[Acne]. / Akne.

Acne vulgaris is one of the most frequent dermatological diseases with a lifetime prevalence of about 85%. The clinical spectrum shows a great variety. Key factors of pathogenesis are increased sebum production, hyperkeratinization of the follicular infundibulum, inflammatory processes, and a dysbiosis of the skin microbiome. In addition to endogenous factors (e.g., disturbances of the androgen metabolism) or other hormonal changes, exogenous factors (e.g., diet, mechanical irritation or the use of inappropriate cosmetics) can also play an important role. The clinical spectrum is broad, extending from neonatal Acne (A.) to adult A., from comedonal A. to fulminant A., from cosmetic A. to A. excoriée (skin picking disorder). The psychological effects of acne can be profound and can cause a severe reduction in quality of life. Therefore, in addition to an effective therapy with regular medical check-ups and good adherence, it is always necessary to consider psychological aspects.

Skin microbiome transplantation and manipulation: Current state of the art.

Many skin conditions are associated with an imbalance in the skin microbiome. In recent years, the skin microbiome has become a hot topic, for both therapeutic and cosmetic purposes. The possibility of manipulating the human skin microbiome to address skin conditions has opened exciting new paths for therapy. Here we review the skin microbiome manipulation strategies, ranging from skin microbiome transplantation, over skin bacteriotherapy to the use of prebiotics, probiotics and postbiotics. We summarize all efforts undertaken to exchange, manipulate, transplant or selectively apply the skin microbiome to date. Multiple microbial groups have been targeted, since they have been proven to be beneficial for skin health. We focus on the most common skin disorders and their associated skin microbiome dysbiosis and we review the existing scientific data and clinical trials undertaken to combat these skin conditions. The skin microbiome represents a novel platform for therapy. Transplantation of a complete microbiome or application of single strains has demonstrated beneficial therapeutic application.

Combined immunotherapy with nivolumab and ipilimumab with and without local therapy in patients with melanoma brain metastasis: a DeCOG* study in 380 patients.

BACKGROUND: Nivolumab combined with ipilimumab have shown activity in melanoma brain metastasis (MBM). However, in most of the clinical trials investigating immunotherapy in this subgroup, patients with symptomatic MBM and/or prior local brain radiotherapy were excluded. We studied the efficacy of nivolumab plus ipilimumab alone or in combination with local therapies regardless of treatment line in patients with asymptomatic and symptomatic MBM. METHODS: Patients with MBM treated with nivolumab plus ipilimumab in 23 German Skin Cancer Centers between April 2015 and October 2018 were investigated. Overall survival (OS) was evaluated by Kaplan-Meier estimator and univariate and multivariate Cox proportional hazard analyses were performed to determine prognostic factors associated with OS. RESULTS: Three hundred and eighty patients were included in this study and 31% had symptomatic MBM (60/193 with data available) at the time of start nivolumab plus ipilimumab. The median follow-up was 18 months and the 2 years and 3 years OS rates were 41% and 30%, respectively. We identified the following independently significant prognostic factors for OS: elevated serum lactate dehydrogenase and protein S100B levels, number of MBM and Eastern Cooperative Oncology Group performance status. In these patients treated with checkpoint inhibition first-line or later, in the subgroup of patients with BRAFV600-mutated melanoma we found no differences in terms of OS when receiving first-line either BRAF and MEK inhibitors or nivolumab plus ipilimumab (p=0.085). In BRAF wild-type patients treated with nivolumab plus ipilimumab in first-line or later there was also no difference in OS (p=0.996). Local therapy with stereotactic radiosurgery or surgery led to an improvement in OS compared with not receiving local therapy (p=0.009), regardless of the timepoint of the local therapy. Receiving combined immunotherapy for MBM in first-line or at a later time point made no difference in terms of OS in this study population (p=0.119). CONCLUSION: Immunotherapy with nivolumab plus ipilimumab, particularly in combination with stereotactic radiosurgery or surgery improves OS in asymptomatic and symptomatic MBM.

Safety and Efficacy of Topically Applied Selected Cutibacterium acnes Strains over Five Weeks in Patients with Acne Vulgaris: An Open-label, Pilot Study.

Imbalance in skin microflora, particularly related to certain Cutibacterium acnes strains, may trigger acne. Application of non-acne-causing strains to the skin may modulate the skin microbiome and thereby lead to a reduction in acne. This pilot study evaluates the safety and efficacy of microbiome modulation on acne-prone skin. The study had 2 phases: active induction (5% benzoyl peroxide gel, 7 days) and interventional C. acnes strains treatment (5 weeks). Patients were randomized to either topical skin formulations PT1 (2 strains of C. acnes Single Locus Sequence Typing [SLST] type C3 and K8, 50% each) or PT2 (4 strains of C. acnes SLST type C3 [55%], K8 [5%], A5 [30%] and F4 [10%]). Safety and efficacy was evaluated in 14 patients (PT1=8/14, PT2=6/14). Skin microbiome composition shifted towards study formulations. No untoward adverse events, visible irritation, or significant flare-up were observed. Non-inflamed lesions and skin pH were reduced. Comedone counts improved clinically with no deterioration in inflammatory lesions.

Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks.

BACKGROUND: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologists in distinguishing dermoscopic melanoma and nevi images. However, such a binary classification does not reflect the clinical reality of skin cancer screenings in which multiple diagnoses need to be taken into account. METHODS: Using 11,444 dermoscopic images, which covered dermatologic diagnoses comprising the majority of commonly pigmented skin lesions commonly faced in skin cancer screenings, a CNN was trained through novel deep learning techniques. A test set of 300 biopsy-verified images was used to compare the classifier's performance with that of 112 dermatologists from 13 German university hospitals. The primary end-point was the correct classification of the different lesions into benign and malignant. The secondary end-point was the correct classification of the images into one of the five diagnostic categories. FINDINGS: Sensitivity and specificity of dermatologists for the primary end-point were 74.4% (95% confidence interval [CI]: 67.0-81.8%) and 59.8% (95% CI: 49.8-69.8%), respectively. At equal sensitivity, the algorithm achieved a specificity of 91.3% (95% CI: 85.5-97.1%). For the secondary end-point, the mean sensitivity and specificity of the dermatologists were at 56.5% (95% CI: 42.8-70.2%) and 89.2% (95% CI: 85.0-93.3%), respectively. At equal sensitivity, the algorithm achieved a specificity of 98.8%. Two-sided McNemar tests revealed significance for the primary end-point (p < 0.001). For the secondary end-point, outperformance (p < 0.001) was achieved except for basal cell carcinoma (on-par performance). INTERPRETATION: Our findings show that automated classification of dermoscopic melanoma and nevi images is extendable to a multiclass classification problem, thus better reflecting clinical differential diagnoses, while still outperforming dermatologists at a significant level (p < 0.001).

Comparing artificial intelligence algorithms to 157 German dermatologists: the melanoma classification benchmark.

BACKGROUND: Several recent publications have demonstrated the use of convolutional neural networks to classify images of melanoma at par with board-certified dermatologists. However, the non-availability of a public human benchmark restricts the comparability of the performance of these algorithms and thereby the technical progress in this field. METHODS: An electronic questionnaire was sent to dermatologists at 12 German university hospitals. Each questionnaire comprised 100 dermoscopic and 100 clinical images (80 nevi images and 20 biopsy-verified melanoma images, each), all open-source. The questionnaire recorded factors such as the years of experience in dermatology, performed skin checks, age, sex and the rank within the university hospital or the status as resident physician. For each image, the dermatologists were asked to provide a management decision (treat/biopsy lesion or reassure the patient). Main outcome measures were sensitivity, specificity and the receiver operating characteristics (ROC). RESULTS: Total 157 dermatologists assessed all 100 dermoscopic images with an overall sensitivity of 74.1%, specificity of 60.0% and an ROC of 0.67 (range = 0.538-0.769); 145 dermatologists assessed all 100 clinical images with an overall sensitivity of 89.4%, specificity of 64.4% and an ROC of 0.769 (range = 0.613-0.9). Results between test-sets were significantly different (P < 0.05) confirming the need for a standardised benchmark. CONCLUSIONS: We present the first public melanoma classification benchmark for both non-dermoscopic and dermoscopic images for comparing artificial intelligence algorithms with diagnostic performance of 145 or 157 dermatologists. Melanoma Classification Benchmark should be considered as a reference standard for white-skinned Western populations in the field of binary algorithmic melanoma classification.

A 2q24.2 microdeletion containing TANK as novel candidate gene for intellectual disability.

Interstitial deletions within the chromosomal region 2q24.2 have already been linked to intellectual disability (ID) in the past. In most cases the described patients showed a syndromic form of ID associated with large deletions containing multiple genes. Here we describe a family with two siblings with mild non-syndromic ID. They shared the same 564 kb deletion in the chromosomal region 2q24.2 containing only the TANK gene, which was inherited from the similarly affected father, thus suggesting haploinsufficiency of TANK as a novel cause of non-syndromic ID. TANK encodes the TRAF family member-associated NF-kappa-B activator (OMIM #603893), which is expressed in many tissues. It functions as an adapter protein that interacts with the NF-kappa-B pathway and SOX11, an essential transcription factor in regeneration, survival and differentiation of the neuronal system. TANK has not been linked to ID or other human diseases before. To further elucidate the role of TANK in non-syndromic ID, we screened a cohort of 288 TANK deletion negative non-syndromic mental retardation patients for TANK mutations without identifying any pathogenic variant.

A Dermatologist's Ammunition in the War Against Smoking: A Photoaging App.

This viewpoint reviews the perspectives for dermatology as a specialty to go beyond the substantial impact of smoking on skin disease and leverage the impact of skin changes on a person's self-concept and behavior in the design of effective interventions for smoking prevention and cessation.