 1031 new patients during the study period. Of these, 43 (4.2%) had AKN. The male to female ratio for AKN was approximately 7:1. Pseudofolliculitis barbae was associated with keloidal plaques on the scalp (OR = 6.22, P = 0.036). Also, when the duration of AKN was divided into two groups (0-5 years and greater than 5 years), there was an association between keloidal plaques and duration of greater than 5 years (OR = 7.5, P = 0.032). However, when the odds ratio was adjusted, only the duration of AKN remained significantly associated with keloidal plaques (OR = 7.08, P = 0.047). Chronic scalp folliculitis (P = 0.001) and the presence of any component disease of the metabolic syndrome (OR = 14, P = 0.008) and specifically hypertension (OR = 6.75, P = 0.036) were significantly associated with the extension of the lesions beyond the nape and occipital scalp. CONCLUSIONS: Pseudofolliculitis barbae, chronic scalp folliculitis, and aspects of the metabolic syndrome may be associated with acne keloidalis nuchae.