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Most melanomas progress from radial to vertical growth phase before spreading locoregionally and distally. Much is still unknown about the metabolic changes in the tumor cells and their microenvironment during this metastatic progression. We aimed to gain new insight into the molecular characteristics of melanoma in regard to spatial lipidomics to deliver new knowledge regarding tumor metastatic progression. We included 10 fresh tumor samples from 10 patients including two in situ melanomas, two invasive primary melanomas, and six metastatic melanomas (four in-transit metastases and two distant metastases). In addition, we analyzed four healthy skin controls from the same patients. Time-of-flight imaging secondary ion mass spectrometry (ToF-SIMS) enabled detailed spatial-lipidomics that could be directly correlated with conventional histopathological analysis of consecutive H&E-stained tissue sections. Significant differences in the lipid profiles were found in primary compared to metastatic melanomas, notably an increase in phosphatidylethanolamine lipids relative to phosphatidylinositol lipids and an increase in GM3 gangliosides in the metastatic samples. Furthermore, analysis of the data from in transit versus distant metastases samples highlighted that specific phospholipids, and a difference in the long versus shorter chain GM3 gangliosides, discriminated the metastatic routes. Further studies are warranted to verify these preliminary findings. Lipidomic changes could serve as a novel biomarker for tumor progression and even serve as a target for novel treatments. Furthermore, analyzing the lipid profiles could help to differentiate between primary and metastatic melanomas in challenging cases., (© 2024 The Author(s). Pigment Cell & Melanoma Research published by John Wiley & Sons Ltd.)

Background: The detection of cutaneous metastases (CMs) from various primary tumours represents a diagnostic challenge., Objectives: Our aim was to evaluate the general characteristics and dermatoscopic features of CMs from different primary tumours., Methods: Retrospective, multicentre, descriptive, cross-sectional study of biopsy-proven CMs., Results: We included 583 patients (247 females, median age: 64 years, 25%-75% percentiles: 54-74 years) with 632 CMs, of which 52.2% (n = 330) were local, and 26.7% (n = 169) were distant. The most common primary tumours were melanomas (n = 474) and breast cancer (n = 59). Most non-melanoma CMs were non-pigmented (n = 151, 95.6%). Of 169 distant metastases, 54 (32.0%) appeared on the head and neck region. On dermatoscopy, pigmented melanoma metastases were frequently structureless blue (63.6%, n = 201), while amelanotic metastases were typified by linear serpentine vessels and a white structureless pattern. No significant difference was found between amelanotic melanoma metastases and CMs of other primary tumours., Conclusions: The head and neck area is a common site for distant CMs. Our study confirms that most pigmented melanoma metastasis are structureless blue on dermatoscopy and may mimic blue nevi. Amelanotic metastases are typified by linear serpentine vessels and a white structureless pattern, regardless of the primary tumour., (© 2024 European Academy of Dermatology and Venereology.)

Background: Use of artificial intelligence (AI), or machine learning, to assess dermoscopic images of skin lesions to detect melanoma has, in several retrospective studies, shown high levels of diagnostic accuracy on par with - or even outperforming - experienced dermatologists. However, the enthusiasm around these algorithms has not yet been matched by prospective clinical trials performed in authentic clinical settings. In several European countries, including Sweden, the initial clinical assessment of suspected skin cancer is principally conducted in the primary healthcare setting by primary care physicians, with or without access to teledermoscopic support from dermatology clinics., Objectives: To determine the diagnostic performance of an AI-based clinical decision support tool for cutaneous melanoma detection, operated by a smartphone application (app), when used prospectively by primary care physicians to assess skin lesions of concern due to some degree of melanoma suspicion., Methods: This prospective multicentre clinical trial was conducted at 36 primary care centres in Sweden. Physicians used the smartphone app on skin lesions of concern by photographing them dermoscopically, which resulted in a dichotomous decision support text regarding evidence for melanoma. Regardless of the app outcome, all lesions underwent standard diagnostic procedures (surgical excision or referral to a dermatologist). After investigations were complete, lesion diagnoses were collected from the patients' medical records and compared with the app's outcome and other lesion data., Results: In total, 253 lesions of concern in 228 patients were included, of which 21 proved to be melanomas, with 11 thin invasive melanomas and 10 melanomas in situ. The app's accuracy in identifying melanomas was reflected in an area under the receiver operating characteristic (AUROC) curve of 0.960 [95% confidence interval (CI) 0.928-0.980], corresponding to a maximum sensitivity and specificity of 95.2% and 84.5%, respectively. For invasive melanomas alone, the AUROC was 0.988 (95% CI 0.965-0.997), corresponding to a maximum sensitivity and specificity of 100% and 92.6%, respectively., Conclusions: The clinical decision support tool evaluated in this investigation showed high diagnostic accuracy when used prospectively in primary care patients, which could add significant clinical value for primary care physicians assessing skin lesions for melanoma., Competing Interests: Conflicts of interest P.P. is a co-founder of the clinical decision support (Dermalyser®) studied in the clinical trial. The other authors declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of British Association of Dermatologists.)

Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. In this study, we attempted to evaluate agreement among experts on exemplar images not only for the presence of melanocytic-specific features but also for spatial localization. This was a cross-sectional, multicenter, observational study. Dermoscopy images exhibiting at least 1 of 31 melanocytic-specific features were submitted by 25 world experts as exemplars. Using a web-based platform that allows for image markup of specific contrast-defined regions (superpixels), 20 expert readers annotated 248 dermoscopic images in collections of 62 images. Each collection was reviewed by five independent readers. A total of 4,507 feature observations were performed. Good-to-excellent agreement was found for 14 of 31 features (45.2%), with eight achieving excellent agreement (Gwet's AC >0.75) and seven of them being melanoma-specific features. These features were peppering/granularity (0.91), shiny white streaks (0.89), typical pigment network (0.83), blotch irregular (0.82), negative network (0.81), irregular globules (0.78), dotted vessels (0.77), and blue-whitish veil (0.76). By utilizing an exemplar dataset, a good-to-excellent agreement was found for 14 features that have previously been shown useful in discriminating nevi from melanoma. All images are public (www.isic-archive.com) and can be used for education, scientific communication, and machine learning experiments., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Atypical pigmented facial lesions (aPFLs) often display clinical and dermoscopic equivocal and/or overlapping features, thus causing a challenging and delayed diagnosis and/or inappropriate excisions. No specific registry dedicated to aPFL paired with clinical data is available to date. Methods : The dataset is hosted on a specifically designed web platform. Each complete case was composed of the following data: (1) one dermoscopic picture; (2) one clinical picture; (3) two lesion data, that is, maximum diameter and facial location (e.g., orbital area/forehead/nose/cheek/chin/mouth); (4) patient's demographics: family history of melanoma, history of sunburns in childhood, phototype, pheomelanine, eyes/hair color, multiple nevi/dysplastic nevi on the body; and (5) acquisition device (videodermatoscope/camera-based/smartphone-based system). Results: A total of 11 dermatologic centers contributed to a final teledermoscopy database of 1,197 aPFL with a distribution of 353 lentigo maligna (LM), 146 lentigo maligna melanoma (LMM), 231 pigmented actinic keratoses, 266 solar lentigo, 125 atypical nevi, 48 seborrheic keratosis, and 28 seborrheic-lichenoid keratoses. The cheek site was involved in half of aPFL cases (50%). Compared with those with the other aPFL cases, patients with LM/LMM were predominantly men, older (69.32 ± 12.9 years on average vs. 62.69 ± 14.51), exhibited larger lesions (11.88 ± 7.74 mm average maximum diameter vs. 9.33 ± 6.46 mm), and reported a positive history of sunburn in childhood. Conclusions: The iDScore facial dataset currently represents a precious source of data suitable for the design of diagnostic support tools based on risk scoring classifiers to help dermatologists in recognizing LM/LMM among challenging aPFL in clinical practice.

Background and objectives : Dermoscopy is a useful tool for the early and non-invasive diagnosis of skin malignancies. Besides many progresses, heavily pigmented and amelanotic skin tumors remain still a challenge. We aimed to investigate by dermoscopy if distinctive morphologic characteristics of vessels may help the diagnosis of equivocal nodular lesions. Materials and Methods: A collage of 16 challenging clinical and dermoscopic images of 8 amelanotic and 8 heavily pigmented nodular melanomas and basal cell carcinomas was sent via e-mail to 8 expert dermoscopists. Results: Dermoscopy improved diagnostic accuracy in 40 cases. Vessels were considered the best clue in 71 cases. Focusing on the diameter of vessels improved diagnosis in 5 cases. Conclusions: vascular diameter in addition to morphology and arrangement may be a useful dermoscopic clue for the differential diagnosis of clinically equivocal nodular malignant tumors.

