Part 2: Management of Intraoperative and Perioperative Bleeding.

With an increase in number of patients on antithrombotic therapies, management of bleeding during dermatologic surgery is increasingly important. As described in Part 1, perioperative discontinuation of antithrombotic therapies may increase the risk of embolic events thus the risks and benefits must be weighed carefully when deciding whether to continue or suspend therapy. However, continuing oral anticoagulants may result in increased intraoperative and postoperative bleeding. Here we describe various methods to effectively achieve hemostasis which include: 1) mechanical methods to compress the vasculature 2) pharmacologic agents that induce vasoconstriction 3) physiologic agents that augment clot formation and 4) physical agents that promote platelet aggregation.

Current status of artificial intelligence methods for skin cancer survival analysis: a scoping review.

Skin cancer mortality rates continue to rise, and survival analysis is increasingly needed to understand who is at risk and what interventions improve outcomes. However, current statistical methods are limited by inability to synthesize multiple data types, such as patient genetics, clinical history, demographics, and pathology and reveal significant multimodal relationships through predictive algorithms. Advances in computing power and data science enabled the rise of artificial intelligence (AI), which synthesizes vast amounts of data and applies algorithms that enable personalized diagnostic approaches. Here, we analyze AI methods used in skin cancer survival analysis, focusing on supervised learning, unsupervised learning, deep learning, and natural language processing. We illustrate strengths and weaknesses of these approaches with examples. Our PubMed search yielded 14 publications meeting inclusion criteria for this scoping review. Most publications focused on melanoma, particularly histopathologic interpretation with deep learning. Such concentration on a single type of skin cancer amid increasing focus on deep learning highlight growing areas for innovation; however, it also demonstrates opportunity for additional analysis that addresses other types of cutaneous malignancies and expands the scope of prognostication to combine both genetic, histopathologic, and clinical data. Moreover, researchers may leverage multiple AI methods for enhanced benefit in analyses. Expanding AI to this arena may enable improved survival analysis, targeted treatments, and outcomes.

From Molecules to Microbes: Tracing Cutaneous T-Cell Lymphoma Pathogenesis through Malignant Inflammation.

The etiology of CTCL is a subject of extensive investigation. Researchers have explored links between CTCL and environmental chemical exposures, such as aromatic hydrocarbons (eg, pesticides and benzene), as well as infectious factors, including various viruses (eg, human T-lymphotropic virus [HTLV]-I and HTLV-II) and bacteria (eg, Staphylococcus aureus). There has been growing emphasis on the role of malignant inflammation in CTCL development. In this review, we synthesize studies of environmental and infectious exposures, along with research on the aryl hydrocarbon receptor and the involvement of pathogens in disease etiology, providing insight into the pathogenesis of CTCL.

Assessing outcomes of topical 5-fluorouracil as primary and adjuvant therapy for squamous cell carcinoma in-situ.

Cutaneous squamous cell carcinoma in-situ (SCCis) is an intraepithelial tumor with a good prognosis. Standard treatment includes both surgical and non-surgical interventions. We determined the clearance rate for SCCis and residual SCCis identified on frozen section during Mohs micrographic surgery (MMS) after treatment with topical fluorouracil 5% cream (5-FU). All MMS cases were initiated for biopsy-proven invasive squamous cell carcinoma (SCC). A retrospective chart review was conducted from January 2017-February 2024 at Columbia University Irving Medical Center (CUIMC) to identify patients with SCCis who were treated with topical 5-FU as primary therapy or adjuvant therapy (AT) for residual SCCis post-MMS for invasive SCC. 41 patients were included (80% males, 70.1 ± 11.8 years). The average follow-up time for the primary therapy group was 25.4 ± 12.8 months, and for the post-MMS AT group 22.5 ± 11.1 months. In the group treated with topical 5-FU as primary therapy (n = 28), 27 patients (96.43%, 95% confidence interval: 81.65-99.91%) achieved complete clearance. One patient had recurrence at 8 months post-treatment. Of the patients in the post-MMS adjuvant treatment group (n = 13), 12 (92.3% clearance, 95% confidence interval 63.97-99.81%) achieved complete clearance. One patient had recurrence at 8 months post-treatment. This study found that topical 5-FU cream is effective as both primary therapy for SCCis and as adjuvant therapy for residual SCCis following MMS of invasive SCC.

Criteria2Query 3.0: Leveraging generative large language models for clinical trial eligibility query generation.

