Incidence and profile of skin cancers in patients following ultraviolet phototherapy without psoralens: A retrospective cohort study.

BACKGROUND: Psoralen + ultraviolet-A (PUVA) is associated with photocarcinogenesis. However, carcinogenic risk with other ultraviolet phototherapies remains unclear. OBJECTIVE: Evaluate whether phototherapy without psoralens increases skin cancer risk. METHODS: Retrospective cohort study of patients treated at a teaching-hospital phototherapy center (1977-2018). Skin cancer records were validated against pathology reports. Age-standardized incidence rates (ASIRs) of skin cancer were evaluated for gender, skin phototype, diagnosis, ultraviolet modality, anatomical site; and compared to provincial population incidence rates (2003). RESULTS: In total, 3506 patients treated with broadband-ultraviolet-B, narrowband-UVB and/or combined UVAB were assessed with a mean follow-up of 7.3 years. Majority of patients had psoriasis (60.9%) or eczema (26.4%). Median number of treatments was 43 (1-3598). Overall, 170 skin cancers (17 melanoma, 33 squamous cell carcinoma and 120 basal cell carcinoma) occurred in 79 patients. Patient-based and tumor-based ASIR of skin cancer was 149 (95% CI: 112-187)/100,000 and 264 (219-309)/100,000 person-years, respectively. There was no significant difference between tumor-based ASIRs for melanoma, squamous cell carcinoma, and basal cell carcinoma compared to the general population; or in phototherapy patients with-psoriasis or eczema; or immunosuppressants. No cumulative dose-response correlation between UVB and skin cancer was seen. LIMITATIONS: Treatment and follow-up duration. CONCLUSION: No increased risk of melanoma and keratinocyte cancer was found with phototherapy.

Micro-relief characterization of benign and malignant skin lesions by polarization speckle analysis in vivo.

BACKGROUND/PURPOSE: A recent direction in skin disease classification is to develop quantitative diagnostic techniques. Skin relief, colloquially known as roughness, is an important clinical feature. The aim of this study is to demonstrate a novel polarization speckle technique to quantitatively measure roughness on skin lesions in vivo. We then calculate the average roughness of different types of skin lesions to determine the extent to which polarization speckle roughness measurements can be used to identify skin cancer. METHODS: The experimental conditions were set to target the fine relief structure on the order of ten microns within a small field of view of 3 mm. The device was tested in a clinical study on patients with malignant and benign skin lesions that resemble cancer. The cancer group includes 37 malignant melanomas (MM), 43 basal cell carcinomas (BCC), and 26 squamous cell carcinomas (SCC), all categories confirmed by gold standard biopsy. The benign group includes 109 seborrheic keratoses (SK), 79 nevi, and 11 actinic keratoses (AK). Normal skin roughness was obtained for the same patients (301 different body sites proximal to the lesion). RESULTS: The average root mean squared (rms) roughness ± standard error of the mean for MM and nevus was equal to 19 ± 5 µm and 21 ± 3 µm, respectively. Normal skin has rms roughness of 31 ± 3 µm, other lesions have roughness of 35 ± 10 µm (AK), 35 ± 7 µm (SCC), 31 ± 4 µm (SK), and 30 ± 5 µm (BCC). CONCLUSION: An independent-samples Kruskal-Wallis test indicates that MM and nevus can be separated from each of the tested types of lesions, except each other. These results quantify clinical knowledge of lesion roughness and could be useful for optical cancer detection.

Full Stokes polarimetry using a monolithic off-axis polarizing interferometer and a 2D array sensor.

This paper describes a full Stokes polarimeter employing a monolithic off-axis polarizing interferometric module and a 2D array sensor. The proposed passive polarimeter provides a dynamic full Stokes vector measurement capability of around 30 Hz. As the proposed polarimeter employs no active devices and is operated by employing an imaging sensor, it has significant potential to become a highly compact polarization sensor for smartphone applications. To show the feasibility of the proposed passive dynamic polarimeter scheme, the full Stokes parameters of a quarter-wave plate are extracted and displayed on a Poincare sphere by varying the polarization state of the measured beam.

InterMEL: An international biorepository and clinical database to uncover predictors of survival in early-stage melanoma.

