Perifollicular linear projections: A dermatoscopic criterion for the diagnosis of lentigo maligna on the face.

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.

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.

Are the MIA and MSKCC nomograms useful in selecting patients with melanoma for sentinel lymph node biopsy?

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.

Sentinel lymph node biopsy status improves adjuvant therapy decision-making in patients with clinical stage IIB/C melanoma: A population-based analysis.

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%.

Clinically Significant Risk Thresholds in the Management of Primary Cutaneous Melanoma: A Survey of Melanoma Experts.

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.

mySmartCheck, a Digital Intervention to Promote Skin Self-examination Among Individuals Diagnosed With or at Risk for Melanoma: A Randomized Clinical Trial.

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).

Skin cancer: Primary, secondary, and tertiary prevention. Part I.

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.

Skin cancer: Primary, secondary, and tertiary prevention. Part II.

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.

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.

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.

Nonmelanoma Skin Cancer in Childhood and Young Adult Cancer Survivors Previously Treated With Radiotherapy.

BACKGROUND: Radiotherapy (RT) is a risk factor for nonmelanoma skin cancer (NMSC), specifically basal cell carcinoma (BCC) and squamous cell carcinoma (SCC), but whether features, histology, or recurrence of NMSC after RT resemble those observed in the general population is unknown. METHODS: A retrospective review (1994-2017) was performed within the Adult Long-Term Follow-Up Program and Dermatology Service at Memorial Sloan Kettering Cancer Center. Demographics, clinical features, histology, treatment, and recurrence were collected for this patient cohort that was under close medical surveillance. Pathology images were reviewed when available. RESULTS: A total of 946 survivors (mean age, 40 years [SD, 13]) were assessed for NMSC. The mean age at first cancer diagnosis was 16 years (range, 0-40 years [11]), and the most common diagnosis was Hodgkin lymphoma (34%; n=318). In 63 survivors, 281 primary in-field lesions occurred, of which 273 (97%) were BCC and 8 (3%) were SCC. Mean intervals from time of RT to BCC and SCC diagnosis were 24 years (range, 2-44 years) and 32 years (range, 14-46 years), respectively. The most common clinical presentation of BCC was macule (47%; n=67), and the most common histologic subtypes were superficial for BCC (48%; n=131) and in situ for SCC (55%; n=5). Mohs surgery predominated therapeutically (42%; n=117), the mean duration of follow-up after treatment was 6 years (range, 12 days-23 years), and the 5-year recurrence rate was 1% (n=1). CONCLUSIONS: Most NMSCs arising in sites of prior RT were of low-risk subtypes. Recurrence was similar to that observed in the general population. Current guidelines recommend surgical intervention for tumors arising in sites of prior RT because they are considered to be at high risk for recurrence. These findings suggest that an expanded role for less aggressive therapy may be appropriate, but further research is needed.

Clinical and dermoscopic features of cutaneous BAP1-inactivated melanocytic tumors: Results of a multicenter case-control study by the International Dermoscopy Society.

BACKGROUND: Multiple BRCA1-associated protein 1 (BAP1)-inactivated melanocytic tumors (BIMTs) have been associated with a familial cancer syndrome involving germline mutations in BAP1. OBJECTIVES: We sought to describe the clinical and dermoscopic features of BIMTs. METHODS: This was a retrospective, multicenter, case-control study. Participating centers contributed clinical data, dermoscopic images, and histopathologic data of biopsy-proven BIMTs. We compared the dermoscopic features between BIMTs and control patients. RESULTS: The dataset consisted of 48 BIMTs from 31 patients (22 women; median age 37 years) and 80 control patients. Eleven patients had a BAP1 germline mutation. Clinically, most BIMTs presented as pink, dome-shaped papules (n = 24). Dermoscopically, we identified 5 patterns: structureless pink-to-tan with irregular eccentric dots/globules (n = 14, 29.8%); structureless pink-to-tan with peripheral vessels (n = 10, 21.3%); structureless pink-to-tan (n = 7, 14.9%); a network with raised, structureless, pink-to-tan areas (n = 7, 14.9%); and globular pattern (n = 4, 8.5%). The structureless with eccentric dots/globules pattern and network with raised structureless areas pattern were only identified in BIMT and were more common in patients with BAP1 germline mutations (P < .0001 and P = .001, respectively). LIMITATIONS: Limitations included our small sample size, retrospective design, the absence of germline genetic testing in all patients, and inclusion bias toward more atypical-looking BIMTs. CONCLUSIONS: Dome-shaped papules with pink-to-tan structureless areas and peripheral irregular dots/globules or network should raise the clinical suspicion for BIMT.

