Multiarm study comparing patient-reported and clinical outcome measures in patients undergoing antipsoriatic therapy with non-biological systemic agents in a real-world setting.

BACKGROUND: Although the inclusion of patients' preferences and needs is essential for therapy adherence, the assessment of patient-reported outcome measures in clinical trials is often neglected. Therefore, the aim of this study was to quantify several patient-reported outcome measures in psoriasis patients undergoing systemic therapy in a real-life clinical setting. METHODS: This clinical trial has been designed as a prospective, multiarm study to investigate the treatment satisfaction, adherence to therapy, quality of life (QoL), and clinical response in a real-life clinical setting during the initial 6 months of treatment with apremilast, methotrexate, and fumaric acids in 80 patients suffering from plaque psoriasis. RESULTS: The treatment satisfaction for the three systemic therapies was rated 'sufficient' with a mean (±SD) Treatment Satisfaction Questionnaire for Medication (TSQM) score of 275.0 (±62.7). Most potential for improvement was seen in the 'effectiveness' domain (54.3 ± 21.5). The highest treatment satisfaction level in all four domains (convenience, effectiveness, global satisfaction, and side-effects) was seen in the methotrexate group with a mean TSQM score of 306.3 ± 50.9, followed by apremilast (267.1 ± 61.6) and fumaric acids (254.9 ± 65.0; p = 0.005). Analysis of the TSQM revealed a considerable discrepancy between patient-reported clinical response and the actual Psoriasis Area and Severity Index (PASI) reduction. This applies equally to the patient- vs. physician-reported side-effects. CONCLUSIONS: This real-life study demonstrates that an adequate assessment of antipsoriatic drugs by PASI-reduction alone is not sufficient and underlines the importance of patient-reported outcome measures not only in clinical trials, but also for improved patient care.

ACKR3 regulates platelet activation and ischemia-reperfusion tissue injury.

Platelet activation plays a critical role in thrombosis. Inhibition of platelet activation is a cornerstone in treatment of acute organ ischemia. Platelet ACKR3 surface expression is independently associated with all-cause mortality in CAD patients. In a novel genetic mouse strain, we show that megakaryocyte/platelet-specific deletion of ACKR3 results in enhanced platelet activation and thrombosis in vitro and in vivo. Further, we performed ischemia/reperfusion experiments (transient LAD-ligation and tMCAO) in mice to assess the impact of genetic ACKR3 deficiency in platelets on tissue injury in ischemic myocardium and brain. Loss of platelet ACKR3 enhances tissue injury in ischemic myocardium and brain and aggravates tissue inflammation. Activation of platelet-ACKR3 via specific ACKR3 agonists inhibits platelet activation and thrombus formation and attenuates tissue injury in ischemic myocardium and brain. Here we demonstrate that ACKR3 is a critical regulator of platelet activation, thrombus formation and organ injury following ischemia/reperfusion.

Does sex matter? Analysis of sex-related differences in the diagnostic performance of a market-approved convolutional neural network for skin cancer detection.

BACKGROUND: Advances in biomedical artificial intelligence may introduce or perpetuate sex and gender discriminations. Convolutional neural networks (CNN) have proven a dermatologist-level performance in image classification tasks but have not been assessed for sex and gender biases that may affect training data and diagnostic performance. In this study, we investigated sex-related imbalances in training data and diagnostic performance of a market-approved CNN for skin cancer classification (Moleanalyzer Pro®, Fotofinder Systems GmbH, Bad Birnbach, Germany). METHODS: We screened open-access dermoscopic image repositories widely used for CNN training for distribution of sex. Moreover, the sex-related diagnostic performance of the market-approved CNN was tested in 1549 dermoscopic images stratified by sex (female n = 773; male n = 776). RESULTS: Most open-access repositories showed a marked under-representation of images originating from female (40%) versus male (60%) patients. Despite these imbalances and well-known sex-related differences in skin anatomy or skin-directed behaviour, the tested CNN achieved a comparable sensitivity of 87.0% [80.9%-91.3%] versus 87.1% [81.1%-91.4%], specificity of 98.7% [97.4%-99.3%] versus 96.9% [95.2%-98.0%] and ROC-AUC of 0.984 [0.975-0.993] versus 0.979 [0.969-0.988] in dermoscopic images of female versus male origin, respectively. In the sample at hand, sex-related differences in ROC-AUCs were not statistically significant in the per-image analysis nor in an additional per-individual analysis (p ≥ 0.59). CONCLUSION: Design and training of artificial intelligence algorithms for medical applications should generally acknowledge sex and gender dimensions. Despite sex-related imbalances in open-access training data, the diagnostic performance of the tested CNN showed no sex-related bias in the classification of skin lesions.

