Background: Ultraviolet radiation is the main environmental risk factor responsible for the development of skin cancer. Other occupational, socioeconomic, and environmental factors appear to be related to the risk of skin cancer. Furthermore, the factors appear to differ for melanoma and non‐melanoma skin cancer (NMSC). The purpose of this study is to analyze mortality rates of skin cancer in the different provinces of Spain and to determine the influence of socioeconomic conditions and other environmental and demographic factors in rates.Methods: Deaths from melanoma and NMSC in the period 2000–2019 were obtained as well as socioeconomic and environmental variables. Annual standardized mortality rates (SMR) were calculated for all Spanish provinces. The Pearson correlation coefficient was calculated.Results: The SMR of melanoma was 2.10/100,000 inhabitants, while that of NMSC was 1.28/100,000. At the provincial level, a great variability is confirmed. Gross domestic product showed a positive correlation with melanoma mortality but a negative correlation with NMSC. Other environmental and socioeconomic variables also showed correlation, as a positive correlation between tobacco sales and melanoma and between agricultural development and the NMSC.Conclusions: There are still important differences between each province that must be taken into account when planning health care and resource distribution. This ecological and province‐wise study helps to elucidate the relationship between social and ambient exposure determinants and skin cancer mortality in Spain.

Background: Dizziness and imbalance are common and disabling symptoms in patients with multiple sclerosis (MS) and are caused by a central, peripheral, or mixed vestibulopathy. Central vestibular disorder is the most frequently reported vestibular problem in the MS population due to demyelination. Vestibular rehabilitation ameliorates these symptoms and their repercussions and improves quality of life. Immersive virtual reality (VRi) is an emerging tool in this field; however, no previous research has been performed studying its effects in MS. Objective: The aim of this study was to apply a VRi vestibular training protocol to a patient with MS and assess the effects induced by the experimental intervention. Methods: This case study included a 54-year-old woman with relapsing-remitting MS. We developed a standardized VRi exercise protocol for vestibular rehabilitation based on the gold-standard Cawthorne-Cooksey vestibular training protocol. The 20-session intervention was made up of 10 initial sessions and 10 advanced sessions. Each 50-minute session was performed two to three times per week for 7 weeks. Four evaluations were carried out over the study period: at baseline (T0), between initial and advances phases (T1), postintervention (T2), and 1 month after the experimental procedure (T3). The research outcomes were dizziness, balance, gait, impact of fatigue, quality of life, repercussions in muscular tone, and usability of the head-mounted display device. Results: After implementing the VRi vestibular protocol, improvements were seen in the following patient parameters: Dizziness Handicap Inventory score (62 points at T0; 4 points at T2); Berg Balance Scale score (47 points at T0; 54 points at T2); instrumented Timed Up and Go time (8.35 seconds at T0; 5.57 seconds at T2); muscular tone of the erector spinae, rectus femoris, and soleus; Modified Fatigue Impact Scale score (61 points at T0; 37 points at T2); and Multiple Sclerosis Quality of Life-54 values (67.16% in the physical health area at T2; 33.56% in the mental health area at T2). The patient rated the usability of the system as 90%, based on the System Usability Scale, and gave the system a grade of A. Conclusions: Although further research is needed, this study provided initial evidence that the first VRi vestibular protocol for the MS population can improve dizziness, balance, gait, impact of fatigue, quality of life, and muscular tone through an exergame intervention. This study may help establish a standardized VRi protocol for vestibular rehabilitation.

Background: Digital strategies are innovative approaches to the prevention of skin cancer, but the attrition following this kind of intervention needs to be analyzed. Objective: The aim of this paper is to assess the dropouts from studies focused on digital strategies for the prevention of skin cancer. Methods: We conducted this systematic review with meta-analyses and metaregression according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statements. Search terms for skin cancer, digital strategies, and prevention were combined to search PubMed, Scopus, Web of Science, CINAHL, and Cochrane Library from inception until July 2022. Randomized clinical trials that reported dropouts of participants and compared digital strategies with other interventions to prevent skin cancer in healthy or disease-free participants were included. Two independent reviewers extracted data for analysis. The Revised Cochrane Collaboration Bias tool was employed. We calculated the pooled dropout rate of participants through a meta-analysis of proportions and examined whether dropout was more or less frequent in digital interventions against comparators via an odds ratio (OR) meta-analysis. Data were pooled using a random-effects model. Subgroup meta-analyses were conducted in a meta-analysis of proportions and OR meta-analysis to assess the dropout events when data were sorted by digital interventions or control comparator. A univariate metaregression based on a random-effects model assessed possible moderators of dropout. Participants’ dropout rates as pooled proportions were calculated for all groups combined, and the digital and comparator groups separately. OR>1 indicated higher dropouts for digital-based interventions. Metaregressions were performed for age, sex, length of intervention, and sample size. Results: A total of 17 studies were included. The overall pooled dropout rate was 9.5% (95% CI 5.0-17.5). The subgroup meta-analysis of proportions revealed a dropout rate of 11.6% for digital strategies (95% CI 6.8-19.0) and 10.0% for comparators (95% CI 5.5-17.7). A trend of higher dropout rates for digital strategies was observed in the overall (OR 1.16, 95% CI 0.98-1.36) and subgroup OR meta-analysis, but no significant differences were found between the groups. None of the covariates moderated the effect size in the univariate metaregression. Conclusions: Digital strategies had a higher dropout rate compared to other prevention interventions, but the difference was not significant. Standardization is needed regarding reporting the number of and reasons for dropouts. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42022329669; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=329669

