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.

Interleukin-17E, inducible nitric oxide synthase and arginase1 as new biomarkers in the identification of neutrophilic dermatoses.

BACKGROUND: Neutrophilic dermatoses (ND) are a heterogeneous group of diseases, but can often have a relatively similar histological appearance. AIM: To identify a combination of biomarkers allowing a better differentiation of ND types. METHODS: Biopsies were obtained from normal human skin (NS; n = 4), chronic plaque-type psoriasis (PsO; n = 7), paradoxical psoriasis (PP; n = 8), generalized pustular psoriasis (GPP; n = 9), subcorneal pustular dermatosis of Sneddon-Wilkinson (SPD; n = 3), acute generalized exanthematous pustulosis (AGEP; n = 3), hidradenitis suppurativa (HS; n = 7), Sweet syndrome (SS; n = 8) and pyoderma gangrenosum (PG; n = 8). Samples were analysed by immunofluorescence using three biomarkers, interleukin (IL)-17E, inducible nitric oxide synthase (iNOS) and arginase1, each one in combination with two cell markers, myeloperoxidase (MPO) and CD68, which allow the identification of neutrophils and macrophages, respectively. RESULTS: We found that SS is characterized by high expression of IL-17E and iNOS in the epidermis, while PG exhibits low expression. The density of the neutrophil infiltrate helps to differentiate PP (high-density infiltrate) from PsO (low-density infiltrate). High expression of arginase1 in the granular layer of the epidermis is a hallmark of SPD. Finally, mature neutrophils and proinflammatory macrophages are readily detectable in PP, SPD and PG, whereas immature neutrophils and anti-inflammatory macrophages are more frequent in GPP, AGEP, HS and SS. CONCLUSIONS: The analysis of ND by immunofluorescence using IL-17E, iNOS and arginase1 in combination with MPO and CD68 allows for characterization of differential expression patterns in the epidermis as well as the determination of the polarization status of the dermal neutrophils and macrophages. The appropriate markers may help in the differentiation of ND in clinical practice.

[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.

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.

Global publication productivity in dermatology: a bibliometric description of the past and estimation of the future.

BACKGROUND: In the past two centuries, generations of dermatologists around the world have created an enormous number of publications. To our knowledge, no bibliometric analysis of these publications has been performed so far, nor have registered trials been analysed to anticipate future publication trends. OBJECTIVES: To determine the global distribution of national publication productivity, most published topics, institutions and funding sources contributing most to publications and to anticipate future trends based on registered clinical trials. METHODS: Following pre-assessment on PubMed, Embase, Web of Science and Scopus, the number of publications for 'dermatology' was determined for each of 195 countries, normalized per 1 Mio inhabitants and bibliometrically analysed. Dermatology-related trials registered at clinicaltrials.gov were specified by the top-10 diagnoses for the top-10 countries. RESULTS: The search yielded 1 071 518 publications between 1832 and 2019 with the top-5 diagnoses being melanoma, basal cell carcinoma, psoriasis, pruritus/itch and atopic dermatitis. The top-3 countries with highest absolute numbers of publications were the USA (30.6%), Germany (8.1%) and the UK (8.1%), whereas Switzerland, Denmark and Sweden had the highest publication rates when normalized by inhabitants. The most productive affiliation was the Harvard Medical School, the leading funding source the National Institutes of Health. Currently, maximum number of trials are registered in the USA (8111), France (1543) and Canada (1368). The highest percentage of all dermatology-related trials in a specific country were as follows: Melanoma in the Netherlands (24.8%), psoriasis in Germany (21.7%) and atopic dermatitis in Japan (15.9%). CONCLUSION: The top-10 countries including the USA, Canada, a few European and Asian countries contributed more than 3/4 of all publications. The USA hold the dominant leader position both in past publication productivity and currently registered trials. While most Western countries continue to focus their research on the top-10 topics, China and India appear to prioritize their scope towards other topics.

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.

[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.

[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.