Severe atopic dermatitis: Dupilumab is not just safer, but more efficient.

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by relapsing eczema and pruritus. Until the development of Dupilumab, a new monoclonal antibody targeting IL-4 and IL-13 receptors, the current treatment of severe cases was based on immunosuppressant agents. Our main goal was to build a case series of five patients with severe atopic dermatitis, who were using immunosuppressive drugs with significant adverse effects and only partially controlled AD, and compare their symptoms, SCORAD index, treatment regimens, total and specific IgE, and blood cell count before and after the introduction of Dupilumab. SCORAD index and topical corticosteroids used on a daily basis had a significant decrease after 16 weeks of Dupilumab. Adverse effects were mild: conjunctivitis, local reaction and regional dermatosis. All patients with severe atopic dermatitis achieved better control of AD with Dupilumab than with immunosuppressive drugs. Adverse effects, secondary infections, total and specific IgE levels were greatly reduced.

Successful treatment of severe atopic dermatitis and alopecia universalis with upadacitinib in a 29-year-old male patient.

A 29-year-old male patient had severe atopic dermatitis (AD) and alopecia universalis (AU) that could not be controlled by using classic therapy. He started taking upadacitinib and achieved an excellent response for both his AD and AU. Thus, upadacitinib represents a promising therapeutic approach for patients with severe AD and alopecia areata.

Medical Expectations of Physicians on AI Solutions in Daily Practice: Cross-Sectional Survey Study.

Background: The use of artificial intelligence (AI) in medicine has been a trending subject in the past few years. Although not frequently used in daily practice yet, it brings along many expectations, doubts, and fears for physicians. Surveys can be used to help understand this situation. Objective: This study aimed to explore the degree of knowledge, expectations, and fears on possible AI use by physicians in daily practice, according to sex and time since graduation. Methods: An electronic survey was sent to physicians of a large hospital in Brazil, from August to September 2022. Results: A total of 164 physicians responded to our survey. Overall, 54.3% (89/164) of physicians considered themselves to have an intermediate knowledge of AI, and 78.5% (128/163) believed that AI should be regulated by a governmental agency. If AI solutions were reliable, fast, and available, 77.9% (127/163) intended to frequently or always use AI for diagnosis (143/164, 87.2%), management (140/164, 85.4%), or exams interpretation (150/164, 91.5%), but their approvals for AI when used by other health professionals (85/163, 52.1%) or directly by patients (82/162, 50.6%) were not as high. The main benefit would be increasing the speed for diagnosis and management (106/163, 61.3%), and the worst issue would be to over rely on AI and lose medical skills (118/163, 72.4%). Physicians believed that AI would be useful (106/163, 65%), facilitate their work (140/153, 91.5%), not alter the number of appointments (80/162, 49.4%), not interfere in their financial gain (94/162, 58%), and not replace their jobs but be an additional source of information (104/162, 64.2%). In case of disagreement between AI and physicians, most (108/159, 67.9%) answered that a third opinion should be requested. Physicians with ≤10 years since graduation would adopt AI solutions more frequently than those with >20 years since graduation (P=.04), and female physicians were more receptive to other hospital staff using AI than male physicians (P=.008). Conclusions: Physicians were shown to have good expectations regarding the use of AI in medicine when they apply it themselves, but not when used by others. They also intend to use it, as long as it was approved by a regulatory agency. Although there was hope for a beneficial impact of AI on health care, it also brings specific concerns.

Hereditary angioedema classification: Expanding knowledge by genotyping and endotyping.