INTRODUCTION: We are conducting a multicenter study to identify classifiers predictive of disease-specific survival in patients with primary melanomas. Here we delineate the unique aspects, challenges, and best practices for optimizing a study of generally small-sized pigmented tumor samples including primary melanomas of at least 1.05mm from AJTCC TNM stage IIA-IIID patients. We also evaluated tissue-derived predictors of extracted nucleic acids' quality and success in downstream testing. This ongoing study will target 1,000 melanomas within the international InterMEL consortium. METHODS: Following a pre-established protocol, participating centers ship formalin-fixed paraffin embedded (FFPE) tissue sections to Memorial Sloan Kettering Cancer Center for the centralized handling, dermatopathology review and histology-guided coextraction of RNA and DNA. Samples are distributed for evaluation of somatic mutations using next gen sequencing (NGS) with the MSK-IMPACTTM assay, methylation-profiling (Infinium MethylationEPIC arrays), and miRNA expression (Nanostring nCounter Human v3 miRNA Expression Assay). RESULTS: Sufficient material was obtained for screening of miRNA expression in 683/685 (99%) eligible melanomas, methylation in 467 (68%), and somatic mutations in 560 (82%). In 446/685 (65%) cases, aliquots of RNA/DNA were sufficient for testing with all three platforms. Among samples evaluated by the time of this analysis, the mean NGS coverage was 249x, 59 (18.6%) samples had coverage below 100x, and 41/414 (10%) failed methylation QC due to low intensity probes or insufficient Meta-Mixed Interquartile (BMIQ)- and single sample (ss)- Noob normalizations. Six of 683 RNAs (1%) failed Nanostring QC due to the low proportion of probes above the minimum threshold. Age of the FFPE tissue blocks (p<0.001) and time elapsed from sectioning to co-extraction (p = 0.002) were associated with methylation screening failures. Melanin reduced the ability to amplify fragments of 200bp or greater (absent/lightly pigmented vs heavily pigmented, p<0.003). Conversely, heavily pigmented tumors rendered greater amounts of RNA (p<0.001), and of RNA above 200 nucleotides (p<0.001). CONCLUSION: Our experience with many archival tissues demonstrates that with careful management of tissue processing and quality control it is possible to conduct multi-omic studies in a complex multi-institutional setting for investigations involving minute quantities of FFPE tumors, as in studies of early-stage melanoma. The study describes, for the first time, the optimal strategy for obtaining archival and limited tumor tissue, the characteristics of the nucleic acids co-extracted from a unique cell lysate, and success rate in downstream applications. In addition, our findings provide an estimate of the anticipated attrition that will guide other large multicenter research and consortia.

SSD-KD: A self-supervised diverse knowledge distillation method for lightweight skin lesion classification using dermoscopic images.

Skin cancer is one of the most common types of malignancy, affecting a large population and causing a heavy economic burden worldwide. Over the last few years, computer-aided diagnosis has been rapidly developed and make great progress in healthcare and medical practices due to the advances in artificial intelligence, particularly with the adoption of convolutional neural networks. However, most studies in skin cancer detection keep pursuing high prediction accuracies without considering the limitation of computing resources on portable devices. In this case, the knowledge distillation (KD) method has been proven as an efficient tool to help improve the adaptability of lightweight models under limited resources, meanwhile keeping a high-level representation capability. To bridge the gap, this study specifically proposes a novel method, termed SSD-KD, that unifies diverse knowledge into a generic KD framework for skin disease classification. Our method models an intra-instance relational feature representation and integrates it with existing KD research. A dual relational knowledge distillation architecture is self-supervised trained while the weighted softened outputs are also exploited to enable the student model to capture richer knowledge from the teacher model. To demonstrate the effectiveness of our method, we conduct experiments on ISIC 2019, a large-scale open-accessed benchmark of skin diseases dermoscopic images. Experiments show that our distilled MobileNetV2 can achieve an accuracy as high as 85% for the classification tasks of 8 different skin diseases with minimal parameters and computing requirements. Ablation studies confirm the effectiveness of our intra- and inter-instance relational knowledge integration strategy. Compared with state-of-the-art knowledge distillation techniques, the proposed method demonstrates improved performance. To the best of our knowledge, this is the first deep knowledge distillation application for multi-disease classification on the large-scale dermoscopy database. Our codes and models are available at https://github.com/enkiwang/Portable-Skin-Lesion-Diagnosis.

Landscape of mutations in early stage primary cutaneous melanoma: An InterMEL study.

