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.

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.

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.

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.

Decision Paralysis: Recognition and Patient-Centered Discourse.

Decision paralysis (DP) can be defined as a patient's inability to commit to a physician and/or initiate appropriate treatment for their condition. An incessant search for greater physician opinions often leads to treatment delay, disease progression, and initiation of care at more advanced stages. Despite the harms associated with DP, a dearth of research on the issue remains. There are no guidelines that assist in both recognition and rectification of DP, leaving patients with chronic illnesses and diagnoses without well-characterized treatment algorithms especially vulnerable. This paper analyzes why patients are inclined toward DP and the clinical implications. Review of the literature affirms that the patient-physician relationship holds considerable influence; physicians identifying DP can improve therapeutic outcomes for their patients. Using these findings, we then propose a framework for broaching this topic with a method that supports patients while respecting their autonomy. A practical approach to both recognition and patient-centered discourse is introduced, providing a foundation for physicians to host these conversations and understand their patients' perspectives. This approach toward recognition and discourse on DP holds clinical importance, given that there is a paucity of established guidance. A future uniform approach may generate optimal patient care recommendations, which will hold far-reaching impact on both the patient-physician relationship and overall patient outcomes.