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In the context of nuclear security, uranium ore concentrates (UOCs) play an important role: they are traded in large quantities and this makes their use “out of regulatory control” a possible scenario. Once an incident of illicit trafficking o f n uclear m aterial is detected, an understanding of its origin and production process is required; this implies the necessity to use analytical techniques able to measure characteristic parameters (e.g. physical, chemical, isotopic characteristics of the nuclear materials) which are referred to, in the field o f t he n uclear f orensics, a s signatures. The present study investigates the potential of image texture analysis (i.e. the angle measure technique), combined with the spectrophotometric determination of colours for the evaluation of the origin of several UOCs. The use of different multivariate statistical techniques allows the categorization of about 80 different samples into a few groups of UOCs powders, which makes this approach a promising method complementing the already established methods in nuclear forensics.

Recent studies have shown a high flood risk exposure in France. It represents and almost one fourth of the total population and a third of jobs. In this context, a global vulnerability assessment methodology is currently elaborated and evaluated in France to bring adequate tools for flood risk management. This study raises the question of the quantification, of the qualification and of the choice of these vulnerability indicators for a given territory. This work aims to propose a new methodology dedicated for classification, for hierarchization and selection of a set of six vulnerability indicators by the means of a statistical analysis including PCA and ANOVA analysis depending of their relative impacts and correlation with the estimated risk level on the territory of Chalon-sur-Saône.

Abstract Background Streptococcus pneumoniae is an important human pathogen representing a major cause of morbidity and mortality worldwide. We sequenced the genome of a serotype 11A, ST62 S. pneumoniae invasive isolate (AP200), that was erythromycin-resistant due to the presence of the erm(TR) determinant, and carried out analysis of the genome organization and comparison with other pneumococcal genomes. Results The genome sequence of S. pneumoniae AP200 is 2,130,580 base pair in length. The genome carries 2216 coding sequences (CDS), 56 tRNA, and 12 rRNA genes. Of the CDSs, 72.9% have a predicted biological known function. AP200 contains the pilus islet 2 and, although its phenotype corresponds to serotype 11A, it contains an 11D capsular locus. Chromosomal rearrangements resulting from a large inversion across the replication axis, and horizontal gene transfer events were observed. The chromosomal inversion is likely implicated in the rebalance of the chromosomal architecture affected by the insertions of two large exogenous elements, the erm(TR)-carrying Tn1806 and a functional prophage designated ϕSpn_200. Tn1806 is 52,457 bp in size and comprises 49 ORFs. Comparative analysis of Tn1806 revealed the presence of a similar genetic element or part of it in related species such as Streptococcus pyogenes and also in the anaerobic species Finegoldia magna, Anaerococcus prevotii and Clostridium difficile. The genome of ϕSpn_200 is 35,989 bp in size and is organized in 47 ORFs grouped into five functional modules. Prophages similar to ϕSpn_200 were found in pneumococci and in other streptococcal species, showing a high degree of exchange of functional modules. ϕSpn_200 viral particles have morphologic characteristics typical of the Siphoviridae family and are capable of infecting a pneumococcal recipient strain. Conclusions The sequence of S. pneumoniae AP200 chromosome revealed a dynamic genome, characterized by chromosomal rearrangements and horizontal gene transfers. The overall diversity of AP200 is driven mainly by the presence of the exogenous elements Tn1806 and ϕSpn_200 that show large gene exchanges with other genetic elements of different bacterial species. These genetic elements likely provide AP200 with additional genes, such as those conferring antibiotic-resistance, promoting its adaptation to the environment.

The National Committee for Palliative Care expressed their commitment to approach the decision of foregoing life sustaining treatment from a palliative care perspective, allowing the implementation of a care program to prevent therapeutic obstinacy, respect the dignity of the patient and their parents, and evaluate a rational, reasonable and adequate use of health and technological resources by focusing on the quality of life of the child, in order to realize their best interest, providing a guide that facilitates the decision-making process in dilemmatic situations in pediatrics., (Sociedad Argentina de Pediatría.)

Competing Interests: Conflicts of interest None disclosed.

Background: A common terminology for diagnosis is critically important for clinical communication, education, research and artificial intelligence. Prevailing lexicons are limited in fully representing skin neoplasms., Objectives: To achieve expert consensus on diagnostic terms for skin neoplasms and their hierarchical mapping., Methods: Diagnostic terms were extracted from textbooks, publications and extant diagnostic codes. Terms were hierarchically mapped to super-categories (e.g. 'benign') and cellular/tissue-differentiation categories (e.g. 'melanocytic'), and appended with pertinent-modifiers and synonyms. These terms were evaluated using a modified-Delphi consensus approach. Experts from the International-Skin-Imaging-Collaboration (ISIC) were surveyed on agreement with terms and their hierarchical mapping; they could suggest modifying, deleting or adding terms. Consensus threshold was >75% for the initial rounds and >50% for the final round., Results: Eighteen experts completed all Delphi rounds. Of 379 terms, 356 (94%) reached consensus in round one. Eleven of 226 (5%) benign-category terms, 6/140 (4%) malignant-category terms and 6/13 (46%) indeterminate-category terms did not reach initial agreement. Following three rounds, final consensus consisted of 362 terms mapped to 3 super-categories and 41 cellular/tissue-differentiation categories., Conclusions: We have created, agreed upon, and made public a taxonomy for skin neoplasms and their hierarchical mapping. Further study will be needed to evaluate the utility and completeness of the lexicon., (© 2024 European Academy of Dermatology and Venereology.)

