International Skin Imaging Collaboration-Designated Diagnoses (ISIC-DX): Consensus terminology for lesion diagnostic labeling.

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.

Factors associated with suspected nonmelanoma skin cancers, dysplastic nevus, and cutaneous melanoma among first-time SpotMe screening program participants during 2009-2010.

BACKGROUND: There have been no studies of the American Academy of Dermatology's SpotMe skin cancer screening program to collectively analyze and determine the factors associated with suspected basal cell carcinoma (BCC), squamous cell carcinoma (SCC), dysplastic nevus (DN), and cutaneous melanoma (CM) diagnoses. OBJECTIVE: Describe the demographics, risk factors, and access to care profiles associated with suspected diagnoses of BCC, SCC, DN, and CM among first-time SpotMe screenees during 2009-2010. METHODS: We conducted a cross-sectional analysis of data from the SpotMe skin cancer screenings conducted in 2009 and 2010. We performed multivariable logistic regression analysis for each diagnosis, incorporating standard demographic, access to care, and risk factor variables in the models. RESULTS: Men, those without a regular dermatologist, persons reporting recently changing moles, and those with a personal history of melanoma were at increased risk for each of the suspected diagnoses analyzed. Uninsured persons were at increased risk for suspected malignancies (BCC, SCC, and CM). LIMITATIONS: Lack of histologic confirmation for diagnoses and cross-sectional design. CONCLUSION: Among first-time SpotMe participants, suspected diagnoses of BCC, SCC, DN, and CM shared several associated factors, which may be considered when planning outreach and screening for populations at risk for skin cancer.

Complementary and alternative therapies in skin cancer a literature review of biologically active compounds.

Complementary and alternative medicine or therapies (CAM) are frequently used by skin cancers patients. Patient's self-administration of CAM in melanoma can reach up to 40%-50%. CAMs such as botanical agents, phytochemicals, herbal formulas ("black salve") and cannabinoids, among others, have been described in skin cancer patients. The objective of this review article was to acknowledge the different CAM for skin cancers through the current evidence, focusing on biologically active CAM rather than mind-body approaches. We searched MEDLINE database for articles published through July 2022, regardless of study design. Of all CAMs, phytochemicals have the best in vitro evidence-supporting efficacy against skin cancer including melanoma; however, to date, none have proved efficacy on human patients. Of the phytochemicals, Curcumin is the most widely studied. Several findings support Curcumin efficacy in vitro through various molecular pathways, although most studies are in the preliminary phase. In addition, the use of alternative therapies is not exempt of risks physicians should be aware of their adverse effects, interactions with standard treatments, and possible complications arising from CAM usage. There is emerging evidence for CAM use in skin cancer, but no human clinical trials support the effectiveness of any CAM in the treatment of skin cancer to date. Nevertheless, patients worldwide frequently use CAM, and physicians should educate themselves on currently available CAMs.

Advances in the Etiology, Detection, and Clinical Management of Seborrheic Keratoses.

Seborrheic keratoses (SKs) are ubiquitous, generally benign skin tumors that exhibit high clinical variability. While age is a known risk factor, the precise roles of UV exposure and immune abnormalities are currently unclear. The underlying mechanisms of this benign disorder are paradoxically driven by oncogenic mutations and may have profound implications for our understanding of the malignant state. Advances in molecular pathogenesis suggest that inhibition of Akt and APP, as well as existing treatments for skin cancer, may have therapeutic potential in SK. Dermoscopic criteria have also become increasingly important to the accurate detection of SK, and other noninvasive diagnostic methods, such as reflectance confocal microscopy and optical coherence tomography, are rapidly developing. Given their ability to mimic malignant tumors, SK cases are often used to train artificial intelligence-based algorithms in the computerized detection of skin disease. These technologies are becoming increasingly accurate and have the potential to significantly augment clinical practice. Current treatment options for SK cause discomfort and can lead to adverse post-treatment effects, especially in skin of color. In light of the discontinuation of ESKATA in late 2019, promising alternatives, such as nitric-zinc and trichloroacetic acid topicals, should be further developed. There is also a need for larger, head-to-head trials of emerging laser therapies to ensure that future treatment standards address diverse patient needs.

