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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., (© 2023. Springer Nature Limited.)

Serum adalimumab concentration is a biomarker of treatment response but therapeutic drug monitoring (TDM) is yet to be implemented in routine psoriasis care. We incorporated adalimumab TDM in a national specialized psoriasis service and evaluated it using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) implementation science framework. We undertook pre-implementation planning (validating local assays) and implementation interventions targeted to patients (pragmatic sampling at routine reviews), clinicians (introduction of a TDM protocol), and healthcare systems (adalimumab TDM as a key performance indicator). Over 5 months, 170 of 229 (74%) individuals treated with adalimumab received TDM. Clinical improvement after TDM-guided dose escalation occurred in 13 of 15 (87%) nonresponders with serum drug concentrations <8.3 μg/ml (median PASI reduction of 3.2 [interquartile range = 2.2-8.2] after 23.4 weeks) and in all nonresponders who had TDM-guided switch in biologic due to supratherapeutic drug concentrations (>8.3 μg/ml; n = 2) or positive antidrug antibody (n = 2) (PASI reduction of 7.8 [interquartile range = 7.5-12.9] after 20.0 weeks). Proactive TDM led to dose reduction in five individuals with clear skin and subtherapeutic or supratherapeutic drug concentrations; four (80%) sustained clear skin after 50 weeks (range = 42-52). Adalimumab TDM based on pragmatic serum sampling is clinically viable and may lead to patient benefit. Context-specific implementation interventions and systematic implementation assessment may bridge the biomarker research-to-practice gap., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Nonadherence to immune-modifying therapy is a complex behaviour which, before the COVID-19 pandemic, was shown to be associated with mental health disorders in people with immune-mediated diseases. The COVID-19 pandemic has led to a rise in the global prevalence of anxiety and depression, and limited data exist on the association between mental health and nonadherence to immune-modifying therapy during the pandemic., Objectives: To assess the extent of and reasons underlying nonadherence to systemic immune-modifying therapy during the COVID-19 pandemic in individuals with psoriasis, and the association between mental health and nonadherence., Methods: Online self-report surveys (PsoProtectMe), including validated screens for anxiety and depression, were completed globally during the first year of the pandemic. We assessed the association between anxiety or depression and nonadherence to systemic immune-modifying therapy using binomial logistic regression, adjusting for potential cofounders (age, sex, ethnicity, comorbidity) and country of residence., Results: Of 3980 participants from 77 countries, 1611 (40.5%) were prescribed a systemic immune-modifying therapy. Of these, 408 (25.3%) reported nonadherence during the pandemic, most commonly due to concerns about their immunity. In the unadjusted model, a positive anxiety screen was associated with nonadherence to systemic immune-modifying therapy [odds ratio (OR) 1.37, 95% confidence interval (CI) 1.07-1.76]. Specifically, anxiety was associated with nonadherence to targeted therapy (OR 1.41, 95% CI 1.01-1.96) but not standard systemic therapy (OR 1.16, 95% CI 0.81-1.67). In the adjusted model, although the directions of the effects remained, anxiety was not significantly associated with nonadherence to overall systemic (OR 1.20, 95% CI 0.92-1.56) or targeted (OR 1.33, 95% CI 0.94-1.89) immune-modifying therapy. A positive depression screen was not strongly associated with nonadherence to systemic immune-modifying therapy in the unadjusted (OR 1.22, 95% CI 0.94-1.57) or adjusted models (OR 1.14, 95% CI 0.87-1.49)., Conclusions: These data indicate substantial nonadherence to immune-modifying therapy in people with psoriasis during the pandemic, with attenuation of the association with mental health after adjusting for confounders. Future research in larger populations should further explore pandemic-specific drivers of treatment nonadherence. Clear communication of the reassuring findings from population-based research regarding immune-modifying therapy-associated adverse COVID-19 risks to people with psoriasis is essential, to optimize adherence and disease outcomes., Competing Interests: Conflict of interests J.W. has presented talks for Abbott, AbbVie, Bayer, Boehringer Ingelheim, Chiesi, Merck and Roche. K.J.M. reports personal fees from LEO Pharma and Novartis, outside the submitted work. H.M. reports grants from AbbVie, Almirall, Celgene, Dermal Laboratories, Eli Lilly, Janssen, LEO Pharma, T & R Derma and UCB, outside the submitted work. D.U. reports grants from AbbVie, Almirall, Amgen, Celgene, Dermal Laboratories, Eli Lilly, Janssen, LEO Pharma, T & R Derma and UCB, outside the submitted work. L.M. reports personal fees from AbbVie, Celgene, Janssen, LEO Pharma, Novartis and