Citations

Background Psychiatric disorders are increasingly contributing to global disability. Despite advances in conservative management, the prevalence of treatment-resistant cases remains high. Meanwhile, neurosurgery for psychiatric disorders (NPD) remains underused, largely due to strict regulations and historical concerns, particularly those related to neuropsychological side effects (NPSE). Objective To address this issue, we conducted a systematic review with meta-analysis to compare NPSE associated with radiofrequency ablative NPD to those observed in neuro-oncological, neurovascular and epilepsy surgeries. Methods PubMed, Embase and LILACS databases were searched in April 2024 for articles published in English/Spanish from 1990 to 2022, following Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Results A total of 48 articles with 2678 participants were included. The frequency of transient and permanent NPSE in the NPD group ranged from 0.94% to 11.50% and 0.94% to 2.03%, respectively, comparable to the other surgical groups (epilepsy: 0.31–11.70%; vascular: 0.52–22.90%; oncology: 0.94–17.60% for transient NPSE; epilepsy: 0.31–12%; vascular: 0.40–1.96% and oncology: 0.84–1.48% for permanent NPSE). Regarding permanent NPSE, arguably the most critical consideration, the NPD group showed better outcomes in memory, language and social cognition than the epilepsy group, but worse outcomes in executive and perceptual-motor functions. Compared with the vascular group, the NPD group had better executive function but worse complex attention. Finally, the NPD group had fewer permanent deficits than the oncology group in executive function, complex attention and perceptual-motor domains, although language performance was lower. Conclusions Contemporary NPD apparently carries a similar risk of NPSE as other conventional neurosurgical procedures, challenging misconceptions and this unjustified barrier to its broader use.

Abstract Large Language Models (LLM) are being widely adopted into the medical field for their impressive ability to analyze and summarize large amounts of text data. These models enable clinicians and researchers to extract meaningful insights from complex datasets and may assist with decision making. Here we present our workflows and application of LLM for the interpretation and summarization of clinical data related to CAR-T cell therapy. Using an LLM (Gemini 2.5 pro) in the Google Cloud Computing (GCP) environment, two applications were developed to analyze CAR-T cell therapy clinical data: 1) extracting and summarizing CRS and ICANS event-related data to streamline the compliance team workflow, and 2) identifying features available at time of CAR-T infusion able to classify patients into high- or low-monitoring needs 14 days post CAR-T. Patient data (vitals, labs, hematology notes, and EKGs) were extracted from the electronic medical record (EMR) using Google BigQuery into SQL tables in GCP. For each application, relevant data fields were retrieved, formatted into JSON objects, and embedded in the LLM prompt for context-aware processing. Both applications have undergone iterative prompt engineering after analyzing the LLM output against ground truth data in the EMR. For the application extracting and summarizing CRS and ICANS events, the LLM was optimized on Mayo Clinic Rochester data. When compared to the IEC compliance database, the LLM achieved 100% accuracy and F1 score for CRS events, and 96% accuracy and 82% F1 score for ICANS events. The match rate for CRS and ICANS grades were 83% and 89% respectively. We applied the same LLM to Mayo Clinic Arizona (MCA) and Mayo Clinic Florida (MCF) cases, who document clinical notes and toxicity flowsheet differently, and achieved an accuracy (MCA: 93%, MCF:93%) and F1 score (MCA: 96%, MCF: 96%) for CRS and accuracy (MCA: 81%, MCF:82%) and F1 score (MCA: 76%, MCF: 75%) for ICANS. LLM was able to capture events missed by manual reviews. For most of the discrepancies where compliance team final adjudication is needed, LLM will be updated to flag discrepancies for review by the compliance team. For the application related to the monitoring needs 14 days post CAR-T, the LLM identified 5 categories predictive of high or low monitoring needs post CAR-T infusion (disease status, inflammatory and tumor burden markers, hematologic status, renal function and performance status). Our model achieved a sensitivity of 85.7%, specificity of 23.8%, and F1 score of 65.5% for our first cohort, compared with data extracted by the LLM from the EMR. For our second cohort, with demographics statistically similar to cohort 1 and using the same 5 categories, the LLM achieved a sensitivity of 83.3%, a specificity of 28.6%, and F1 score of 65.4%. Our workflow and applications of LLM’s provide examples and guidance to others interested in applying LLM’s for clinical and research applications. Citation Format: Emmanuel Contreras Guzman, Matthew Jankowski, Andre De Menezes Silva Corraes, Malvika Gupta, Monica L. Shaw, Madiha Iqbal, Talal Hilal, Saurabh Chhabra, Ricardo Daniel Parrondo, Jody K. Mclean, Kim R. Riester, Kayla Joseph, Melinda Tan, Holly Ross, Cleyonia Barnett, Sylvia Carter, Semy Girmay, Rachel Wolan, Milana Ramsey, Christian Downhour, Kristy Morgan, Shae Sibley, Erica Rushing, Lucy Holmes, Allison Burgstahler, Stephen M. Ansell, Hassan Alkhateeb, Matthew Hathcock, Ramona Bruno, Allison C. Rosenthal, Hemant Murthy, Patrick B. Johnston, Jonas Paludo, Yi Lin. Applications of large language models to CAR-T cell therapy clinical data using Google cloud computing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 2740.