OBJECTIVE: Automated identification of eligible patients is a bottleneck of clinical research. We propose Criteria2Query (C2Q) 3.0, a system that leverages GPT-4 for the semi-automatic transformation of clinical trial eligibility criteria text into executable clinical database queries. MATERIALS AND METHODS: C2Q 3.0 integrated three GPT-4 prompts for concept extraction, SQL query generation, and reasoning. Each prompt was designed and evaluated separately. The concept extraction prompt was benchmarked against manual annotations from 20 clinical trials by two evaluators, who later also measured SQL generation accuracy and identified errors in GPT-generated SQL queries from 5 clinical trials. The reasoning prompt was assessed by three evaluators on four metrics: readability, correctness, coherence, and usefulness, using corrected SQL queries and an open-ended feedback questionnaire. RESULTS: Out of 518 concepts from 20 clinical trials, GPT-4 achieved an F1-score of 0.891 in concept extraction. For SQL generation, 29 errors spanning seven categories were detected, with logic errors being the most common (n = 10; 34.48 %). Reasoning evaluations yielded a high coherence rating, with the mean score being 4.70 but relatively lower readability, with a mean of 3.95. Mean scores of correctness and usefulness were identified as 3.97 and 4.37, respectively. CONCLUSION: GPT-4 significantly improves the accuracy of extracting clinical trial eligibility criteria concepts in C2Q 3.0. Continued research is warranted to ensure the reliability of large language models.

Part 1: Management of Antithrombotic Medications in Dermatologic Surgery.

Perioperative management of antithrombotic agents requires practical and medical considerations. Discontinuing antithrombotic therapies increases the risk of thrombotic adverse events including cerebrovascular accidents, myocardial infarction, pulmonary embolism, deep vein thrombosis, and retinal artery occlusion. Conversely, continuation of antithrombotic therapy during surgical procedures has associated bleeding risks. Currently, no guidelines exist regarding management of antithrombotic agents in the perioperative period for cutaneous surgeries and practice differs by surgeon. Here, we review the data on antithrombotic medications in patients undergoing cutaneous surgery including medication-specific surgical and postoperative bleeding risk if the medications are continued, and thromboembolic risk if the medications are interrupted. Specifically, we focus on vitamin K antagonist (VKA) (warfarin), direct-acting oral anticoagulants (DOAC) (rivaroxaban, apixaban, edoxaban, dabigatran), antiplatelet medications (aspirin, clopidogrel, prasugrel, ticagrelor, dipyridamole), unfractionated heparin, low molecular weight heparin (enoxaparin and dalteparin), fondaparinux, bruton tyrosine kinase inhibitors (BTKi) (ibrutinib, acalabrutinib), and dietary supplements (i.e., garlic, ginger, gingko).

Gammopathic dermopathy: characterization of cutaneous MGUS.

Monoclonal Gammopathy of Undetermined Significance (MGUS) is a clonal plasma cell disorder that is considered preneoplastic, asymptomatic, and only requiring observation. However, MGUS may result in cutaneous complications, which are poorly understood, causing treatment delays and patient suffering. We present 30 patients with cutaneous findings associated with MGUS, characterizing clinical presentations, isoforms, treatments, and outcomes. These included: MGUS-associated 'rashes' (pruritic eczematous rashes), reactive and mucin-depositional conditions (pyoderma gangrenosum, scleromyxedema), M-protein-related deposition disorders (POEMS syndrome, Waldenstrom macroglobulinemia), and cutaneous lymphomas. Twelve of 30 (40%) patients received multiple myeloma drugs (MMDs). Eleven (92%) patients improved, and those not receiving MMDs rarely improved, suggesting that MMDs have efficacy for cutaneous manifestations of MGUS. Therefore, trialing MMDs may be warranted for patients with MGUS not responding to other therapies. Moreover, evaluation for monoclonal gammopathy in elderly patients with intractable pruritus or other chronic skin conditions that are non-responsive to skin-directed therapies should be considered.

A Survey of Clinicians' Views of the Utility of Large Language Models.

OBJECTIVES: Large language models (LLMs) like Generative pre-trained transformer (ChatGPT) are powerful algorithms that have been shown to produce human-like text from input data. Several potential clinical applications of this technology have been proposed and evaluated by biomedical informatics experts. However, few have surveyed health care providers for their opinions about whether the technology is fit for use. METHODS: We distributed a validated mixed-methods survey to gauge practicing clinicians' comfort with LLMs for a breadth of tasks in clinical practice, research, and education, which were selected from the literature. RESULTS: A total of 30 clinicians fully completed the survey. Of the 23 tasks, 16 were rated positively by more than 50% of the respondents. Based on our qualitative analysis, health care providers considered LLMs to have excellent synthesis skills and efficiency. However, our respondents had concerns that LLMs could generate false information and propagate training data bias.Our survey respondents were most comfortable with scenarios that allow LLMs to function in an assistive role, like a physician extender or trainee. CONCLUSION: In a mixed-methods survey of clinicians about LLM use, health care providers were encouraging of having LLMs in health care for many tasks, and especially in assistive roles. There is a need for continued human-centered development of both LLMs and artificial intelligence in general.