It is unclear why some melanomas aggressively metastasize while others remain indolent. Available studies employing multi-omic profiling of melanomas are based on large primary or metastatic tumors. We examine the genomic landscape of early-stage melanomas diagnosed prior to the modern era of immunological treatments. Untreated cases with Stage II/III cutaneous melanoma were identified from institutions throughout the United States, Australia and Spain. FFPE tumor sections were profiled for mutation, methylation and microRNAs. Preliminary results from mutation profiling and clinical pathologic correlates show the distribution of four driver mutation sub-types: 31% BRAF; 18% NRAS; 21% NF1; 26% Triple Wild Type. BRAF mutant tumors had younger age at diagnosis, more associated nevi, more tumor infiltrating lymphocytes, and fewer thick tumors although at generally more advanced stage. NF1 mutant tumors were frequent on the head/neck in older patients with severe solar elastosis, thicker tumors but in earlier stages. Triple Wild Type tumors were predominantly male, frequently on the leg, with more perineural invasion. Mutations in TERT, TP53, CDKN2A and ARID2 were observed often, with TP53 mutations occurring particularly frequently in the NF1 sub-type. The InterMEL study will provide the most extensive multi-omic profiling of early-stage melanoma to date. Initial results demonstrate a nuanced understanding of the mutational and clinicopathological landscape of these early-stage tumors.

Polarization memory rate as a metric to differentiate benign and malignant tissues.

Non-invasive optical methods for cancer diagnostics, such as microscopy, spectroscopy, and polarimetry, are rapidly advancing. In this respect, finding new and powerful optical metrics is an indispensable task. Here we introduce polarization memory rate (PMR) as a sensitive metric for optical cancer diagnostics. PMR characterizes the preservation of circularly polarized light relative to linearly polarized light as light propagates in a medium. We hypothesize that because of well-known indicators associated with the morphological changes of cancer cells, like an enlarged nucleus size and higher chromatin density, PMR should be greater for cancerous than for the non-cancerous tissues. A thorough literature review reveals how this difference arises from the anomalous depolarization behaviour of many biological tissues. In physical terms, though most biological tissue primarily exhibits Mie scattering, it typically exhibits Rayleigh depolarization. However, in cancerous tissue the Mie depolarization regime becomes more prominent than Rayleigh. Experimental evidence of this metric is found in a preliminary clinical study using a novel Stokes polarimetry probe. We conducted in vivo measurements of 20 benign, 28 malignant and 59 normal skin sites with a 660 nm laser diode. The median PMR values for cancer vs non-cancer are significantly higher for cancer which supports our hypothesis. The reported fundamental differences in depolarization may persist for other types of cancer and create a conceptual basis for further developments in polarimetry applications for cancer detection.

Persistent organic pollutants and risk of cutaneous malignant melanoma among women.

BACKGROUND: Despite the increasing trend of cutaneous malignant melanoma (CMM) incidence in Canada, especially among females, few risk factors other than ultraviolet radiation exposure, have been identified. AIM: We conducted a case-control study of 406 CMM cases and 181 controls to evaluate the potential impact of body burdens of various persistent organic pollutants on CMM risk. METHODS: Detailed data on potential confounding factors, including lifetime repeated sun exposure and skin reaction to repeated sun exposure, were collected. Gas chromatography tandem mass spectrometry was used to assay plasma levels of 14 polychlorinated biphenyl (PCB) congeners and 11 organochlorine (OC) pesticides among cases and controls. RESULTS: Statistically significant trends of increased CMM risk were observed with increasing plasma concentrations of multiple PCB congeners, including PCBs 138, 153, 170, 180, 183 and 187. For example, compared to lowest plasma concentration quartile of PCB-138, the second, third and fourth quartiles were associated with 1.7 (95% CI: 0.9-2.9), 2.3 (95% CI: 1.3-4.1) and 2.4 (95% CI: 1.3-4.5) -fold increased risks of CMM, respectively. Similarly, increasing plasma concentrations of several OC pesticides (i.e., ß-HCH, HCB, Mirex, oxychlordane and trans-Nonachlor) showed statistically significant trends with increased CMM risk. For example, compared to lowest plasma concentration quartile of ß-HCH, the second, third and fourth quartiles were associated with 1.3 (95% CI: 0.7-2.3), 2.1 (95% CI: 1.2-3.7) and 2.3 (95% CI: 1.2-4.4) -fold increased risks of CMM, respectively. CONCLUSION: Plasma levels of several persistent organic pollutants were highly correlated, suggesting that observed associations were not necessarily independent of each other. Given the highly correlated nature of exposure to PCB and OC analytes, sophisticated analyses that consider complex mixtures should be considered in future studies.