Hereditary angioedema (HAE) encompasses a group of diseases characterized by recurrent, genetically mediated angioedema associated with increased vascular permeability primarily due to bradykinin. The disease poses diagnostic challenges, leading to underdiagnosis and delayed therapy. Severe manifestations include laryngeal and intestinal angioedema, contributing to significant morbidity and mortality. If left undiagnosed, the estimated mortality rate of the disease ranges from 25% to 40% due to asphyxiation caused by laryngeal angioedema. There is a pressing need to enhance awareness of hereditary angioedema and its warning signs. The acronym "H4AE" may facilitate the memorization of these signs. This study comprehensively reviews clinical, laboratory, and physiopathological features of documented HAE subtypes. The study advocates for an improved HAE classification based on endotypes, building on the knowledge of angioedema pathophysiology. The proposed endotype classification of HAE offers a clear and applicable framework, encouraging advancements in disease understanding and classification.

Brazilian Medical Survey on Telemedicine since the onset of COVID-19.

OBJECTIVE: The primary aim of this study was to understand the difference in the use of Telemedicine by Brazilian physicians before and after the onset of COVID-19 pandemic and their intention to continue using it post the pandemic period. The secondary objective was to analyze the differences of opinion between physicians in the private and public sectors. METHODS: We conducted an online medical survey through the SurveyMonkey platform in a large hospital in São Paulo, Brazil, from May to July 2022. RESULTS: Three-hundred-and -two physicians responded to the survey. We found that there was a significant increase in the number of physicians who started using Telemedicine in both the public and private sectors (p<0.0001) since the onset of COVID-19 pandemic and that >50% of them intend to continue using Telemedicine in their daily practice. Most responders consider that Telemedicine is useful in screening, diagnosis and management of patients; that it facilitates the physician's daily practice; that it can maintain or even add financial gains through reducing office expenses; and that is another medium for dispensing medical care. They also believe that Telemedicine should be regulated by the Brazilian Federal Council of Medicine. There were no significant differences between the responses from private and public sector physicians. CONCLUSION: Telemedicine has played a major role in healthcare since the onset of COVID-19 pandemic and most of the physicians approve its use and intend to continue using Telemedicine in their daily practice.

Explainability agreement between dermatologists and five visual explanations techniques in deep neural networks for melanoma AI classification.

Introduction: The use of deep convolutional neural networks for analyzing skin lesion images has shown promising results. The identification of skin cancer by faster and less expensive means can lead to an early diagnosis, saving lives and avoiding treatment costs. However, to implement this technology in a clinical context, it is important for specialists to understand why a certain model makes a prediction; it must be explainable. Explainability techniques can be used to highlight the patterns of interest for a prediction. Methods: Our goal was to test five different techniques: Grad-CAM, Grad-CAM++, Score-CAM, Eigen-CAM, and LIME, to analyze the agreement rate between features highlighted by the visual explanation maps to 3 important clinical criteria for melanoma classification: asymmetry, border irregularity, and color heterogeneity (ABC rule) in 100 melanoma images. Two dermatologists scored the visual maps and the clinical images using a semi-quantitative scale, and the results were compared. They also ranked their preferable techniques. Results: We found that the techniques had different agreement rates and acceptance. In the overall analysis, Grad-CAM showed the best total+partial agreement rate (93.6%), followed by LIME (89.8%), Grad-CAM++ (88.0%), Eigen-CAM (86.4%), and Score-CAM (84.6%). Dermatologists ranked their favorite options: Grad-CAM and Grad-CAM++, followed by Score-CAM, LIME, and Eigen-CAM. Discussion: Saliency maps are one of the few methods that can be used for visual explanations. The evaluation of explainability with humans is ideal to assess the understanding and applicability of these methods. Our results demonstrated that there is a significant agreement between clinical features used by dermatologists to diagnose melanomas and visual explanation techniques, especially Grad-Cam.

Artificial intelligence for skin cancer detection and classification for clinical environment: a systematic review.