Training and Retaining Physician‒Scientists in Dermatology: The German Perspective.

In an ideal setting, physician‒scientists combine clinical practice and knowledge with scientific curiosity and research in synergy. Li et al. address the current challenges regarding the rare breed of physician‒scientists in the United States-much similar to those faced in German dermatology departments. The authors discuss multiple angles to transform the so-called leaky pipeline into a streamline of dermatologists in science.

Monitoring patients at risk for melanoma: May convolutional neural networks replace the strategy of sequential digital dermoscopy?

BACKGROUND: Sequential digital dermoscopy (SDD) is applied for early melanoma detection by uncovering dynamic changes of monitored lesions. Convolutional neural networks (CNN) are capable of high diagnostic accuracies similar to trained dermatologists. OBJECTIVES: To investigate the capability of CNN to correctly classify melanomas originally diagnosed by mere dynamic changes during SDD. METHODS: A retrospective cross-sectional study using image quartets of 59 high-risk patients each containing one melanoma diagnosed by dynamic changes during SDD and three nevi (236 lesions). Two validated CNN classified quartets at baseline or after SDD follow-up at the time of melanoma diagnosis. Moreover, baseline quartets were rated by 26 dermatologists. The main outcome was the number of quartets with correct classifications. RESULTS: CNN-1 correctly classified 9 (15.3%) and CNN-2 8 (13.6%) of 59 baseline quartets. In baseline images, CNN-1 attained a sensitivity of 25.4% (16.1%-37.8%) and specificity of 92.7% (87.8%-95.7%), whereas CNN-2 of 28.8% (18.8%-41.4%) and 75.7% (68.9%-81.4%). Expectedly, after SDD follow-up CNN more readily detected melanomas resulting in improved sensitivities (CNN-1: 44.1% [32.2%-56.7%]; CNN-2: 49.2% [36.8%-61.6%]). Dermatologists were told that each baseline quartet contained one melanoma, and on average, correctly classified 24 (22-27) of 59 quartets. Correspondingly, accepting a baseline quartet to be appropriately classified whenever the highest malignancy score was assigned to the melanoma within, CNN-1 and CNN-2 correctly classified 28 (47.5%) and 22 (37.3%) of 59 quartets, respectively. CONCLUSIONS: The tested CNN could not replace the strategy of SDD. There is a need for CNN capable of integrating information on dynamic changes into analyses.

Mikrovaskuläre Pathologien bei Patienten mit Psoriasis vulgaris mittels Nagelfalzkapillarmikroskopie identifiziert: Ergebnisse einer prospektiven kontrollierten Studie.

Hintergrund: Die Psoriasis gilt als unabhängiger kardiovaskulärer Risikofaktor und Treiber einer Atherogenese. Mikrovaskuläre Veränderungen in psoriatischen Plaques sind gut beschrieben, wohingegen Veränderungen außerhalb betroffener Hautareale kaum untersucht wurden. In dieser Studie wurden Nagelfalzkapillaren von Psoriasispatienten in nicht betroffener Haut systematisch untersucht. Patienten und Methodik: Prospektive Studie mit Untersuchung von Nagelfalzkapillaren bei Psoriasispatienten im Vergleich zu gesunden Kontrollen mittels digitaler Videokapillarmikroskopie. Es wurden 21 kapillarmikroskopische Parameter bewertet und die Ergebnisse mit Charakteristika der Patienten und der Psoriasiserkrankung, mit Laborparametern und Messungen der Intima-Media-Dicke der Arteria carotis communis korreliert. Ergebnisse: Die 77 Psoriasispatienten (24 mit zusätzlicher Psoriasisarthritis) und 71 Kontrollen zeigten sich hinsichtlich demographischer Merkmale und relevanter Einflussfaktoren für eine Mikroangiopathie ausbalanciert. Im Vergleich zur Kontrollgruppe zeigten Psoriasispatienten eine signifikante Minderung der kapillaren Dichte, häufigere Kapillarerweiterung mit mehr Verzweigungen, Torquierungen und kapillaren Unregelmäßigkeiten. Zusätzlich zeigten Psoriasispatienten signifikant höhere inflammatorische Serummarker und eine gesteigerte Intima-Media-Dicke. In unserem Kollektiv bestand kein Zusammenhang zwischen Krankheitsdauer oder Schweregrad der Psoriasis und spezifischen Kapillarveränderungen. Schlussfolgerungen: Die Nagelfalzkapillaren der untersuchten Psoriasispatienten zeigten ausgeprägte mikrovaskuläre Veränderungen, welche mit erhöhten Markern einer systemischen Entzündung und Frühzeichen einer Atherosklerose korrelierten. Weitere Studien sind erforderlich, um die Rolle der digitalen Videokapillarmikroskopie in der Bewertung des kardiovaskulären Risikos von Psoriasispatienten zu untersuchen.

