Citations

Abstract Background: Young BRCA carriers may undergo breast conserving surgery (BCS) or mastectomy with or without contralateral risk reducing mastectomy at the time of an index breast cancer diagnosis. A variety of factors may influence surgical decision making. Methods: The BRCA BCY Collaboration (NCT03673306) is an international, hospital-based, retrospective cohort study conducted at 109 centres across 5 continents including women with germline pathogenic or likely pathogenic variants (PV) in BRCA1/2 diagnosed between 2000 and 2020 with invasive stage I-III breast cancer prior to or at age 40 years. The primary objective of the present analysis was to evaluate surgical management in these patients. Breast surgery was defined as BCS, unilateral mastectomy, or bilateral mastectomy administered as part of primary treatment for a first diagnosis of invasive breast cancer. Multivariable logistic regression was used to determine factors associated with receipt of bilateral mastectomy. Results: Of 5660 eligible BRCA1/2 carriers, 4715 had unilateral stage I-III breast cancer with surgical treatment details available. The median age of the cohort was 35 years (IQR, 31-38 years). Overall, 1805 (38.3%) patients underwent BCS, 1752 (37.2%) underwent unilateral mastectomy, and 1158 (24.6%) underwent bilateral mastectomy. The proportion of young BRCA1/2 carriers undergoing BCS decreased over the study period (55.7% in 2000 vs. 27.0% in 2020), whereas the use of bilateral mastectomy significantly increased (8.0% in 2000 vs. 44.4% in 2020). Bilateral mastectomy was more common in women who had genetic testing performed before (57.0%) or within 6 months of a breast cancer diagnosis (38.5%), compared to those tested after diagnosis (5.1%, p<0.001). On multivariable analysis, compared to those tested after diagnosis, earlier genetic testing remained the strongest predictor of bilateral mastectomy receipt (testing prior to diagnosis: OR 20.7 [95% CI 15.3-28.1]; testing at diagnosis: OR 6.8 [95% CI 5.4-8.7]). Other predictors of bilateral mastectomy receipt included geographic region, later year of diagnosis, smaller tumor size, node negative disease, and neoadjuvant treatment. In subgroup analysis including 2327 patients who had genetic testing performed before or within 6 months of diagnosis, 42.0% underwent bilateral mastectomy, with the lowest rates reported in Asia/Africa (26.1%) and the highest rates reported in North America (66.4%, p<0.001). In adjusted subgroup analyses, BRCA1 PV, later year of diagnosis, smaller tumor size, node negative disease, neoadjuvant treatment, and geographic region remained independently associated with bilateral mastectomy. Conclusions: In this large, international study of young affected BRCA carriers, geographic region and timing of genetic testing strongly impacted surgical management. These data support early genetic testing for young women with breast cancer to help optimize local therapy decisions. Citation Format: S. M. Wong, E. Blondeaux, V. Delucchi, F. Coussy, R. Bernstein Molho, S. Linn, A. Di Meglio, A. Kwong, K. Pogoda, E. Agostinetto, I. Nevelsteen, J. Balmana, H. C. Moore, A. Toss, A. Ferrari, C. Rousset-Jablonski, T. Renaud, K. Phillips, F. A. PeccatorI, M. Agustina Ipina, S. Paluch-Shimon, J. Ryu, W. Kui, M. Lee, R. Fruscio, M. Rozenblit, C. Vernieri, A. Matikas, M. Dieci, F. J. Couch, L. De Marchis, S. E. Hwang, D. Aguilar-y Mendez, D. Can Guven, M. Swain, C. Gianni, S. Spinaci, G. Montagna, M. Lambertini, H. Kim. Surgical management of young BRCA1/2 carriers with early onset breast cancer [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PD12-01.

Abstract Recent advances in long-read transcriptome sequencing enable high-throughput profiling of full-length RNA isoforms in bulk, single-cell, and single-nucleus samples. However, long-read datasets typically contain a mixture of complete and partial transcripts, leading to pervasive ambiguity in read-to-isoform assignment and complicating accurate isoform identification and quantification, particularly in the absence of reliable reference annotations. These challenges are further amplified in single-cell and single-nucleus samples, where coverage is sparse and transcriptional heterogeneity is high. Here, we present the Long Read Alignment Assembler (LRAA), a unified and versatile computational framework for isoform identification and quantification from long-read RNA sequencing data across bulk, single-cell, and single-nucleus transcriptomic samples. LRAA combines splice-graph based structural modeling with expectation maximization based optimization to probabilistically resolve ambiguous read assignments and improve isoform abundance estimation. The framework supports quantification-only, reference-guided, and fully reference-free (de novo) modes of analysis within a single methodological paradigm. We benchmarked LRAA using both simulated and genuine long-read datasets spanning sequencing standards and whole transcriptomes. Central to this evaluation is a novel benchmarking strategy based on Multiplexed Overexpression of Regulatory Factors (MORFs), which provides biologically expressed, barcoded isoforms with unambiguous read-level ground truth. Across all benchmarks, including MORFs, synthetic spike-ins, and whole-transcriptome datasets, LRAA consistently outperformed state-of-the-art methods in isoform identification accuracy, sensitivity, and expression quantification. Finally, we demonstrate the biological utility of LRAA by resolving cell-type-specific isoform usage across peripheral blood immune cell populations and by detecting a pathogenic cryptic isoform of STMN2 with associated transcriptional changes in single-nucleus RNA-seq data from frontal cortex tissue of an individual with frontotemporal dementia (FTD). Together, these results establish LRAA as a robust and general solution for resolving transcript diversity in complex biological systems, from development to disease.