Background: Skin cancer is one of the most common forms worldwide, with a significant increase in incidence over the last few decades. Early and accurate detection of this type of cancer can result in better prognoses and less invasive treatments for patients. With advances in Artificial Intelligence (AI), tools have emerged that can facilitate diagnosis and classify dermatological images, complementing traditional clinical assessments and being applicable where there is a shortage of specialists. Its adoption requires analysis of efficacy, safety, and ethical considerations, as well as considering the genetic and ethnic diversity of patients. Objective: The systematic review aims to examine research on the detection, classification, and assessment of skin cancer images in clinical settings. Methods: We conducted a systematic literature search on PubMed, Scopus, Embase, and Web of Science, encompassing studies published until April 4th, 2023. Study selection, data extraction, and critical appraisal were carried out by two independent reviewers. Results were subsequently presented through a narrative synthesis. Results: Through the search, 760 studies were identified in four databases, from which only 18 studies were selected, focusing on developing, implementing, and validating systems to detect, diagnose, and classify skin cancer in clinical settings. This review covers descriptive analysis, data scenarios, data processing and techniques, study results and perspectives, and physician diversity, accessibility, and participation. Conclusion: The application of artificial intelligence in dermatology has the potential to revolutionize early detection of skin cancer. However, it is imperative to validate and collaborate with healthcare professionals to ensure its clinical effectiveness and safety.

Clinical Features of Acne in Primary Care Patients Assessed Through Teledermatology.

INTRODUCTION/OBJECTIVES: Acne is present in about 90% of teenagers and 12% to 14% of adults. Face and trunk are the most affected areas. Lesions can result in postinflammatory hyperpigmentation and scarring, leading to reduced quality of life. Asynchronous teledermatology has been increasingly used around the world, facilitating patient access to dermatologists. Our objectives were to assess: (1) clinical features of acne patients according to gender, age, severity, site of lesions, excoriation, postinflammatory hyperpigmentation (PIH), and atrophic scar (AS) and (2) how many referrals to in-person consultations with dermatologists could be avoided using asynchronous teledermatology in primary care attention? METHODS: We analyzed images, demographic and clinical data of 2459 acne patients assisted by teledermatology, with the aim to confirm the diagnoses, to classify acne severity according to grades I to IV, and to search for the presence of postinflammatory hyperpigmentation, atrophic scars, and/or excoriated acne (EA). We compared the clinical and biological data, looking for associations among them. RESULTS: Acne severity and age were associated with the most common sequels: postinflammatory hyperpigmentation (mainly on the trunk and in females, P < .0001) and atrophic scars (mainly on the face and in males, P < .0001). We also observed different frequencies according to age and sex: 13 to 24 years in males (P = .0023); and <12 (P = .0023) and 25 to 64 years old (P <.0001) for females; 68% of the patients had no need for in-person dermatologists' referral, being kept at primary care attention with proper diagnosis and treatment. CONCLUSION: Clinical features of acne and its sequels differ according to gender, age, site, and severity. The new findings of PIH associated with women and AS, with men, may help offer a more personalized management to patients. Teledermatology was suitable for the majority of the acne cases in primary care.

Diagnosis and treatment of systemic mastocytosis in Brazil: Recommendations of a multidisciplinary expert panel.

INTRODUCTION: Systemic Mastocytosis comprises a group of neoplastic diseases characterized by clonal expansion and infiltration of mast cells into several organs. The diagnosis and treatment of this disease may be challenging for non-specialists. OBJECTIVE: Make suggestions or recommendations in Systemic Mastocytosis based in a panel of Brazilian specialists. METHOD AND RESULTS: An online expert panel with 18 multidisciplinary specialists was convened to propose recommendations on the diagnosis and treatment of Systemic Mastocytosis in Brazil. Recommendations were based on discussions of topics and multiple-choice questions and were graded using the Oxford Centre for Evidence-Based Medicine 2011 Levels of Evidence Chart. CONCLUSION: Twenty-two recommendations or suggestions were proposed based on a literature review and graded according to the findings.

Efficacy and safety of dupilumab in two adolescents with severe atopic dermatitis.