UCB, outside the submitted work. Additional disclosures from L.M. include Almirall, BMS and Lilly. H.B. reports personal fees from AbbVie, Almirall, Biocad, Boehringer-Ingelheim, Janssen, Kyowa Kirin, LEO Pharma, Novartis, Pfizer and UCB, outside the submitted work. F.C. reports consultancy fees from AnaptysBio, grants from Boehringer Ingelheim, outside the submitted work. C.D.l.C. reports personal fees from Boehringer Ingelheim and UCB Pharma; grants from Janssen, Pfizer, Sandoz, Sanofi; grants and personal fees from AbbVie, Novartis, outside the submitted work. P.D.M. reports grants and personal fees from UCB; personal fees from Janssen and Novartis, outside the submitted work. P.G. reports personal fees from AbbVie, Amgen, Eli Lilly, Janssen, Novartis, Pierre Fabre, Sandoz and UCB, outside the submitted work. D.J. reports personal fees and nonfinancial support from AbbVie, Celgene, Janssen-Cilag, Lilly, LEO Pharma, MEDAC and Novartis; and personal fees from Amgen, outside the submitted work. L.P. reports grants and personal fees from AbbVie, Almirall, Amgen, Boehringer Ingelheim, Janssen, Lilly, Novartis and UCB; and personal fees from Bristol Myers Squibb, Fresenius-Kabi, Mylan, Pfizer, Samsung-Bioepis, Sandoz, Sanofi, outside the submitted work. P.S. has done consultancies in the past for Sanofi 111017 and AbbVie 041217 (unpaid); has received departmental independent research grants for TREAT NL registry from pharma companies since December 2019; is involved in performing clinical trials with many pharmaceutical industries that manufacture drugs used for the treatment of diseases such as psoriasis and atopic dermatitis, for which financial compensation is paid to the department/hospital; and is chief investigator of the systemic and phototherapy atopic eczema registry (TREAT NL) for adults and children, as well as one of the main investigators of the SECURE-AD registry. T.T. reports grants and personal fees from AbbVie, Almirall, Amgen, Arena Pharmaceuticals, Biocad, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, LEO Pharma, MSD, Novartis, Pfizer, Samsung-Bioepis and Sandoz, during the conduct of the study. R.B.W. reports grants from AbbVie, Almirall, Amgen, Celgene, Janssen, LEO, Lilly, Medac, Novartis, Pfizer and UCB. R.B.W. also reports consultancy fees from AbbVie, Almirall, Amgen, Arena, Astellas, Avillion, Biogen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, DiCE, GSK, Janssen, LEO, Lilly, Medac, Novartis, Pfizer, Sanofi, Sun Pharma, UCB and UNION. H.W. is on the Board of the International Federation of Psoriasis Associations who have received grants from AbbVie, Almirall, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, LEO Pharma, Novartis, Pfizer, Sun Pharma and UCB, outside the submitted work. J.B.G. reports personal fees from AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, Sanofi and UCB, outside the submitted work. C.E.M.G. reports grants and personal fees from AbbVie, Janssen, Lilly and Novartis and UCB Pharma; and grants from Almirall, Amgen, BMS, LEO and Pfizer, outside the submitted work. J.N.B. reports grants and personal fees from AbbVie, J&J, Lilly and Novartis during the conduct of the study. J.N.B. has attended advisory boards, and/or received consultancy fees, and/or spoken at sponsored symposia, and/or received grant funding from AbbVie, Almirall, Amgen, Boehringer Ingelheim, Bristol Meyers Squibb, Celgene, Janssen, LEO Pharma, Lilly, Novartis, Pfizer, Samsung, Sun Pharma and UCB. C.H.S. reports grants from AbbVie, Novartis, Pfizer and Sanofi; and through consortia with multiple academic partners (psort.org.uk, BIOMAP-IMI.eu), outside the submitted work. S.K.M. reports departmental income from AbbVie, Almirall, Eli Lilly, Janssen-Cilag, Novartis, Sanofi and UCB, outside the submitted work., (© The Author(s) 2022. Published by Oxford University Press on behalf of British Association of Dermatologists.)

Targeted biologic therapies can elicit an undesirable host immune response characterized by the development of antidrug antibodies (ADA), an important cause of treatment failure. The most widely used biologic across immune-mediated diseases is adalimumab, a tumor necrosis factor inhibitor. This study aimed to identify genetic variants that contribute to the development of ADA against adalimumab, thereby influencing treatment failure. In patients with psoriasis on their first course of adalimumab, in whom serum ADA had been evaluated 6-36 months after starting treatment, we observed a genome-wide association with ADA against adalimumab within the major histocompatibility complex (MHC). The association signal mapped to the presence of tryptophan at position 9 and lysine at position 71 of the HLA-DR peptide-binding groove, with both residues conferring protection against ADA. Underscoring their clinical relevance, these residues were also protective against treatment failure. Our findings highlight antigenic peptide presentation via MHC class II as a critical mechanism in the development of ADA against biologic therapies and downstream treatment response.