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.)

Importance: Patients with melanoma are selected for sentinel lymph node biopsy (SLNB) based on their risk of a positive SLN. To improve selection, the Memorial Sloan Kettering Cancer Center (MSKCC) and Melanoma Institute Australia (MIA) developed predictive models, but the utility of these models remains to be tested., Objective: To determine the clinical utility of the MIA and MSKCC models., Design, Setting, and Participants: This was a population-based comparative effectiveness research study including 10 089 consecutive patients with cutaneous melanoma undergoing SLNB from the Swedish Melanoma Registry from January 2007 to December 2021. Data were analyzed from May to August 2023., Main Outcomes and Measures,: The predicted probability of SLN positivity was calculated using the MSKCC model and a limited MIA model (using mitotic rate as absent/present instead of count/mm2 and excluding the optional variable lymphovascular invasion) for each patient. The operating characteristics of the models were assessed and compared. The clinical utility of each model was assessed using decision curve analysis and compared with a strategy of performing SLNB on all patients., Results: Among 10 089 included patients, the median (IQR) age was 64.0 (52.0-73.0) years, and 5340 (52.9%) were male. The median Breslow thickness was 1.8 mm, and 1802 patients (17.9%) had a positive SLN. Both models were well calibrated across the full range of predicted probabilities and had similar external area under the receiver operating characteristic curves (AUC; MSKCC: 70.8%; 95% CI, 69.5-72.1 and limited MIA: 69.7%; 95% CI, 68.4-71.1). At a risk threshold of 5%, decision curve analysis indicated no added net benefit for either model compared to performing SLNB for all patients. At risk thresholds of 10% or higher, both models added net benefit compared to SLNB for all patients. The greatest benefit was observed in patients with T2 melanomas using a threshold of 10%; in that setting, the use of the nomograms led to a net reduction of 8 avoidable SLNBs per 100 patients for the MSKCC nomogram and 7 per 100 patients for the limited MIA nomogram compared to a strategy of SLNB for all., Conclusions and Relevance: This study confirmed the statistical performance of both the MSKCC and limited MIA models in a large, nationally representative data set. However, decision curve analysis demonstrated that using the models only improved selection for SLNB compared to biopsy in all patients when a risk threshold of at least 7% was used, with the greatest benefit seen for T2 melanomas at a threshold of 10%. Care should be taken when using these nomograms to guide selection for SLNB at the lowest thresholds.

Background: For patients with melanoma, the decision to perform sentinel lymph node biopsy (SLNB) is based on the estimated risk of lymph node metastasis. We assessed 3 melanoma SLNB risk-prediction models' statistical performance and their ability to improve clinical decision making (clinical utility) on a cohort of melanoma SLNB cases., Study Design: Melanoma patients undergoing SLNB at a single center from 2003 to 2021 were identified. The predicted probabilities of sentinel lymph node positivity using the Melanoma Institute of Australia, Memorial Sloan Kettering Cancer Center (MSK), and Friedman nomograms were calculated. Receiver operating characteristic and calibration curves were generated. Clinical utility was assessed via decision curve analysis, calculating the net SLNBs that could have been avoided had a given model guided selection at different risk thresholds., Results: Of 2,464 melanoma cases that underwent SLNB, 567 (23.0%) had a positive sentinel lymph node. The areas under the receiver operating characteristic curves for the Melanoma Institute of Australia, MSK, and Friedman models were 0.726 (95% CI, 0.702 to 0.750), 0.720 (95% CI, 0.697 to 0.744), and 0.721 (95% CI, 0.699 to 0.744), respectively. For all models, calibration was best at predicted positivity rates below 30%. The MSK model underpredicted risk. At a 10% risk threshold, only the Friedman model would correctly avoid a net of 6.2 SLNBs per 100 patients. The other models did not reduce net avoidable SLNBs at risk thresholds of ≤10%., Conclusions: The tested nomograms had comparable performance in our cohort. The only model that achieved clinical utility at risk thresholds of ≤10% was the Friedman model., (Copyright © 2023 by the American College of Surgeons. Published by Wolters Kluwer Health, Inc. All rights reserved.)

Background: Lentigo maligna (LM) can mimic benign, flat, pigmented lesions and can be challenging to diagnose., Objective: To describe a new dermatoscopic feature termed "perifollicular linear projections (PLP)" as a diagnostic criterion for LM on the face., Methods: Retrospective study on reflectance confocal microscopy and dermatoscopy images of flat facial pigmented lesions originating from 2 databases. PLP were defined as short, linear, pigmented projections emanating from hair follicles. Dermatoscopy readers were blinded to the final histopathologic diagnosis., Results: From 83 consecutive LMs, 21/83 (25.3%) displayed "bulging of hair follicles" on reflectance confocal microscopy and 18 of these 21 (85.7%), displayed PLP on dermatoscopy. From a database of 2873 consecutively imaged and biopsied lesions, 252 flat-pigmented facial lesions were included. PLP was seen in 47/76 melanomas (61.8%), compared with 7/176 lesions (3.9%) with other diagnosis (P < .001). The sensitivity was 61.8% (95% CI, 49.9%-72.7%), specificity 96.0% (95% CI, 92.9%-98.4%). PLP was independently associated with LM diagnosis on multivariate analysis (OR 26.1 [95% CI, 9.6%-71.0])., Limitations: Retrospective study., Conclusion: PLP is a newly described dermatoscopic criterion that may add specificity and sensitivity to the early diagnosis of LM located on the face. We postulate that PLP constitutes an intermediary step in the LM progression model., Competing Interests: Conflicts of interest None disclosed., (Copyright © 2023 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