Digital skin imaging applications, part I: Assessment of image acquisition technique features.

BACKGROUND: The rapid adoption of digital skin imaging applications has increased the utilization of smartphone-acquired images in dermatology. While this has enormous potential for scaling the assessment of concerning skin lesions, the insufficient quality of many consumer/patient-taken images can undermine clinical accuracy and potentially harm patients due to lack of diagnostic interpretability. We aim to characterize the current state of digital skin imaging applications and comprehensively assess how image acquisition features address image quality. MATERIALS AND METHODS: Publicly discoverable mobile, web, and desktop-based skin imaging applications, identified through keyword searches in mobile app stores, Google Search queries, previous teledermatology studies, and expert recommendations were independently assessed by three reviewers. Applications were categorized by primary audience (consumer-facing, nonhospital-based practice, or enterprise/health system), function (education, store-and-forward teledermatology, live-interactive teledermatology, electronic medical record adjunct/clinical imaging storage, or clinical triage), in-app connection to a healthcare provider (yes or no), and user type (patient, provider, or both). RESULTS: Just over half (57%) of 191 included skin imaging applications had at least one of 14 image acquisition technique features. Those that were consumer-facing, intended for educational use, and designed for both patient and physician users had significantly greater feature richness (p < 0.05). The most common feature was the inclusion of text-based imaging tips, followed by the requirement to submit multiple images and body area matching. CONCLUSION: Very few skin imaging applications included more than one image acquisition technique feature. Feature richness varied significantly by audience, function, and user categories. Users of digital dermatology tools should consider which applications have standardized features that improve image quality.

Digital skin imaging applications, part II: a comprehensive survey of post-acquisition image utilization features and technology standards.

BACKGROUND: Despite the increasing ubiquity and accessibility of teledermatology applications, few studies have comprehensively surveyed their features and technical standards. Importantly, features implemented after the point of capture are often intended to augment image utilization, while technical standards affect interoperability with existing healthcare systems. We aim to comprehensively survey image utilization features and technical characteristics found within publicly discoverable digital skin imaging applications. MATERIALS AND METHODS: Applications were identified and categorized as described in Part I. Included applications were then further assessed by three independent reviewers for post-imaging content, tools, and functionality. Publicly available information was used to determine the presence or absence of relevant technology standards and/or data characteristics. RESULTS: A total of 20 post-image acquisition features were identified across three general categories: (1) metadata attachment, (2) functional tools (i.e., those that utilized images or in-app content to perform a user-directed function), and (3) image processing. Over 80% of all applications implemented metadata features, with nearly half having metadata features only. Individual feature occurred and feature richness varied significantly by primary audience (p < 0.0001) and function (p < 0.0001). On average, each application included under three features. Less than half of all applications requested consent for user-uploaded photos and fewer than 10% provided clear data use and privacy policies. CONCLUSION: Post-imaging functionality in skin imaging applications varies significantly by primary audience and intended function, though nearly all applications implemented metadata labeling. Technical standards are often not implemented or reported consistently. Gaps in the provision of clear consent, data privacy, and data use policies should be urgently addressed.

Suggested methodology for longitudinal evaluation of nevi based on clinical images.

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.

Dermoscopic features of basal cell carcinoma and its subtypes: A systematic review.

BACKGROUND: Multiple studies have reported on dermoscopic structures in basal cell carcinoma (BCC) and its subtypes, with varying results. OBJECTIVE: To systematically review the prevalence of dermoscopic structures in BCC and its subtypes. METHODS: Databases and reference lists were searched for relevant trials according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Studies were assessed for the relative proportion of BCC dermoscopic features. Random-effects models were used to estimate summary effect sizes. RESULTS: Included were 31 studies consisting of 5950 BCCs. The most common dermoscopic features seen in BCC were arborizing vessels (59%), shiny white structures (49%), and large blue-grey ovoid nests (34%). Arborizing vessels, ulceration, and blue-grey ovoid nests and globules were most common in nodular BCC; short-fine telangiectasia, multiple small erosions, and leaf-like, spoke wheel and concentric structures in superficial BCC; porcelain white areas and arborizing vessels in morpheaform BCC; and arborizing vessels and ulceration in infiltrative BCC. LIMITATIONS: Studies had significant heterogeneity. Studies reporting BCC histopathologic subtypes did not provide clinical data on pigmentation of lesions. CONCLUSION: In addition to arborizing vessels, shiny white structures are a common feature of BCC. A constellation of dermoscopic features may aid in differentiating between BCC histopathologic subtypes.

