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Introduction: Psoriasis affecting the genital, palmoplantar, and scalp regions is recognized as difficult-to-treat, and data on the efficacy of biologics in these areas remains limited., Research Design and Methods: This single-center study evaluated the effectiveness of anti-IL-17 and anti-IL-23 agents on scalp, genital, and palmoplantar psoriasis. We retrospectively analyzed data from all patients with psoriasis being treated with IL inhibitors at our clinic. Effectiveness was evaluated at 16, 28, and 52 weeks, according to the achievement of relative and mean PSSI, PGA-G, and ppPASI., Results: In all, 308 patients showed involvement of the scalp, 136 in the genital area, and 94 in the palmoplantar regions. On scalp psoriasis, anti-IL-17 agents demonstrated superiority in disease control compared to anti-IL-23 agents. PSSI100 at week 16 was reached by 59% of patients on an anti-IL17 vs 39.8% on an anti-IL-23 ( p  < 0.003). At genital sites, no significant differences between anti-IL-17 and anti-IL-23 agents were observed, and all classes achieved PGA-G 0/1. No significant differences between anti-IL-17 and anti-IL-23 agents were observed in palmoplantar areas., Conclusions: The present data support the utility of both anti-IL-17 and anti-IL-23 agents for the treatment of difficult-to-treat areas in patients with psoriasis. Anti-IL-17 agents achieved better control of scalp psoriasis.

Background: Early diagnosis is the most effective intervention to improve the prognosis of cutaneous melanoma. Even though the introduction of dermoscopy has improved the diagnostic accuracy, it can still be difficult to distinguish some melanomas from benign melanocytic lesions. Digital dermoscopy monitoring can identify dynamic changes of melanocytic lesions: To date, some algorithms were proposed, but a universally accepted one is still lacking., Objectives: To identify independent predictive variables associated with the diagnosis of cutaneous melanoma and develop a multivariable dermoscopic prediction model able to discriminate benign from malignant melanocytic lesions undergoing digital dermoscopy monitoring., Methods: We collected dermoscopic images of melanocytic lesions excised after dermoscopy monitoring and carried out static and dynamic evaluations of dermoscopic features. We built two multivariable predictive models based on logistic regression and random forest., Results: We evaluated 173 lesions (65 cutaneous melanomas and 108 nevi). Forty-two melanomas were in situ, and the median thickness of invasive melanomas was 0.35 mm. The median follow-up time was 9.8 months for melanomas and 9.1 for nevi. The logistic regression and random forest models performed with AUC values of 0.87 and 0.89, respectively, were substantially higher than those of the static evaluation models (ABCD TDS score, 0.57; 7-point checklist, 0.59). Finally, we built two risk calculators, which translate the proposed models into user-friendly applications, to assist clinicians in the decision-making process., Conclusions: The present study demonstrates that the integration of dynamic and static evaluations of melanocytic lesions is a safe approach that can significantly boost the diagnostic accuracy for cutaneous melanoma. We propose two diagnostic tools that significantly increase the accuracy in discriminating melanoma from nevi during digital dermoscopy monitoring., (© 2021 European Academy of Dermatology and Venereology.)