The use of artificial intelligence (AI) has the potential to improve the assessment of lesions suspicious of melanoma, but few clinical studies have been conducted. We validated the accuracy of an open-source, non-commercial AI algorithm for melanoma diagnosis and assessed its potential impact on dermatologist decision-making. We conducted a prospective, observational clinical study to assess the diagnostic accuracy of the AI algorithm (ADAE) in predicting melanoma from dermoscopy skin lesion images. The primary aim was to assess the reliability of ADAE's sensitivity at a predefined threshold of 95%. Patients who had consented for a skin biopsy to exclude melanoma were eligible. Dermatologists also estimated the probability of melanoma and indicated management choices before and after real-time exposure to ADAE scores. All lesions underwent biopsy. Four hundred thirty-five participants were enrolled and contributed 603 lesions (95 melanomas). Participants had a mean age of 59 years, 54% were female, and 96% were White individuals. At the predetermined 95% sensitivity threshold, ADAE had a sensitivity of 96.8% (95% CI: 91.1-98.9%) and specificity of 37.4% (95% CI: 33.3-41.7%). The dermatologists' ability to assess melanoma risk significantly improved after ADAE exposure (AUC 0.7798 vs. 0.8161, p = 0.042). Post-ADAE dermatologist decisions also had equivalent or higher net benefit compared to biopsying all lesions. We validated the accuracy of an open-source melanoma AI algorithm and showed its theoretical potential for improving dermatology experts' ability to evaluate lesions suspicious of melanoma. Larger randomized trials are needed to fully evaluate the potential of adopting this AI algorithm into clinical workflows., (© 2023. The Author(s).)

Background and Methods: The Melanoma Institute of Australia (MIA) and Memorial Sloan Kettering Cancer Center (MSKCC) nomograms were developed to help guide sentinel lymph node biopsy (SLNB) decisions. Although statistically validated, whether these prediction models provide clinical benefit at National Comprehensive Cancer Network guideline-endorsed thresholds is unknown. We conducted a net benefit analysis to quantify the clinical utility of these nomograms at risk thresholds of 5%-10% compared to the alternative strategy of biopsying all patients. External validation data for MIA and MSKCC nomograms were extracted from respective published studies., Results: The MIA nomogram provided added net benefit at a risk threshold of 9% but net harm at 5%-8% and 10%. The MSKCC nomogram provided added net benefit at risk thresholds of 5% and 9%-10% but net harm at 6%-8%. When present, the magnitude of net benefit was small (1-3 net avoidable biopsies per 100 patients)., Conclusion: Neither model consistently provided added net benefit compared to performing SLNB for all patients., Discussion: Based on published data, use of the MIA or MSKCC nomograms as decision-making tools for SLNB at risk thresholds of 5%-10% does not clearly provide clinical benefit to patients., (© 2023 Wiley Periodicals LLC.)

Competing Interests: Yuna Oh: Dennis Gross Skincare Foundation Grant; Mary Sun: None; Lilly Gu: None; Trina Salvador: None; Liliane Sar-Graycar: None; Dr Hay: None; Dr Quigley: None; Dr Marchetti: None; Dr Halpern: Receiving personal fees from Canfield Scientific, SciBase, and Lloyd Charitable Trust and having an equity position with HCW Health and Skip Derm; Dr Rotemberg: Expert advising for Inhabit Brands, Inc.

Background: Existing artificial intelligence for melanoma detection has relied on analysing images of lesions of clinical interest, which may lead to missed melanomas. Tools analysing the entire skin surface are lacking., Objectives: To determine if melanoma can be distinguished from other skin lesions using data from automated analysis of 3D-images., Methods: Single-centre, retrospective, observational convenience sample of patients diagnosed with melanoma at a tertiary care cancer hospital. Eligible participants were those with a whole-body 3D-image captured within 90 days prior to the diagnostic skin biopsy. 3D-images were obtained as standard of care using VECTRA WB360 Whole Body 3-dimensional Imaging System (Canfield Scientific). Automated data from image processing (i.e. lesion size, colour, border) for all eligible participants were exported from VECTRA DermaGraphix research software for analysis. The main outcome was the area under the receiver operating characteristic curve (AUC)., Results: A total of 35 patients contributed 23,538 automatically identified skin lesions >2 mm in largest diameter (102-3021 lesions per participant). All were White patients and 23 (66%) were males. The median (range) age was 64 years (26-89). There were 49 lesions of melanoma and 22,489 lesions that were not melanoma. The AUC for the prediction model was 0.94 (95% CI: 0.92-0.96). Considering all lesions in a patient-level analysis, 14 (28%) melanoma lesions had the highest predicted score or were in the 99th percentile among all lesions for an individual patient., Conclusions: In this proof-of-concept pilot study, we demonstrated that automated analysis of whole-body 3D-images using simple image processing techniques can discriminate melanoma from other skin lesions with high accuracy. Further studies with larger, higher quality, and more representative 3D-imaging datasets would be needed to improve and validate these results., (© 2023 European Academy of Dermatology and Venereology.)

