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BackgroundEarly detection of melanoma can be lifesaving but this remains a challenge. Recent diagnostic studies have revealed the superiority of artificial intelligence (AI) in classifying dermoscopic images of melanoma and nevi, concluding that these algorithms should assist a dermatologist’s diagnoses. ObjectiveThe aim of this study was to investigate whether AI support improves the accuracy and overall diagnostic performance of dermatologists in the dichotomous image–based discrimination between melanoma and nevus. MethodsTwelve board-certified dermatologists were presented disjoint sets of 100 unique dermoscopic images of melanomas and nevi (total of 1200 unique images), and they had to classify the images based on personal experience alone (part I) and with the support of a trained convolutional neural network (CNN, part II). Additionally, dermatologists were asked to rate their confidence in their final decision for each image. ResultsWhile the mean specificity of the dermatologists based on personal experience alone remained almost unchanged (70.6% vs 72.4%; P=.54) with AI support, the mean sensitivity and mean accuracy increased significantly (59.4% vs 74.6%; P=.003 and 65.0% vs 73.6%; P=.002, respectively) with AI support. Out of the 10% (10/94; 95% CI 8.4%-11.8%) of cases where dermatologists were correct and AI was incorrect, dermatologists on average changed to the incorrect answer for 39% (4/10; 95% CI 23.2%-55.6%) of cases. When dermatologists were incorrect and AI was correct (25/94, 27%; 95% CI 24.0%-30.1%), dermatologists changed their answers to the correct answer for 46% (11/25; 95% CI 33.1%-58.4%) of cases. Additionally, the dermatologists’ average confidence in their decisions increased when the CNN confirmed their decision and decreased when the CNN disagreed, even when the dermatologists were correct. Reported values are based on the mean of all participants. Whenever absolute values are shown, the denominator and numerator are approximations as every dermatologist ended up rating a varying number of images due to a quality control step. ConclusionsThe findings of our study show that AI support can improve the overall accuracy of the dermatologists in the dichotomous image–based discrimination between melanoma and nevus. This supports the argument for AI-based tools to aid clinicians in skin lesion classification and provides a rationale for studies of such classifiers in real-life settings, wherein clinicians can integrate additional information such as patient age and medical history into their decisions.

BackgroundThe incidence of melanoma is increasing faster than any other major cancer both in Brazil and worldwide. Southeast Brazil has especially high incidences of melanoma, and early detection is low. Exposure to ultraviolet (UV) radiation is a primary risk factor for developing melanoma. Increasing attractiveness is a major motivation among adolescents for tanning. A medical student-delivered intervention that takes advantage of the broad availability of mobile phones and adolescents’ interest in their appearance indicated effectiveness in a recent study from Germany. However, the effect in a high-UV index country with a high melanoma prevalence and the capability of medical students to implement such an intervention remain unknown. ObjectiveIn this pilot study, our objective was to investigate the preliminary success and implementability of a photoaging intervention to prevent skin cancer in Brazilian adolescents. MethodsWe implemented a free photoaging mobile phone app (Sunface) in 15 secondary school classes in southeast Brazil. Medical students “mirrored” the pupils’ altered 3-dimensional (3D) selfies reacting to touch on tablets via a projector in front of their whole grade accompanied by a brief discussion of means of UV protection. An anonymous questionnaire capturing sociodemographic data and risk factors for melanoma measured the perceptions of the intervention on 5-point Likert scales among 356 pupils of both sexes (13-19 years old; median age 16 years) in grades 8 to 12 of 2 secondary schools in Brazil. ResultsWe measured more than 90% agreement in both items that measured motivation to reduce UV exposure and only 5.6% disagreement: 322 (90.5%) agreed or strongly agreed that their 3D selfie motivated them to avoid using a tanning bed, and 321 (90.2%) that it motivated them to improve their sun protection; 20 pupils (5.6%) disagreed with both items. The perceived effect on motivation was higher in female pupils in both tanning bed avoidance (n=198, 92.6% agreement in females vs n=123, 87.2% agreement in males) and increased use of sun protection (n=197, 92.1% agreement in females vs n=123, 87.2% agreement in males) and independent of age or skin type. All medical students involved filled in a process evaluation revealing that they all perceived the intervention as effective and unproblematic, and that all pupils tried the app in their presence. ConclusionsThe photoaging intervention was effective in changing behavioral predictors for UV protection in Brazilian adolescents. The predictors measured indicated an even higher prospective effectiveness in southeast Brazil than in Germany (>90% agreement in Brazil vs >60% agreement in Germany to both items that measured motivation to reduce UV exposure) in accordance with the theory of planned behavior. Medical students are capable of complete implementation. A randomized controlled trial measuring prospective effects in Brazil is planned as a result of this study.

Objectives were to identify patients' treatment experiences and treatment expectations and assess their trajectories over the course of treatment with the IL-17A inhibitor secukinumab. Moreover, we aimed to document effects of psoriasis, factors that influence symptomatology, and prior treatment experiences. Patients and Methods: We conducted semi-structured interviews with n = 24 patients with moderate-to-severe plaque psoriasis and employed a qualitative content analysis to derive thematic and evaluative codes. Findings were validated via peer debriefings with experienced dermatologists. Results: Patients reported burdensome physical and psychological psoriasis symptoms and identified factors that can improve or worsen symptomatology, including stress and self-efficacy. Prior treatment experiences were mostly negative. Past barriers to effective treatment included time constraints or limited access. Concerning secukinumab, patients initially expected complete to partial remission of symptoms and occurrence or absence of side effects. Closer inspection of expectations and experiences revealed three trajectories. For most patients, initial expectations were met and future expectations remained unchanged. For the other patients, however, the experience did not match their initial expectation. One group then adapted their future expectations according to their experience, while the other group did not. Conclusion: To our knowledge, this is the first qualitative study to assess expectations towards treatment effectiveness and side effects, their trajectories, and interplay with experiences among psoriasis patients. Our findings highlight the value of further research on the subject in order to optimize care for psoriasis patients and to learn more about the trajectories and influence of treatment expectations in general. Plain Language Summary: Patients' expectations towards a certain treatment can influence how well it will work and whether side effects occur or not. Such effects have been shown for a wide range of conditions, including dermatological ones. For patients suffering from psoriasis, a chronic inflammatory skin disease, modern biologics offer promising treatment options. Therefore, modern biologics are likely associated with high expectations by patients. Yet, the roles of treatment expectations and the experiences of patients undergoing biologic treatment have only received little attention to date. With this qualitative study, we aimed to understand patients' perspectives on these treatments, the symptoms they suffer from, expectations towards treatment effectiveness and side effects as well as treatment experiences in the past and over the course of treatment with a modern biologic. To this end, we conducted and transcribed interviews with 24 patients after several months of biologic treatment. We then analyzed interview transcripts to determine underlying categories and summarized these in a common framework. We found that patients' debilitating physical and psychological symptoms were often not well controlled in past treatments. Still, patients had positive expectations with regard to biologic treatment. For a large group of patients, their actual experiences met their expectations, leaving them with unchanged expectations for the future. Another important finding was the good understanding of factors influencing their symptomatology that patients had, like stress and self-efficacy. The reported findings may aid doctors in their clinical work, to further improve care for psoriasis patients. [ABSTRACT FROM AUTHOR]