Zusammenfassung Das epitheloide Hämangiom ist eine benigne vaskuläre Neoplasie mit einem charakteristischen histologischen und immunhistochemischen Muster, insbesondere gekennzeichnet durch ein lymphozytäres Entzündungsinfiltrat mit beigemengten Eosinophilen und eine FOS-B-Expression. Die Abklärung der Diagnose ist von besonderem Stellenwert, da differenzialdiagnostisch auch maligne epitheloidzellig differenzierte vaskuläre Tumoren infrage kommen. Wir präsentieren eine Patientin mit multiplen epitheloiden Hämangiomen der Kopfhaut, begleitet von starken Schmerzen und Juckreiz. Die lange Vorgeschichte mit multiplen Therapieversuchen verdeutlicht den oft begrenzten Erfolg der aktuell zur Verfügung stehenden Behandlungsmodalitäten.

BackgroundImmune checkpoint inhibitors (ICIs) are the standard of care for metastatic cutaneous melanoma (mCM) patients, but their efficacy in young adults aged less than 40 years remains unclear.Materials and methodsWe retrospectively analyzed 303 stage IV melanoma patients of different ages treated with nivolumab, pembrolizumab, or ipilimumab plus nivolumab combination therapy. Clinical data and blood values such as LDH, CRP, and absolute immune cell counts were retrieved from the medical records. Pre-treatment serum concentrations of soluble immune checkpoint proteins were measured using ELISA. In addition, information on frequencies of various T cell subsets in the peripheral blood was collected from a previously reported study (ELEKTRA). Patient characteristics and clinical information was correlated with PFS and OS using univariate and multivariate cox regression analysis.ResultsOf 303 patients, 33 (11%) were ≤ 40 years old. The older patients had a median age of 64 (95% CI: 61–66). Concerning prognostic parameters, there was no difference between the age groups, e.g., in gender, LDH, or the existence of brain or liver metastases. Patients aged ≤ 40 years [p = 0.014; HR: 1.6 (95% CI: 1.1–2.4)], presence of liver metastases [p = 0.016; HR: 1.4 (95% CI: 1.0–1.9)], line of ICI treatment [p = 0.009; HR: 1.4 (1.0–1.9)], elevated LDH [p = 0.076; HR: 1.3 (95% CI: 0.97–1.8)], and brain metastasis [p = 0.080; HR: 1.3 (95% CI: 0.97–1.7)], were associated with shorter PFS in univariate analysis. Multivariate analysis revealed that the patient’s age (≤ 40 years) remains a high-risk factor upon adjusting for all potential confounders [p = 0.067; HR: 1.5 (95% CI: 0.97–2.3)]. Blood parameters revealed that patients ≤ 40 years have relatively higher frequencies of activated CD4 T cells (CD4 + Ki67 + CD4 + ICOS +) in the blood, and significantly lower number of basophils and CD45RA- memory T cells, compared to patients above 40 years (p < 0.05). In addition, patients ≤ 40 years experiencing disease progression within 6 months of ICI treatment had increased concentrations of sPDL1 (p = 0.05) and sTIM3 (p = 0.054) at baseline.ConclusionYoung patients with stage IV melanoma may experience shorter progression-free survival upon ICI treatment compared to patients above 40 years and are characterized by fewer basophils and memory T cells in the blood.

The impact of age on the clinical benefit of anti-PD1 immunotherapy in advanced melanoma patients has been evolving recently. Due to a reduced immune function in elderly patients, young patients with a robust immune system are theoretically expected to benefit more from the treatment approach. However, in contrast to this hypothesis, recent studies in patients with metastatic melanoma have demonstrated that immunotherapy, especially with anti-PD1 treatment, is less effective in patients below 65 years, on average, with significantly lower responses and reduced overall survival compared to patients above 65 years of age. Besides, data on young patients are even more sparse. Hence, in this review, we will focus on age-dependent differences in the previously described resistance mechanisms to the treatment and discuss the development of potential combination treatment strategies for enhancing the anti-tumor efficacy of anti-PD1 or PDL1 treatment in young melanoma patients.