We report the cases of two adolescent siblings with severe atopic dermatitis, who, despite weighing approximately 40kg, presented a good response to dupilumab with the off-label dose for individuals aged 12 years and weighing 60kg. Both had already used cyclosporine, azathioprine, methotrexate and oral corticosteroids for long periods, plus topical treatments with no adequate disease control. Skin lesions were constant and widespread, with frequent skin infections and very poor quality of life, with numerous physical and psychosocial consequences, such as dropping out of school activities due to severe itching, appearance and bullying. They also showed delayed growth and development. In 2018, dupilumab, an immunobiological agent, was approved for treatment of moderate to severe atopic dermatitis in adults and, in 2019, extended to the 12-17-year age group. Although it had already been approved by the Brazilian Health Surveillance Agency, the 200mg presentation (indicated for the weight of patients) was not available, with no expected arrival date. Therefore, weighing the risks and benefits of the situation of both, we chose to treat them with an adult dose (loading dose of 600mg subcutaneously, and 300mg subcutaneously every 2 weeks) despite the low weight. So far, they have received eight injections, showing significant improvement of disease and quality of life. There were no major adverse effects, only worsening of allergic conjunctivitis in one of them. The patients and their family are very satisfied, and we believe that the therapy has been successful.

Accuracy of Deep Neural Network in Triaging Common Skin Diseases of Primary Care Attention.

Access to dermatological care can be challenging in certain regions of the world. The triage process is usually conducted by primary care physicians; however, they may not be able to diagnose and assign the correct referral and level of priority for different dermatosis. The present research aimed to test different deep neural networks to obtain the highest level of accuracy for the following: (1) diagnosing groups of dermatoses; (2) correct referrals; and (3) the level of priority given to the referral compared to dermatologists. Using 140,446 images from a teledermatology project, previously labeled with the clinical diagnosis, and their respective referrals, namely biopsy, in-person dermatologist visits or monitoring the case via teledermatology along with the general physician, 27 different scenarios of neural networks were derived, and the algorithm accuracies in classifying different dermatosis, according to the group of the diagnosis they belong to, were calculated. The most accurate algorithm was then tested for accuracy in diagnosis, referral, and level of priority given to 6,945 cases. The GoogLeNet architecture, trained with 24,000 images and 1,000 epochs, using weight random initialization and learning rates of 10-3 was found to be the most accurate network, showing an accuracy of 89.72% for diagnosis, 96.03% for referrals and 92.54% for priority level in 6,975 image testing. Our study population, however, was confined to individuals with chronic skin conditions and, therefore, it has limited value as a triage tool because it has not been tested for acute conditions. Deep neural networks are accurate in triaging, correct referral and prioritizing common chronic skin diseases related to primary care attention. They can also help health-care systems optimize patients' access to dermatologists.

Dermatologists' perceptions on the utility and limitations of teledermatology after examining 55,000 lesions.

INTRODUCTION: Few studies have assessed the perception of teledermatologists about the utility and limitations of teledermatology, especially to diagnose a broad range of skin diseases. This study aimed to evaluate dermatologists' confidence in teledermatology, its utility and limitations for dermatological conditions in primary care. METHODS: An analytical study that used a survey for dermatologists who diagnosed 30,916 patients with 55,012 lesions through teledermatology during a 1-year project in São Paulo, Brazil. RESULTS: Dermatologists found teledermatology useful for triage and diagnosis, especially for xerotic eczema, pigmentary disorders and superficial infections. Their confidence in teledermatology was statistically higher by the end of the project (p = 0.0012). Limitations included some technical issues and the impossibility to suggest how soon the patient should be assisted face-to-face by a dermatologist. The most treatable group of diseases by teledermatology was superficial infections (92%). The use of dermoscopy images would significantly increase the confidence to treat atypical naevi and malignant tumours (p < 0.0001 and p = 0.0003 respectively). Follow-ups by teledermatology or feedback from primary-care physicians would be desirable, according to the dermatologists. DISCUSSION: We found it interesting that dermatologists became increasingly confident in teledermatology after the project and how they classified teledermatology as useful for triage, diagnosis and even treatment of most types of skin conditions followed at primary care. Dermoscopy should definitely be added to the photographs, especially for malignant tumours and atypical naevi. Most of the technical limitations found could be solved with a few improvements in the software/platform.