Importance: Therapy for advanced melanoma has transformed during the past decade, but early detection and prognostic assessment of cutaneous melanoma (CM) remain paramount goals. Best practices for screening and use of pigmented lesion evaluation tools and gene expression profile (GEP) testing in CM remain to be defined., Objective: To provide consensus recommendations on optimal screening practices and prebiopsy diagnostic, postbiopsy diagnostic, and prognostic assessment of CM., Evidence Review: Case scenarios were interrogated using a modified Delphi consensus method. Melanoma panelists (n = 60) were invited to vote on hypothetical scenarios via an emailed survey (n = 42), which was followed by a consensus conference (n = 51) that reviewed the literature and the rationale for survey answers. Panelists participated in a follow-up survey for final recommendations on the scenarios (n = 45)., Findings: The panelists reached consensus (≥70% agreement) in supporting a risk-stratified approach to melanoma screening in clinical settings and public screening events, screening personnel recommendations (self/partner, primary care provider, general dermatologist, and pigmented lesion expert), screening intervals, and acceptable appointment wait times. Participants also reached consensus that visual and dermoscopic examination are sufficient for evaluation and follow-up of melanocytic skin lesions deemed innocuous. The panelists reached consensus on interpreting reflectance confocal microscopy and some but not all results from epidermal tape stripping, but they did not reach consensus on use of certain pigmented lesion evaluation tools, such as electrical impedance spectroscopy. Regarding GEP scores, the panelists reached consensus that a low-risk prognostic GEP score should not outweigh concerning histologic features when selecting patients to undergo sentinel lymph node biopsy but did not reach consensus on imaging recommendations in the setting of a high-risk prognostic GEP score and low-risk histology and/or negative nodal status., Conclusions and Relevance: For this consensus statement, panelists reached consensus on aspects of a risk-stratified approach to melanoma screening and follow-up as well as use of visual examination and dermoscopy. These findings support a practical approach to diagnosing and evaluating CM. Panelists did not reach consensus on a clearly defined role for GEP testing in clinical decision-making, citing the need for additional studies to establish the clinical use of existing GEP assays.

Background: Given the results of the recent KEYNOTE-716 trial, the performance of sentinel lymph node (SLN) biopsy for patients with clinical stage IIB/C melanoma has been questioned., Objective: Determine the utility of SLN status in guiding the recommendations for adjuvant therapy., Methods: Patients with clinical stage IIB/C cutaneous melanoma who underwent wide local excision and SLN biopsy between 2004 and 2011 were identified from the Surveillance, Epidemiology, and End Results database. Two prognostic models, with and without SLN status, were developed predicting risk of melanoma-specific death (MSD). The primary outcome was net benefit at treatment thresholds of 20% to 40% risk of 5-year MSD., Results: For the 4391 patients included, the 5-year MSD rate was 46%. The model estimating 5-year MSD risk that included SLN status provided greater net benefit at treatment thresholds from 30% to 78% compared to the model without SLN status. The added net benefit for the SLN biopsy-containing model persisted in subgroup analysis of patients in different age groups and with various T stages., Limitations: Retrospective study., Conclusions: A prognostic model with SLN status estimating patient risk for 5-year MSD provides superior net benefit compared to a model with primary tumor staging factors alone for threshold mortality rates ≥30%., Competing Interests: Conflicts of interest Bartlett receives institutional research support from SkylineDx and discloses an honorarium from Excite International. Karakousis is a PI of an investigator-initiated trial with institutional support by Merck and serves on the Merck advisory board. The other authors have no conflict to disclose., (Copyright © 2022 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: There is little understanding regarding the long-term natural history of melanocytic nevi among adults., Objective: The objective of the study was to describe the long-term natural history of individual nevi located on the torso of high-risk patients., Methods: All patients attending Memorial Sloan Kettering Cancer Center (MSKCC) who underwent two total body photography (TBP) sessions 15+ years apart were included ('retrospective' group). To account for a potential selection bias, we also included consecutive patients who had TBP 15+ years ago and consented to undergo follow-up TBP ('prospective' group). We compared baseline and follow-up torso images on the TBPs and evaluated the number of total, new and disappearing nevi; number of seborrheic keratoses and actinic keratoses; each nevus' diameter at both time points; each nevus' colour change; the presence of clinical atypia; and when dermoscopy was available, the dermoscopic features at each time point., Results: One hundred six patients were included in the study. Although the average age of the patients was 40 at baseline TBP, most patients developed new nevi between imaging sessions (median 16.4 years) with an average of 2.6 (SD = 4.8) nevi per participant. The average number of disappearing nevi was 0.3 (SD = 0.6). In addition, 62/106 (58%) patients had an absolute increase, and 9/106 (8%) patients had an absolute decrease in their total nevus count. Roughly half (49%: 1416/2890) of the nevi that could be evaluated at both time points increased in diameter by at least 25%. Only 6% (159/2890) of nevi shrunk in diameter by at least 25%. Patients with a history of melanoma had a higher rate of disappearing nevi, and their nevi were more likely to grow. Most nevi demonstrated no significant dermoscopic changes., Conclusions: High-risk patients acquire new nevi throughout life with very few nevi disappearing over time. Contrary to prior reports, most nevi in adults increase in diameter, while few nevi shrink., (© 2022 The Authors. Journal of the European Academy of Dermatology and Venereology published by John Wiley & Sons Ltd on behalf of European Academy of Dermatology and Venereology.)