BACKGROUND:Anti-PD1-based immunotherapy is currently used in most patients with advanced melanoma. Despite the remarkable data regarding overall survival, the optimal treatment duration is still unknown.METHODS:We evaluated the outcome of 125 patients with advanced melanoma with and without brain metastases (MBM), treated either with anti-PD1 monotherapy (N = 97) or combined with anti-CTLA4 (N = 28) after elective treatment discontinuation due to complete response (CR) (group A, N = 86), or treatment-limiting toxicity (N = 33) and investigator's decision (ID, N = 6) (group B) with subsequent CR.RESULTS:For group A, median duration of treatment (mDoT) was 22 months (range 5-49) and median time to CR 9 months (range 2-47). Accordingly, mDoT for group B was 3 months (range 0-36) and median time to CR 7 months (range 1-32). Seven patients from group A and three from group B experienced disease recurrence. Off-treatment survival was not reached. Median off-treatment response time (mOTRt) was 19 months (range 0-42) and 25 months (range 0-66), respectively. For MBM, mOTRt was 17 months (range 7-41) and 28 months (range 9-39), respectively. After a median follow-up of 38 months (range 9-70), seven (5.6%) patients had deceased, one (0.8%) due to melanoma.CONCLUSIONS:Treatment discontinuation is feasible also in patients with MBM. Efficacy outcomes seemed to be similar in both groups of patients who achieved CR, regardless of reason for discontinuation. In patients who experienced disease relapse, treatment re-challenge with anti-PD1 resulted in subsequent renewed response.

Eine 28-jährige Patientin präsentierte sich in unserer Ambulanz mit rezidivierenden, stark juckenden Papeln am Rumpf. Diese bestanden seit etwa 12 Monaten und seien zwischenzeitlich mehrmals spontan abgeheilt. Im Vordergrund stand der tageszeitunabhängige, quälende Juckreiz. Es bestanden keine Komorbiditäten, die Patientin war bisher hautgesund und nahm keinerleiMedikamente ein. Bereits ein halbes Jahr zuvor erfolgte die Vorstellung in einer anderen Hautklinik, wo mittels Hautprobe die Diagnose einer Follikulitis gestellt wurde. Eine Dermatitis herpetiformis Duhring und ein Lichen ruber seien ausgeschlossen worden. Vortherapien erfolgten mit antiseptischen Waschlotionen, steroidhaltigen Externa und topischen Antibiotika sowie Antimykotika jeweils ohne Befundbesserung.

Noduläre Hauttumoren bei Kindern beunruhigen bisweilen aufgrund ihrer dynamischen Veränderungen und raschen Wachstums Eltern und Behandler. Die Häufigkeit des Auftretens bei Kindern macht klinisch-praktische Hinweise zur Einordnung notwendig. Die Arbeit liefert eine Übersicht häufiger, schnell wachsender, nodulärer Hauttumoren im Kindesalter. Makroskopische, dermatoskopische sowie dermatohistopathologische Charakteristika werden neben Hinweisen zu Diagnostik und Therapie dargestellt. Das im Artikel vorgestellte juvenile Xanthogranulom, Mastozytom und Pilomatrixom können ebenso wie eine kutane Langerhans-Zell-Histiozytose auf eine Multisystemerkrankung bzw. bestehende Grunderkrankungen hinweisen. Die meisten Hauttumoren bei Kindern sind benigne, selbstlimitierend und bedürfen keiner weiteren Therapie, während beispielsweise der Spitz-Nävus im Zweifel exzidiert oder zumindest engmaschig verlaufsbeobachtet werden sollte. Trotz der Gutartigkeit und hohen Spontanheilungstendenz vieler Hauttumoren im Kindesalter ist die klinische Unterscheidung oft schwierig, sodass zur Diagnosestellung eine histologische Untersuchung indiziert ist. Dabei sollte auf eine vollständige Entfernung ohne Entstehung entstellender Narben geachtet werden. Pädiater sowie Dermatologen sollten mit dem klinischen und histologischen Bild häufiger kindlicher Hauttumoren vertraut sein. Bei Entitäten mit möglichem Systembefall sollte eine weiterführende Diagnostik veranlasst werden.