Implementation of artificial intelligence algorithms for melanoma screening in a primary care setting.

Skin cancer is currently the most common type of cancer among Caucasians. The increase in life expectancy, along with new diagnostic tools and treatments for skin cancer, has resulted in unprecedented changes in patient care and has generated a great burden on healthcare systems. Early detection of skin tumors is expected to reduce this burden. Artificial intelligence (AI) algorithms that support skin cancer diagnoses have been shown to perform at least as well as dermatologists' diagnoses. Recognizing the need for clinically and economically efficient means of diagnosing skin cancers at early stages in the primary care attention, we developed an efficient computer-aided diagnosis (CAD) system to be used by primary care physicians (PCP). Additionally, we developed a smartphone application with a protocol for data acquisition (i.e., photographs, demographic data and short clinical histories) and AI algorithms for clinical and dermoscopic image classification. For each lesion analyzed, a report is generated, showing the image of the suspected lesion and its respective Heat Map; the predicted probability of the suspected lesion being melanoma or malignant; the probable diagnosis based on that probability; and a suggestion on how the lesion should be managed. The accuracy of the dermoscopy model for melanoma was 89.3%, and for the clinical model, 84.7% with 0.91 and 0.89 sensitivity and 0.89 and 0.83 specificity, respectively. Both models achieved an area under the curve (AUC) above 0.9. Our CAD system can screen skin cancers to guide lesion management by PCPs, especially in the contexts where the access to the dermatologist can be difficult or time consuming. Its use can enable risk stratification of lesions and/or patients and dramatically improve timely access to specialist care for those requiring urgent attention.

Teledermatology reduces dermatology referrals and improves access to specialists.

BACKGROUND: Teledermatology may be used for triage in primary care to address skin conditions, improving access and reducing time to treat the most severe or surgical cases. We aimed to evaluate the proportion of individuals who could be assessed in primary care using teledermatology, and how this affected the waiting time for an in-person dermatologist appointment. METHODS: A cross-sectional retrospective study, involving 30,976 individuals and 55,624 skin lesions, was performed from July 2017 to July 2018 We assessed the frequency of diagnoses and referrals to biopsy, to in-person dermatologists, or to primary care, and compared the waiting time for an in-person dermatologist appointment before and after the teledermatology implementation. FINDINGS: 53% of the patients were managed with the primary care physician, 43% were referred to in-person dermatologists and 4% directly to biopsy, leading to a reduction of 78% in the waiting time for in-person appointments when compared to the previous period. The most frequent diseases were: melanocytic nevus, seborrheic keratosis, acne, benign neoplasms, onychomycosis, atopic dermatitis, solar lentigo, melasma, xerosis, and epidermoid cyst, with significant differences according to sex, age and referrals. The most frequent treatment prescribed was emollient. INTERPRETATION: The use of teledermatology as a triage tool significantly reduced the waiting time for in-person visits, improving health care access and utilizing public resources wisely. Knowledge of sex, age, diagnoses and treatment of common skin conditions can enable public policies for the prevention and orientation of the population, as it can be used to train general physicians to address such cases. FUNDING: None.

Part I: Accuracy of Teledermatology in Inflammatory Dermatoses.