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasive melanoma, 88 melanoma in situ, 115 dysplastic naevi, and 48 non-dysplastic naevi. The study included a training set of 358,800 pixels and a validation set of 7,313 pixels, which was then tested with a training set of 24,375 pixels. The majority vote classification achieved high overall sensitivity of 95% and a specificity of 92% (95% confidence interval (95% CI) 0.024-0.029) in differentiating malignant from benign lesions. In the pixel-wise classification, the overall sensitivity and specificity were both 82% (95% CI 0.005-0.005). When divided into 4 subgroups, the diagnostic accuracy was lower. Hyperspectral imaging provides high sensitivity and specificity in distinguishing between naevi and melanoma. This novel method still needs further validation.

Convolutional neural networks (CNNs) have shown promise in discriminating between invasive and in situ melanomas. The aim of this study was to analyse how a CNN model, integrating both clinical close-up and dermoscopic images, performed compared with 6 independent dermatologists. The secondary aim was to address which clinical and dermoscopic features dermatologists found to be suggestive of invasive and in situ melanomas, respectively. A retrospective investigation was conducted including 1,578 cases of paired images of invasive (n = 728, 46.1%) and in situ melanomas (n = 850, 53.9%). All images were obtained from the Department of Dermatology and Venereology at Sahlgrenska University Hospital and were randomized to a training set (n = 1,078), a validation set (n = 200) and a test set (n = 300). The area under the receiver operating characteristics curve (AUC) among the dermatologists ranged from 0.75 (95% confidence interval 0.70-0.81) to 0.80 (95% confidence interval 0.75-0.85). The combined dermatologists' AUC was 0.80 (95% confidence interval 0.77-0.86), which was significantly higher than the CNN model (0.73, 95% confidence interval 0.67-0.78, p = 0.001). Three of the dermatologists significantly outperformed the CNN. Shiny white lines, atypical blue-white structures and polymorphous vessels displayed a moderate interobserver agreement, and these features also correlated with invasive melanoma. Prospective trials are needed to address the clinical usefulness of CNN models in this setting.

Several melanoma-specific dermoscopic features have been described, some of which have been reported as indicative of in situ or invasive melanomas. To assess the usefulness of these features to differentiate between these 2 categories, a retrospective, single-centre investigation was conducted. Dermoscopic images of melanomas were reviewed by 7 independent dermatologists. Fleiss' kappa (κ) was used to analyse interobserver agreement of predefined features. Logistic regression and odds ratios were used to assess whether specific features correlated with melanoma in situ or invasive melanoma. Overall, 182 melanomas (101 melanoma in situ and 81 invasive melanomas) were included. The interobserver agreement for melanoma-specific features ranged from slight to substantial. Atypical blue-white structures (κ=0.62, 95% confidence interval 0.59-0.65) and shiny white lines (κ=0.61, 95% confidence interval 0.58-0.64) had a substantial interobserver agreement. These 2 features were also indicative of invasive melanomas >1.0 mm in Breslow thickness. Furthermore, regression/peppering correlated with thin invasive melanomas. The overall agreement for classification of the lesions as invasive or melanoma in situ was moderate (κ=0.52, 95% confidence interval 0.49-0.56).

Methotrexate treatment has been linked with an increased risk of melanoma. However, a possible dose-response relationship with respect to methotrexate exposure and melanoma has not been addressed. The aim of the present study was to investigate whether higher accumulated doses of methotrexate correlate with an increased risk of melanoma, which would further support a possible association. A nationwide retrospective cohort study was conducted. All Swedish patients over 18 years of age who were dispensed methotrexate in the period 2005 to 2014 were registered (n = 101,966) and matched to the cancer registry. A Cox proportional hazards model, testing risk of melanoma vs. total accumulated methotrexate dose, controlled for sex, age group, and time from first to last dispensed prescription of methotrexate, yielded no significant risk dependence on dose, and a hazard ratio of 1.02 (95% CI 0.97-1.08). Overall, no conclusive dose-response relationship was observed between methotrexate exposure and risk of melanoma.