Ethical considerations for artificial intelligence in dermatology: a scoping review.

The field of dermatology is experiencing the rapid deployment of artificial intelligence (AI), from mobile applications (apps) for skin cancer detection to large language models like ChatGPT that can answer generalist or specialist questions about skin diagnoses. With these new applications, ethical concerns have emerged. In this scoping review, we aimed to identify the applications of AI to the field of dermatology and to understand their ethical implications. We used a multifaceted search approach, searching PubMed, MEDLINE, Cochrane Library and Google Scholar for primary literature, following the PRISMA Extension for Scoping Reviews guidance. Our advanced query included terms related to dermatology, AI and ethical considerations. Our search yielded 202 papers. After initial screening, 68 studies were included. Thirty-two were related to clinical image analysis and raised ethical concerns for misdiagnosis, data security, privacy violations and replacement of dermatologist jobs. Seventeen discussed limited skin of colour representation in datasets leading to potential misdiagnosis in the general population. Nine articles about teledermatology raised ethical concerns, including the exacerbation of health disparities, lack of standardized regulations, informed consent for AI use and privacy challenges. Seven addressed inaccuracies in the responses of large language models. Seven examined attitudes toward and trust in AI, with most patients requesting supplemental assessment by a physician to ensure reliability and accountability. Benefits of AI integration into clinical practice include increased patient access, improved clinical decision-making, efficiency and many others. However, safeguards must be put in place to ensure the ethical application of AI.

The use of artificial intelligence (AI) in dermatology is rapidly increasing, with applications in dermatopathology, medical dermatology, cutaneous surgery, microscopy/spectroscopy and the identification of prognostic biomarkers (characteristics that provide information on likely patient health outcomes). However, with the rise of AI in dermatology, ethical concerns have emerged. We reviewed the existing literature to identify applications of AI in the field of dermatology and understand the ethical implications. Our search initially identified 202 papers, and after we went through them (screening), 68 were included in our review. We found that ethical concerns are related to the use of AI in the areas of clinical image analysis, teledermatology, natural language processing models, privacy, skin of colour representation, and patient and provider attitudes toward AI. We identified nine ethical principles to facilitate the safe use of AI in dermatology. These ethical principles include fairness, inclusivity, transparency, accountability, security, privacy, reliability, informed consent and conflict of interest. Although there are many benefits of integrating AI into clinical practice, our findings highlight how safeguards must be put in place to reduce rising ethical concerns.

Cutaneous lymphoproliferative disorders after COVID-19 vaccination: clinical presentation, histopathology, and outcomes.

Individual reports described lymphoproliferative disorders (LPDs) after COVID-19 vaccination; however, the relationship between cases is unexamined. We aim to determine if there are cases of cutaneous LPDs associated with COVID-19 vaccination and their outcomes. We present a review of world literature, vaccine registries, and two unreported cases of LPDs after COVID-19 vaccination. Review of the medical literature, VAERS, and our two cases reveal predominance of Pfizer-BioNTech vaccine, younger patients, and males. All cases resulted in favorable outcomes. Approximately 84% of cases demonstrated CD30+ positivity in their skin biopsies, suggesting that an antigenic trigger may lead to a type IV adaptive immune response, with clonal expansion of CD30+ T-cells and subsequent oncogenic mutational hits eventuating in transient LPDs. LPDs after COVID-19 vaccination appear in the context of the same vaccines (proportionally to their global market shares), share clinical and pathological findings, and have indolent, self-limited character.

Carmofur prevents cell cycle progression by reducing E2F8 transcription in temozolomide-resistant glioblastoma cells.