Reflectance confocal microscopy terminology glossary for melanocytic skin lesions: A systematic review.

BACKGROUND: There is lack of uniformity in the reflectance confocal microscopy (RCM) terminology for melanocytic lesions. OBJECTIVE: To review published RCM terms for melanocytic lesions and identify redundant, synonymous terms. METHODS: A systematic review of original research articles adhering to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines was conducted until August 15, 2018. Two investigators gathered all published RCM terms used to describe melanoma and melanocytic nevi. Synonymous terms were grouped based on similarity in definition and in histopathologic correlation. RESULTS: Out of 156 full-text screened articles, 59 studies met the inclusion criteria. We identified 209 terms; 191 (91.4%) corresponding to high-magnification/cellular-level terms and 18 (8.6%) corresponding to low-magnification/architectural patterns terms. The overall average use frequency of RCM terms was 3.1 times (range, 1-31). By grouping of individual RCM terms based on likely synonymous definitions and by eliminating terms lacking clear definition, the total number of RCM terms could be potentially reduced from 209 to 40 terms (80.8% reduction). LIMITATIONS: Non-English and non-peer-reviewed articles were excluded. CONCLUSIONS: This systematic review of published RCM terms identified significant terminology redundancy. It provides the basis for subsequent terminology consensus on melanocytic neoplasms.

Number needed to biopsy ratio and diagnostic accuracy for melanoma detection.

BACKGROUND: The number needed to biopsy (NNB) ratio for melanoma diagnosis is calculated by dividing the total number of biopsies by the number of biopsied melanomas. It is the inverse of positive predictive value (PPV), which is calculated by dividing the number of biopsied melanomas by the total number of biopsies. NNB is increasingly used as a metric to compare the diagnostic accuracy of health care practitioners. OBJECTIVE: To investigate the association of NNB with the standard statistical measures of sensitivity and specificity. METHODS: We extracted published diagnostic accuracy data from 5 cross-sectional skin cancer reader studies (median [min-max] readers/study was 29 [8-511]). Because NNB is a ratio, we converted it to PPV. RESULTS: Four studies showed no association and 1 showed a negative association between PPV and sensitivity. All 5 studies showed a positive association between PPV and specificity. LIMITATIONS: Reader study data. CONCLUSIONS: An individual health care practitioner with a lower NNB is likely to have a higher specificity than one with a higher NNB, assuming they practice under similar conditions; no conclusions can be made about their relative sensitivities. We advocate for additional research to define quality metrics for melanoma detection and caution when interpreting NNB.

Computer algorithms show potential for improving dermatologists' accuracy to diagnose cutaneous melanoma: Results of the International Skin Imaging Collaboration 2017.

BACKGROUND: Computer vision has promise in image-based cutaneous melanoma diagnosis but clinical utility is uncertain. OBJECTIVE: To determine if computer algorithms from an international melanoma detection challenge can improve dermatologists' accuracy in diagnosing melanoma. METHODS: In this cross-sectional study, we used 150 dermoscopy images (50 melanomas, 50 nevi, 50 seborrheic keratoses) from the test dataset of a melanoma detection challenge, along with algorithm results from 23 teams. Eight dermatologists and 9 dermatology residents classified dermoscopic lesion images in an online reader study and provided their confidence level. RESULTS: The top-ranked computer algorithm had an area under the receiver operating characteristic curve of 0.87, which was higher than that of the dermatologists (0.74) and residents (0.66) (P < .001 for all comparisons). At the dermatologists' overall sensitivity in classification of 76.0%, the algorithm had a superior specificity (85.0% vs. 72.6%, P = .001). Imputation of computer algorithm classifications into dermatologist evaluations with low confidence ratings (26.6% of evaluations) increased dermatologist sensitivity from 76.0% to 80.8% and specificity from 72.6% to 72.8%. LIMITATIONS: Artificial study setting lacking the full spectrum of skin lesions as well as clinical metadata. CONCLUSION: Accumulating evidence suggests that deep neural networks can classify skin images of melanoma and its benign mimickers with high accuracy and potentially improve human performance.

