Characteristics and management of generalized pustular psoriasis (GPP): Experience from the Central and Eastern Europe (CEE) GPP Expert Network.

BACKGROUND: Generalized pustular psoriasis (GPP) is a rare, inflammatory skin disease characterized by widespread eruption of sterile pustules with or without systemic symptoms. OBJECTIVES: This study aimed to describe the demographics of patients with GPP in Central and Eastern Europe (CEE), present the clinical characteristics of individual GPP flares and explore the current treatment landscape. METHODS: Patient demographics were collected at the times of last observation and previous treatment. Characteristics of a patient's last (most recent) and most severe (from all documented episodes) flare were provided at clinician's discretion. RESULTS: Fifty-eight patients were recruited from 12 centres in nine CEE countries; median (range) age was 61 (16-92) years and 60.3% (35 out of 58) were female. The most common comorbidities were hypertension (43.1% [25 out of 58]) and hyperlipidaemia (32.8% [19 out of 58]). Thirty-four patients (58.6%) presented with concomitant plaque psoriasis before or during the course of GPP. Data from two separate flares were recorded in 26 individuals; in 32 patients, the most recent flare was reported as the most severe. Over 90% of patients with a flare episode classified as most severe by clinicians were hospitalized, with >75% of these individuals having a Generalized Pustular Psoriasis Physician Global Assessment (GPPGA) total score of 3 or 4. Systemic symptoms were more common in patients with a GPPGA score of 3 or 4 but were also manifest in individuals with a GPPGA score ≤2. A significant correlation was observed between a combined systemic disease score of clinical and laboratory features and both GPPGA total score (r = 0.385, p < 0.001) and GPPGA pustulation subscore (r = 0.305, p < 0.05). CONCLUSIONS: Considerable heterogeneity in the presentation of GPP flares was observed, both between patients and within-patient. All GPP flares were associated with a significant clinical burden, highlighting the unmet need for accurate and early diagnosis.

Consistency of convolutional neural networks in dermoscopic melanoma recognition: A prospective real-world study about the pitfalls of augmented intelligence.

BACKGROUND: Deep-learning convolutional neural networks (CNNs) have outperformed even experienced dermatologists in dermoscopic melanoma detection under controlled conditions. It remains unexplored how real-world dermoscopic image transformations affect CNN robustness. OBJECTIVES: To investigate the consistency of melanoma risk assessment by two commercially available CNNs to help formulate recommendations for current clinical use. METHODS: A comparative cohort study was conducted from January to July 2022 at the Department of Dermatology, University Hospital Basel. Five dermoscopic images of 116 different lesions on the torso of 66 patients were captured consecutively by the same operator without deliberate rotation. Classification was performed by two CNNs (CNN-1/CNN-2). Lesions were divided into four subgroups based on their initial risk scoring and clinical dignity assessment. Reliability was assessed by variation and intraclass correlation coefficients. Excisions were performed for melanoma suspicion or two consecutively elevated CNN risk scores, and benign lesions were confirmed by expert consensus (n = 3). RESULTS: 117 repeated image series of 116 melanocytic lesions (2 melanomas, 16 dysplastic naevi, 29 naevi, 1 solar lentigo, 1 suspicious and 67 benign) were classified. CNN-1 demonstrated superior measurement repeatability for clinically benign lesions with an initial malignant risk score (mean variation coefficient (mvc): CNN-1: 49.5(±34.3)%; CNN-2: 71.4(±22.5)%; p = 0.03), while CNN-2 outperformed for clinically benign lesions with benign scoring (mvc: CNN-1: 49.7(±22.7)%; CNN-2: 23.8(±29.3)%; p = 0.002). Both systems exhibited lowest score consistency for lesions with an initial malignant risk score and benign assessment. In this context, averaging three initial risk scores achieved highest sensitivity of dignity assessment (CNN-1: 94%; CNN-2: 89%). Intraclass correlation coefficients indicated 'moderate'-to-'good' reliability for both systems (CNN-1: 0.80, 95% CI:0.71-0.87, p < 0.001; CNN-2: 0.67, 95% CI:0.55-0.77, p < 0.001). CONCLUSIONS: Potential user-induced image changes can significantly influence CNN classification. For clinical application, we recommend using the average of three initial risk scores. Furthermore, we advocate for CNN robustness optimization by cross-validation with repeated image sets. TRIAL REGISTRATION: ClinicalTrials.gov (NCT04605822).