Investigating the depolarization property of skin tissue by degree of polarization uniformity contrast using polarization-sensitive optical coherence tomography.

The depolarization property of skin has been found to be important for skin cancer detection. Previous techniques based on light polarization lack the capability of depth differentiation. Polarization-sensitive optical coherence tomography (PS-OCT) has the advantage of both depth-resolved 3D imaging and high sensitivity to polarization. In this study, we investigate the depolarization property of skin tissue using PS-OCT, especially with the degree of polarization uniformity (DOPU) contrast. Well designed skin phantoms with various surface roughness levels and optical properties mimicking skin are imaged by PS-OCT and the DOPU values are quantified. The result shows a correlation between DOPU and surface roughness, where a higher roughness corresponds to a lower DOPU value. An index matching experiment with a water layer confirms the impact of surface condition on light depolarization. Refraction of backscattered photons on the surface boundary is attributed to the broadening of backscattering angle and thus depolarization. To the best of our knowledge, this is the first time the impact of surface roughness on DOPU is reported and its mechanism explained. Furthermore, through preliminary in vivo skin imaging, the capability of DOPU in detecting depolarization in skin is demonstrated. By utilizing the 3D imaging from PS-OCT, DOPU can offer a high-resolution depth differentiation and quantification of depolarization in skin tissue.

Incorporating clinical knowledge with constrained classifier chain into a multimodal deep network for melanoma detection.

In recent years, vast developments in Computer-Aided Diagnosis (CAD) for skin diseases have generated much interest from clinicians and other eventual end-users of this technology. Introducing clinical domain knowledge to these machine learning strategies can help dispel the black box nature of these tools, strengthening clinician trust. Clinical domain knowledge also provides new information channels which can improve CAD diagnostic performance. In this paper, we propose a novel framework for malignant melanoma (MM) detection by fusing clinical images and dermoscopic images. The proposed method combines a multi-labeled deep feature extractor and clinically constrained classifier chain (CC). This allows the 7-point checklist, a clinician diagnostic algorithm, to be included in the decision level while maintaining the clinical importance of the major and minor criteria in the checklist. Our proposed framework achieved an average accuracy of 81.3% for detecting all criteria and melanoma when testing on a publicly available 7-point checklist dataset. This is the highest reported results, outperforming state-of-the-art methods in the literature by 6.4% or more. Analyses also show that the proposed system surpasses the single modality system of using either clinical images or dermoscopic images alone and the systems without adopting the approach of multi-label and clinically constrained classifier chain. Our carefully designed system demonstrates a substantial improvement over melanoma detection. By keeping the familiar major and minor criteria of the 7-point checklist and their corresponding weights, the proposed system may be more accepted by physicians as a human-interpretable CAD tool for automated melanoma detection.

A novel automated approach to rapid and precise in vivo measurement of hair morphometrics using a smartphone.

BACKGROUND: Although many hair disorders can be readily diagnosed based on their clinical appearance, their progression and response to treatment are often difficult to monitor, particularly in quantitative terms. We introduce an innovative technique utilizing a smartphone and computerized image analysis to expeditiously and automatically measure and compute hair density and diameter in patients in real time. METHODS: A smartphone equipped with a dermatoscope lens wirelessly transmits trichoscopy images to a computer for image processing. A black-and-white binary mask image representing hair and skin is produced, and the hairs are thinned into single-pixel-thick fiber skeletons. Further analysis based on these fibers allows morphometric characteristics such as hair shaft number and diameters to be computed rapidly. The hair-bearing scalps of fifty participants were imaged to assess the precision of our automated smartphone-based device in comparison with a specialized trichometry device for hair shaft density and diameter measurement. The precision and operation time of our technique relative to manual trichometry, which is commonly used by hair disorder specialists, is determined. RESULTS: An equivalence test, based on two 1-sided t tests, demonstrates statistical equivalence in hair density and diameter values between this automated technique and manual trichometry within a 20% margin. On average, this technique actively required 24 seconds of the clinician's time whereas manual trichometry necessitated 9.2 minutes. CONCLUSION: Automated smartphone-based trichometry is a rapid, precise, and clinically feasible technique which can significantly facilitate the assessment and monitoring of hair loss. Its use could be easily integrated into clinical practice to improve standard trichoscopy.