Improvement of diagnostic confidence and management of equivocal skin lesions by integration of reflectance confocal microscopy in daily practice: Prospective study in 2 referral skin cancer centers.

BACKGROUND: Reflectance confocal microscopy (RCM) allows accurate, noninvasive, in vivo diagnosis for skin cancer. However, its impact on physicians' diagnostic confidence and management is unknown. OBJECTIVES: We sought to assess the physicians' diagnostic confidence and management before and after RCM of equivocal skin lesions. METHODS: Prospective, 2-center, observational study. During clinical practice, 7 dermatologists recorded their diagnostic confidence level (measured in a scale from 0 to 10), diagnosis, and management before and after RCM of clinically/dermoscopically equivocal lesions that raised concern for skin cancer. We also evaluated the diagnostic accuracy before and after RCM. RESULTS: We included 272 consecutive lesions from 226 individuals (mean age, 53.5 years). Diagnostic confidence increased from 6.2 to 8.1 after RCM (P < .001) when RCM confirmed or changed the diagnosis. Lesion management changed in 33.5% cases after RCM (to observation in 51 cases and to biopsy/excision in 31 cases). After RCM, the number needed to excise was 1.2. Sensitivity for malignancy before and after RCM was 78.2% and 85.1%, respectively. Specificity before and after RCM was 78.8% and 80%, respectively. LIMITATIONS: Small sample size, real-life environment, and different levels of expertise among RCM users. CONCLUSION: Physicians' diagnostic confidence and accuracy increased after RCM when evaluating equivocal tumors, frequently resulting in management changes while maintaining high diagnostic accuracy.

Comparison of the accuracy of human readers versus machine-learning algorithms for pigmented skin lesion classification: an open, web-based, international, diagnostic study.

BACKGROUND: Whether machine-learning algorithms can diagnose all pigmented skin lesions as accurately as human experts is unclear. The aim of this study was to compare the diagnostic accuracy of state-of-the-art machine-learning algorithms with human readers for all clinically relevant types of benign and malignant pigmented skin lesions. METHODS: For this open, web-based, international, diagnostic study, human readers were asked to diagnose dermatoscopic images selected randomly in 30-image batches from a test set of 1511 images. The diagnoses from human readers were compared with those of 139 algorithms created by 77 machine-learning labs, who participated in the International Skin Imaging Collaboration 2018 challenge and received a training set of 10 015 images in advance. The ground truth of each lesion fell into one of seven predefined disease categories: intraepithelial carcinoma including actinic keratoses and Bowen's disease; basal cell carcinoma; benign keratinocytic lesions including solar lentigo, seborrheic keratosis and lichen planus-like keratosis; dermatofibroma; melanoma; melanocytic nevus; and vascular lesions. The two main outcomes were the differences in the number of correct specific diagnoses per batch between all human readers and the top three algorithms, and between human experts and the top three algorithms. FINDINGS: Between Aug 4, 2018, and Sept 30, 2018, 511 human readers from 63 countries had at least one attempt in the reader study. 283 (55·4%) of 511 human readers were board-certified dermatologists, 118 (23·1%) were dermatology residents, and 83 (16·2%) were general practitioners. When comparing all human readers with all machine-learning algorithms, the algorithms achieved a mean of 2·01 (95% CI 1·97 to 2·04; p<0·0001) more correct diagnoses (17·91 [SD 3·42] vs 19·92 [4·27]). 27 human experts with more than 10 years of experience achieved a mean of 18·78 (SD 3·15) correct answers, compared with 25·43 (1·95) correct answers for the top three machine algorithms (mean difference 6·65, 95% CI 6·06-7·25; p<0·0001). The difference between human experts and the top three algorithms was significantly lower for images in the test set that were collected from sources not included in the training set (human underperformance of 11·4%, 95% CI 9·9-12·9 vs 3·6%, 0·8-6·3; p<0·0001). INTERPRETATION: State-of-the-art machine-learning classifiers outperformed human experts in the diagnosis of pigmented skin lesions and should have a more important role in clinical practice. However, a possible limitation of these algorithms is their decreased performance for out-of-distribution images, which should be addressed in future research. FUNDING: None.

