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PURPOSE We tested the hypothesis that adding metastasis-directed therapy (MDT) to standard-of-care (SOC) systemic therapy improves progression-free survival (PFS) among patients with oligometastatic disease. METHODS EXTEND was a multicenter randomized phase II trial. Patients with 1-5 metastases were randomly assigned to MDT + SOC versus SOC in one of the six baskets (breast, pancreas, kidney, two prostate baskets, and an other basket) with basket-specific stratification and powering. PFS, the primary end point, was prespecified in the per-protocol set within each basket, across all baskets, and across all baskets excluding the prostate baskets. Exploratory end points included circulating tumor DNA (ctDNA) and immune profiling. RESULTS From 2018 through 2023, 521 patients were screened, 350 were randomly assigned, and 334 were analyzed per protocol (MDT + SOC, n = 166; SOC, n = 168). Radiotherapy was used as MDT for 98% of metastases (370/379). Overall, after a median follow-up of 53 months, PFS was improved with MDT + SOC (hazard ratio [HR], 0.54 [95% CI, 0.41 to 0.72], P < .001). Similarly, PFS was improved when excluding the prostate baskets (HR, 0.60 [95% CI, 0.40 to 0.89]). Within each basket, PFS superiority was identified for the pancreas, prostate, and other baskets, whereas the breast and kidney baskets were inconclusive. At enrollment, detectable ctDNA correlated with shorter PFS and survival; by contrast, ctDNA clearance 3 months postenrollment correlated with improved survival. MDT + SOC-induced systemic immune activation was most pronounced among baskets demonstrating PFS superiority. CONCLUSION The phase II EXTEND trial supports the addition of MDT to SOC for oligometastatic disease. Histology-specific efficacy signals were identified for phase III testing. Translational insights suggest the potential for optimizing the definition of oligometastasis using ctDNA and point to systemic immune responses as a possible mechanism of benefit from MDT.

Objectives To compare patients’ perception of their degree of subglottic stenosis to their endoscopic exam findings, Clinical Dyspnea Questionnaire, and peak flow results. Study Design Prospective Multi-Institutional. Setting Tertiary Care Clinic. Methods A study of 50 patients comparing patients’ perception of their degree of subglottic stenosis to their endoscopic exam findings. All patients filled out a Clinical Dyspnea Questionnaire and a 10-point scale reflecting their perceived degree of stenosis in 10% intervals. Surgeons filled out the same scale based on measurements from the patients’ exam. Accuracy was defined as +/-1 on a 10-point scale. Pulmonary function testing, number of dilation procedures undergone, cause of stenosis, and demographic information were collected. Results Data complete for 49/50 patients. 48 (98%) were female, 47 (97.9%) Caucasian, 44 (89.8%) had idiopathic subglottic stenosis, and 28 (58.3%) had Grade I subglottic stenosis on the Cotton-Meyer scale. Spearman correlation coefficient was 0.67 indicating moderate correlation overall but 0.88, or high correlation, for those with normal Body Mass Index. Increased Dyspnea Index scores and higher Body Mass Index were correlated with decreased accuracy. Number of previous procedures was not correlated with accuracy. Higher Body Mass Index was correlated with increased dyspnea and lower peak flow volume. Conclusion Patients with normal Body Mass Index have strong predictive accuracy regarding their degree of subglottic stenosis. Better dyspnea scores were correlated with improved accuracy. There is no standard consensus on subglottic stenosis patient follow up. Prior studies have looked at using peak flow meters and validated questionnaires to monitor symptoms.

