How can physicians improve medication adherence and outcomes in dermatological conditions?

INTRODUCTION: Medication non-adherence is a major contributor to suboptimal disease treatment across medical specialties and is a particular hurdle with topicals. While adherence is a patient behavior affected by many socioeconomic and health system factors, physicians can play an important role in encouraging good adherence. AREAS COVERED: We discuss methods for measuring adherence, including ethics of such research, provide select examples of dermatology-specific adherence studies, and conclude with physician-focused practices to improve patients' adherence. Articles were selected from a PubMed search spanning 2003 to 10 December 2023, using the following terms: 'dermatology,' 'medication,' 'treatment,' 'adherence,' 'compliance,' and 'intervention.' EXPERT OPINION: Poor adherence to treatment is a major cause of poor treatment outcomes. As the goal of medical care is to achieve successful treatment outcomes, encouraging good adherence may be as much a foundation of care as making the right diagnosis and prescribing the right treatment. Taking a doctor-centric perspective on reasons for non-adherence may be more productive than simply finding fault with the patient. Establishing trust and accountability is a foundation for good adherence; after establishing the provider-patient relationship, physicians can improve adherence by incorporating behavioral and counseling strategies, communicating through technology, and advocating for distribution of validated educational information.

Tapinarof cream for the topical treatment of plaque psoriasis in adults.

INTRODUCTION: Plaque psoriasis, a chronic immune-mediated skin disorder, is characterized by well-demarcated erythematous plaques with silvery scales. This condition stems from complex interactions between genetic predisposition, immune dysregulation, and environmental triggers. Tapinarof downregulates the cytokine IL-17, diminishes the inflammatory infiltrate, and provides antioxidant properties while enhancing the expression of skin barrier proteins. AREAS COVERED: This review begins by assessing tapinarof's mechanism in treating plaque psoriasis. Subsequently, it examines the effectiveness and safety of tapinarof 1% cream in adult patients. EXPERT OPINION: Tapinarof 1% cream, which works by activating the aryl hydrocarbon receptor, is an FDA-approved treatment for adult plaque psoriasis. This therapy introduces a novel, nonsteroidal method for addressing inflammation and skin barrier issues, potentially serving as an alternative to conventional treatments. The once-daily, convenient cream formulation and favorable safety profile may enhance patient adherence, which is often poor with topical treatments. Tapinarof also maintains disease clearance for a mean of 4 months after treatment cessation.

Adherence to Psoriasis Therapies.

Understanding the underlying causes of nonadherence among patients with psoriasis and adopting strategies to address these issues may allow providers to share responsibility and work alongside patients to overcome these barriers. The review explores patient adherence to different types of psoriasis treatment, suggestions for interventions to overcome barriers, and methods to promote adherence that have been published in the literature.

Validity of facial skin analysis pore detection: A comparative analysis.

BACKGROUND: Reliable, objective measures to assess facial characteristics would aid in the assessment of many dermatological treatments. Previous work utilized an iOS application-based artificial intelligence (AI) tool compared to the "gold standard" computer-based and a physician assessment on five skin metrics (British Journal of Dermatology, 2013, 169, 474). The AI tool had superior agreement for all skin metrics except pores and subsequently underwent an algorithm update for its pore detection system. AIMS: This comparative analysis assessed the performance of the updated AI tool's pore scores across all Fitzpatrick skin phototypes to determine whether the AI tool more accurately represents a dermatologist's assessment of pores. PATIENTS/METHODS: Frontal facing photographs in uniform lighting conditions were taken of each participant. Percentile scores were generated by each of the four self-learning models of the updated AI tool. The pore percentile scores generated by the original and updated AI tool were used to rate "worse" pores among participant pairs. These ratings were compared to pore assessments performed by a "gold-standard" device and a board-certified dermatologist. RESULTS: Compared to the original pore detection tool and the computer-based program, models A and D had the highest concordance with the physician's pore assessments for Fitzpatrick skin phototypes III-IV and V-VI, respectively. CONCLUSIONS: The AI tool's pores detection update was successful in its ability to accurately detect pores on all Fitzpatrick skin types, improving on the performance of the AI prior to the update. Responsibly developed AI tools that can accurately and reliably detect skin metrics across diverse Fitzpatrick skin types can facilitate dermatologic evaluation, individualize treatment, and determine treatment response.