Development of polarization speckle based on random polarization phasor sum.

The random-walk approach has been extended and applied to study the development of polarization speckle by taking the vector nature into account for stochastic electric fields. Based on the random polarization phasor sum, the first and second moments of the Stokes parameters of the resultant polarization speckle have been examined. Under certain assumptions about the statistics of the component polarization phasors that make up the sum, we present some of the details of the spatial derivation that lead to the expressions for the degree of polarization and the newly proposed Stokes contrast that are suitable for describing the polarization speckle development. This vectorial extension of the random walk will provide an intuitive explanation for the development of the polarization speckle.

Degree of optical polarization as a tool for detecting melanoma: proof of principle.

Determining the optical polarization properties of a skin lesion is a proposed method to differentiate melanoma from other skin lesions. We developed an in vivo Stokes polarimetry probe that fires a laser of known polarization at the skin and measures the Stokes parameters of the backscattered light in one shot. From these measured Stokes parameters, we can calculate the degree of polarization (DOP). Through testing on rough skin phantoms, a correlation between backscattered DOP and skin roughness was identified for both linear and circular input polarization, the latter of which was found to be more useful. In a pilot clinical trial of 69 skin lesions in vivo, it was found that the mean DOP for melanoma (linear input on melanoma: 0.46 ± 0.09) was greater than that of other lesions (linear input on all other lesions: 0.28 ± 0.01). This separation is greater for circular polarized input light, and it is likely that circular polarized light's greater sensitivity to surface roughness contributes to this result. In addition, all skin lesions demonstrated a stronger depolarizing effect on circular polarized light than linear polarized light. We have identified DOP as a potentially useful measurement to identify melanoma among other types of skin lesions.

A Computer-Aided Decision Support System for Detection and Localization of Cutaneous Vasculature in Dermoscopy Images Via Deep Feature Learning.

Vascular structures of skin are important biomarkers in diagnosis and assessment of cutaneous conditions. Presence and distribution of lesional vessels are associated with specific abnormalities. Therefore, detection and localization of cutaneous vessels provide critical information towards diagnosis and stage status of diseases. However, cutaneous vessels are highly variable in shape, size, color and architecture, which complicate the detection task. Considering the large variability of these structures, conventional vessel detection techniques lack the generalizability to detect different vessel types and require separate algorithms to be designed for each type. Furthermore, such techniques are highly dependent on precise hand-crafted features which are time-consuming and computationally inefficient. As a solution, we propose a data-driven feature learning framework based on stacked sparse auto-encoders (SSAE) for comprehensive detection of cutaneous vessels. Each training image is divided into small patches of either containing or non-containing vasculature. A multilayer SSAE is designed to learn hidden features of the data in hierarchical layers in an unsupervised manner. The high-level learned features are subsequently fed into a classifier which categorizes each patch into absence or presence of vasculature and localizes vessels within the lesion. Over a test set of 3095 patches derived from 200 images, the proposed framework demonstrated superior performance of 95.4% detection accuracy over a variety of vessel patterns; outperforming other techniques by achieving the highest positive predictive value of 94.7%. The proposed Computer-Aided Diagnosis (CAD) framework can serve as a decision support system assisting dermatologists for more accurate diagnosis, especially in teledermatology applications in remote areas.

Quantifying the visual appearance of sunscreens applied to the skin using indirect computer image colorimetry.

BACKGROUND: There is no accepted method to objectively assess the visual appearance of sunscreens on the skin. METHODS: We present a method for sunscreen application, digital photography, and computer analysis to quantify the appearance of the skin after sunscreen application. Four sunscreen lotions were applied randomly at densities of 0.5, 1.0, 1.5, and 2.0 mg/cm2 to areas of the back of 29 subjects. Each application site had a matched contralateral control area. High-resolution standardized photographs including a color card were taken after sunscreen application. After color balance correction, CIE L*a*b* color values were extracted from paired sites. Differences in skin appearance attributed to sunscreen were represented by ΔE, which in turn was calculated from the linear Euclidean distance within the L*a*b* color space between the paired sites. RESULTS: Sunscreen visibility as measured by median ΔE varied across different products and application densities and ranged between 1.2 and 12.1. The visibility of sunscreens varied according to product SPF, composition (organic vs inorganic), presence of tint, and baseline b* of skin (P < .05 for all). CONCLUSION: Standardized sunscreen application followed by digital photography and indirect computer-based colorimetry represents a potential method to objectively quantify visibility of sunscreen on the skin.