Competing Interests: Conflicts of interest None disclosed.

Introduction: Among the various widely recognized basal cell carcinoma (BCC) clinical patterns, linear basal cell carcinoma (LBCC) is an uncommon morphologic variant of BCC., Objectives: Describe the clinical and dermoscopic characteristics of LBCC., Methods: Retrospective study including LBCC cases from 5 dermatology centers in North and South America. Biopsy-proven primary BCCs, that presented with at least 3:1 length:width ratio on physical examination, irrespective of tumor subtype or location, were included. Clinical and dermoscopic analysis were performed by 2 experts in dermoscopy., Results: Eighteen cases of LBCC met our inclusion criteria and were included in the study. Median age at diagnosis was 86.0 years, 10 patients (58.8%) were males. Regarding anatomic location, 11/18 (61.1%) were located on the head and neck, 5/18 (27.7%) cases were found on the trunk, and 2 on lower extremities (11.1%). Under dermoscopy, 15/18 (83.3%) of LBCC were pigmented. All tumors displayed at least one of the BCC-specific dermoscopic criteria the most common being blue-grey globules (72.2%)., Conclusions: Dermoscopy might be useful in the differentiation of LBCC from other diagnoses presenting as linear lesions such as scars, scratches/erosions, and tattoos, among others. Some of these lesions might be confused by naked eye examination alone., Competing Interests: Competing interests: None., (©2022 Navarrete-Dechent et al.)

Competing Interests: Conflicts of interest Drs Yamada and Prow have a conflict of interest with Trajan Scientific & Medical Pty Ltd as they are currently commercializing microbiopsy. Drs Jain, Busam, Marchetti, and Halpern and authors Autuori, Everett, Harris, and Orlow do not have any conflicts of interest to disclose.

Competing Interests: Conflicts of interest Dr Marghoob declares research support from Incyte and Amryt Pharma and serves on the advisory board of Alira Health. Dr Rotemberg is an expert advisor for Inhabit Brands, Inc. Dr Rajadhyaksha owns equity in Caliber ID (formerly, Lucid Inc). The Vivascope is the commercial version of an original laboratory prototype that was developed by Dr Rajadhyaksha when he was at Massachusetts General Hospital, Harvard Medical School. Drs Cordova, Chen, Halpern, Kentley, Kose, Lee, Marchetti, Markova, Navarrete-Dechent, Nehal, Rossi, Sahu, and Jain and Authors Mehta, Oh, Harris, Kurtansky, and Sun have no conflicts of interest to declare.

Background: Risk-based thresholds to guide management are undefined in the treatment of primary cutaneous melanoma but are essential to advance the field from traditional stage-based treatment to more individualized care., Methods: To estimate treatment risk thresholds, hypothetical clinical melanoma scenarios were developed and a stratified random sample was distributed to expert melanoma clinicians via an anonymous web-based survey. Scenarios provided a defined 5-year risk of recurrence and asked for recommendations regarding clinical follow-up, imaging, and adjuvant therapy. Marginal probability of response across the spectrum of 5-year recurrence risk was estimated. The risk at which 50% of respondents recommended a treatment was defined as the risk threshold., Results: The overall response rate was 56% (89/159). Three separate multivariable models were constructed to estimate the recommendations for clinical follow-up more than twice/year, for surveillance cross-sectional imaging at least once/year, and for adjuvant therapy. A 36% 5-year risk of recurrence was identified as the threshold for recommending clinical follow-up more than twice/year. The thresholds for recommending cross-sectional imaging and adjuvant therapy were 30 and 59%, respectively. Thresholds varied with the age of the hypothetical patient: at younger ages they were constant but increased rapidly at ages 60 years and above., Conclusions: To our knowledge, these data provide the first estimates of clinically significant treatment thresholds for patients with cutaneous melanoma based on risk of recurrence. Future refinement and adoption of thresholds would permit assessment of the clinical utility of novel prognostic tools and represents an early step toward individualizing treatment recommendations., (© 2022. Society of Surgical Oncology.)

