Citations

Importance Contemporary guidelines recommend sentinel lymph node biopsy (SLNB) for patients with melanoma with predicted risk of SLN metastasis greater than 10% and consideration of SLNB when the risk is 5% to 10%. A gene expression profile (GEP)–based test that can accurately identify patients with a low risk of SLN metastasis would refine selection for SLNB. Objective To establish the predictive capability of the combined clinicopathological factors and GEP (CP-GEP) test to identify patients with primary cutaneous melanoma who can safely forgo SLNB and to investigate the prognostic value of CP-GEP regarding the outcome in patients with cutaneous melanoma after a negative SLNB (not reported herein). Design, Setting, and Participants This prognostic study was conducted from September 2021 to June 2024 at 9 academic medical centers with experienced melanoma surgeons. Included were patients with biopsy-proven invasive cutaneous melanoma with T1 to T3 tumors and clinically negative regional LNs. All patients were deemed candidates for SLNB using standard clinical criteria. GEP was performed on formalin-fixed, paraffin-embedded tissue from the primary melanoma biopsy. Analyses were performed from December 2024 to August 2025. Intervention CP-GEP testing to determine risk of having a positive SLNB in patients with T1 to T3 cutaneous melanoma who were considered appropriate candidates for the procedure based on standard clinical parameters. Main Outcomes and Measures CP-GEP results were reported as low risk or high risk; the primary outcome measure was negative predictive value (NPV) in low-risk cases. Analyses included NPV assessment by tumor (T) subcategory, primary site, and age. Results A total of 1761 patients (median [IQR] age, 64 [53-72] years; 997 male [56.6%]) underwent SLNB (310 [17.6%] SLN positive) and had a successful CP-GEP test; GEP was successful in 97.7% of samples. A total of 651 patients (37.0%) were considered low risk by CP-GEP. Among low-risk cases, 46 (7.1%) were SLN positive, and NPV was 92.9% (95% CI, 90.7%-94.8%). High-risk cases had a 23.8% (264 of 1110) SLN-positive rate. The percentage of cases with low-risk CP-GEP declined with increasing T category (T1 = 346 of 507 [68.2%]; T2 = 295 of 897 [32.9%]; T3 = 10 of 357 [2.8%]). CP-GEP results were consistent in discriminating SLN-positive rates across primary sites, histologic subtypes, and mitotic count categories. In 2 large subsets, clinical stage IB (n = 1187) and patients 65 years and older (n = 832), 6.5% (95% CI, 4.6%-8.8%) of low-risk clinical stage IB cases and 6.6% (95% CI, 4.2%-9.7%) of all low-risk cases in patients 65 years and older were SLN positive vs 18.3% (95% CI, 15.3%-21.6%) and 20.3% (95% CI, 16.8%-24.2%) for high-risk cases, respectively. Conclusions and Relevance In this multicenter, prospective, blinded, prognostic study, the CP-GEP test reliably identified patients with melanoma with less than 10% SLN metastasis risk. SLN metastasis rates were approximately 3-fold greater for high-risk vs low-risk CP-GEP cases. In appropriately selected patients, the CP-GEP test may add value for shared patient-surgeon decision-making.

We performed a retrospective review of patients with lichen planus pemphigoides (LPP) over almost a 23-year period to gather clinical, histopathological, immunological and treatment-related information and to compare idiopathic LPP with drug-induced LPP. This study represents the largest single-institution case series of LPP to date and includes novel findings related to mucosal involvement, autoantibody profiles and the value of monitoring bullous pemphigoid (BP) autoantibodies in predicting treatment response. This study also includes characteristic histopathological findings that can aid in the diagnosis and differentiation of LPP from BP, in addition to comparisons between idiopathic LPP and drug-induced LPP.

ABSTRACTBackgroundIntercellular IgG4 deposition is variably present on DIF in patients with pemphigus. Whether this feature has clinical, serologic, or histopathologic correlates was unknown.MethodsWe identified 34 patients with pemphigus who had 55 DIF specimens reported to show intercellular IgG, IgG4, and/or C3 deposition (8/22/2017–11/30/2023). Patients and biopsies were stratified by intercellular IgG4 status. Clinical and serologic data were extracted from electronic records, and corresponding biopsy slides were reviewed for histopathologic findings.ResultsAmong the 34 patients with pemphigus, patients with positive IgG4 were significantly more likely to have detectable serum anti‐desmoglein 1/3 antibodies by ELISA (p = 0.014 and p = 0.030, respectively). Paraneoplastic pemphigus (PNP) was more frequent in the IgG4‐negative group (p = 0.037), particularly among patients with ocular involvement. Of 55 DIF biopsy specimens meeting inclusion criteria, 52 (94.5%) had intercellular IgG deposition and 42 (76.4%) had intercellular IgG4 on DIF. Compared to IgG4‐negative specimens, IgG4‐positive specimens were significantly more likely to represent a vesiculobullous lesion (p = 0.024), to be derived from the trunk (p = 0.047), to show histologic acantholysis (p = 0.019) and to lack lichenoid inflammation (p = 0.0004).ConclusionFor pemphigus, DIF IgG4 status correlated with ocular involvement, the clinical morphology selected for biopsy, the likelihood of detecting circulating desmoglein antibodies, the presence of specific histopathologic features such as acantholysis and lichenoid inflammation, and the likelihood of having a final diagnosis of PNP. Further studies are needed to determine whether the presence of tissue‐bound intercellular IgG4 antibodies correlates with particular disease variants or lesion‐specific characteristics.