Improved diagnosis by automated macro- and micro-anatomical region mapping of skin photographs.

BACKGROUND: The exact location of skin lesions is key in clinical dermatology. On one hand, it supports differential diagnosis (DD) since most skin conditions have specific predilection sites. On the other hand, location matters for dermatosurgical interventions. In practice, lesion evaluation is not well standardized and anatomical descriptions vary or lack altogether. Automated determination of anatomical location could benefit both situations. OBJECTIVE: Establish an automated method to determine anatomical regions in clinical patient pictures and evaluate the gain in DD performance of a deep learning model (DLM) when trained with lesion locations and images. METHODS: Retrospective study based on three datasets: macro-anatomy for the main body regions with 6000 patient pictures partially labelled by a student, micro-anatomy for the ear region with 182 pictures labelled by a student and DD with 3347 pictures of 16 diseases determined by dermatologists in clinical settings. For each dataset, a DLM was trained and evaluated on an independent test set. The primary outcome measures were the precision and sensitivity with 95% CI. For DD, we compared the performance of a DLM trained with lesion pictures only with a DLM trained with both pictures and locations. RESULTS: The average precision and sensitivity were 85% (CI 84-86), 84% (CI 83-85) for macro-anatomy, 81% (CI 80-83), 80% (CI 77-83) for micro-anatomy and 82% (CI 78-85), 81% (CI 77-84) for DD. We observed an improvement in DD performance of 6% (McNemar test P-value 0.0009) for both average precision and sensitivity when training with both lesion pictures and locations. CONCLUSION: Including location can be beneficial for DD DLM performance. The proposed method can generate body region maps from patient pictures and even reach surgery relevant anatomical precision, e.g. the ear region. Our method enables automated search of large clinical databases and make targeted anatomical image retrieval possible.

Association of sex and systemic therapy treatment outcomes in psoriasis: a two-country, multicentre, prospective, noninterventional registry study.

BACKGROUND: Few systematic data on sex-related treatment responses exist for psoriasis. OBJECTIVES: To evaluate sex differences with respect to systemic antipsoriatic treatment. METHODS: Data from patients with moderate-to-severe psoriasis in the PsoBest or Swiss Dermatology Network of Targeted Therapies (SDNTT) registries were analysed. Treatment response was defined as achieving a ≥ 75% reduction in Psoriasis Area and Severity Index (PASI 75) or PASI ≤ 3 at treatment months 3, 6 and 12, supplemented by patient-reported outcomes [i.e. Dermatology Life Quality Index (DLQI) ≤ 1 and delta DLQI ≥ 4]. RESULTS: In total, 5346 patients registered between 2007 and 2016 were included (PsoBest, n = 4896; SDNTT, n = 450). The majority received nonbiological treatment (67·3% male, 69·8% female). Women showed slightly higher PASI response rates after 3 (54·8% vs. 47·2%; P ≤ 0·001), 6 (70·8% vs. 63·8%; P ≤ 0·001) and 12 months (72·3% vs. 66·1%; P ≤ 0·004). A significantly higher proportion of women achieved a reduction in DLQI ≥ 4 [month 3: 61·4% vs 54·8% (P ≤ 0·001); month 6: 69·6% vs. 62·4% (P ≤ 0·001); month 12: 70·7% vs. 64·4% (P ≤ 0·002)]. Regarding PASI ≤ 3, women on biologics showed a significantly superior treatment response compared with men at 3 (57·8% vs. 48·5%; P ≤ 0·004) and 6 months (69·2% vs. 60·9%; P ≤ 0·018). Women in the nonbiological treatment group had a significantly better treatment response (PASI response, PASI 75 and PASI ≤ 3) over 12 months compared with men. CONCLUSIONS: We provide evidence that women experience better treatment outcomes with systemic antipsoriatic therapy than men.