Objective: Brief alcohol interventions (BAIs) have historically centered on young adults attending 4-year predominantly white institutions. The purpose of this scoping review is to determine BAIs evaluated among young adults with one or more marginalized/understudied racial, ethnic, sexual, gender, and military/Veteran identities and/or who are embedded in an understudied context based on houselessness, attending a 2-year institution, or not attending college. A secondary objective is to explore definitions of the constructs young adult and brief to inform subsequent systematic reviews., Method: Sources had to be published in English between January 1, 1999 and December 31, 2019 and report the evaluation of an intervention ≤ 5 hr long, delivered over ≤ 4 weeks, among participants aged 18-30 years (or 16-30 in college contexts) within a specified marginalized/understudied subpopulation/context wherein alcohol use and/or consequences were a primary outcome. Systematic searches were conducted in APA PsycNet, the EBSCO Psychology and Behavioral Sciences Collection, PubMed, Sociological Abstracts, and Web of Science. Screening was independently performed by two coders who also extracted data., Results: Of 4,825 identified records, 158 provided data; 86 described interventions fitting our definition of brief; of these, only 21 met criteria based on our definition of young adult , with nine meeting full inclusion criteria based on young adult subpopulation., Conclusions: Findings signify a need for additional research evaluating BAIs among young adult subpopulations and highlight the importance of carefully defining and reporting participant characteristics. Increased attention to sociocultural considerations and strengths relevant to the diverse contexts and intersecting identities of young adults may strengthen extant BAIs and equitably mitigate alcohol-related harm. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Background: Regular skin self-examination (SSE) reduces melanoma mortality but is not often conducted., Purpose: To promote SSE performance in individuals at increased risk for melanoma., Methods: One hundred sixteen individuals at heightened risk for development of melanoma (i.e., personal/family history of melanoma, high-risk mole phenotype) who did not conduct a thorough SSE during in the prior 3 months were randomly assigned to receive either an automated internet-based intervention (mySmartCheck) or usual care (UC). One hundred sixteen participants completed surveys before random assignment and 99 completed the follow-up survey 13-weeks afterward. The primary outcome was participant self-reported examination (SSE) of all 15 parts of the body in the last 3 months. Secondary outcomes were SSE of any part of the body in the last 3 months and number of body parts examined during the last SSE., Results: More mySmartCheck participants examined all 15 body parts (32.6% vs. 7.1%, p = .001). More individuals in mySmartCheck reported conducting SSE on any body part than those in UC (81.4% vs. 62.5%, p = .04). Effect sizes were large (d = 1.19 all 15 body parts) to moderate (d = 0.55 for any body part). mySmartCheck participants examined more body areas than UC participants (12.7 vs. 10.3, p = 0.003) during the last SSE. Participants in mySmartCheck reported higher levels of knowledge of suspicious lesions, SSE benefits, SSE self-efficacy, and planning for SSE, and lower SSE barriers, than those assigned to UC., Conclusions: mySmartCheck had a significant positive impact on SSE performance and behaviors. Additional research with a larger sample size, a longer follow-up, and more varied clinical settings is needed., Trial Registration: ClinicalTrials.gov registration # NCT03725449 (https://clinicaltrials.gov/ct2/show/NCT03725449)., (© Society of Behavioral Medicine 2021. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Skin cancer is the most commonly diagnosed cancer worldwide. Understanding the natural history of skin cancer provides the framework for the creation of prevention and control strategies that aim to reduce the skin cancer burden. Based on the target (individual vs population), disease stage, and risk factors (modifiable vs nonmodifiable), strategies can be categorized into 4 levels-health promotion (also known as primordial prevention), primary prevention, secondary prevention, and tertiary prevention. This is the first of a 2-part review, which will cover the epidemiology, risk factors, primordial prevention, and primary prevention of melanoma and keratinocyte skin cancers. In particular, we highlight preventive strategies centered on mitigating the impact of modifiable risk factors and potential interventions for health promotion and primary prevention of skin cancer. Summaries of existing recommendations, challenges, opportunities, and future directions are also discussed., Competing Interests: Conflicts of interest None disclosed., (Copyright © 2022 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Skin cancer is the most commonly diagnosed cancer worldwide. Understanding the natural history of skin cancer will provide a framework for the creation of prevention and control strategies that aim to reduce skin cancer burden. The strategies include health promotion, primary prevention, secondary prevention, and tertiary prevention. Health promotion and primary prevention were covered in the first part of this 2-part review. The second part covers the secondary and tertiary prevention of skin cancer. In particular, preventive strategies centered on the early detection of skin cancer, the prevention of disease progression, clinical surveillance, and educational and behavioral interventions are highlighted. The summaries of existing recommendations, challenges, opportunities, and future directions are discussed., Competing Interests: Conflicts of interest None disclosed., (Copyright © 2022 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

The primary cause of the increase in melanoma incidence in the United States has been suggested to be overdiagnosis. We used Surveillance, Epidemiology, and End Result Program data from 1975 to 2017 to examine epidemiologic trends of melanoma incidence and mortality and better characterize overdiagnosis in white Americans. Over the 43-year period, incidence and mortality showed discordant temporal changes across population subgroups; trends most suggestive of overdiagnosis alone were present in females aged 55-74. Other groups showed mixed changes suggestive of overdiagnosis plus changes in underlying disease risk (decreasing risk in younger individuals and increasing risk in older males). Cohort effects were identified for male and female mortality and male incidence but were not as apparent for female incidence, suggesting that period effects have had a greater influence on changes in incidence over time in females. Encouraging trends included long-term declines in mortality in younger individuals and recent stabilization of invasive incidence in individuals aged 15-44 years and males aged 45-54 years. Melanoma in situ incidence, however, has continued to increase throughout the population. Overdiagnosis appears to be relatively greater in American females and for melanoma in situ., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Competing Interests: Conflicts of Interest MAM is an unpaid Editorial advisor to DermWorld (an American Academy of Dermatology publication).