Sphingolipid metabolism is dysregulated in many cancers, allowing cells to evade apoptosis through increased sphingosine-1-phosphate (S1P) and decreased ceramides. Ceramidases hydrolyze ceramides to sphingosine, which is phosphorylated by sphingosine kinases to generate S1P. The S1P allows cells to evade apoptosis by shifting the equilibrium away from ceramides, which favor cell death. One tumor type that exhibits a shift in the sphingolipid balance towards S1P is glioblastoma (GBM), a highly aggressive brain tumor. GBMs almost always recur despite surgical resection, radiotherapy, and chemotherapy with temozolomide (TMZ). Understanding sphingolipid metabolism in GBM is still limited, and currently, there are no approved treatments to target dysregulation of sphingolipid metabolism in GBM. Carmofur, a derivative of 5-fluorouracil, inhibits acid ceramidase (ASAH1), a key enzyme in the production of S1P, and is in use outside the USA to treat colorectal cancer. We find that the mRNA for ASAH1, but not other ceramidases, is elevated in recurrent GBM. When TMZ-resistant GBM cells were treated with carmofur, decreased cell growth and increased apoptosis were observed along with cell cycle perturbations. RNA-sequencing identified decreases in cell cycle control pathways that were specific to TMZ-resistant cells. Furthermore, the transcription factor and G1 to S phase regulator, E2F8, was upregulated in TMZ-resistant versus parental GBM cells and inhibited by carmofur treatment in TMZ-resistant GBM cells, specifically. These data suggest a possible role for E2F8 as a mediator of carmofur effects in the context of TMZ resistance. These data suggest the potential utility of normalizing the sphingolipid balance in the context of recurrent GBM.

Clusters, crop dusters, and myth busters: a scoping review of environmental exposures and cutaneous T-cell lymphoma.

INTRODUCTION: Cutaneous T-cell lymphoma (CTCL) is a heterogenous group of non-Hodgkin lymphomas. Similar presentation to benign conditions, significant genetic variation, and lack of definitive biomarkers contributes to diagnostic delay. The etiology of CTCL is unknown, and environmental exposures, such as geographic, occupational, chemicals, sunlight, and insects have been investigated. EVIDENCE ACQUISITION: Review of the literature for CTCL and exposures was performed in PubMed and Google Scholar in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) Extension for Scoping Reviews. This search yielded 193 total results, which were initially screened with defined inclusion and exclusion criteria. The 45 remaining articles were reviewed and classified by exposure type. EVIDENCE SYNTHESIS: The most frequently investigated CTCL exposure type was geographic (13/45 articles, 29%). Chemical exposures were commonly discussed (10/45 articles, 22%), along with occupational (10/45 articles, 22%). Insect exposures (6/45, 13%) and sun exposure (3/45, 7%) were also reviewed, along with articles describing multiple exposure types (3/45, 7%). Article types ranged from cases to systematic reviews and case-control studies. Evidence linking CTCL and these exposures was mixed. Limitations of this investigation include reliance on patient reporting and frequent speculation on disease association versus causality. CONCLUSIONS: This investigation synthesizes the current literature on exposures potentially implicated in the pathogenesis of CTCL, while offering guidance on patient history-taking to ensure potential exposures are captured. Awareness of these possible associations may improve understanding of disease pathogenesis and diagnosis. Moreover, these insights may help with public health decision-making and disease mitigation.

Genomic analysis reveals HDAC1 regulates clinically relevant transcriptional programs in Pancreatic cancer.

Novel strategies are needed to combat multidrug resistance in pancreatic ductal adenocarcinoma (PDAC). We applied genomic approaches to understand mechanisms of resistance in order to better inform treatment and precision medicine. Altered function of chromatin remodeling complexes contribute to chemoresistance. Our study generates and analyzes genomic and biochemical data from PDAC cells overexpressing HDAC1, a histone deacetylase involved in several chromatin remodeling complexes. We characterized the impact of overexpression on drug response, gene expression, HDAC1 binding, and chromatin structure using RNA-sequencing and ChIP-sequencing for HDAC1 and H3K27 acetylation. Integrative genomic analysis shows that HDAC1 overexpression promotes activation of key resistance pathways including epithelial to mesenchymal transition, cell cycle, and apoptosis through global chromatin remodeling. Target genes are similarly altered in patient tissues and show correlation with patient survival. We also demonstrate that direct targets of HDAC1 that also show altered chromatin are enriched near genes associated with altered GTPase activity. HDAC1 target genes identified using in vitro methods and observed in patient tissues were used to develop a clinically relevant nine-transcript signature associated with patient prognosis. Integration of multiple genomic and biochemical data types enables understanding of multidrug resistance and tumorigenesis in PDAC, a disease in desperate need of novel treatment strategies.

An update on methods for detection of prognostic and predictive biomarkers in melanoma.