Nailfold videocapillaroscopy identifies microvascular pathologies in psoriasis vulgaris: Results of a prospective controlled study.

BACKGROUND: Psoriasis is considered an independent cardiovascular risk factor, evidentially driving atherosclerosis. However, little is known about changes in the microvasculature of non-lesional skin in psoriasis patients. This study systematically examined capillary pathologies in psoriasis patients by digital video nailfold capillaroscopy. PATIENTS AND METHODS: Prospective study comparing nailfold capillaries of psoriasis patients with those of healthy controls. Nailfold capillaries were evaluated for 21 parameters and results were correlated with characteristics of patients and psoriatic disease, laboratory parameters, and measurements of carotid intima-media thickness. RESULTS: 77 psoriasis patients (24 patients with additional psoriatic arthritis) and 71 controls were well-matched for demographic features and for relevant confounding factors causing microangiopathy. In comparison with controls, psoriasis patients showed a significant loss of capillaries, capillary expansion with increased ramifications and tortuosity and capillary irregularities. Moreover, in psoriasis patients we found significantly elevated serum markers of inflammation and significantly increased intima-media-thickness measurements. We found no effect of disease duration nor disease activity on capillary changes. CONCLUSIONS: Nailfold capillaries of psoriasis patients showed marked microvascular abnormalities accompanied by increased markers of systemic inflammation and atherosclerosis. Prospective cohort studies are needed to assess the role of nailfold capillaroscopy for predicting the cardiovascular risk of psoriasis patients.

Auswirkungen des "dunklen Rand-Artefakts" in dermatoskopischen Bildern auf die diagnostische Leistungsfähigkeit eines deep learning neuronalen Netzwerkes mit Marktzulassung.

HINTERGRUND UND ZIELE: Systeme künstlicher Intelligenz (durch "deep learning" faltende neuronale Netzwerke; engl. convolutional neural networks, CNN) erreichen inzwischen bei der Klassifikation von Hautläsionen vergleichbar gute Ergebnisse wie Dermatologen. Allerdings müssen die Limitationen solcher Systeme vor flächendeckendem klinischem Einsatz bekannt sein. Daher haben wir den Einfluss des "dunklen Rand-Artefakts" (engl. dark corner artefact; DCA) in dermatoskopischen Bildern auf die diagnostische Leistung eines CNN mit Marktzulassung zur Klassifikation von Hautläsionen untersucht. PATIENTEN UND METHODEN: Ein Datensatz aus 233 Bildern von Hautläsionen (60 maligne und 173 benigne) ohne DCA (Kontrolle) wurde digital so modifiziert, dass kleine, mittlere oder große DCA zu sehen waren. Alle 932 Bilder wurden dann mittels CNN mit Marktzulassung (Moleanalyzer-Pro® , FotoFinder Systems) auf Malignitätsscores hin analysiert. Das Spektrum reichte von 0-1; ein Score von > 0,5 wurde als maligne klassifiziert. ERGEBNISSE: In der Kontrollserie ohne DCA erreichte das CNN eine Sensitivität von 90,0 % (79,9 %-95,3 %), eine Spezifität von 96,5 % (92,6 %-98,4 %) sowie eine Fläche unter der Kurve (AUC, area under the curve) der "receiver operating characteristic" (ROC) von 0,961 (0,932-0,989). In den Datensätzen mit kleinen beziehungsweise mittleren DCA war die diagnostische Leistung vergleichbar. In den Bildersätzen mit großen DCA wurden allerdings signifikant höhere Malignitätsscores erzielt. Dies führte zu einer signifikant verminderten Spezifität (87,9 % [82,2 %-91,9 %], P < 0,001) sowie einer nicht signifikant erhöhten Sensitivität (96,7 % [88,6 %-99,1 %]). Die ROC-AUC blieb mit 0,962 (0,935-0,989) unverändert. SCHLUSSFOLGERUNGEN: Die Klassifizierung mittels des CNN war bei dermatoskopischen Bildern mit kleinen oder mittleren DCA nicht beeinträchtigt, das System zeigte jedoch Schwächen bei großen DCA. Wenn Ärzte solche Bilder zur Klassifikation mittels CNN einreichen, sollten sie sich dieser Grenzen der Technologie bewusst sein.