Genomic profiling of late-onset basal cell carcinomas from two brothers with nevoid basal cell carcinoma syndrome.

BACKGROUND: Nevoid basal cell carcinoma syndrome (NBCCS) is an autosomal dominant genetic disorder. It is commonly caused by mutations in PTCH1 and chiefly characterized by multiple basal cell carcinomas (BCCs) developing prior to the age of 30 years. In rare cases, NBCCS presents with a late onset of BCC development. OBJECTIVE: To investigate BCC tumorigenesis in two brothers, who showed characteristic features of NBCCS but developed their first BCCs only after the age of 40 years. Two other siblings did not show signs of NBCCS. RESULTS: We obtained blood samples from four siblings and nine BCCs from the two brothers with NBCCS. Whole exome sequencing and RNA sequencing revealed loss of heterozygosity (LOH) of PTCH1 in eight out of nine tumours that consistently involved the same haplotype on chromosome 9. This haplotype contained a germinal splice site mutation in PTCH1 (NM_001083605:exon9:c.763-6C>A). Analysis of germline DNA confirmed segregation of this mutation with the disease. All BCCs harboured additional somatic loss-of-function (LoF) mutations in the remaining PTCH1 allele which are not typically seen in other cases of NBCCS. This suggests a hypomorphic nature of the germinal PTCH1 mutation in this family. Furthermore, all BCCs had a similar tumour mutational burden compared to BCCs of unrelated NBCCS patients while harbouring a higher number of damaging PTCH1 mutations. CONCLUSIONS: Our data suggest that a sequence of three genetic hits leads to the late development of BCCs in two brothers with NBCCS: a hypomorphic germline mutation, followed by somatic LOH and additional mutations that complete PTCH1 inactivation. These genetic events are in line with the late occurrence of the first BCC and with the higher number of damaging PTCH1 mutations compared to usual cases of NBCCS.

[Clinical, pathology-associated and molecular biomarkers of hidradenitis suppurativa/acne inversa]. / Klinische, pathologische und molekulare Biomarker der Hidradenitis suppurativa/Acne inversa.

Hidradenitis suppurativa/acne inversa is a scarring disease of the intertrigines that is now intensively researched. Improved pathogenetic understanding has led to the introduction of tumor necrosis factor alpha (TNF­α) inhibition, which represents a major advance over traditional broad immunosuppression and antibiotic administration. In addition, a wide range of newer and promising treatments is or is about to be clinically evaluated. These include various specific antibodies against cytokines and the complement system and small molecules. Successful use of the individual drugs depends on the stratification of suitable patient groups with the help of clinically relevant biomarkers. While molecular investigations have shown a number of possible biomarkers and/or therapeutic target molecules, the detection of robust predictive biomarkers is still in its initial phase. In summary, the therapeutic options for hidradenitis suppurativa/acne inversa are improving through the introduction of new drugs, possibly in combination with surgical interventions, whereby the possibilities for predictive therapeutic decisions through the discovery of biomarkers would revolutionize the chances of therapeutic success.

Observer-independent assessment of psoriasis-affected area using machine learning.

BACKGROUND: Assessment of psoriasis severity is strongly observer-dependent, and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate-to-severe psoriasis motivates the development of higher quality assessment tools. OBJECTIVE: To establish an accurate and objective psoriasis assessment method based on segmenting images by machine learning technology. METHODS: In this retrospective, non-interventional, single-centred, interdisciplinary study of diagnostic accuracy, 259 standardized photographs of Caucasian patients were assessed and typical psoriatic lesions were labelled. Two hundred and three of those were used to train and validate an assessment algorithm which was then tested on the remaining 56 photographs. The results of the algorithm assessment were compared with manually marked area, as well as with the affected area determined by trained dermatologists. RESULTS: Algorithm assessment achieved accuracy of more than 90% in 77% of the images and differed on average 5.9% from manually marked areas. The difference between algorithm-predicted and photograph-based estimated areas by physicians was 8.1% on average. CONCLUSION: The study shows the potential of the evaluated technology. In contrast to the Psoriasis Area and Severity Index (PASI), it allows for objective evaluation and should therefore be developed further as an alternative method to human assessment.