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.

Clinical and dermoscopic features associated with lichen planus-like keratoses that undergo skin biopsy: A single-center, observational study.

BACKGROUND/OBJECTIVES: Lichen planus-like keratoses (LPLK) are benign skin lesions that can mimic malignancy; the clinical and dermoscopic features distinguishing lichen planus-like keratoses from skin tumors have not been extensively studied. The objective of this study was to identify dermoscopic features that may prevent unnecessary biopsies of lichen planus-like keratoses. METHODS: Retrospective, single-center, observational study of biopsied skin lesions at a tertiary center. We compared 355 lichen planus-like keratoses to 118 non-lichen planus-like keratoses lesions with lichen planus-like keratosis in the differential diagnosis biopsied from August 1, 2015, to December 31, 2016. The investigators were blinded to the diagnosis of the lesions. RESULTS: Lichen planus-like keratoses were most frequently non-pigmented (61.7%), truncal (52.1%), and on sun-damaged skin (69.6%); the majority occurred in Whites (95.5%) and females (62.8%). Dermoscopically, lichen planus-like keratoses were more likely than non-lichen planus-like keratoses to have scale (42.5% vs 31.4%, P = 0.03) and orange colour (8.2% vs 0.9%, P = 0.01). Among lesions with peppering (n = 76; 63 lichen planus-like keratoses and 13 non-lichen planus-like keratoses), coarse ± fine peppering (73% vs 38.5%, P = 0.02) and peppering as the only feature (34.9% vs 0%, P = 0.01) were associated with lichen planus-like keratoses. CONCLUSIONS: Lichen planus-like keratoses can be challenging to distinguish from benign and malignant skin tumors. The presence of dermoscopic scale and orange colour may aid in the recognition of lichen planus-like keratosis. Coarse peppering and the presence of peppering as the only dermoscopic feature may further aid the identification of pigmented lichen planus-like keratoses.

Inflammatory dermatoses, infections, and drug eruptions are the most common skin conditions in hospitalized cancer patients.

BACKGROUND: Dermatologic conditions cause morbidity and mortality among hospitalized cancer patients. An improved understanding is critical for implementing clinical and research programs in inpatient oncodermatology. OBJECTIVE: To characterize inpatient dermatology consultations at a large comprehensive cancer center. METHODS: Retrospective database query of new admissions and medical record review of initial inpatient dermatology consultations comparing inpatients consulted and not consulted during January-December 2015. RESULTS: In total, 412 of 11,533 inpatients received 471 dermatology consultations (54% male, median age 59.5 years). Patients with hematologic cancers were 6 times more likely to receive dermatologic consultations compared with nonhematologic cancers (odds ratio 6.56, 95% confidence interval 5.35-8.05, P < .0001). Patients consulted by a dermatologist had a significantly longer length of stay than inpatients not consulted by dermatology (median 11 vs 5 days, P < .0001). Among the 645 dermatologic conditions diagnosed, the most common categories were inflammatory diseases, infections, and drug reactions; the most frequent conditions were contact dermatitis, herpes zoster, and chemotherapy-induced drug eruptions. LIMITATIONS: The study's retrospective nature and single-institution setting are potential limitations. CONCLUSION: Hematologic malignancies are a significant risk factor for dermatology inpatient consultations. A significantly longer length of stay was associated with dermatology consultations, suggesting high comorbidities in these patients. Increased dermatologic care of these inpatients might improve quality of life, dermatologic health, and ability to receive anticancer agents.