OBJECTIVE The aim of this study was to evaluate freedom from tumor progression and clinical outcomes in older adults with small- to medium-sized vestibular schwannoma (VS) managed by observation versus stereotactic radiosurgery (SRS) to better inform optimal management in this patient population. METHODS In this international multicenter study, patients aged ≥ 60 years with Koos grade I or II VS managed by observation or SRS were retrospectively reviewed. Propensity score matching was conducted using patient characteristics, tumor size, and hearing assessments. Outcome measures of freedom from tumor progression, serviceable hearing preservation (SHP), and neurological function (tinnitus, vestibulopathy, House-Brackmann grade, and trigeminal nerve function) were assessed for both groups. RESULTS The observation and SRS groups each comprised 51 matched patients (median age 68 years for both). Ipsilateral serviceable hearing was observed at presentation for 35 patients in each group. The median follow-up duration was 39 months in the observation group versus 27 months in the SRS group (p = 0.5). Tumor progression was significantly lower with SRS than with observation (2% vs 52.9%, p < 0.001). The rate of 5-year freedom from tumor progression was 100% in the SRS group versus 43% (95% CI 29%–64%) in the observation group. The rate of 10-year freedom from tumor progression was 90% (95% CI 73%–100%) in the SRS group versus 20% (95% CI 8.5%–49%) in the observation group. At the last follow-up, hearing loss occurred in 42.9% of the observation group and 51.4% of those who underwent SRS (p = 0.5). The 3-year SHP rate was 68% (95% CI 53%–88%) versus 65% (95% CI 49%–85%) (p = 0.8), and the 5-year SHP rate was 53% in both groups (95% CI 36%–78% in the observation group and 95% CI 35%–79% in the SRS group, p = 0.8). The composite endpoint of tumor progression and/or worsened neurological outcome, including hearing loss, tinnitus, vestibulopathy, facial nerve dysfunction (House-Brackmann grade), or trigeminal dysfunction, demonstrated a significantly lower rate in the SRS group (17.6%) compared with the observation group (66.7%) (p < 0.001). CONCLUSIONS SRS in older patients for management of Koos grade I or II VS resulted in significantly superior rates of freedom from tumor progression, comparable hearing preservation rates, and significantly higher rates of favorable overall radiographic and neurological outcomes than observation alone. Compared with observation, SRS might be the preferred management option in this patient population.

ABSTRACT Novel β-lactam/β-lactamase inhibitors (βL/βLIs) are important therapies for carbapenem-resistant Pseudomonas aeruginosa (CRPA). However, the global extent of resistance to these agents and the impact of resistance on patient outcomes are unclear. We therefore evaluated patients with CRPA isolates at 35 hospitals (nine countries) from December 2018 to November 2019. Antimicrobial susceptibility testing was performed at a central laboratory by agar dilution for ceftolozane-tazobactam (C/T) and ceftazidime-avibactam (CZA) and by broth microdilution for imipenem-relebactam (I/R). Characteristics and outcomes, including desirability of outcome rankings (DOOR), were compared between patients infected with isolates not susceptible vs susceptible to each agent. Of 800 CRPA isolates, susceptibility to C/T, CZA, and I/R was 69%, 67%, and 33%, respectively. USA isolates ( n = 526) were more frequently susceptible to these agents than isolates from other countries ( n = 274; C/T: 83% vs 42%; CZA: 77% vs 47%; I/R: 37% vs 23%; P < 0.001 for each comparison) and isolates with carbapenemases ( n = 157) were less frequently susceptible than isolates without carbapenemases ( n = 643; C/T: 7% vs 84%; CZA: 24% vs 77%; I/R: 6% vs 39%; P < 0.001 for each comparison). Thirty-day mortality and DOOR were similar overall in patients infected with isolates not susceptible vs susceptible to each βL/βLI. However, the adjusted probability of a better DOOR outcome for a randomly selected patient with bacteremia due to a C/T-not susceptible vs -susceptible isolate was 38.2% (95% confidence interval, 25.6%–52.7%). Resistance to novel βL/βLIs, especially I/R, is common in CRPA, particularly outside the USA and in carbapenemase-producing isolates. Additional treatment options are needed for CRPA infections.

Preeclampsia (PE) is a multifactorial hypertensive disorder of pregnancy that significantly increases both short- and long-term cardiovascular risk for affected women. PE and cardiovascular disease (CVD) share common risk factors, including endothelial dysfunction, obesity, insulin resistance, and dyslipidemia. Women with a history of PE face a markedly elevated risk of chronic hypertension, heart failure, and adverse cardiac remodeling, with evidence suggestive of persistent vascular and myocardial changes after pregnancy. The complex pathophysiology of PE is multifactorial and is thought to involve a combination of abnormal placentation, immune dysregulation, and anti-angiogenic factors, which may induce permanent cardiovascular alterations. Genetic predispositions may further link PE with cardiomyopathies and peripartum cardiomyopathy. However, despite these well-established risks, standardized long-term surveillance and management strategies for women with prior PE remain lacking. Early identification and targeted intervention in women with a history of PE represent critical opportunities to mitigate future cardiovascular morbidity and mortality. This review highlights the urgent need for comprehensive, evidence-based strategies that incorporate personalized follow-up and risk stratification to improve cardiovascular outcomes in this high-risk population.