Background: Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking., Methods: Google's Inception v4 CNN architecture was trained and validated using dermoscopic images and corresponding diagnoses. In a comparative cross-sectional reader study a 100-image test-set was used (level-I: dermoscopy only; level-II: dermoscopy plus clinical information and images). Main outcome measures were sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for diagnostic classification (dichotomous) of lesions by the CNN versus an international group of 58 dermatologists during level-I or -II of the reader study. Secondary end points included the dermatologists' diagnostic performance in their management decisions and differences in the diagnostic performance of dermatologists during level-I and -II of the reader study. Additionally, the CNN's performance was compared with the top-five algorithms of the 2016 International Symposium on Biomedical Imaging (ISBI) challenge., Results: In level-I dermatologists achieved a mean (±standard deviation) sensitivity and specificity for lesion classification of 86.6% (±9.3%) and 71.3% (±11.2%), respectively. More clinical information (level-II) improved the sensitivity to 88.9% (±9.6%, P = 0.19) and specificity to 75.7% (±11.7%, P < 0.05). The CNN ROC curve revealed a higher specificity of 82.5% when compared with dermatologists in level-I (71.3%, P < 0.01) and level-II (75.7%, P < 0.01) at their sensitivities of 86.6% and 88.9%, respectively. The CNN ROC AUC was greater than the mean ROC area of dermatologists (0.86 versus 0.79, P < 0.01). The CNN scored results close to the top three algorithms of the ISBI 2016 challenge., Conclusions: For the first time we compared a CNN's diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians' experience, they may benefit from assistance by a CNN's image classification., Clinical Trial Number: This study was registered at the German Clinical Trial Register (DRKS-Study-ID: DRKS00013570; https://www.drks.de/drks&#95;web/).

The incidence rates of thin melanomas (≤1 mm Breslow thickness) have increased in many fair-skinned populations, prompting a need to better identify patients with thin melanomas who will eventually die from the disease. This study aimed to describe the clinicopathological characteristics of lethal melanomas in Western Sweden, with a focus on thin lesions. Population-based data on invasive melanomas diagnosed during the years 1990 to 2014 were extracted from the Swedish Melanoma Registry, and linked to the Swedish Cause of Death Registry. The age-standardized incidence (US population 2000) of thin melanomas increased from 9.1×10-5 (95% confidence interval (95% CI) 8.5-9.8) to 21.3×10-5 (95% CI 20.4-22.1) during the study period. Thin melanomas comprised 55.2% of the total and contributed to 13.5% of all melanoma deaths. Non-ulcerated melanomas 0.76-1 mm and ulcerated melanomas 0.26-1.0 mm showed a poorer survival compared with other thin melanomas.

Patients diagnosed with a single primary cutaneous melanoma are at increased risk of developing multiple primary melanomas. The aim of this study is to describe the epidemiology of multiple primary melanomas (invasive and in situ) in Western Sweden. Data from the Swedish Melanoma Registry from 1990 to 2013 revealed that 898 patients (7.4%) developed 2,037 multiple primary lesions and 11,254 patients developed single lesions. The proportion of subsequent lesions that were melanoma in situ was 47%, compared with 26% of first melanomas (p < 0.0001).The median and mean time to diagnosis of a subsequent melanoma was 38 and 58 months (95% confidence interval (CI), 53-62 months). In total, 49% of subsequent melanomas were detected within 3 years. Patients and physicians should be aware of the high proportion of multiple primary melanomas in Western Sweden, especially during the first years of follow-up.

Incidence rates for cutaneous malignant melanoma are increasing worldwide. Estimates of the future number of melanoma cases are important for strategic planning of the care pathway. The aim of this study was to use system dynamics modelling to evaluate the long-term effects of changes in incidence, population growth and preventive interventions. Historical data on invasive melanoma cases in Western Sweden from 1990 to 2006 were obtained. Using computer simulation software, a model estimating the accumulated number of melanoma cases for 2014 to 2023 was developed. Five future scenarios were designed: stable incidence, business-as-usual, 25% reduced patient's delay, 50% reduced doctor's delay, and a combination of the last two, called improved overall secondary prevention. After 10 years, improved overall secondary prevention would have resulted in a 42% decrease in melanomas > 4 mm and a 10% increase in melanomas ≤ 1 mm, compared with business-as-usual. System dynamics is a valuable tool, which can help policymakers choose the preventive interventions with the greatest impact.

