Different mutational profiles of subcutaneous panniculitis-like T-cell lymphoma and lupus panniculitis: an additional case series.

BACKGROUND AND OBJECTIVE: subcutaneous panniculitis-like T-cell lymphoma (SPTCL) is a rare cytotoxic T-cell lymphoma with indolent behavior, mostly present in women and associated with immunological diseases whose pathogenic background is still poorly understood. SPTCL is associated with lupus erythematosus panniculitis (LEP) and histologically misdiagnosed. OBJECTIVES: the aim of our study was to identify mutations affecting the pathogenesis of both SPTCL and LEP. MATERIALS AND METHODS: we studied a total of 10 SPTCL and 10 LEP patients using targeted Next Generation Sequencing and pyrosequencing. Differences in gene expression between molecular subgroups were investigated using NanoString technology. Clinical data were collected, and correlations sought with the molecular data obtained. RESULTS: the mutational profile of SPTCL and LEP is different. We identified fewer pathogenic mutations than previously reported in SPTCL, noting a single HAVCR2-mutated SPTCL case. Interestingly, 40% of our SPTCL cases showed the pathogenic TP53 (p.Pro72Arg) (P72R) variant. Although cases showing HAVCR2 mutations or the TP53 (P72R) variant had more severe symptomatic disease, none developed hemophagocytic syndrome (HPS). Furthermore, TP53 (P72R)-positive cases were characterized by a lower metabolic signaling pathway and higher levels of CD28 expression and Treg signaling genes. In addition, 30% of our cases featured the same mutation (T735C) of the epigenetic modificatory gene DNMT3A. None of the LEP cases showed mutations in any of the studied genes. CONCLUSIONS: the mutational landscape of SPTCL is broader than previously anticipated. We describe, for the first time, the involvement of the TP53 (P72R) pathogenic variant in this subgroup of tumors, consider the possible role of different genetic backgrounds in the development of SPTCL, and conclude that LEP does not follow the same pathogenic pathway as SPTCL.

Cutaneous reactions after SARS-CoV-2 vaccination: a cross-sectional Spanish nationwide study of 405 cases.

BACKGROUND: Cutaneous reactions after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines are poorly characterized. OBJECTIVE: To describe and classify cutaneous reactions after SARS-CoV-2 vaccination. METHODS: A nationwide Spanish cross-sectional study was conducted. We included patients with cutaneous reactions within 21 days of any dose of the approved vaccines at the time of the study. After a face-to-face visit with a dermatologist, information on cutaneous reactions was collected via an online professional survey and clinical photographs were sent by email. Investigators searched for consensus on clinical patterns and classification. RESULTS: From 16 February to 15 May 2021, we collected 405 reactions after vaccination with the BNT162b2 (Pfizer-BioNTech; 40·2%), mRNA-1273 (Moderna; 36·3%) and AZD1222 (AstraZeneca; 23·5%) vaccines. Mean patient age was 50·7 years and 80·2% were female. Cutaneous reactions were classified as injection site ('COVID arm', 32·1%), urticaria (14·6%), morbilliform (8·9%), papulovesicular (6·4%), pityriasis rosea-like (4·9%) and purpuric (4%) reactions. Varicella zoster and herpes simplex virus reactivations accounted for 13·8% of reactions. The COVID arm was almost exclusive to women (95·4%). The most reported reactions in each vaccine group were COVID arm (mRNA-1273, Moderna, 61·9%), varicella zoster virus reactivation (BNT162b2, Pfizer-BioNTech, 17·2%) and urticaria (AZD1222, AstraZeneca, 21·1%). Most reactions to the mRNA-1273 (Moderna) vaccine were described in women (90·5%). Eighty reactions (21%) were classified as severe/very severe and 81% required treatment. CONCLUSIONS: Cutaneous reactions after SARS-CoV-2 vaccination are heterogeneous. Most are mild-to-moderate and self-limiting, although severe/very severe reactions are reported. Knowledge of these reactions during mass vaccination may help healthcare professionals and reassure patients.

