The utility of artificial intelligence platforms for patient-generated questions in Mohs micrographic surgery: a multi-national, blinded expert panel evaluation.

BACKGROUND: Artificial intelligence (AI) and large language models (LLMs) transform how patients inform themselves. LLMs offer potential as educational tools, but their quality depends upon the information generated. Current literature examining AI as an informational tool in dermatology has been limited in evaluating AI's multifaceted roles and diversity of opinions. Here, we evaluate LLMs as a patient-educational tool for Mohs micrographic surgery (MMS) in and out of the clinic utilizing an international expert panel. METHODS: The most common patient MMS questions were extracted from Google and transposed into two LLMs and Google's search engine. 15 MMS surgeons evaluated the generated responses, examining their appropriateness as a patient-facing informational platform, sufficiency of response in a clinical environment, and accuracy of content generated. Validated scales were employed to assess the comprehensibility of each response. RESULTS: The majority of reviewers deemed all LLM responses appropriate. 75% of responses were rated as mostly accurate or higher. ChatGPT had the highest mean accuracy. The majority of the panel deemed 33% of responses sufficient for clinical practice. The mean comprehensibility scores for all platforms indicated a required 10th-grade reading level. CONCLUSIONS: LLM-generated responses were rated as appropriate patient informational sources and mostly accurate in their content. However, these platforms may not provide sufficient information to function in a clinical environment, and complex comprehensibility may represent a barrier to utilization. As the popularity of these platforms increases, it is important for dermatologists to be aware of these limitations.

Establishing Consensus for Mohs Micrographic Surgical Techniques in the Treatment of Melanoma in Situ for Future Clinical Trials: A Modified Delphi Study.

BACKGROUND: Mohs micrographic surgery (MMS) is a promising treatment modality for melanoma in situ (MIS). However, variations in surgical technique limit the generalizability of existing data and may impede future study of MMS in clinical trials. METHODS: A modified Delphi method was selected to establish consensus on optimal MMS techniques for treating MIS in future clinical trials. The Delphi method was selected due to the limited current data, the wide range of techniques used in the field, and the intention to establish a standardized technique for future clinical trials. A literature review and interviews with experienced MMS surgeons were performed to identify dimensions of the MMS technique for MIS that (1) likely impacted costs or outcomes of the procedure, and (2) showed significant variability between surgeons. A total of 8 dimensions of technical variation were selected. The Delphi process consisted of 2 rounds of voting and commentary, during which 44 expert Mohs surgeons across the United States rated their agreement with specific recommendations using a Likert scale. RESULTS: Five of eight recommendations achieved consensus in Round 1. All 3 of the remaining recommendations achieved consensus in Round 2. Techniques achieving consensus in Round 1 included the use of a starting peripheral margin of ≤5 mm, application of immunohistochemistry, frozen tissue processing, and resecting to the depth of subcutaneous fat. Consensus on the use of Wood's lamp, dermatoscope, and negative tissue controls was established in Round 2. CONCLUSIONS: This study generated 8 consensus recommendations intended to offer guidance for Mohs surgeons treating MIS. The adoption of these recommendations will promote standardization to facilitate comparisons of aggregate data in multicenter clinical trials.

Refining Field Cancerization: An Institutional Cohort Analysis of Patient Characteristics in a Validation Cohort.

BACKGROUND: Field cancerization is poorly defined in dermatology. The author group previously proposed and applied a classification system in an original cohort to risk-stratify patients with field cancerization. OBJECTIVE: Apply the authors' classification system within a validation cohort. METHODS: Patients with keratinocyte carcinoma history completed a survey regarding demographic information, medical history, and chemoprevention use. Patients were assigned a field cancerization class, and differences between validation and original cohorts were assessed. RESULTS: A total of 363 patients were enrolled (mean age 67.4; 61.7% male). After comparing validation and original cohorts, there were differences in age between class II (p = .02) and class IVb (p = .047), and differences in chemoprevention use in class III (p = .04). Similar to the original cohort, the validation cohort was associated with increases in total number of skin cancers in the last year (p < .001), 5 years (p < .001), lifetime (p < .001), years since first skin cancer (p < .001), and chemoprevention use (p < .001). In the validation cohort, there were increases in age (p = .03) and immunocompromised status (p = .04) with increasing class, which were not observed in the original cohort. CONCLUSION: Differences among field cancerization classes were similar in a validation cohort, further highlighting the importance of class-specific treatment and management.

Cutaneous Angiosarcoma Subtypes: A Quantitative Systematic Review of Demographics, Treatments, and Outcomes Within Published Patient-Level Cases.

BACKGROUND: Cutaneous angiosarcoma (cAS) is a highly aggressive malignancy arising from the vascular endothelium. Given its rarity, there is insufficient data detailing patient demographics, management, and survival outcomes. OBJECTIVE: To systematically compile published patient-level cases of cAS and to quantify and analyze data on demographics, management, and outcomes while determining prognostic indicators. MATERIALS AND METHODS: Searches of EBSCOhost, MEDLINE, EMBASE, and the Cochrane Library generated 1,500 cases of cAS with individual level data available. PRISMA guidelines were followed. RESULTS: Cutaneous angiosarcoma presented most often on the scalp of elderly men. Metastasis occurred in 36.3% of cases. Aggregate 5-year survival was 31.6% with the median survival of 25 months. The best 5-year survival was in the radiation-associated subtype (48.8%), whereas the worst was in the Stewart-Treves subtype (21.6%). Using multivariate analysis, gender, age group, disease subtype, treatment modality, and metastasis at presentation had significant effects on survival outcomes ( p < .05). CONCLUSION: The breadth of information obtained enables this study to serve as a resource that clinicians may reference when they encounter cAS.

Integrating the 40-Gene Expression Profile (40-GEP) Test Improves Metastatic Risk-Stratification Within Clinically Relevant Subgroups of High-Risk Cutaneous Squamous Cell Carcinoma (cSCC) Patients.

INTRODUCTION: The validated 40-gene expression profile (40-GEP) test independently stratifies risk of regional or distant metastasis for cutaneous squamous cell carcinoma (cSCC) tumors with high-risk clinicopathologic features. This study evaluated the stratification of risk by the 40-GEP test in a large cohort of tumors with one or more high-risk factors and in clinically relevant subgroups, including tumors within National Comprehensive Cancer Network (NCCN) high- and very-high-risk groups, lower-stage BWH T1 and T2a tumors, and patients > 65 years old. METHODS: This multicenter (n = 58) performance study of the 40-GEP included 897 patients. Kaplan-Meier analyses were performed to assess risk stratification profiles for 40-GEP Class 1 (low), Class 2A (higher) and Class 2B (highest) risk groups, while nested Cox regression models were used to compare risk prediction of clinicopathologic risk classification systems versus risk classification systems in combination with 40-GEP. RESULTS: Patients classified as 40-GEP Class 1, Class 2A, or Class 2B had significantly different metastatic risk profiles (p < 0.0001). Integrating 40-GEP results into models with individual clinicopathologic risk factors or risk classification systems (Brigham and Women's Hospital, American Joint Committee on Cancer Staging Manual, 8th Edition) and NCCN demonstrated significant improvement in accuracy for prediction of metastatic events (ANOVA for model deviance, p < 0.0001 for all models). CONCLUSION: The 40-GEP test demonstrates accurate, independent, clinically actionable stratification of metastatic risk and improves predictive accuracy when integrated into risk classification systems. The improved accuracy of risk assessment when including tumor biology via the 40-GEP test ensures more risk-aligned, personalized patient management decisions.