Abstract The growing availability of large-scale biomarker datasets has allowed data-driven methods to characterize Alzheimer’s disease biological heterogeneity. However, most prior studies have focused on cohorts of late-onset amnestic cases, leaving early-onset Alzheimer’s disease underexplored. We aimed to characterize tau-PET-based subtypes through a robust data-driven approach in the Longitudinal Early-Onset Alzheimer’s Disease Study. Baseline [18F]Flortaucipir PET scans from 365 amyloid-PET-positive participants with sporadic early-onset Alzheimer’s disease were quantified in the left and right medial temporal, lateral temporal, occipital, parietal, and frontal cortices. Tau PET values were z-scored against 85 amyloid-PET-negative cognitively normal age-matched participants and fitted into Subtype and Stage Inference (SuStaIn)—an unsupervised clustering algorithm that simultaneously models subtypes and progression from cross-sectional data. The derived subtypes were subsequently characterized by baseline and longitudinal clinical, cognitive, MRI, tau and amyloid PET features. We identified three tau-PET-based subtypes: on average, Subtype 1/Typical (n = 144, 40%) showed a predominant bilateral temporoparietal pattern typical of Alzheimer’s disease. Subtype 2/Left temporal (n = 111, 31%) showed predominant left temporal binding. Subtype 3/Posterior (n = 104, 29%) showed early and permeating occipitoparietal involvement. Subtypes did not differ in demographics or global amyloid burden, but were relatively more enriched for specific clinical presentations: S1/Typical for amnestic presentations, S2/Left Temporal for primary progressive aphasia, and S3/Posterior for posterior cortical atrophy. Baseline tau PET subtypes aligned with cortical atrophy patterns and domain-specific cognitive impairment. When follow-up tau PET scans were fitted to SuStaIn trained on baseline data, 85.6% (n = 172/201) of participants retained the same subtype classification, indicating subtype temporal stability, and progressed within subtypes by 0.56 ± 0.70 SuStaIn stage/year. Longitudinal voxel-wise linear mixed-effects modelling revealed tau accumulation patterns for each subtype in regions relatively spared at baseline: occipital lobe accumulation predominated in S1/Typical, bilateral frontal and right temporal in S2/Left Temporal, and bilateral frontotemporal lobes in S3/Posterior. All subtypes showed longitudinal increases in Clinical Dementia Rating-Sum of Boxes, but with slower worsening in S3/Posterior compared with the other subtypes. Our findings reveal robust subtypes in sporadic early-onset Alzheimer’s disease characterized by distinct spatiotemporal tau patterns that parallel differences in clinical presentations and trajectories of neurodegeneration. These subtypes extend beyond traditional clinical syndromes and support a more nuanced framework for individualized prognosis and care. Incorporating tau PET subtyping into clinical trial design could enable more targeted therapeutic approaches for this younger population.