BACKGROUND: Catheter ablation for atrial fibrillation is a widely used rhythm-control strategy, yet its role in reducing thromboembolic risk and enabling oral anticoagulation (OAC) discontinuation remains uncertain. This meta-analysis aims to comprehensively synthesize and evaluate randomized controlled trial evidence supporting long-term antithrombotic strategies in patients with atrial fibrillation undergoing catheter ablation. METHODS: A systematic literature search was performed in MEDLINE/PubMed, Embase, and the Cochrane Central Register of Controlled Trials to identify randomized controlled trials evaluating antithrombotic strategies after catheter ablation for atrial fibrillation. The primary outcome was ischemic stroke. A frequentist network meta-analysis comparing reported treatment arms, along with a pooled incidence meta-analysis for outcomes of interest, was conducted. RESULTS: Four randomized controlled trials, including 3924 patients, met the inclusion criteria. Three trials compared long-term OAC continuation versus OAC discontinuation, and 1 compared OAC continuation with left atrial appendage occlusion after catheter ablation. No significant differences in stroke incidence were observed when comparing OAC or left atrial appendage occlusion with no antithrombotic therapy (incidence rate ratio, 0.90 [95% CI, 0.02–33.85]; P =0.95; incidence rate ratio, 0.79 [95% CI, 0.00–241.01]; P =0.94, respectively). Among patients who discontinued antithrombotic therapy without undergoing left atrial appendage occlusion (n=1161), with 2864 cumulative person-years of follow-up, the pooled incidence of stroke was 0.23 events per 100 person-years (95% CI, 0.02–2.43; I 2 =0%). CONCLUSIONS: This analysis reinforces that, across randomized data, the incidence of thromboembolic events in patients who discontinued OAC after successful ablation remained low. However, the evaluation of net clinical benefit is limited by the low number of events across all treatment arms, underscoring the need for larger studies with prolonged follow-up to further validate the safety of this strategy, particularly in higher-risk populations.

Abstract Background: Hypogammaglobulinemia at the time of CLL diagnosis predicts shorter time to first therapy (TTFT). However, the depth of immunoparesis and its impact on TTFT in newly diagnosed MBL/CLL remains unexplored. Methods: We identified previously untreated MBL/CLL patients from Mayo Clinic CLL Database (2000-2024) who had serum immunoglobulin (Ig; IgG, IgM and IgA) and monoclonal protein assessed within 1 year of diagnosis. Immunoparesis was evaluated: a) qualitatively by classifying patients into preserved, partial and full Ig suppression, based on the number of suppressed Igs; and b) quantitatively by calculating the average relative difference (ARD), defined as the mean percentage below normal for all Igs. For both methods, only uninvolved Igs were considered for those with monoclonal protein. TTFT was estimated by Kaplan-Meier with competing risk of death. Cox models estimated hazard ratios (HR) and 95% confidence intervals (CI). Results: Among 1420 patients, median age at diagnosis was 65 (range 28-96); 954 (67%) were male; 493 (44.8%) had unmutated IGHV, and 86 (6.8%) had TP53 disruption. The median [range, mg/dL] serum IgG, IgA, and IgM were 889 [111-5290], 132 [1-4880], and 49 [4-9480]. Low IgG was present in 472 (33.2%), low IgA in 223 (16.4%), and low IgM in 530 (37.3%) patients. An M-spike was detected in 122 (8.6%) patients; distribution was: IgG (73), IgM (30), IgA (6), or multiple (13). By qualitative assessment, preserved Ig were seen in 664 (46.8%), partial Ig suppression in 604 (42.5%), and full suppression in 152 (10.7%) patients. By quantitative assessment, median ARD was 0.6 (-0.8 to 11.3); 280 (19.7%) patients had negative ARD, and 1140 (80.3%) had positive ARD. In those with negative ARD, 128 (9%) had partial Ig suppression and 152 (10.7%) had full Ig suppression; in those with positive ARD, 664 (46.8%) had preserved Ig and 476 (33.5%) had partial Ig suppression. Median follow-up was 14.7 years; 510 patients progressed requiring therapy. Median TTFT was 9.6 years. Median TTFT for patients with preserved Ig was 12.6 years, 8.0 years for partial Ig suppression (HR 1.4, 95%CI 1.1-1.7), and 1.8 years for full Ig suppression (HR 3.1, 95%CI 2.4-4.0). The median TTFT was 2.3 and 12.1 years for patients with negative vs positive ARD; negative ARD was associated with shorter TTFT (HR 2.4, 95%CI 2.0-2.9). After adjusting for sex and CLL-International Prognostic Index (CLL-IPI) score, full Ig suppression (HR 2.9, 95%CI 2.2-3.9) and partial Ig suppression (HR 1.6, 95% CI 1.3-2.0) were associated with shorter TTFT (model 1, c-stat 0.77); and negative ARD (HR 2.4, 95%CI 2.0-2.9) was associated with shorter TTFT (model 2, c-stat 0.76). Negative ARD identified an additional 9% of patients at higher risk for shorter TTFT beyond full Ig suppression. Conclusions: The depth of immunoparesis at diagnosis predicts TTFT and enhances risk stratification in newly diagnosed MBL/CLL. Citation Format: Yuan Yao, Kari G. Rabe, Eli Muchtar, Paul Hampel, Yucai Wang, Lindsey Roeker, Saad Kenderian, Amber Koehler, Catherine Wagner, Amy Behnken, Jose F. Leis, Mazie Tsang, Talal Hilal, Ricardo Daniel Parrondo, Susan M. Schwager, Min Shi, Curtis A. Hanson, Celine M. Vachon, Shaji Kunnathu Kumar, Esteban Braggio, Neil E. Kay, Susan Slager, Sameer A. Parikh. Depth of immunoparesis predicts time to first therapy in newly diagnosed monoclonal B-cell lymphocytosis and chronic lymphocytic leukemia [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 1191.