BACKGROUND: The Ventral Rectopexy International Expert Panel recently published a consensus update on ventral rectopexy. The ability of large language models to synthesize the literature on ventral rectopexy without an explicit knowledge base was studied before the publication of the consensus. OBJECTIVE: To compare the responses and citations of different large language models on ventral rectopexy using the expert panel consensus as the reference standard. DESIGN: ChatGPT-4o, Gemini 1.5 Pro, and OpenEvidence were compared on content appropriateness (1 = inappropriate to 5 = appropriate), readability (Flesch reading ease), response length, citation fabrication, and citation quality per Oxford Levels of Evidence. The most content-appropriate chatbot response selected by the expert panel was de-identified and presented alongside the consensus text to 15 colorectal surgeons who attempted to identify the chatbot-generated text. SETTINGS: Questions were submitted from September 18 to 19, 2024. Analysis was performed before the online publication of the consensus on January 30, 2025. MAIN OUTCOME MEASURES: The main outcome measures included content appropriateness, fabricated citation rate, citation quality, and the accuracy of identifying human versus chatbot text by colorectal surgeons. RESULTS: OpenEvidence ranked highest for content appropriateness (mean 3.5/5), above Gemini (3.0/5) and ChatGPT (2.8/5; p < 0.001). ChatGPT was most verbose with the highest readability scores ( p = 0.021). ChatGPT fabricated 53% of citations; Gemini fabricated 12%; OpenEvidence fabricated 0% ( p < 0.001). All OpenEvidence citations were peer reviewed, with 40 of 117 (34%) citing level I to III studies compared with 46 of 94 (49%) of the references cited in the consensus ( p = 0.043). Chatbot-generated responses were identified with 28 of 51 (55%) accuracy. LIMITATIONS: Reproducibility may be affected due to the nature of large language models and the availability of the consensus after publication. CONCLUSIONS: OpenEvidence outperformed Gemini 1.5 Pro and ChatGPT-4o in content appropriateness and peer-reviewed citation quantity and quality. Chatbot-generated text was indistinguishable from expert-authored consensus to subject matter experts. Large language models, as an early-stage research tool, may be viable for future consensus working groups, provided transparent disclosure and rigorous oversight. See Video Abstract . ¿PUEDEN LOS MODELOS LINGÜÍSTICOS DE GRAN TAMAÑO SER UNA HERRAMIENTA VIABLE PARA LOS GRUPOS DE TRABAJO DE CONSENSO? LA EXPERIENCIA DEL GRUPO DE CONSENSO DE EXPERTOS EN RECTOPEXIA VENTRAL ANTECEDENTES: El Panel Internacional de Expertos en Rectopexia Ventral publicó recientemente una actualización consensuada sobre la rectopexia ventral. Antes de la publicación del consenso, se estudió la capacidad de los grandes modelos lingüísticos para sintetizar la bibliografía sobre la rectopexia ventral sin una base de conocimientos explícita. Objetivo: Comparar las respuestas y citas de diferentes grandes modelos lingüísticos sobre la rectopexia ventral utilizando el consenso del panel de expertos como estándar de referencia. DISEÑO: Se compararon ChatGPT-4o, Gemini 1.5 Pro y OpenEvidence en cuanto a la idoneidad del contenido (1 = inadecuado a 5 = adecuado), la legibilidad (índice de legibilidad de Flesch), la longitud de la respuesta, la fabricación de citas y la calidad de las citas según los niveles de evidencia de Oxford. La respuesta del chatbot más adecuada en cuanto al contenido seleccionada por el panel de expertos se anonimizó y se presentó junto con el texto del consenso a 15 cirujanos colorrectales que intentaron identificar el texto generado por el chatbot. ENTORNO: Las preguntas se enviaron los días 18 y 19 de septiembre de 2024. El análisis se realizó antes de la publicación del consenso en línea el 30 de enero de 2025. PRINCIPALES MEDIDAS DE RESULTADOS: Adecuación del contenido, tasa de citas inventadas, calidad de las citas, precisión en la identificación del texto humano frente al del chatbot por parte de los cirujanos colorrectales. RESULTADOS: OpenEvidence obtuvo la puntuación más alta en cuanto a la adecuación del contenido (media de 3,5/5), por encima de Gemini (3,0/5) y ChatGPT (2,8/5) (p<0,001). ChatGPT fue el más prolijo, con las puntuaciones más altas en legibilidad (p = 0,021). ChatGPT inventó el 53% de las citas; Gemini inventó el 12 %; OpenEvidence inventó el 0 % (p < 0,001). Todas las citas de OpenEvidence fueron revisadas por pares, con 40/117 (34 %) que citaban estudios de nivel I-III frente a 46/94 (49 %) de las referencias citadas en el consenso (p = 0,043). Las respuestas generadas por el chatbot se identificaron con una precisión del 28/51 (55 %). LIMITACIONES: Reproducibilidad debido a la naturaleza de los modelos de lenguaje grandes y a la disponibilidad del consenso tras la publicación. CONCLUSIONES: OpenEvidence superó a Gemini 1.5 Pro y ChatGPT-4o en cuanto a la idoneidad del contenido y la cantidad y calidad de las citas revisadas por pares. El texto generado por el chatbot era indistinguible del consenso redactado por expertos para los expertos en la materia. Los modelos de lenguaje grandes como herramienta de investigación en fase inicial pueden ser viables para futuros grupos de trabajo de consenso, siempre que se garantice una divulgación transparente y una supervisión rigurosa. ( AI-generated translation )

