Background and objectives The incidence of skin cancer is rising worldwide and there is medical need to optimize its early detection. This study was conducted to determine the diagnostic and risk-assessment accuracy of two new diagnosis-based neural networks (analyze and detect), which comply with the CE-criteria, in evaluating the malignant potential of various skin lesions on a smartphone. Of note, the intention of our study was to evaluate the performance of these medical products in a clinical setting for the first time. Methods This was a prospective, single-center clinical study at one tertiary referral center in Graz, Austria. Patients, who were either scheduled for preventive skin examination or removal of at least one skin lesion were eligible for participation. Patients were assessed by at least two dermatologists and by the integrated algorithms on different mobile phones. The lesions to be recorded were randomly selected by the dermatologists. The diagnosis of the algorithm was stated as correct if it matched the diagnosis of the two dermatologists or the histology (if available). The histology was the reference standard, however, if both clinicians considered a lesion as being benign no histology was performed and the dermatologists were stated as reference standard. Results A total of 238 patients with 1171 lesions (86 female; 36.13%) with an average age of 66.19 (SD = 17.05) was included. Sensitivity and specificity of the detect algorithm were 96.4% (CI 93.94–98.85) and 94.85% (CI 92.46–97.23); for the analyze algorithm a sensitivity of 95.35% (CI 93.45–97.25) and a specificity of 90.32% (CI 88.1–92.54) were achieved. Discussion The studied neural networks succeeded analyzing the risk of skin lesions with a high diagnostic accuracy showing that they are sufficient tools in calculating the probability of a skin lesion being malignant. In conjunction with the wide spread use of smartphones this new AI approach opens the opportunity for a higher early detection rate of skin cancer with consecutive lower epidemiological burden of metastatic cancer and reducing health care costs. This neural network moreover facilitates the empowerment of patients, especially in regions with a low density of medical doctors. Registration Approved and registered at the ethics committee of the Medical University of Graz, Austria (Approval number: 30–199 ex 17/18).
Background Checkpoint inhibitors provide an effective approach for the melanoma treatment. They prolong lymphocyte effects, which explains the cytotoxicity underlying immune‐related adverse events (IrAEs). Cutaneous IrAEs affect nearly 40% of PD‐1i and 50% of CTLA4i‐treated patients. Severe cutaneous irAE do not often occur but could be life‐threatening and may persist despite treatment discontinuation. Methods We aimed to investigate cutaneous IrAEs in a cohort of patients treated with ICI across Europe in an effort to characterize the reactions in a real‐world, phase IV, post‐marketing study using a follow‐up questionnaire. Data since November 2016 until March 2021 were obtained from the Melskintox database, a European multicentric biobank dedicated to the follow‐up of melanoma and cutaneous adverse events, supported by EADO. The dermatoses reported were pooled into four categories: inflammatory dermatosis, bullous diseases, drug‐related eruptions and pigmentary diseases. Results Inflammatory benign dermatoses (n = 63) represented the most common group of reactions (52.5%), followed by drug‐related eruptions (n = 24, 20%), pigmentary diseases (n = 23, 19.2%) and bullous diseases (n = 10, 8.3%). Grade II (n = 41, 34.2%) are represented by bullous pemphigoid, eczema, hypodermitis, lichenoid eruption, maculopapular rash, pruritus, psoriasis‐like rash, urticarial eruption and vitiligo. Grade III (n = 18, 15.0%) are represented by bullous pemphigoid, lichenoid eruption and rashes. Grade IV (n = 2, 1.7%) is only represented by bullous disease. Most cutaneous IrAEs led to immunotherapy continuation (n = 95, 88.0%). CR is associated with more severe the cutaneous irAEs. We report an average time‐to‐onset of 208 days and some late‐onset events. Conclusion Our study has characterized the clinical spectrum of cutaneous irAEs, their timing and severity and their relationship with tumour response. Grade I–II cutaneous IrAE are easily managed allowing ongoing anticancer treatment. Severe late‐onset cutaneous irAE are not uncommon. A dermatological follow‐up helps mitigate the risk of life‐threatening adverse events. These findings highlight the importance of oncodermatological involvement in management of patients with melanoma receiving immunotherapy.