ABSTRACT BACKGROUND Increasing evidence suggests that accurate prediction of Alzheimer’s disease (AD) symptom onset requires more than amyloid- and tau-centric biomarkers such as cerebrospinal fluid (CSF) Aβ42/40, total tau and p-tau181 and plasma p-tau217. Autosomal dominant AD (ADAD), caused by pathogenic PSEN1, PSEN2 and APP mutations with predictable age at symptom onset, presents a unique opportunity to characterize the chronological changes in proteins beyond amyloid and tau and clarify them as early biomarkers of disease onset or as biomarkers related to disease staging and progression monitoring. METHODS We measured 972 CSF samples corresponding to 484 participants of the Dominantly Inherited Alzheimer Disease Network (DIAN) using the NULISASeq 120 CNS Disease Panel. We first benchmarked the technology against gold-standard measurements followed by the identification of proteins that were differentially abundant in relation to mutation status and symptomatology. Next, we determined the chronological emergence of protein changes in relation to the estimated years to onset (EYO). Finally, we assessed whether specific protein measures improved the prediction of EYO in the ADAD. FINDINGS NULISA measurements were comparable to those previously published. We demonstrated that known early alterations in CSF amyloid and tau were followed by inflammatory and neurodegenerative responses suggesting that clinical manifestation of AD happens before the inflammatory processes is fully developed. Finally, we found a multi-protein composite approach for predicting EYO that outperformed single biomarker values. INTERPRETATION Our results suggest that the main CSF proteomic landscape changes in ADAD are due to the presence of a pathogenic mutation and occur prior to symptom onset. Improved performance of multi-protein composite to predict EYO compared to single biomarker values highlights the added value of multiplex proteomic signatures for biomarker panel development. FUNDING National Institute on Aging, Alzheimer’s Association, German Center for Neurodegenerative Diseases, Raul Carrea Institute for Neurological Research, Japan Agency for Medical Research and Development, Ministry of Health & Welfare and Ministry of Science and ICT, Republic of Korea, Spanish Institute of Health Carlos III.