Predictors of 25-Hydroxyvitamin D Concentration Measured at Multiple Time Points in a Multiethnic Population.

The evidence for a relationship between serum vitamin D levels and nonskeletal health outcomes is inconsistent. The validity of single or predicted measurements of 25-hydroxyvitamin D (25(OH)D) concentration is unknown, as levels of this biomarker are highly seasonally variable. We compared models of 25(OH)D measured at baseline, at multiple time points throughout the year, and averaged over the year among 309 persons in Toronto, Ontario, Canada (43°N latitude) during 2009-2013. Information and blood samples were collected every 2 months. Baseline and average 25(OH)D concentrations were correlated (r = 0.88). Major factors associated with 25(OH)D level were similar across models and included race/ethnicity (concentrations in non-European groups were lower than those in Europeans), vitamin D supplement use of ≥1,000 IU/day (18.9 nmol/L (95% confidence interval (CI): 16.1, 21.8) vs. no supplement use in a full data set with all factors), and the presence of the group-specific component/vitamin D binding protein gene (GC/DBP) rs4588 functional polymorphism (AA vs. CC: -16.7 nmol/L (95% CI: -26.2, -7.1); CA vs. CC: -10.7 nmol/L (95% CI: -14.9, -6.5)). Most factors had similar associations in Europeans and non-Europeans. Genetic factors may play a greater role in average 25(OH)D concentrations. Prediction models for 25(OH)D are challenging and population-specific, but use of genetic factors along with a few common population-relevant, quantifiable nongenetic factors with strong associations may be the most feasible approach to vitamin D assessment over time.

Automated Detection and Segmentation of Vascular Structures of Skin Lesions Seen in Dermoscopy, With an Application to Basal Cell Carcinoma Classification.

Blood vessels are important biomarkers in skin lesions both diagnostically and clinically. Detection and quantification of cutaneous blood vessels provide critical information toward lesion diagnosis and assessment. In this paper, a novel framework for detection and segmentation of cutaneous vasculature from dermoscopy images is presented and the further extracted vascular features are explored for skin cancer classification. Given a dermoscopy image, we segment vascular structures of the lesion by first decomposing the image using independent-component analysis into melanin and hemoglobin components. This eliminates the effect of pigmentation on the visibility of blood vessels. Using k-means clustering, the hemoglobin component is then clustered into normal, pigmented, and erythema regions. Shape filters are then applied to the erythema cluster at different scales. A vessel mask is generated as a result of global thresholding. The segmentation sensitivity and specificity of 90% and 86% were achieved on a set of 500 000 manually segmented pixels provided by an expert. To further demonstrate the superiority of the proposed method, based on the segmentation results, we defined and extracted vascular features toward lesion diagnosis in basal cell carcinoma (BCC). Among a dataset of 659 lesions (299 BCC and 360 non-BCC), a set of 12 vascular features are extracted from the final vessel images of the lesions and fed into a random forest classifier. When compared with a few other state-of-art methods, the proposed method achieves the best performance of 96.5% in terms of area under the curve (AUC) in differentiating BCC from benign lesions using only the extracted vascular features.

The prevalence of anxiety and depression in patients with or without hyperhidrosis (HH).

BACKGROUND: There are conflicting data about the correlation between hyperhidrosis (HH) and anxiety and depression. OBJECTIVE: We sought to determine the prevalence of anxiety and depression in patients with or without HH. METHODS: We examined 2017 consecutive dermatology outpatients from Vancouver, British Columbia, Canada, and Shanghai, China, using Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 scales for anxiety and depression assessments. Multivariable logistic regression analysis was performed to evaluate if the impact of HH on anxiety and depression is dependent on demographic factors and diagnoses of the patients' presenting skin conditions. RESULTS: The prevalence of anxiety and depression was 21.3% and 27.2% in patients with HH, respectively, and 7.5% and 9.7% in patients without HH, respectively (P value <.001 for both). There were positive correlations between HH severity and the prevalence of anxiety and depression. Multivariable analysis showed that HH-associated increase in anxiety and depression prevalence is independent of demographic factors and presenting skin conditions. LIMITATION: The data from the questionnaires relied on the accuracy of patients' self-reports. CONCLUSION: Both single variant and multivariable analyses showed a significant association between HH and the prevalence of anxiety and depression in a HH severity-dependent manner.