Melanoma is considered a global public health challenge and is responsible for more than 90% deaths related to skin cancer. Although the diagnosis of early melanoma is the main goal of dermoscopy, the discrimination between dermoscopic images of in situ and invasive melanomas can be a difficult task even for experienced dermatologists. Recent advances in artificial intelligence in the field of medical image analysis show that its application to dermoscopy with the aim of supporting and providing a second opinion to the medical expert could be of great interest. In this work, four datasets from different sources were used to train and evaluate deep learning models on in situ versus invasive melanoma classification and on Breslow thickness prediction. Supervised learning and semi-supervised learning using a multi-teacher ensemble knowledge distillation approach were considered and evaluated using a stratified 5-fold cross-validation scheme. The best models achieved AUCs of 0.6186 $\pm$ 0.0410 and of 0.7501 $\pm$ 0.0674 on the former and latter classification tasks, respectively. The best results were obtained using semi-supervised learning, with the best model achieving 0.7751 and 0.8164 AUC, respectively. The results obtained show that semi-supervised learning could improve the performance of trained models in different melanoma classification tasks compared to supervised learning. Automatic deep learning-based diagnosis systems could support medical professionals in their decision, serving as a second opinion or as a triage tool for medical centers.

Purpose: Nonmelanoma skin cancer (NMSC), predominantly basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), represents the most common malignancy among fair-skinned populations. While BCC is rarely fatal, SCC contributes significantly to NMSC-related mortality. This study aimed to investigate long-term trends in NMSC incidence and SCC mortality across 28 European countries from 1992 to 2021, focusing on regional, sex-specific, and age-related variations. Methods/patients: A longitudinal ecological analysis was conducted using the Global Burden of Disease (GBD) database. Age-standardized incidence rates (ASIRs) for NMSC and age-standardized mortality rates (ASMRs) for SCC were calculated based on the 2013 European Standard Population. Temporal trends were evaluated using joinpoint regression, and age–period–cohort (APC) models were employed to disentangle independent effects on SCC mortality. Results: Europe registered over 27 million NMSC cases between 1992 and 2021. Overall ASIRs slightly declined, although increasing incidence was observed in individuals under 45 in Central and Northern Europe. SCC accounted for more than 570,000 deaths, with overall ASMRs decreasing—particularly among women and younger men. However, mortality rose in men aged over 75, notably in Northern and Western Europe. APC analysis indicated elevated SCC mortality in cohorts born before 1940, with a notable reversal in Northern European males born after 1960, who exhibited increasing mortality. Period effects further confirmed a recent rise in SCC mortality among these populations. Conclusions: Although NMSC incidence appears to be stabilizing or declining in much of Europe, increasing trends in younger individuals and rising SCC mortality in older men—especially in Northern Europe—highlight the need for age- and region-specific prevention and screening strategies. Improved cancer registry harmonization remains essential for guiding effective public health interventions. Graphical

Background: The distinction between in situ melanoma (MIS) and invasive melanoma is challenging even for expert dermatologists. The use of pretrained convolutional neural networks (CNNs) as ancillary decision systems needs further research. Aim: To develop, validate and compare three deep transfer learning (DTL) algorithms to predict MIS vs. invasive melanoma and melanoma with a Breslow thickness (BT) of < 0.8 mm vs. ≥ 0.8 mm. Methods: A dataset of 1315 dermoscopic images of histopathologically confirmed melanomas was created from Virgen del Rocio University Hospital and open repositories of the International Skin Imaging Collaboration archive and Polesie S et al. (Dermatol Pract Concept 2021; 11:e2021079). The images were labelled as MIS or invasive melanoma and < 0.8 mm or ≥ 0.8 mm of BT. We conducted three trainings, and overall means for receiver operating characteristic (ROC) curves, sensitivity, specificity, positive and negative predictive value, and balanced diagnostic accuracy outcomes were evaluated on the test set with ResNetV2, EfficientNetB6 and InceptionV3. The results of 10 dermatologists were compared with the algorithms. Grad-CAM gradient maps were generated, highlighting relevant areas considered by the CNNs within the images. Results: EfficientNetB6 achieved the highest diagnostic accuracy for the comparison between MIS vs. invasive melanoma (61%) and BT < 0.8 mm vs. ≥ 0.8 mm (75%). For the BT comparison, ResNetV2 with an area under the ROC curve of 0.76 and InceptionV3 with an area under the ROC curve of 0.75, outperformed the results obtained by the dermatologist group with an area under the ROC curve of 0.70. Conclusion: EfficientNetB6 recorded the best prediction results, outperforming the dermatologists for the comparison of 0.8 mm of BT. DTL could be an ancillary aid to support dermatologists’ decisions in the near future.