Melanoma in Solid Organ Transplant Recipients. / Melanoma en pacientes receptores de un trasplante de órgano sólido.

In this review, we analyze the 3 clinical scenarios related to the development of melanoma in solid organ transplant recipients: melanoma in patients with a history of the tumor prior to a transplant, de novo melanoma following a transplant, and melanoma of donor origin. The main factors to consider in organ-transplant candidates with a history of melanoma are tumor stage, presence or absence of residual disease, and time from diagnosis to transplantation. Solid organ transplant recipients have a greater risk of melanoma than immunocompetent individuals. Mortality is also higher in this population, especially in patients with advanced melanoma, as treatment is especially challenging. Clinical history and physical examination provide the most useful information for preventing donor-to-recipient transmission of melanoma. Donor-derived melanoma has a very poor prognosis.

Uso del aprendizaje automático en el diagnóstico del melanoma. Limitaciones por superar / Machine Learning in Melanoma Diagnosis. Limitations About to be Overcome

ANTECEDENTES: La clasificación automática de imágenes es una rama prometedora del aprendizaje automático (de sus siglas en inglés Machine Learning [ML]), y es una herramienta útil en el diagnóstico de cáncer de piel. Sin embargo, poco se ha estudiado acerca de las limitaciones de su uso en la práctica clínica diaria. OBJETIVO: Determinar las limitaciones que existen en cuanto a la selección de imágenes usadas para el análisis por ML de las neoplasias cutáneas, en particular del melanoma. MÉTODOS: Se diseñó un estudio de cohorte retrospectivo, donde se incluyeron de forma consecutiva 2.849 imágenes dermatoscópicas de alta calidad de tumores cutáneos para su valoración por un sistema de ML, recogidas entre los años 2010 y 2014. Cada imagen dermatoscópica fue clasificada según las características de elegibilidad para el análisis por ML. RESULTADOS: De las 2.849 imágenes elegidas a partir de nuestra base de datos, 968 (34%) cumplieron los criterios de inclusión. De los 528 melanomas, 335 (63,4%) fueron excluidos. La ausencia de piel normal circundante (40,5% de todos los melanomas de nuestra base de datos) y la ausencia de pigmentación (14,2%) fueron las causas más frecuentes de exclusión para el análisis por ML. DISCUSIÓN: Solo el 36,6% de nuestros melanomas se consideraron aceptables para el análisis por sistemas de ML de última generación. Concluimos que los futuros sistemas de ML deberán ser entrenados a partir de bases de datos más grandes que incluyan imágenes representativas de la práctica clínica habitual. Afortunadamente, muchas de estas limitaciones están siendo superadas gracias a los avances realizados recientemente por la comunidad científica, como se ha demostrado en trabajos recientes

BACKGROUND: Automated image classification is a promising branch of machine learning (ML) useful for skin cancer diagnosis, but little has been determined about its limitations for general usability in current clinical practice. OBJECTIVE: To determine limitations in the selection of skin cancer images for ML analysis, particularly in melanoma. METHODS: Retrospective cohort study design, including 2,849 consecutive high-quality dermoscopy images of skin tumors from 2010 to 2014, for evaluation by a ML system. Each dermoscopy image was assorted according to its eligibility for ML analysis. RESULTS: Of the 2,849 images chosen from our database, 968 (34%) met the inclusion criteria for analysis by the ML system. Only 64.7% of nevi and 36.6% of melanoma met the inclusion criteria. Of the 528 melanomas, 335 (63.4%) were excluded. An absence of normal surrounding skin (40.5% of all melanomas from our database) and absence of pigmentation (14.2%) were the most common reasons for exclusion from ML analysis. DISCUSSION: Only 36.6% of our melanomas were admissible for analysis by state-of-the-art ML systems. We conclude that future ML systems should be trained on larger datasets which include relevant non-ideal images from lesions evaluated in real clinical practice. Fortunately, many of these limitations are being overcome by the scientific community as recent works show

Classification of the cutaneous manifestations of COVID-19: a rapid prospective nationwide consensus study in Spain with 375 cases.