Importance: A neural network-based model (i31-GEP-SLNB) that uses clinicopathologic factors (thickness, mitoses, ulceration, patient age) plus molecular analysis (31-gene expression profiling) has become commercially available to guide selection for sentinel lymph node (SLN) biopsy in cutaneous melanoma, but its clinical utility is not well characterized., Objective: To determine if use of the i31-GEP-SLNB model is associated with clinical benefit when used to select patients for SLN biopsy., Design, Setting, and Participants: This decision-analytic study used data derived from a published external validation study of the i31-GEP-SLNB prediction model. Participants included patients with primary cutaneous melanoma., Main Outcomes and Measures: The primary outcome was the net benefit associated with using the i31-GEP-SLNB model for SLN biopsy selection compared with other selection strategies (SLN biopsy for all patients and SLN biopsy for no patients) at a 5% risk threshold. Analyses were stratified by American Joint Committee on Cancer (AJCC) T category. The reduction in the number of avoidable SLN biopsies and relative utility were also calculated., Results: Compared with other SLN biopsy selection strategies, use of the i31-GEP-SLNB model had greater net benefit for patients with T1b (+0.012), T2a (+0.002), and T2b melanoma (+0.002) but not for those with high-risk T1a (-0.003) disease. The improvement in relative utility was +22% in patients with T1b, +1% in T2a, and +2% in T2b melanoma. Compared with SLN biopsy for all patients, use of the model would equate to a 23% decrease in SLN biopsies among patients with T1b disease without an SLN metastasis with no increase in the number of patients with an SLN metastasis left untreated; among patients with T2a and T2b melanoma, the net decrease in avoidable biopsies compared with SLN biopsy for all was 3% and 4%, respectively., Conclusions and Relevance: The findings of this decision-analytic study suggest that i31-GEP SLNB has significant potential for risk-stratifying patients with T1b melanoma if using a 5% risk threshold; its role among patients with T1a and T2 melanoma or using other risk thresholds requires further study. A prospective validation study confirming the added clinical benefit and cost-effectiveness of i31-GEP-SLNB compared with free clinicopathologic-based prediction models is needed in patients with T1b melanoma.

Background: Previous studies of artificial intelligence (AI) applied to dermatology have shown AI to have higher diagnostic classification accuracy than expert dermatologists; however, these studies did not adequately assess clinically realistic scenarios, such as how AI systems behave when presented with images of disease categories that are not included in the training dataset or images drawn from statistical distributions with significant shifts from training distributions. We aimed to simulate these real-world scenarios and evaluate the effects of image source institution, diagnoses outside of the training set, and other image artifacts on classification accuracy, with the goal of informing clinicians and regulatory agencies about safety and real-world accuracy., Methods: We designed a large dermoscopic image classification challenge to quantify the performance of machine learning algorithms for the task of skin cancer classification from dermoscopic images, and how this performance is affected by shifts in statistical distributions of data, disease categories not represented in training datasets, and imaging or lesion artifacts. Factors that might be beneficial to performance, such as clinical metadata and external training data collected by challenge participants, were also evaluated. 25 331 training images collected from two datasets (in Vienna [HAM10000] and Barcelona [BCN20000]) between Jan 1, 2000, and Dec 31, 2018, across eight skin diseases, were provided to challenge participants to design appropriate algorithms. The trained algorithms were then tested for balanced accuracy against the HAM10000 and BCN20000 test datasets and data from countries not included in the training dataset (Turkey, New Zealand, Sweden, and Argentina). Test datasets contained images of all diagnostic categories available in training plus other diagnoses not included in training data (not trained category). We compared the performance of the algorithms against that of 18 dermatologists in a simulated setting that reflected intended clinical use., Findings: 64 teams submitted 129 state-of-the-art algorithm predictions on a test set of 8238 images. The best performing algorithm achieved 58·8% balanced accuracy on the BCN20000 data, which was designed to better reflect realistic clinical scenarios, compared with 82·0% balanced accuracy on HAM10000, which was used in a previously published benchmark. Shifted statistical distributions and disease categories not included in training data contributed to decreases in accuracy. Image artifacts, including hair, pen markings, ulceration, and imaging source institution, decreased accuracy in a complex manner that varied based on the underlying diagnosis. When comparing algorithms to expert dermatologists (2460 ratings on 1269 images), algorithms performed better than experts in most categories, except for actinic keratoses (similar accuracy on average) and images from categories not included in training data (26% correct for experts vs 6% correct for algorithms, p<0·0001). For the top 25 submitted algorithms, 47·1% of the images from categories not included in training data were misclassified as malignant diagnoses, which would lead to a substantial number of unnecessary biopsies if current state-of-the-art AI technologies were clinically deployed., Interpretation: We have identified specific deficiencies and safety issues in AI diagnostic systems for skin cancer that should be addressed in future diagnostic evaluation protocols to improve safety and reliability in clinical practice., Funding: Melanoma Research Alliance and La Marató de TV3., Competing Interests: Declaration of interests NC was an employee of IBM during a portion of this work. IBM's only involvement was through the work of NC. NC is currently employed at Microsoft, but Microsoft's only involvement is through the work of NC. NC holds two dermatology patents (US patent 10568695 B2 for surgical skin lesion removal and US patent 10255674 B2 for surface reflectance reduction in images using non-specular portion replacement) that are not relevant to this work. NC reports holding stock in IBM and Microsoft; payment or honoraria from Memorial Sloan-Kettering; and support for attending meetings or travel from Memorial Sloan-Kettering and IBM. SPu consults or receives honoraria from Almirall, ISDIN, Bristol Myers Squibb, La Roche-Posay, Pfizer, Regeneron, Sanofi, and SunPharma. VR is an expert advisor for Inhabit Brands. PT receives honoraria from Silverchair and Lilly. BH is employed by Kitware. AH consults for Canfield Scientific. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Minimal knowledge exists regarding skin cancers in Black individuals, which may adversely affect patient care., Objectives: To describe clinical features and risk factors of skin cancers in Black individuals., Methods: Retrospective study of Black individuals diagnosed with skin cancer between January 2000 and January 2020 at our institution., Results: 38,589 patients were diagnosed with skin cancer, of which 165 were Black individuals. One-hundred-thirteen of these Black individuals were diagnosed with melanoma, 35 with squamous cell carcinoma (SCC), and 17 with basal cell carcinoma (BCC). Most melanomas (80.0%, n = 90) were of the acral subtype; 75% (6 of 8 cases with dermoscopic images) displayed a parallel ridge pattern (PRP). The surrounding uninvolved background skin was visible in 7 cases, all demonstrating a PRP. This disappeared adjacent to most of the melanoma lesions (n = 4, 57.1%). creating a peripheral hypopigmented "halo". The nonmelanoma skin cancers were pigmented and had similar dermoscopic features as reported in predominantly White populations. Most SCCs (n = 5, 71.4%) had a hypopigmented "halo" and most BCCs (n = 10, 55.6%) had an accentuated reticular network adjacent to the lesions., Conclusions: Skin cancers are pigmented in Black individuals. In both acral melanomas and SCCs, we noted a peripheral rim of hypopigmentation between the lesions and the surrounding uninvolved background skin, while BCCs had accentuation of the background pigmentation adjacent to the lesions. Most acral melanomas displayed a PRP, which was also seen in surrounding uninvolved background skin., Competing Interests: Competing interests: None., (©2022 Manci et al.)