Smart identification of psoriasis by images using convolutional neural networks: a case study in China.

BACKGROUND: Psoriasis is a chronic inflammatory skin disease, which holds a high incidence in China. However, professional dermatologists who can diagnose psoriasis early and correctly are insufficient in China, especially in the rural areas. A smart approach to identify psoriasis by pictures would be highly adaptable countrywide and could play a useful role in early diagnosis and regular treatment of psoriasis. OBJECTIVES: Design and evaluation of a smart psoriasis identification system based on clinical images (without relying on a dermatoscope) that works effectively similar to a dermatologist. METHODS: A set of deep learning models using convolutional neural networks (CNNs) was explored and compared in the system for automatic identification of psoriasis. The work was carried out on a standardized dermatological dataset with 8021 clinical images of 9 common disorders including psoriasis along with full electronic medical records of patients built over the last 9 years in China. A two-stage deep neural network was designed and developed to identify psoriasis. In the first stage, a multilabel classifier was trained to learn the visual patterns for each individual skin disease. In the second stage, the output of the first stage was utilized to distinguish psoriasis from other skin diseases. RESULTS: The area under the curve (AUC) of the two-stage model reached 0.981 ± 0.015, which outperforms a single-stage model. And, the classifier showed superior performance (missed diagnosis rate: 0.03, misdiagnosis rate: 0.04) than 25 Chinese dermatologists (missed diagnosis rate: 0.19, misdiagnosis rate: 0.10) in the diagnosis of psoriasis on 100 clinical images. CONCLUSIONS: Using clinical images to identify psoriasis is feasible and effective based on CNNs, which also builds a solid technical base for smart care of skin diseases especially psoriasis using mobile/tablet applications for teledermatology in China.

[Pathophysiology of autoinflammatory dermatoses]. / Pathophysiologie der autoinflammatorischen Dermatosen.

Autoinflammation leads to inflammation that mostly occurs without any clinically obvious reason. It can be so severe that organ damage with relevant tissue damage occurs. Inflammasomes are the drivers of autoinflammation. Although IL­1 beta and the inflammasomes as its critical regulators are very important in autoinflammation, not all patients respond to inhibition of this signalling pathway. Several autoinflammatory diseases were associated with mutations in proteasome-immunoproteasome components. Autoinflammatory diseases caused by highly relevant genetic variants are mostly hereditary. Usually in childhood but not always. The coming years will show whether inflammatory dermatoses will be increasingly treated with suppression of the innate immune system in addition to inhibition of adaptive immunity.

[Artificial intelligence to support telemedicine in Africa]. / Künstliche Intelligenz zur Unterstützung der Telemedizin am Beispiel Afrikas.

Telemedicine has been used in the daily routine of dermatologists for decades. The potential advantages are especially obvious in African countries having limited medical care, long geographical distances, and a meanwhile relatively well-developed telecommunication sector. National and international working groups support the establishment of teledermatological projects and in recent years have increasingly been using artificial intelligence (AI)-based technologies to support the local physicians. Ethnic variations represent a challenge in the development of automated algorithms. To further improve the accuracy of the systems and to be able to globalize, it is important to increase the amount of available clinical data. This can only be achieved with the active participation of local health care providers as well as the dermatological community and must always be in the interest of the individual patient.

Perspectives of online surveys in dermatology.

The striking rise in the Internet utilization worldwide has led to major changes in the methods of data collection and processing. Online surveying has been used to assess different health services, explore patients' perceptions and measure interventions. The discipline of dermatology is one of the fields that gained benefits from surveying patients and dermatologists online; however, some disadvantages such as the low response rate and participation bias were suggested. This review summarizes the applications of online surveying in dermatology and discusses the methods of enhancing response to online surveys. It also offers a guide for dermatologists to formulate their online surveys and avoid the possibility of bias. The role of social network in data collection and the concerns about anonymity and data security have been discussed.

Gender and age significantly determine patient needs and treatment goals in psoriasis - a lesson for practice.