BACKGROUND: The cutaneous manifestations of COVID-19 disease are poorly characterized. OBJECTIVES: To describe the cutaneous manifestations of COVID-19 disease and to relate them to other clinical findings. METHODS: We carried out a nationwide case collection survey of images and clinical data. Using a consensus we described five clinical patterns. We later described the association of these patterns with patient demographics, the timing in relation to symptoms of the disease, the severity and the prognosis. RESULTS: The lesions may be classified as acral areas of erythema with vesicles or pustules (pseudo-chilblain) (19%), other vesicular eruptions (9%), urticarial lesions (19%), maculopapular eruptions (47%) and livedo or necrosis (6%). Vesicular eruptions appear early in the course of the disease (15% before other symptoms). The pseudo-chilblain pattern frequently appears late in the evolution of the COVID-19 disease (59% after other symptoms), while the rest tend to appear with other symptoms of COVID-19. The severity of COVID-19 shows a gradient from less severe disease in acral lesions to more severe in the latter groups. The results are similar for confirmed and suspected cases, in terms of both clinical and epidemiological findings. Alternative diagnoses are discussed but seem unlikely for the most specific patterns (pseudo-chilblain and vesicular). CONCLUSIONS: We provide a description of the cutaneous manifestations associated with COVID-19 infection. These may help clinicians approach patients with the disease and recognize cases presenting with few symptoms. What is already known about this topic? Previous descriptions of cutaneous manifestations of COVID-19 were case reports and mostly lacked illustrations. What does this study add? We describe a large, representative sample of patients with unexplained skin manifestations and a diagnosis of COVID-19, using a consensus method to define morphological patterns associated with COVID-19. We describe five clinical patterns associated with different patient demographics, timing and prognosis, and provide illustrations of these patterns to allow for easy recognition.

Machine Learning in Melanoma Diagnosis. Limitations About to be Overcome. / Uso del aprendizaje automático en el diagnóstico del melanoma. Limitaciones por superar.

BACKGROUND: Automated image classification is a promising branch of machine learning (ML) useful for skin cancer diagnosis, but little has been determined about its limitations for general usability in current clinical practice. OBJECTIVE: To determine limitations in the selection of skin cancer images for ML analysis, particularly in melanoma. METHODS: Retrospective cohort study design, including 2,849 consecutive high-quality dermoscopy images of skin tumors from 2010 to 2014, for evaluation by a ML system. Each dermoscopy image was assorted according to its eligibility for ML analysis. RESULTS: Of the 2,849 images chosen from our database, 968 (34%) met the inclusion criteria for analysis by the ML system. Only 64.7% of nevi and 36.6% of melanoma met the inclusion criteria. Of the 528 melanomas, 335 (63.4%) were excluded. An absence of normal surrounding skin (40.5% of all melanomas from our database) and absence of pigmentation (14.2%) were the most common reasons for exclusion from ML analysis. DISCUSSION: Only 36.6% of our melanomas were admissible for analysis by state-of-the-art ML systems. We conclude that future ML systems should be trained on larger datasets which include relevant non-ideal images from lesions evaluated in real clinical practice. Fortunately, many of these limitations are being overcome by the scientific community as recent works show.

Análisis de la proporción de derivaciones potencialmente evitables desde Atención Primaria a Dermatología por lesiones quísticas o tumorales benignas en España. Datos del estudio DIADERM / Proportion of Potentially Avoidable Referrals From Primary Care to Dermatologists for Cystic Lesions or Benign Neoplasms in Spain: Analysis of Data From the DIADERM Study