Abstract Context Crinecerfont, a first-in-class corticotropin-releasing factor type 1 receptor antagonist, is FDA-approved as an adjunct to the physiologic glucocorticoid (GC) required to treat the underlying adrenal insufficiency in patients (≥4 years old) with classic congenital adrenal hyperplasia (CAH). By reducing elevated adrenocorticotropic hormone, crinecerfont controls excess adrenal androgens, thereby enabling lower GC doses. However, there are no published recommendations for how to reduce supraphysiologic GC doses after initiating crinecerfont. This manuscript aims to provide a framework developed by experienced endocrinologists for reducing supraphysiologic GC doses in patients taking crinecerfont. Evidence Acquisition An experienced panel of 11 endocrinologists discussed strategies and considerations when reducing GC doses and developed an algorithm to guide GC dose reductions after introducing crinecerfont in adults with CAH. Evidence Synthesis Approaches to GC reduction should be individualized based on the patient's therapeutic goals, cortisol needs, lifestyle preferences, and the clinician's experience to set appropriate targets for clinical parameters, androgens, and GC dose regimen. In general, GC doses should be reduced gradually to minimize the risks of developing symptoms of GC withdrawal or adrenal insufficiency. GC doses should be adjusted to the lowest level needed to maintain androgens at goal, without reducing below what is needed for cortisol replacement. Practical considerations during GC dose reduction include switching from longer- to shorter-acting GCs (eg, from dexamethasone to hydrocortisone), optimizing dose distribution to mimic normal circadian cortisol exposure, and consolidating or eliminating doses to improve adherence. Conclusion This framework for reducing supraphysiologic GC doses in adult patients taking crinecerfont may become increasingly relevant as treatment of CAH shifts toward physiologic GC replacement with adjunctive control of adrenal androgens.

Hypertension is the main risk factor for cardiovascular disease (CVD), affecting 20–40% of Latin American (LATAM) adults, and responsible for more than two million deaths annually due to CVD. The different ethnic, economic, geographic, and cultural characteristics of the LATAM population influence the high prevalence of all cardiovascular risk factors (CVRF), particularly metabolic disturbances such as type 2 diabetes (DM2), obesity and the metabolic syndrome. Their main determinants in LATAM includes environment, food quality, social inequity, low education, political aspects, contextual behaviour, and genetics. The prevalence of overweight and obesity in LATAM increased during the last four decades reaching figures of 10–20% in childhood, 30–40% in adolescence, and 60–70% in adults. Many studies in the region have reported the extremely low rates of awareness, treatment, and control of CVRF in the general population of LATAM, particularly in patients with metabolic disorders, and the consequent high cardiovascular morbidity and mortality. This 2026 LATAM consensus is developed by a large group of experts from different LATAM countries, the USA and Europe, representing areas of internal medicine, cardiology, nephrology, endocrinology, geriatrics, paediatrics, pharmacology, and epidemiology. A careful search for novel studies in LATAM, together with new evidence that has emerged since the 2019 LATAM consensus, support the statements and recommendations in the current report. This update aims to provide clear and useful recommendations for health professionals to improve awareness, treatment, and control of hypertension and associated CVRF in the region.

Abstract Glioblastoma (GBM) remains the most common and lethal adult malignant primary brain cancer with few treatment options. A significant issue hindering GBM therapeutic development is intratumor heterogeneity and plasticity. GBM tumors contain neoplastic cells within a fluid spectrum of diverse transcriptional states. Identifying effective therapeutics requires a platform that predicts the differential sensitivity and resistance of these states to various treatments. Here, we develop scFOCAL (Single-Cell Framework for -Omics Connectivity and Analysis via L1000), to quantify the cellular drug sensitivity and resistance landscape. Using single-cell RNA sequencing of newly diagnosed and recurrent GBM tumors, we identify compounds from the LINCS L1000 database with transcriptional response signatures selectively discordant with distinct GBM cell states, and leverage this capability to predict combination synergy. We validate the significance of these findings in vitro, ex vivo, and in vivo, and use the Olig2 inhibitor CT-179 as a reference drug to identify additional small molecules that would maximize the cell-drug discordance across the GBM transcriptional landscape. Our analysis leads to the combination of Olig2 inhibition with treatment with Depatux-M, of with which we demonstrate synergy in vivo. Our studies suggest that scFOCAL identifies cell states that are sensitive and resistant to targeted therapies in GBM using a measure of cell and drug connectivity, which can be applied to identify new synergistic combinations. Citation Format: Robert K. Suter, Anna M. Jermakowicz, Rithvik Veeramachaneni, Matthew D'Antuono, Longwei Zhang, Rishika Chowdary, Simon Kaeppeli, Madison Sharp, Pravallika Palwai, Vasileios Stathias, Grace Baker, Luz Ruiz, Winston Walters, Maria Cepero, Danielle Burgenske, Edward B. Reilly, Anatol Oleksijew, Mark G. Anderson, Sion Ll. Williams, Michael E. Ivan, Ricardo J. Komotar, Macarena I. De La Fuente, Gregory Stein, Alexandre Wojcinski, Santosh Kesari, Jann N. Sarkaria, Stephan C. Schürer, Nagi G. Ayad. Drug and single-cell gene expression integration identifies heterogeneity-aware synergistic combinations for glioblastoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Brain Cancer; 2026 Mar 23-25; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(6_Suppl):Abstract nr B032.