BACKGROUND: Though patient needs are key drivers of treatment decisions, they are rarely systematically investigated in routine care. OBJECTIVE: This study aimed at analysing needs and expectations from the patient perspective in the German and Swiss psoriasis registries PsoBest and Swiss Dermatology Network of Targeted Therapies (SDNTT) with respect to treatment choice, age and gender. METHODS: The German and Swiss psoriasis registries observe patients recruited at first-time use of systemic drugs. Within 10 years, clinical [Psoriasis Area Severity Index (PASI), Body Surface Area (BSA)] and patient-reported outcomes are documented, including the Dermatology Quality of Life Index (DLQI) and the Patient Benefit Index (PBI), characterizing patient needs for treatment. The analysis data set includes n = 4894 patients from PsoBest and n = 449 from SDNTT with mean follow-up time of 7.5 months. RESULTS: A total of 5343 patients registered between 2008 and 2016 were included in the analyses (at baseline: 59.6% male, mean age 47.6 years ± 14.5, PASI 14.2 ± 9.7, BSA 22.7 ± 19.7, DLQI 11.3 ± 7.2). The most important patient needs were to 'get better skin quickly' and to 'be healed of all skin defects'. Subgroup analyses by age revealed significant differences in needs, especially higher needs regarding social impairments in patients younger than 65 years. Patients 65 years or older attributed more importance to sleep quality, less dependency on medical visits, fewer side-effects and confidence in the therapy. Out of 25 items reflecting patient needs, 20 items were rated significantly more important by women than men, with the greatest differences regarding feeling of depression, sleep quality and everyday productivity. Divided by treatment, needs were rated differently, recommending individualized and targeted choice of therapy. CONCLUSION: Age and gender stratify patient needs. Women showed higher expectations and rated specific needs in psoriasis treatment higher than men. Analysing the patient needs on an individual level will facilitate shared decisions by patient and physician in finding the optimal personalized treatment.

Linkage between patients' characteristics and prescribed systemic treatments for psoriasis: a semantic connectivity map analysis of the Swiss Dermatology Network for Targeted Therapies registry.

BACKGROUND: Several treatment options are currently available for the treatment of psoriasis. OBJECTIVE: To explore the main associations between patients' characteristics and systemic treatments prescribed for psoriasis in a large group of patients observed in real-life clinical practice. METHODS: This was a retrospective analysis of baseline data collected within the Swiss Dermatology Network for Targeted Therapies registry in Switzerland between March 2011 and December 2017. Semantic map analysis was used in order to capture the best associations between variables taking into account other covariates in the system. RESULTS: A total of 549 patients (mean age 46.7 ± 14.7 years) were included in the analysis. Conventional therapies such as retinoids and methotrexate were associated with no previous systemic therapies for psoriasis, a moderate quality of life (QoL) at therapy onset and older age (≥60 years). Fumaric acid derivatives were associated with mild psoriasis (psoriasis area severity index < 10) and long disease duration (≥20 years). On the other side, cyclosporine and psoralen and ultraviolet A/ultraviolet B treatments were linked to a more severe condition, including impaired QoL, hospitalization and inability to work. Regarding biological therapies, both infliximab and adalimumab were connected to the presence of psoriatic arthritis, severe disease condition and other comorbidities, including chronic liver or kidney diseases and tuberculosis. Etanercept, ustekinumab and secukinumab were all connected to a complex history of previous systemic treatments for psoriasis, moderate disease condition, overweight and university education. CONCLUSIONS: The analysis shows multifaceted associations between patients' characteristics, comorbidities, disease severity and systemic treatments prescribed for psoriasis. In particular, our semantic map indicates that comorbidities play a central role in decision-making of systemic treatments usage for psoriasis. Future studies should further investigate specific connections emerging from our data.

Acne and hidradenitis suppurativa.