Antecedentes y objetivo: Las lesiones cutáneas constituyen un motivo de consulta frecuente en Atención Primaria (AP). Aquellas que no supongan un problema de salud, sino una cuestión estética, no deben ser tratadas en el Sistema Nacional de Salud, según la legislación vigente. El objetivo de este trabajo es estimar qué porcentaje de derivaciones remitidas desde AP a Dermatología por lesiones quísticas o tumores benignos corresponde a lesiones que podríamos considerar potencialmente evitables. Material y método: Utilizamos los diagnósticos principales de los pacientes derivados de AP, recogidos en el estudio representativo nacional DIADERM. Cada uno de los diagnósticos derivados fue clasificado como potencialmente evitable si se correspondía con alguno de los diagnósticos con criterio de alta desde AP, establecidos en el documento de consenso propuesto por la sección territorial andaluza de la Academia Española de Dermatología y Venereología. Resultados: Se recogieron datos de 2.171 motivos principales de consulta derivados de AP como primeras consultas. De estos, 686 (31,6%) son diagnósticos que podrían corresponderse con derivaciones potencialmente evitables por lesiones quísticas o tumorales benignas. Un 22% (478) del total de las consultas fueron dadas de alta en la primera visita. Los diagnósticos más frecuentes entre estos fueron las queratosis seborreicas (9,3%) y los nevus melanocíticos (8,6%). Conclusiones: La proporción de derivaciones potencialmente evitables a Dermatología desde AP por lesiones quísticas y tumorales benignas supone casi un tercio de las consultas. El conocimiento de la realidad asistencial de nuestro entorno puede ser útil para mejorar la planificación, la formación y la gestión sanitaria

Background and objective: Skin lesions are a common reason for consulting a primary care physician. Current legislation in Spain states that purely aesthetic skin problems that do not pose a health problem are not to be treated within the National Health Service. The aim of this study was to estimate the proportion of referrals from primary care physicians to dermatologists that were for cystic lesions or benign tumors and could potentially have been avoided. Material and methods: We consulted cases registered in the DIADERM study dataset, which is representative of dermatology practice in Spain, and collected the main diagnoses given on referring patients from primary care. A referral diagnosis was classified as potentially avoidable if it corresponded to one of the primary care discharge diagnoses listed in a consensus paper of the Andalusian section of the Spanish Academy of Dermatology and Venereology (AEDV). Results: We collected 2171 main reasons for first-visit referrals to dermatologists; 686 of them (31.6%) were for cystic lesions or benign tumors and classified as potentially avoidable. In 478 cases (22%) the patients were discharged on the first visit. The most frequent diagnoses in such cases were seborrheic keratosis (9.3%) and melanocytic nevus (8.6%). Conclusions: Nearly a third of referrals from primary care to a dermatologist were for cystic lesions and benign tumors and could have been avoided. A clearer understanding of our caseload can be useful for improving planning, training, and health care system management

Pápulas faciales induradas / Indurated Papules on the Face

No disponible

Proportion of Potentially Avoidable Referrals From Primary Care to Dermatologists for Cystic Lesions or Benign Neoplasms in Spain: Analysis of Data From the DIADERM Study. / Análisis de la proporción de derivaciones potencialmente evitables desde Atención Primaria a Dermatología por lesiones quísticas o tumorales benignas en España. Datos del estudio DIADERM.

BACKGROUND AND OBJECTIVE: Skin lesions are a common reason for consulting a primary care physician. Current legislation in Spain states that purely aesthetic skin problems that do not pose a health problem are not to be treated within the National Health Service. The aim of this study was to estimate the proportion of referrals from primary care physicians to dermatologists that were for cystic lesions or benign tumors and could potentially have been avoided. MATERIAL AND METHODS: We consulted cases registered in the DIADERM study dataset, which is representative of dermatology practice in Spain, and collected the main diagnoses given on referring patients from primary care. A referral diagnosis was classified as potentially avoidable if it corresponded to one of the primary care discharge diagnoses listed in a consensus paper of the Andalusian section of the Spanish Academy of Dermatology and Venereology (AEDV). RESULTS: We collected 2171 main reasons for first-visit referrals to dermatologists; 686 of them (31.6%) were for cystic lesions or benign tumors and classified as potentially avoidable. In 478 cases (22%) the patients were discharged on the first visit. The most frequent diagnoses in such cases were seborrheic keratosis (9.3%) and melanocytic nevus (8.6%). CONCLUSIONS: Nearly a third of referrals from primary care to a dermatologist were for cystic lesions and benign tumors and could have been avoided. A clearer understanding of our caseload can be useful for improving planning, training, and health care system management.