Abstract Background: Immune checkpoint inhibitors (ICIs) have improved survival in non-small-cell lung cancer (NSCLC), yet only a subset of patients benefits, and biomarkers like PD-L1 remain limited. Here, we introduce a deep learning-based pathomics framework that utilizes routine H&E-stained slides to predict therapeutic response and survival outcomes in ICI-treated metastatic NSCLC. Methods: The study included 797 ICI-treated NSCLC patients from MD Anderson, with external validation in 280 patients from Mayo Clinic, Gustave Roussy, and the Phase III ICI-naïve LUSC Lung-MAP S1400I trial receiving nivolumab with or without ipilimumab. Path-IO (Pathology-Driven Immunotherapy Optimization) comprised of four major steps: (1) pathologist-verified tissue classifier segmented WSIs into eight compartments—Background, Bronchi, Immune, Lung, Necrosis, Stroma, Tumor, and Vessel—and was validated on TCGA and CPTAC dataset; (2) a survival prediction module generating patient-level risk scores in the MD Anderson cohort and validated across external datasets; (3) integration of Path-IO risk scores with radiomics and clinical features to improve prognostic accuracy; and (4) biological interpretability analyses correlating Path-IO risk immune contexture from multiplex immunofluorescence and transcriptomic signatures from NanoString profiling. Results: Path-IO effectively stratified patients into high and low-risk groups with significant survival differences. In the MD Anderson cohort, it achieved HR = 2.11 (p &lt; 0.001) and HR = 2.51 (p &lt; 0.001) for OS in the discovery and validation sets, and HR = 2.34 (p &lt; 0.001) and HR = 1.87 (p &lt; 0.001) for PFS, respectively. In the multicenter Phase III Lung-MAP S1400I trial, Path-IO achieved HR = 1.78 (p = 0.016) for OS and HR = 2.76 (p = 0.006) for PFS. In external validation, it predicted outcomes in the Gustave Roussy (OS = 1.97, p = 0.003; PFS = 1.51, p = 0.046) and Mayo Clinic (OS = 2.46, p = 0.007; PFS = 2.45, p = 0.027) cohorts. Path-IO outperformed PD-L1 and remained an independent predictor in multivariate analysis (p &lt; 0.001). It enabled data-driven frontline selection between anti-PD-1 monotherapy and chemo-immunotherapy, offering guidance toward more personalized treatment decisions. Integration with radiomics and clinical features further improved predictive accuracy (OS 0.63→0.75; PFS C-index 0.58→0.70), while high Path-IO risk scores correlated with immune-cold phenotypes identified by multiplex immunofluorescence and NanoString transcriptomics. Conclusions: Path-IO demonstrates that deep learning models rooted in histopathologic architecture can generate interpretable and biologically informed survival predictions in NSCLC treated with ICIs. By integrating pathology, radiology, and clinical data, Path-IO provides complementary predictive value beyond established biomarkers such as PD-L1. Citation Format: Rukhmini Bandyopadhyay, Linghzi Hong, Mihaela Aldea, Shenduo Li, Lodovica Zullo, Frank R. Rojas, Maliazurina B. Saad, Maricel C. Marin, Muhammad Waqas, Jiexin Zhang, Eman Showkatian, Claudio A. Arrechedera, Xiaoyu Han, Yuliya Kitsel, Sherif Ismail, Muhammad Aminu, Bo Zhu, Carol C. Wu, Brett W. Carter, Joe Y Chang, Zhongxing Liao, Maria R. Ghigna, Davide Soldato, Hai T. Tran, Xiuning Le, Tina Cascone, Bingnan Zhang, Haniel A. Araujo, Mehmet Altan, Simon Heeke, David Jaffray, Don L. Gibbons, Ara Vaporciyan, J Jack Lee, Neda Kalhor, Cara Haymaker, Ignacio Wistuba, John V. Heymach, Yanyan Lou, Natalie Vokes, Luisa M. Solis Soto, Jianjun Zhang, Jia Wu. Path-IO: A deep learning pathomics framework for personalized immunotherapy selection and outcome prediction in metastatic non-small cell lung cancer [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 4003.

ABSTRACT Objectives The increasing volume of medical education research necessitates efficient, reliable, and scalable methods for conducting quality appraisals. The Medical Education Research Study Quality Instrument (MERSQI) is a widely used tool, although its manual scoring process remains resource‐intensive. This study evaluated how well large language models (LLMs) appraise medical education research using the MERSQI tool in comparison with human judges. Methods Three LLMs (GPT‐5, Claude Sonnet 4, and Gemini 2.5 Pro) assigned MERSQI domain scores to 1423 medical education research articles. The authors compared AI‐generated scores with human‐generated scores using intraclass correlation coefficients (ICCs) across the six MERSQI domains. They evaluated the agreement between AI‐ and human‐generated MERSQI composite scores using Bland–Altman plots. Results Domain‐level ICC values ranged from fair (0.24) to near perfect (0.81), with the lowest agreement observed in the ‘sampling,’ ‘validity evidence,’ and ‘data analysis’ domains. No single LLM consistently outperformed the others across all domains. Composite score agreement with human ratings was substantial and similar across LLMs (ICC range: 0.65–0.69). GPT‐5 produced slightly lower composite scores than humans, while Claude Sonnet 4 and Gemini 2.5 Pro produced higher scores, with Gemini showing the largest deviation. The Bland–Altman plots for Gemini 2.5 Pro suggested proportional bias, indicating its agreement with human scores varied across the range of study quality. Conclusions These LLMs demonstrated substantial agreement with human raters for MERSQI composite scores, but domain‐level agreement varied. Systematic differences in scoring patterns highlight the need for human oversight and additional calibrations before integrating LLMs into systematic review appraisal workflows.