Acne and hidradenitis suppurativa (HS) both centre on hair follicles. They often occur together as part of the acne tetrad, but are found in distinct localizations. Acne is primarily defined by the presence of comedones and inflammatory lesions. However, in HS the intertriginous localization and chronicity play equally important roles for the diagnosis to the inflammatory lesions. Genetics, bacteria, environmental factors and innate inflammation have all been found to play a role in acne and/or HS. Surprisingly, there is little overlap between the findings so far. The genetics of acne and HS are distinct, bacteria have not been shown convincingly to play a role in HS, and the important risk factors obesity and smoking in HS cannot be easily translated to acne. The one driving factor central to both diseases is innate inflammation, most strikingly involving interleukin-1. Hence the interleukin-1 family, as already shown in autoinflammatory conditions associated with acne, could represent attractive treatment targets.

Paradoxical ulcerative colitis during adalimumab treatment of psoriasis resolved by switch to ustekinumab.

Here we report the case of a patient with psoriasis who developed ulcerative colitis most likely caused by adalimumab. After cessation of adalimumab, colitis improved significantly. However, as psoriasis worsened, the patient was switched to ustekinumab, which resulted in complete cessation of colitis. During the 2-year follow-up under ustekinumab therapy, no further gastrointestinal complaints occurred. Paradoxical psoriasis manifestations in inflammatory bowel disease (IBD) under tumour necrosis factor (TNF)-inhibitor therapy have been reported and paradoxical IBD occurred rarely (mostly Crohn disease) in patients with rheumatological conditions treated with infliximab or etanercept. Due to the highly probable association of adalimumab with the onset of colitis in this case, we would like to suggest the term 'paradoxical ulcerative colitis' (PUC) for this as yet extremely rarely reported phenomenon. To the best of our knowledge this is the first description of PUC in a patient with psoriasis and in adalimumab treatment. Our observation suggests that ustekinumab is an effective treatment option in patients with paradoxical anti-TNF-driven inflammatory reactions like psoriasis or IBD.

Low immunoglobulin E flags two distinct types of immune dysregulation.

During the last two decades, hyper-immunoglobulin (Ig)E syndromes have been characterized clinically and molecularly in patients with genetically determined primary immunodeficiencies. However, the detection of low IgE levels, defined here as below detection limit in the routine clinical immunology laboratory, has received little attention. We analysed the association of serum IgA, IgM and IgG levels (including IgG subclasses) with low, normal or high serum IgE levels in patients evaluated in a single-centre out-patient immunodeficiency and allergy clinic. The correlation of serum IgE levels with IgG subclasses depended on the clinical phenotype. In patients with immunodeficiencies, IgE correlated with IgG2 and IgG4 but not with IgG3. In contrast, in patients referred for signs of allergy, IgE correlated with IgG3 but not with IgG2. A low IgE result was associated with low IgG3 and IgG4 in allergy referrals, while immunodeficiency referrals with a low IgE result had significantly lower IgG1, IgG2 and IgG4 levels. Hierarchical clustering of non-IgE immunoglobulin profiles (IgM, IgA, IgG, IgG1-4) validated that non-IgE immunoglobulin levels predict the clinic referral, i.e. phenotype, of low-IgE patients. These results suggesto guide the clinical management of patients with low serum IgE levels.

Genetic architecture of acne vulgaris.

Acne vulgaris is a ubiquitary skin disease characterized by chronic inflammation of the pilosebaceous unit resulting from bacterial colonization of hair follicles by Propionibacterium acnes, androgen-induced increased sebum production, altered keratinization and inflammation. Here, we review our current understanding of the genetic architecture of this intriguing disease. We analysed genomewide association studies (GWAS) and candidate genes studies for acne vulgaris. Moreover, we included GWAS studies for the associated disease polycystic ovary syndrome (PCOS). Overall, the available data revealed sixteen genetic loci flagged by single nucleotide polymorphisms (SNPs), none of which has been confirmed yet by independent studies. Moreover, a GWAS for PCOS identified 21 susceptible loci. The genetic architecture is complex which has been revealed by GWAS. Further and larger studies in different populations are required to confirm or disprove results from candidate gene studies as well to identify signals that may overlap between different populations. Finally, studies on rare genetic variants in acne and associated diseases like PCOS may deepen our understanding of its pathogenesis.