Abstract Secondary central nervous system (CNS) large B-cell lymphoma (SCNSL) occurs in the de novo setting, as a CNS-isolated relapse, or synchronous (concomitant CNS and systemic) relapse. SCNSL is a devastating event without therapeutic consensus. Thus, we aimed to evaluate treatment outcomes in an international cohort. Progression-free survival (PFS), overall survival (OS), and cumulative incidence of relapse (CIR, estimated using competing-risk models) were reported. Prognostic factors were identified in a 6-month landmark multivariate analysis. Outcomes after thiotepa autologous stem cell transplant (ASCT) and chimeric antigen receptor (CAR) T-cell therapy (CAR-T) delivered at relapse were compared after propensity score matching (PSM). A total of 1139 patients were included in the analysis (de novo: 537; relapsed SCNSL: 602). Two-year PFS estimates were 40.4%, 43.9%, and 16.2% for de novo SCNSL, CNS-isolated relapse, and synchronous relapse, respectively. Patients with CNS-isolated relapse demonstrated low rates of systemic recurrence (24-month CIR, 6%). Thiotepa-ASCT correlated with longer survival in de novo SCNSL (PFS: hazard ratio [HR], 0.57; P = .005; and OS: HR, 0.62; P = .023) and CNS-isolated relapses (PFS: HR, 0.55; P = .002; and OS: HR, 0.39; P&lt; .0001). ASCT (thiotepa or no thiotepa) also associated with improved survival in synchronous relapses (PFS: HR, 0.57; P = .023; and OS: HR, 0.48; P = .019). Higher survival with thiotepa-ASCT than CAR-T was observed after PSM (PFS: HR, 0.45; P = .005 and OS: HR, 0.41; P = .014). These data support thiotepa-ASCT in eligible patients, particularly de novo disease and CNS-isolated relapses. CNS-isolated relapse was infrequently associated with systemic recurrence, supporting treatment regimens adopted from primary CNS lymphoma.

Abstract Cockayne Syndrome is an ultra-rare premature aging condition associated with UV sensitivity, neurocognitive decline, retinopathy, metronidazole-induced lethality, and sensorineural hearing loss. In 70% of affected patients, bi-allelic pathogenic variants in ERCC6 are identified. Although the role of ERCC6 in DNA damage repair has been studied, little is known about the mechanism for defective ERCC6 function in clinical findings, particularly hearing loss. To identify the mechanism of disease caused by pathogenic variants in ERCC6, we developed a zebrafish (Danio rerio) ercc6 loss of function model. We assessed survival after UV and metronidazole exposure, measured basal respiration rates, and evaluated mechanoelectrical transduction function and counts of lateral line hair cells. We found that UV exposure significantly reduces ercc6−/− larval viability. Metronidazole treatment results in complete lethality; wildtype controls show nearly complete survival. ercc6−/− embryos have significantly increased oxygen consumption, suggesting abnormal mitochondrial function. Phalloidin staining of lateral line hair cells with and without UV treatment shows no difference in hair cell counts per neuromast between treatment groups. Mechanoelectrical transduction function after UV exposure, measured by FM1–43 uptake, is reduced. Metronidazole lethality is reduced, oxygen consumption rates are restored, and mechanoelectrical transduction function is preserved by treatment with Mn(III)tetrakis(4-benzoic acid)porphyrin Chloride (MnTBAP), a superoxide dismutase mimetic. We propose that defective mitochondrial function and increased reactive oxygen species levels provide a mechanism for hair cell dysfunction in this model of Cockayne Syndrome. These results provide a foundation for further experiments to explore disease mechanisms and treatment modalities for this premature aging condition.