ZusammenfassungDie COVID-19-Pandemie stellt das weltweite Gesundheitssystem seit 2020 vor einzigartige Herausforderungen. Faszinierend und v. a. von besonderer gesundheitspolitischer Bedeutung ist es, dass es kaum 1 Jahr nach den ersten Berichten über COVID-19-Infektionen mehreren Forschungsgruppen gelungen ist, Impfstoffe gegen das Coronavirus zu entwickeln. Derzeit sind 3 Klassen von Impfstoffen verfügbar (mRNA-Impfstoffe, Vektorimpfstoffe und Impfstoffe, die das gesamte inaktivierte Virus enthalten). Wir berichten über eine Patientin, die kurz nach der ersten Gabe des Coronaimpfstoffes von AstraZeneca/Oxford (ChAdOx1) rötliche, teilweise urtikarielle Hautveränderungen am rechten Arm und der rechten Flanke entwickelte. Die Läsionen waren flüchtig, rezidivierten allerdings in loco und anderen Lokalisationen über einige Tage. Das klinische Bild war ungewöhnlich. Eine Unterscheidung zwischen einer – für uns am ehesten wahrscheinlichen – Impfstoff-getriggerten akuten Urtikaria und einem urtikariellen Exanthem war uns nicht sicher möglich.
BACKGROUNDThe incidence of malignant melanoma (MM) is continuously rising with nearly 300.000 cases worldwide in 2018, mostly due to improved early detection. 1,2 Dermoscopy showed an excellent diagnostic accuracy to distinguish early melanoma from atypical, pigmented skin lesions, which is, among others, indicated by a low reported tumour thickness. [3][4][5][6] However, ambiguous cases always require histopathological or molecular examination, which is still the gold standard. Several studies demonstrated that tape-stripping (TS), a technique to sample cells from the stratum corneum using adhesive tapes, can be used as a non-invasive alternative to tissue biopsies. [7][8][9][10][11] TS has been initially described decades ago, 12 but mostly in the context of assessing the morphology and number of keratinocytes using microscopy [13][14][15] or to determine the percutaneous penetration of topically applied drugs. 16 Early TS studies focused on epidermal pathology, but there is increasing research into the use of TS in other dermatoses, such as skin cancer, 11,17 and the microbiome. 18 Moreover, TS has been used to quantify protein of the stratum corneum by weight measurements or spectroscopy. 19 More recently TS has been used to detect epidermal transcriptomic changes from melanoma. 20 Using quantitative real-time polymerase, the company DermTech Inc. (La Jolla, CA, USA) offers a non-invasive assay to differentiate pigmented lesions from melanoma based on the expression of two marker genes for melanoma, LINC and PRAME. 20 Cullison and colleagues tried to improve the diagnostic accuracy of this test, by including mutations analysis of genes commonly mutated in melanoma such as TERT, BRAF and NRAS. 21 Moreover, TS enabled a differentiation of basal cell and squamous cell carcinomas from benign lesions. 22 Although not recommended for routine diagnostic evaluation in cutaneous melanoma, molecular testing may be useful to identify BRAF V600 mutations, which are associated with sensitivity to BRAF inhibitors, MEK (also known as MAP2K, mitogen-activated portein kinase kinase) inhibitors, and a combination of the two. 23 Furthermore, certain KIT mutations, which are found in 10%-15% of MM of mucosal and acral origin and in 2%-3% of MM that result from chronic sun exposure, appear to be highly sensitive to KIT inhibitors. 23 NRAS mutations may provide prognostic information and are found in roughly 15%. Although extremely rare, fusions in NTRK1, NTRK2, NTRK3,This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
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