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.

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). (C) 2019 The Author(s). Published by Elsevier Ltd.

Background: Recent studies have demonstrated the use of convolutional neural networks (CNNs) to classify images of melanoma with accuracies comparable to those achieved by board-certified dermatologists. However, the performance of a CNN exclusively trained with dermoscopic images in a clinical image classification task in direct competition with a large number of dermatologists has not been measured to date. This study compares the performance of a convolutional neuronal network trained with dermoscopic images exclusively for identifying melanoma in clinical photographs with the manual grading of the same images by dermatologists. Methods: We compared automatic digital melanoma classification with the performance of 145 dermatologists of 12 German university hospitals. We used methods from enhanced deep learning to train a CNN with 12,378 open-source dermoscopic images. We used 100 clinical images to compare the performance of the CNN to that of the dermatologists. Dermatologists were compared with the deep neural network in terms of sensitivity, specificity and receiver operating characteristics. Findings: The mean sensitivity and specificity achieved by the dermatologists with clinical images was 89.4% (range: 55.0%-100%) and 64.4% (range: 22.5%-92.5%). At the same sensitivity, the CNN exhibited a mean specificity of 68.2% (range 47.5%-86.25%). Among the dermatologists, the attendings showed the highest mean sensitivity of 92.8% at a mean specificity of 57.7%. With the same high sensitivity of 92.8%, the CNN had a mean specificity of 61.1%. Interpretation: For the first time, dermatologist-level image classification was achieved on a clinical image classification task without training on clinical images. The CNN had a smaller variance of results indicating a higher robustness of computer vision compared with human assessment for dermatologic image classification tasks. (C) 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

e21042 Background: Immunotherapy (IT) has demonstrated an improved overall survival (OS) in advanced melanoma with 15% complete responses (CR) in treatment-naïve patients (pts) with brain metastases (met) in the anti-PD1/anti-CTLA4 combination. However, data on brain-met pts who discontinue treatment (EoT) after achieving a CR are lacking. Methods: Disease characteristics and clinical outcome were retrospectively collected from 6 centers on advanced melanoma pts treated with anti-PD1 or anti-PD1/anti-CTLA4. Pts were followed for at least 10 weeks (10.8 – 242). Off-treatment survival (OTS) was defined as time between last IT dose to disease progression or death. Results: Out of 890 pts, 62 achieved a CR; 40 pts stopped treatment due to CR, while 22 due to an adverse event (AE) (n = 19) or investigator decision (n = 3) with subsequent CR. 14 were treated with anti-PD1/anti-CTLA4 and 48 with anti-PD1. 24 had a BRAF mutation, of which 10 had previously received targeted therapy (TT). The median time to first CR was 31 weeks (6 – 138), median duration of response and OTS was 91.1 and 60.7 (10.6 – 242) weeks respectively. OTS was numerically longer for those pts with EoT after AE (85 weeks, 13-242) versus those with EoT due to CR (60 weeks, 11-130). Median OS was not reached. 6/62 (3%) progressed after EoT; 4 locoregionally while 2 were subsequently treated with IT. All pts were alive at last follow-up. 19 pts had brain mets. 8 were BRAF mutated. 10 were treatment naïve, 6 received previously anti-CTLA4, 1 chemotherapy and only 2 TT. Data on reasons for EoT and responses in brain mets are seen in the table. Conclusions: Early data suggest that OTS is numerically longer in patients with EoT due to AE with subsequent CR. EoT due to sustained CR is a feasible option also in brain mets. EoT due to AE with subsequent CR was a more frequent event in the combination treatment. [Table: see text]