Abstract Immune checkpoint inhibitor–associated immune thrombocytopenia (ICI-ITP) has been described in case reports and small case series, but comprehensive data on its incidence, risk factors, clinical features, treatment, and outcomes are lacking. We reviewed medical records of all adults initiating ICI therapy between 2016 and 2023 at 29 US hospitals across 7 major cancer centers to identify patients with ICI-ITP. Multivariable logistic regression was used to identify risk factors, and Cox modeling was performed to assess the association between ICI-ITP, its severity, and mortality. Among 86 467 patients, ICI-ITP occurred in 214 (0.25%). Independent risk factors included lower baseline platelet count, combination ICI therapy, stage IV cancer, and additional immune-related adverse events. ICI-ITP occurred at a median of 8 weeks (interquartile range [IQR], 4-18) after ICI initiation, with a median nadir platelet count of 41 × 109/L (IQR, 17 × 109/L to 64 × 109/L). Patients were treated with glucocorticoids (n = 106 [49.5%]), immune globulin (n = 39 [18.2%]), and thrombopoietin receptor agonists (n = 29 [13.6%]). Recovery occurred in 161 patients (75.2%) at a median of 2.3 weeks (IQR, 1.0-5.3). Of 76 patients rechallenged with ICIs, 23 (30.3%) developed recurrent ICI-ITP. ICI-ITP and its severity were associated with higher all-cause mortality, with a nearly threefold increase in risk among patients with severe ICI-ITP than those without ICI-ITP (adjusted hazard ratio, 2.96 [95% confidence interval, 2.14-4.08]). These findings establish ICI-ITP as a rare but clinically significant complication of ICI therapy, provide, to our knowledge, the first large-scale description of its risk factors and clinical course, and underscore the importance of timely recognition and management.

Introduction: Mass casualty incident (MCI) simulation scenarios are developed based on detailed review and planning by multidisciplinary trauma teams. This study aimed to assess the feasibility of using generative artificial intelligence (AI) in developing mass casualty trauma simulation scenarios. The study evaluated a range of mass casualty trauma simulation scenarios generated from a public generative artificial intelligence platform based on publicly available data with a validated objective simulation scoring tool. Methods: Using a large language model (LLM) platform (ChatGPT4, OpenAI, San Francisco, CA, USA), 10 complex MCI trauma simulation scenarios were generated based on publicly available US reported trauma data. Each scenario was evaluated by two Advanced Trauma Life Support (ATLS) certified raters based on the Simulation Scenario Evaluation Tool (SSET), a validated scoring tool out of 100 points. The tool scoring is based on learning objectives, tasks for performance, clinical progression, debriefing criteria, and resources. Two publicly available mass casualty trauma scenarios were similarly evaluated as controls. Revision and recommended feedback was provided for the scenarios, with review time recorded. Post-revision scenarios were evaluated. Interrater reliability was calculated based on Intraclass Correlation Coefficients (2, k) (ICCs). For the scenarios, scores and review times were reported as medians with interquartile range (IQR) as 25th and 75th percentiles. Results: Ten mass casualty trauma simulation scenarios were generated by an LLM, producing a total of 62 simulated patients. The initial LLM-generated scenarios demonstrated a median SSET score of 78.5 (IQR 74–82), substantially lower than the median score of 94 (IQR 93–95) observed in publicly available scenarios. The interrater reliability ICC for the LLM-generated scenarios was 0.965 and 1.00 for publicly available scenarios. Following secondary human revision and iterative refinement, the LLM-generated scenarios improved, achieving a median SSET score of 94 (IQR 93–96) with an interrater reliability ICC of 0.7425. Conclusions: The feasibility study suggests that a structured, collaborative workflow combining LLM-based generation with expert human review may enable a new approach to mass casualty trauma simulation scenario creation. LLMs hold promise as a scalable tool for the development of MCI training materials. However, consistent human oversight, quality assurance processes, and governance frameworks remain essential to ensure clinical accuracy, safety, and educational value.