The approval of immunotherapy for stage II-IV melanoma has underscored the need for improved immune-based predictive and prognostic biomarkers. For resectable stage II-III patients, adjuvant immunotherapy has proven clinical benefit, yet many patients experience significant adverse events and may not require therapy. In the metastatic setting, single agent immunotherapy cures many patients but, in some cases, more intensive combination therapies against specific molecular targets are required. Therefore, the establishment of additional biomarkers to determine a patient's disease outcome (i.e., prognostic) or response to treatment (i.e., predictive) is of utmost importance. Multiple methods ranging from gene expression profiling of bulk tissue, to spatial transcriptomics of single cells and artificial intelligence-based image analysis have been utilized to better characterize the immune microenvironment in melanoma to provide novel predictive and prognostic biomarkers. In this review, we will highlight the different techniques currently under investigation for the detection of prognostic and predictive immune biomarkers in melanoma.

Accessibility and readability of online patient education on cutaneous lymphomas.

Background: Patients facing a cutaneous lymphoma diagnosis frequently turn to the internet for information but finding patient-accessible education may be a challenge. Objective: To investigate accessibility and readability of patient-oriented online education on cutaneous lymphomas, including cutaneous T-cell and B-cell lymphoma subtypes. Methods: This study queried a search engine for 11 cutaneous lymphoma terms, resulting in 1083 webpages. Webpages were screened using defined inclusion/exclusion criteria; literature directed to physicians and scientists was excluded. Webpages were stratified by academic/nonacademic and dermatology/nondermatology hosts and assessed by order of appearance. Readability, including text complexity, was analyzed for grade level understanding using 5 established calculators. Overall readability was assessed by Flesch-Kincaid Reading Ease. Results: Academic webpages had earlier order of appearance. There was a dearth in dermatology-hosted webpages. Rarer cutaneous lymphomas yielded fewer patient-accessible results. Search term readability significantly exceeded the American Medical Association-recommended sixth grade level (P < .001∗), with higher grade levels for cutaneous T-cell lymphoma subtype webpages than cutaneous B-cell lymphoma subtypes. Limitations: Webpage quality, accuracy, and language were not assessed. Conclusion: Current online education for cutaneous lymphomas exceeds the American Medical Association's maximum readability recommendation. There is a need for more patient-accessible education amidst predominance of scientific literature, greater dermatology host websites, and enhanced readability of existing online education.

Transcriptomic and functional analysis of ANGPTL4 overexpression in pancreatic cancer nominates targets that reverse chemoresistance.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers based on five-year survival rates. Genes contributing to chemoresistance represent novel therapeutic targets that can improve treatment response. Increased expression of ANGPTL4 in tumors correlates with poor outcomes in pancreatic cancer. METHODS: We used statistical analysis of publicly available gene expression data (TCGA-PAAD) to test whether expression of ANGPTL4 and its downstream targets, ITGB4 and APOL1, were correlated with patient survival. We measured the impact of ANGPTL4 overexpression in a common pancreatic cancer cell line, MIA PaCa-2 cells, using CRISPRa for overexpression and DsiRNA for knockdown. We characterized global gene expression changes associated with high levels of ANGPTL4 and response to gemcitabine treatment using RNA-sequencing. Gemcitabine dose response curves were calculated on modified cell lines by measuring cell viability with CellTiter-Glo (Promega). Impacts on cell migration were measured using a time course scratch assay. RESULTS: We show that ANGPTL4 overexpression leads to in vitro resistance to gemcitabine and reduced survival times in patients. Overexpression of ANGPTL4 induces transcriptional signatures of tumor invasion and metastasis, proliferation and differentiation, and inhibition of apoptosis. Analyses revealed an overlapping signature of genes associated with both ANGPTL4 activation and gemcitabine response. Increased expression of the genes in this signature in patient PDAC tissues was significantly associated with shorter patient survival. We identified 42 genes that were both co-regulated with ANGPTL4 and were responsive to gemcitabine treatment. ITGB4 and APOL1 were among these genes. Knockdown of either of these genes in cell lines overexpressing ANGPTL4 reversed the observed gemcitabine resistance and inhibited cellular migration associated with epithelial to mesenchymal transition (EMT) and ANGPTL4 overexpression. CONCLUSIONS: These data suggest that ANGPTL4 promotes EMT and regulates the genes APOL1 and ITGB4. Importantly, we show that inhibition of both targets reverses chemoresistance and decreases migratory potential. Our findings have revealed a novel pathway regulating tumor response to treatment and suggest relevant therapeutic targets in pancreatic cancer.