Teledermatology is assuming a progressively greater role as a healthcare delivery method, especially now, during this pandemic time. It is important to know how accurate this tool is for different skin diseases. Most of the studies have focused on skin neoplasms or general dermatology. Studies based on a large number of inflammatory dermatoses have not yet been performed. Such knowledge can help dermatologists to decide whether endorsing this method or not. Our objective was to determine the accuracy of teledermatology in inflammatory dermatoses in a robust number of cases. A retrospective cohort study was conducted in São Paulo, Brazil, from July 2017-18, where a store-and-forward Teledermatology project was implemented under primary-care attention to triage surgical, more complex, or severe dermatoses. A total of 30,976 patients presenting 55,012 lesions took part in the project. Thirteen participating teledermatologists had three options to refer the patients: directly to biopsy, to the in-person dermatologist or back to the general physician with most probable diagnosis and management. In the group referred to the in-person dermatologist, we looked for the 20 most frequent International Classification of Diseases and Related Health Problems- 10th revision (ICD-10) of inflammatory dermatoses, which resulted in 739 patients and 739 lesions. As patients had been triaged by teledermatology previously, we were able to compare ICD-10 codes filled both by teledermatogists and by in-person dermatologists. The proportion of complete, partial, and no agreement rates between the in-person dermatologist's and the teledermatologist's diagnoses was used for accuracy. We also calculated Cohen's kappa, a statistical measure of inter-rater agreement, for complete agreement. The mean complete agreement rate for all twenty dermatoses was 78% (31-100%) and kappa = 0.743; partial agreement 8%; and no agreement 14%, presenting variability according to the disease. Our study showed that teledermatology for inflammatory dermatoses has a high accuracy. This result reassures that it can be a proper option for patient care.

Accuracy and efficiency of telemedicine in atopic dermatitis.

BACKGROUND: Telemedicine provides accurate diagnoses for skin disorders and has gained emphasis. It may be used for the triage and management of common skin diseases in primary care, improving patients' access and reducing time to treatment. OBJECTIVE: To evaluate the proportion of atopic dermatitis patients who could be managed with the support of telemedicine and its accuracy. Second, we aimed to assess the frequency of atopic dermatitis, demographics, clinical features, and therapies dispensed in relation to the disease. METHODS: Retrospective study in a population of 30,976 individuals, assisted by telemedicine. We assessed patients with the diagnosis of atopic dermatitis and evaluated the proportion of cases referred to biopsy, in-person dermatologists, or to be managed by primary care; the treatments suggested; and telemedicine accuracy to diagnose atopic dermatitis. RESULTS: Atopic dermatitis was diagnosed in 1648 patients (5.3%), the sixth most common dermatosis, with 2058 lesions (3.7%) analyzed. Primary care physicians were able to manage 72% of the atopic dermatitis patients, whereas 28% of them were referred to in-person dermatologists. Accuracy for atopic dermatitis diagnosis was 84.4%. CONCLUSION: Telemedicine was an accurate method and helped primary care physicians to treat 72% of the atopic dermatitis lesions, thereby optimizing the availability of in-person appointments with dermatologists for more severe cases.

Part II: Accuracy of Teledermatology in Skin Neoplasms.

Teledermatology has been proving to be of great help for delivering healthcare, especially now, during the SARS-CoV-2 pandemic. It is crucial to assess how accurate this method can be for evaluating different dermatoses. Such knowledge can contribute to the dermatologists' decision of whether to adhere to teledermatology or not. Our objective was to determine the accuracy of teledermatology in the 10 most frequent skin neoplasms in our population, comparing telediagnosis to histopathological report and in-person dermatologists' diagnosis. A retrospective cohort study was conducted in São Paulo, Brazil, where a store-and-forward teledermatology project was implemented under primary-care attention to triage surgical, more complex, or severe dermatoses. A total of 30,976 patients presenting 55,012 lesions took part in the project. Thirteen teledermatologists who participated in the project had three options to refer the patients: send them directly to biopsy, to the in-person dermatologist, or back to the general physician with the most probable diagnosis and management. In the groups referred to the in-person dermatologist and biopsy, we looked for the 10 most frequent International Statistical Classification of Diseases and Related Health Problems-10 (ICD-10) of skin neoplasms, which resulted in 289 histopathologic reports and 803 in-person dermatologists' diagnosis. We were able to compare the ICD-10 codes filled by teledermatologists, in-person dermatologists, and from histopathological reports. The proportion of complete, partial, and no agreement rates between the in-person dermatologist's, histopathologic report, and the teledermatologist's diagnosis was assessed. We also calculated Cohen's kappa, for complete and complete plus partial agreement. The mean complete agreement rate comparing telediagnosis to histopathological report was 54% (157/289; kappa = 0.087), being the highest for malign lesions; to in-person dermatologists was 61% (487/803; kappa = 0.213), highest for benign lesions. When accuracy of telediagnosis for either malign or benign lesions was evaluated, the agreement rate with histopathology was 70% (kappa = 0.529) and with in-person dermatologist, 81% (kappa = 0.582). This study supports that teledermatology for skin neoplasms has moderate accuracy. This result reassures that it can be a proper option for patient care, especially when the goal is to differentiate benign from malign lesions.