Background: Although donor and recipient characteristics are used to estimate graft failure risk, they remain limited in predicting early acute rejection. We developed and validated a next-generation sequencing (NGS) assay targeting the pre-transplant immunologic profile to predict early acute rejection following kidney transplantation. Methods: This prospective, international study enrolled 321 kidney transplant participants across 13 sites, forming discovery and validation cohorts. Peripheral blood was collected prior to transplant and at 1, 3, 6, 12, and 24 months post-transplant, with protocol biopsies performed at 3 and 12 months, as well as any indication biopsies. Biopsies were assessed by a blinded central pathologist according to the 2019 Banff criteria. The pre-transplant risk assessment (PTRA™) test to evaluate RNA expression of a 29-gene signature algorithm designed to predict early acute rejection risk was clinically validated utilizing 122 deceased donor kidney transplant recipients. Results: PTRA classified 31 of 122 participants (25%) as high-risk and 91 (75%) as low-risk. There were 9 early acute rejection events in the first 60 days post-transplant: 6/31 (19%) in the high-risk group and 3/91 (3%) in the low-risk group. PTRA discrimination for early acute rejection at 60 days post-transplant yielded an AUC of 0.78 (95% confidence interval [CI]: 64.4 to 91.5), p<0.001. A cut-off of ≤45 was defined as low-risk and >45 as high-risk for early acute rejection within 60 days post-transplant. Sensitivity 0.67 (95% CI: 0.36 to 0.97), specificity 0.78 (95% CI: 0.70 to 0.86), positive predictive value 0.19 (95% CI: 0.05 to 0.33), and negative predictive value 0.97 (95% CI: 0.93 to 1.00). The odds ratio comparing patients identified as high- vs low-risk by PTRA was 7.04 (95% CI: 1.64 to 30.2), p=0.009. Conclusions: This study validates the ability of PTRA to stratify kidney transplant recipients as high- or low-risk for early acute rejection using a pre-transplant transcriptomic profile, with implications for graft health and personalized treatment management.

Abstract A working group of cIMPACT-NOW evaluated the literature on IDH-mutant gliomas for opportunities to improve pathology-based risk stratification and grading, especially at the interface of CNS WHO grades 2 and 3, since therapeutic decisions depend on risk assessment for clinical management. The group also evaluated newly described IDH-mutant glioma subgroups and considered multidisciplinary aspects of therapeutic decision-making. PDGFRA amplification was associated with highly aggressive clinical behavior of IDH-mutant astrocytomas, consistent with CNS WHO grade 4. Other genetic alterations associated with intermediate risk and most consistent with CNS WHO grade 3 included PIK3 mutations; EGFR alteration; MYCN amplification; and specific retinoblastoma pathway alterations, including CDK4, CDK6, and CCND2 amplification, RB1 homozygous deletion or mutation, and mutation of CDKN2A. DNA methylation signatures of G-CIMP-low or A_IDH_HG were consistent with CNS WHO grade 3 or 4, depending upon other grading criteria. We suggest a mitotic count of ≥3 per 2.4 mm2 could be considered as a CNS WHO grade 3 criterion. Our review did not uncover features to improve the grading of oligodendroglioma, IDH-mutant and 1p/19q-codeleted, although CNS WHO grade 3 tumors with elevated mitotic rates, yet lacking necrosis, microvascular proliferation, CDKN2A/B homozygous deletion, and MRI contrast enhancement, may be associated with extended survival. Implementing evidence-based criteria for risk stratification and grading will improve guidance for clinical decision-making.