Massively parallel sequencing analysis of benign melanocytic naevi.

AIMS: Melanocytic naevi are benign lesions of the skin or mucosa that may constitute non-obligate precursors of malignant melanoma, particularly when they show lentiginous and dysplastic features. The aim of this study was to investigate the repertoire of somatic genetic alterations in melanocytic naevi. METHODS AND RESULTS: DNA extracted from 12 melanocytic naevi and DNA from matching normal tissue were separately microdissected and subjected to targeted massively parallel sequencing of ≥300 cancer genes. A median of 5.5 (range 1-12) non-synonymous somatic mutations were detected, with 10 cases harbouring mutually exclusive BRAF V600E (6/12) or NRAS (4/12) clonal hotspot mutations. One of the two cases lacking BRAF and NRAS mutations was a dysplastic naevus harbouring an HRAS Q61L hotspot mutation. Analysis of the laser-capture microdissected components of a naevus synchronously diagnosed with in-situ and invasive malignant melanoma revealed a truncal, clonal BRAF V600E mutation, and the acquisition of a CDKN2A homozygous deletion in the invasive component, in conjunction with additional clonal mutations affecting NF2, FAT4 and KDR in both in-situ and invasive malignant components. CONCLUSION: Melanocytic naevi harbour recurrent BRAF V600E or NRAS hotspot mutations with low mutational burdens. Our findings also show that progression from naevi to malignant melanoma may be driven by the acquisition of additional genetic alterations, including CDKN2A homozygous deletions.

Developing an international standard for the classification of surface anatomic location for use in clinical practice and epidemiologic research.

BACKGROUND: There is currently no universally adopted terminology for defining human surface anatomic location. The lack of precision, accuracy, and reliability of terms used by health care providers, in particular dermatologic surgeons, is unsatisfactory both for epidemiologic research and for high-quality patient care. OBJECTIVE: We sought to create a clinically relevant yet concise surface anatomy terminology for international use including the International Classification of Diseases and to map it to existing disparate terminologies. METHODS: Widely used surface anatomy terminology data sets and diagrams were reviewed. A Delphi consensus convened to create a novel surface anatomy terminology. The new terminology was hierarchically mapped to Systematized Nomenclature of Medicine terms and New York University numbers and physically mapped to 2-dimensional anatomic diagrams for clarity and reproducibility. RESULTS: The final terminology data set contains 519 discrete terms arranged in a 9-level hierarchy and has been adopted by the World Health Organization for the International Classification of Diseases, 11th revision. LIMITATIONS: Specification of most locations requires linking to laterality qualifiers. Fine granularity for larger sites may require the use of additional qualifiers. CONCLUSION: Consistent use of precise and accurate surface anatomy terms is crucial to the practice of dermatology, particularly procedural dermatology. The proposed terminology is designed to form the basis for evolution of a universally adoptable terminology set to improve patient care, interprovider communication, and epidemiologic tracking.

Reflectance confocal microscopy terminology glossary for nonmelanocytic skin lesions: A systematic review.