Background: Information is an unmet need among cancer survivors. There is a paucity of population-based data examining the health information-seeking behaviors and attitudes of skin cancer survivors., Objective: We aimed to identify the prevalence and patterns of health information-seeking behaviors and attitudes among skin cancer survivors across age groups., Methods: We analyzed population-based data from the 2019 Health Information National Trends Survey 5 (Cycle 3)., Results: The 5438 respondents included 346 (6.4%) skin cancer survivors (mean age 65.8 years); of the 346 skin cancer survivors, the majority were White (96.4% [weighted percentages]), and 171 (47.8%) were men. Most reported having ever looked for health- (86.1%) or cancer-related (76.5%) information; 28.2% stated their last search took a lot of effort, and 21.6% were frustrated. The internet was most often cited as being the first source that was recently used for health or medical information (45.6%). Compared to skin cancer survivors younger than 65 years old, those 65 years of age or older were more likely to see a doctor first for important health information (≥65 years: 68.3%;<65 years: 36.2%; P <.001) and less likely to have health and wellness apps (≥65 years: 26.4%; <65 years: 54.0%, P =.10), to have watched a health-related YouTube video (≥65 years: 13.3%; <65 years: 27.4%; P =.02), and to have used electronic means to look for information (≥65 years: 61.4%;<65 years: 82.3%, P <.001)., Conclusions: Searches for health information are common among skin cancer survivors, but behaviors and attitudes are associated with age, which highlights the importance of access to doctors and personalized information sources., Competing Interests: Conflicts of Interest None declared.

Background: Melanoma screening includes the assessment of changes in melanocytic lesions using images. However, previous studies of normal nevus temporal changes showed variable results and the optimal method for evaluating these changes remains unclear. Our aim was to evaluate the reproducibility of (a) nevus count done at a single time point (method I) versus two time points (method II); and (b) manual and automated nevus diameter measurements., Materials and Methods: In a first experiment, participants used either a single time point or a two time point annotation method to evaluate the total number and size of nevi on the back of an atypical mole syndrome patient. A Monte Carlo simulation was used to calculate the variance observed. In a second experiment, manual measurements of nevi on 2D images were compared to an automated measurement on 3D images. Percent difference in the paired manual and automated measurements was calculated., Results: Mean nevus count was 137 in method I and 115.5 in method II. The standard deviation was greater in method I (38.80) than in method II (4.65) (p = 0.0025). Manual diameter measurements had intraclass correlation coefficient of 0.88. The observed mean percent difference between manual and automated diameter measurements was 1.5%. Lightly pigmented and laterally located nevi had a higher percent difference., Conclusions: Comparison of nevi from two different time points is more consistent than nevus count performed separately at each time point. In addition, except for selected cases, automated measurements of nevus diameter on 3D images can be used as a time-saving reproducible substitute for manual measurement on 2D images., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)