Background: Previous studies have shown statistically significant differences in electrical impedance between various cutaneous lesions. Electrical impedance spectroscopy (EIS) may therefore be able to aid clinicians in differentiating between benign and malignant skin lesions., Objectives: The aim of the study was to develop a classification algorithm to distinguish between melanoma and benign lesions of the skin with a sensitivity of at least 98% and a specificity approximately 20 per cent higher than the diagnostic accuracy of dermatologists., Patients/methods: A total of 1300 lesions were collected in a multicentre, prospective, non-randomized clinical trial from 19 centres around Europe. All lesions were excised and subsequently evaluated independently by a panel of three expert dermatopathologists. From the data two classification algorithms were developed and verified., Results: For the first classification algorithm, approximately 40% of the data were used for calibration and 60% for testing. The observed sensitivity for melanoma was 98.1% (101/103), non-melanoma skin cancer 100% (25/25) and dysplastic nevus with severe atypia 84.2% (32/38). The overall observed specificity was 23.6% (66/280). For the second classification algorithm, approximately 55% of the data were used for calibration. The observed sensitivity for melanoma was 99.4% (161/162), for non-melanoma skin cancer was 98.0% (49/50) and dysplastic nevus with severe atypia was 93.8% (60/64). The overall observed specificity was 24.5% (116/474)., Conclusion: EIS has the potential to be an adjunct diagnostic tool to help clinicians differentiate between benign and malignant (melanocytic and non-melanocytic) skin lesions. Further studies are needed to confirm the validity of the automatic assessment algorithm., (© 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.)

The aim of this study was to describe the increasing incidence of cutaneous malignant melanoma (CMM) in Western Sweden during the period 1970-2007. A secondary aim was to show a geographical variation in incidence between coastal and inland areas, considering the effects of the local average duration of sunshine, and the sun exposure-related behavior in the populations. The Swedish Cancer Registry provided data on invasive melanomas during 1970-2007. Meteorological maps showed the annual average duration of sunshine during 1961-1990. A survey from 2007 with 2871 participants, carried out by the National Board of Health and Welfare, provided data on self-reported sun exposure. During the period studied, the age-standardized incidence for men in Western Sweden more than quadrupled to 31.1/100 000 inhabitants, whereas it tripled for women to 27.1/100 000. Coastal areas, including Gothenburg city, had a high average duration of sunshine (1701-1900 h of sun/year), whereas inland areas had lower average duration of sunshine (≤1700 h). The incidence of CMM was higher in coastal areas and in Gothenburg city, compared with inland areas. This may be linked to ultraviolet radiation, a consequence of the higher average duration of sunshine. The sun exposure survey showed additional factors, which possibly led to the increased incidence, for example high sun exposure on holidays abroad. The alarming increase in the incidence of CMM in Western Sweden, during the period 1970-2007, shows the need for additional primary preventive measures, for example sun protection programs targeted at populations in this area.

Standard treatment for lentigo maligna (LM) is surgical excision, yet insights into the frequency of and risk factors for incomplete excisions remain limited. The primary objectives were to assess the incomplete excision rate (IER) in primary LM and to explore potential risk factors for incomplete excisions. A retrospective analysis was conducted encompassing consecutive histopathologically confirmed LMs from 2014-2020. Descriptive statistics were used for LM characteristics and IER, while uni- and multivariate analyses were used for calculating risk factors. The study included 395 LMs with an IER of 16.7% (n = 66). Risk factors for higher incomplete excision rates included: head and neck lesions (p = 0.0014), clinical excision margins < 5 mm (p = 0.040), and utilization of preoperative partial biopsies (p = 0.023). Plastic surgeons had higher IERs than dermatologists (p = 0.036). Lesion diameter (p = 0.20) and surgeon experience (p = 0.20) showed no associations with incomplete excisions, yet LMs with a diameter ≥ 20 mm exhibited higher incomplete excision rates (23.2%) compared with those < 10 mm (12.9%). LMs should be excised with at least 5-mm clinical margins, especially in the head and neck area. LMs ≥ 20 mm may be more surgically challenging. Higher incomplete excision rates associated with the use of preoperative biopsies and/or plastic surgeons may reflect challenging anatomical locations, larger lesion diameter, and/or ill-defined borders. [ABSTRACT FROM AUTHOR]