BACKGROUND: There is lack of uniformity in reflectance confocal microscopy (RCM) terminology for nonmelanocytic lesions (NMLs). OBJECTIVE: To review published RCM terms for NMLs and identify likely synonymous terms. METHODS: We conducted a systematic review of original research articles published up to August 19, 2017, adhering to Preferred Reporting Items for Systemic Reviews and Meta-Analyses guidelines. Two investigators gathered all published RCM terms used to describe basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and seborrheic keratosis/solar lentigo/lichen planus-like keratosis (SK/SL/LPLK). Synonymous terms were grouped on the basis of similarity in definition and histopathologic correlates. RESULTS: The inclusion criteria was met by 31 studies. Average frequency of use per term was 1.6 (range 1-8). By grouping synonymous terms, the number of terms could be reduced from 58 to 18 for BCC, 58 to 36 for SCC, 23 to 12 for SK/SL/LPLK, and from 139 to 66 terms (52.5% reduction) in total. The frequency of term usage stratified by anatomic layer (suprabasal epidermis vs epidermal basal layer, dermoepidermal junction, and superficial dermis) was 27 (25.7%) versus 78 (74.2%) for BCC; 60 (64.5%) versus 33 (34.5%) for SCC, and 15 (45.4%) versus 18 (54.5%) for SK/SL/LPLK, respectively. LIMITATIONS: Articles that were not peer reviewed were excluded. CONCLUSION: Systematic review of published RCM terms provides the basis for future NMLs terminology consensus.

Guidelines of care for the management of primary cutaneous melanoma.

The incidence of primary cutaneous melanoma continues to increase each year. Melanoma accounts for the majority of skin cancer-related deaths, but treatment is usually curative following early detection of disease. In this American Academy of Dermatology clinical practice guideline, updated treatment recommendations are provided for patients with primary cutaneous melanoma (American Joint Committee on Cancer stages 0-IIC and pathologic stage III by virtue of a positive sentinel lymph node biopsy). Biopsy techniques for a lesion that is clinically suggestive of melanoma are reviewed, as are recommendations for the histopathologic interpretation of cutaneous melanoma. The use of laboratory, molecular, and imaging tests is examined in the initial work-up of patients with newly diagnosed melanoma and for follow-up of asymptomatic patients. With regard to treatment of primary cutaneous melanoma, recommendations for surgical margins and the concepts of staged excision (including Mohs micrographic surgery) and nonsurgical treatments for melanoma in situ, lentigo maligna type (including topical imiquimod and radiation therapy), are updated. The role of sentinel lymph node biopsy as a staging technique for cutaneous melanoma is described, with recommendations for its use in clinical practice. Finally, current data regarding pregnancy and melanoma, genetic testing for familial melanoma, and management of dermatologic toxicities related to novel targeted agents and immunotherapies for patients with advanced disease are summarized.

Melanoma risk stratification of individuals with a high-risk naevus phenotype - A pilot study.

BACKGROUND/OBJECTIVES: High a naevus counts and atypical naevi are risk factors for cutaneous melanoma. However, many individuals with a high-risk naevus phenotype do not develop melanoma. In this study, we describe the clinical and dermoscopic attributes of naevi associated with melanoma in a high-risk naevus phenotype population. METHODS: This single-centre, hospital-based case-control study included 54 prospectively enrolled adult patients ≥18 years old with a high-risk naevus phenotype (18 cases with a history of melanoma and 36 age- and gender-matched controls without a history of melanoma). We analysed clinical and dermoscopic images of the 20 largest naevi for each participant. RESULTS: Cases had a higher mean age than controls (48.2 vs. 39.1 years, P = 0.007) but there was no difference in the male-to-female ratio between groups. Nearly, all participants (97%) were Fitzpatrick skin type II or III. Naevi in cases were more likely to be truncal, (72.6% vs. 53.6%, P = 0.01), particularly anterior truncal, (29.2% vs. 14.4%, P < 0.001) and larger than 8 mm (17.4% vs. 7.8%%, P = 0.01) compared to controls. CASH score of naevi did not differ between groups. Naevi in cases were more likely to have a multicomponent dermoscopic pattern than in controls (18.4% vs. 12.6%, P = 0.02). CONCLUSION: Larger naevi, truncal naevi, and naevi, with a multicomponent dermoscopic pattern may be risk factors for melanoma among individuals with a high-risk naevus phenotype. Further studies are needed to validate these findings.