Nodular primary cutaneous melanoma is associated with PD-L1 expression.

BACKGROUND: In previous studies, patients with Stage III melanomas expressing PD-L1 in more than 5% of their neoplastic cells had improved recurrence-free survival with anti-PD1 adjuvant therapy. OBJECTIVES: We examined PD-L1 expression as a possible biomarker of primary cutaneous melanomas in the vertical growth phase. MATERIALS AND METHODS: This was a retrospective study including 66 patients with invasive primary cutaneous melanomas. We assessed patient clinical and histopathological data and performed immunohistochemical assays with melanoma specimens from the patients to evaluate PD-L1, PD-1, CD3, CD8 and FoxP3 expression. RESULTS: We observed PD-L1 expression in 21% (14/66) of our samples, and this expression correlated with increased melanoma thickness (p = 0.002) and nodular-type melanoma (p = 0.001). After adjusting for tumor thickness using a logistic regression test, the association of PD-L1 with nodular-type melanoma persisted. Nodular-type melanoma was 6.48 times more likely to be positive for PD-L1 than other histological types (p = 0.014; 95% CI: 1.46-28.82). As expected, PD-L1 expression correlated with the number of PD-1-expressing cells in the tumor-infiltrating lymphocyte population (p = 0.04). No correlation with PD-L1 was observed for age, sex, tumor site, skin phototype, ulceration status, sentinel lymph node status, metastasis development or survival. Regarding the immune profile of the tumor-infiltrating lymphocytes of PD-L1-positive and -negative groups, no significant differences were observed in the numbers of CD3 + , CD8 + FoxP3-, CD8-FoxP3+ and CD8 + FoxP3+ cells by immunohistochemistry. CONCLUSION: Nodular-type melanoma is associated with PD-L1 expression and may be a suitable candidate for adjuvant therapy of primary melanomas treated with immunotherapy.

Worse survival of invasive melanoma patients in men and "de novo" lesions.

BACKGROUND: The incidence and mortality of melanoma is increasing in many countries, including Brazil. Survival studies are still scarce in our country, but much needed to know and address this problem better. OBJECTIVE: To analyze the disease-specific survival of patients with invasive melanoma and to correlate it with clinical and histopathological variables. METHODS: Retrospective cohort analysis of 565 cases of invasive melanoma in a tertiary hospital with the objective of testing variables that could be associated with a worse prognosis, such as gender, phototype, thickness, histological type and presence of pre-existing clinical lesion at the site of the tumor. RESULTS: The worst survival rates were significantly associated with thicker tumors (p<0.001), male sex (p=0.014), high phototype (p=0.047), nodular melanoma (p=0.024) and "de novo" lesions (p=0.005). When all variables were adjusted for melanoma thickness, male patients (p=0.011) and "de novo" melanomas (p=0.025) remained associated with worse survival. STUDY LIMITATIONS: Retrospective study of a single tertiary hospital. CONCLUSIONS: Although the causes are still unknown, melanoma-specific survival was statistically worse for males and for "de novo" melanomas even after adjustment of tumor thickness.