ABSTRACTBackground/ObjectivesImmune‐mediated skin disorders, such as immunobullous dermatoses and leukocytoclastic vasculitis, rarely affect children. While direct immunofluorescence (DIF) biopsy is a standard diagnostic tool, limited data exist on pediatric DIF patterns, rates of positivity, pretest diagnostic concordance, and the relevance of biopsy site. This study sought to address these gaps.MethodsDIF data from all skin and mucosal specimens interpreted at Mayo Clinic's reference immunodermatology laboratory for patients aged 0–18 years (August 22, 2017 to November 30, 2023) were reviewed. DIF results were classified as positive if a characteristic pattern was seen and negative if the findings were negative or nondiagnostic.ResultsOf 986 pediatric DIF studies, 153 (15.5%) were positive and comparable to adult positivity rates (20.9%) during the same period. The most frequent DIF patterns were IgA‐predominant vasculitis (N = 85/153; 55.5%) and lichenoid tissue reaction (N = 21/153;13.7%). Concordance between pretest diagnosis and positive DIF results was highest for linear IgA bullous dermatosis (N = 7/7; 100%) and dermatitis herpetiformis (N = 6/6; 100%). Excluding these entities, DIF changed the pretest diagnosis in 16.7% (N = 19/114) of cases. While lower extremity biopsies were initially more likely to yield positive DIF results, this association disappeared when IgA vasculitis cases were excluded.ConclusionThe most frequent DIF pattern in children was that of IgA‐predominant vasculitis. Pediatric DIF positivity rates closely mirrored those of adults, supporting similar biopsy thresholds. DIF results differed from the pretest impression in a substantial percentage, supporting the value of DIF in select situations in the pediatric population. After controlling for IgA vasculitis, biopsy site was not associated with DIF positivity.

ImportanceDirect immunofluorescence (DIF) testing has been an important ancillary tool for the diagnosis of various inflammatory mucocutaneous conditions for more than 50 years. Current DIF test panels are based on historical clinical descriptions; few studies have rigorously addressed preanalytical, analytical, and/or postanalytical aspects, and even fewer have been replicated or validated. Recent unresolved key issues include whether DIF testing and test panels should be triaged or truncated based on clinical indication or histopathologic findings.ObjectiveTo assess levels of consensus regarding practical aspects of DIF testing among immunodermatology testing specialists in the US.Design, Setting, and ParticipantsUsing modified Delphi methods with a priori characterized criteria, a survey containing 54 statements pertaining to DIF testing was created and distributed to assess consensus. Statements not initially reaching consensus were discussed in 2 live virtual sessions, which were supplemented by relevant literature review and free-text survey comments. These statements were then reassessed in a second survey. Immunodermatology testing specialists in US academic institution–based and independent laboratories were invited based on serving as immunodermatology laboratory medical directors, authoring pertinent literature, or delivering relevant talks at major conferences or by referral. The first survey was conducted from January to February 2024, and the second survey was conducted from March to April 2024.Main Outcomes and MeasuresThe primary measured outcome was degree of consensus for various DIF testing practice, including DIF testing triage by histopathology/dermatopathology findings and DIF testing panel tailored truncations by clinical indication.ResultsA total of 23 respondents to the survey invitation had a mean (SD) of 18.5 (11.1) years and median (range) of 20.0 (1.5-46.0) years in immunodermatology laboratory practice. Consensus was achieved for 46 of 54 statements (85.2%) in the initial survey and for an additional 4 statements in the second survey (50 of 54 [92.6%]). Strong consensus was found against tailored truncation of DIF panel based on the clinical indication in the first survey round. The general acceptability of triaging specimens for DIF testing based on histopathology findings remained without consensus after both surveys.Conclusions and RelevanceOverall, participating US specialists in immunodermatology laboratory testing agreed on many practical aspects of DIF testing, including matters not queried previously. The findings also revealed areas of continued controversy and identified issues for prioritized future study.

Objectives/Goals: Manual skin assessment in chronic graft-versus-host disease (cGVHD) can be time consuming and inconsistent (>20% affected area) even for experts. Building on previous work we explore methods to use unmarked photos to train artificial intelligence (AI) models, aiming to improve performance by expanding and diversifying the training data without additional burden on experts. Methods/Study Population: Common to many medical imaging projects, we have a small number of expert-marked patient photos (N = 36, n = 360), and many unmarked photos (N = 337, n = 25,842). Dark skin (Fitzpatrick type 4+) is underrepresented in both sets; 11% of patients in the marked set and 9% in the unmarked set. In addition, a set of 20 expert-marked photos from 20 patients were withheld from training to assess model performance, with 20% dark skin type. Our gold standard markings were manual contours around affected skin by a trained expert. Three AI training methods were tested. Our established baseline uses only the small number of marked photos (supervised method). The semi-supervised method uses a mix of marked and unmarked photos with human feedback. The self-supervised method uses only unmarked photos without any human feedback. Results/Anticipated Results: We evaluated performance by comparing predicted skin areas with expert markings. The error was given by the absolute difference between the percentage areas marked by the AI model and expert, where lower is better. Across all test patients, the median error was 19% (interquartile range 6 – 34) for the supervised method and 10% (5 – 23) for the semi-supervised method, which incorporated unmarked photos from 83 patients. On dark skin types, the median error was 36% (18 – 62) for supervised and 28% (14 – 52) for semi-supervised, compared to a median error on light skin of 18% (5 – 26) for supervised and 7% (4 – 17) for semi-supervised. Self-supervised, using all 337 unmarked patients, is expected to further improve performance and consistency due to increased data diversity. Full results will be presented at the meeting. Discussion/Significance of Impact: By automating skin assessment for cGVHD, AI could improve accuracy and consistency compared to manual methods. If translated to clinical use, this would ease clinical burden and scale to large patient cohorts. Future work will focus on ensuring equitable performance across all skin types, providing fair and accurate assessments for every patient.