Incomplete excisions of melanocytic lesions occur despite the intention of complete removal. The aim of this study was to determine the incomplete excision rates for benign and malignant melanocytic lesions and the associated risk factors. Demographic, clinical, and histopathological data possibly associated with incomplete excision were collected from 2,782 consecutive excisions between 2014 and 2015. Of these, 269 melanocytic lesions (9.7%) were incompletely excised. Multivariate analysis revealed the following risk factors for significantly higher incomplete excision rates: lesions located in the head and neck area (odds ratio (OR) 3.95, 95% confidence interval (95% CI) 2.35-6.65), surgery performed by general practitioners (OR 3.01, 95% CI 2.16-4.19), the use of a punch excision technique (OR 2.83, 95% CI 1.96-4.08), and excision of non-dysplastic naevi (OR 1.58, 95% CI 1.11-2.23). In conclusion, more caution should be taken when excising melanocytic lesions in the head and neck area, general practitioners require more surgical training, and punch excisions of melanocytic lesions should be avoided. [ABSTRACT FROM AUTHOR]

The article offers information on the data and basic statistics for surveillance of sociodemographic inequalities in early detection of cancer. It mentions that surveillance of sociodemographic disparities in early detection of cancer rely on data on clinical stage at diagnosis obtained from cancer and quality registers with high coverage; sociodemographic data and adequate statistics.

Summary: Background: Photodynamic therapy (PDT) can be used to treat large fields of actinic keratoses (AKs) with high clearance rates. A notable downside is the amount of pain that accompany the treatment. This study aimed to optimize the illumination protocol during conventional PDT in order to reduce pain without compromising treatment effectiveness. Methods: In this prospective, randomized study with a split‐face design, patients with, symmetrically distributed AKs were included. All patients were treated using a ALA 78 mg/g gel. One side was illuminated with the Aktilite® CL‐128 lamp and the other side with the RhodoLED® lamp in which the light intensity gradually increased to a maximum of 60%. Both sides received a total light dose of 37 J/cm2. Pain during the treatment was measured using a visual analogue scale. The clinical effectiveness of the 2 treated sides was assessed after 12 weeks. Results: Twenty‐nine patients with 399 AKs were included. Illumination with the gradually increasing light intensity resulted in a decrease in the median visual analogue scale score by 1.1 points. Clearance rates were similar between the 2 lamps. Conclusion: Minimizing the light intensity during the illumination phase of PDT reduces pain, while still preserving a high clearance rate of AKs. [ABSTRACT FROM AUTHOR]

Background: Nonpigmented skin cancer is common, and diagnosis with the unaided eye is error prone.Objective: To investigate whether dermatoscopy improves the diagnostic accuracy for nonpigmented (amelanotic) cutaneous neoplasms.Methods: We collected a sample of 2072 benign and malignant neoplastic lesions and inflammatory conditions and presented close-up images taken with and without dermatoscopy to 95 examiners with different levels of experience.Results: The area under the curve was significantly higher with than without dermatoscopy (0.68 vs 0.64, P < .001). Among 51 possible diagnoses, the correct diagnosis was selected in 33.1% of cases with and 26.4% of cases without dermatoscopy (P < .001). For experts, the frequencies of correct specific diagnoses of a malignant lesion improved from 40.2% without to 51.3% with dermatoscopy. For all malignant neoplasms combined, the frequencies of appropriate management strategies increased from 78.1% without to 82.5% with dermatoscopy.Limitations: The study deviated from a real-life clinical setting and was potentially affected by verification and selection bias.Conclusions: Dermatoscopy improves the diagnosis and management of nonpigmented skin cancer and should be used as an adjunct to examination with the unaided eye. [ABSTRACT FROM AUTHOR]

In this open, controlled, multicentre and prospective observational study, smartphone teledermoscopy referrals were sent from 20 primary healthcare centres to 2 dermatology departments for triage of skin lesions of concern using a smartphone application and a compatible digital dermoscope. The outcome for 816 patients referred via smartphone teledermoscopy was compared with 746 patients referred via the traditional paper-based system. When surgical treatment was required, the waiting time was significantly shorter using teledermoscopy for patients with melanoma, melanoma in situ, squamous cell carcinoma, squamous cell carcinoma in situ and basal cell carcinoma. Triage decisions were also more reliable with teledermoscopy and over 40% of the teledermoscopy patients could potentially have avoided face-to-face visits. Only 4 teledermoscopy referrals (0.4%) had to be excluded due to poor image quality. Smartphone teledermoscopy referrals allow for faster and more efficient management of patients with skin cancer as compared to traditional paper referrals. [ABSTRACT FROM AUTHOR]