Citations

Abstract Rationale Lymphangioleiomyomatosis (LAM) is a rare, progressive, cystic lung disease affecting women. Sirolimus has been shown to stabilize lung function in women with LAM, but real-world data on long-term safety and efficacy are limited. Methods The NIH Multicenter Safety and Durability of Sirolimus for LAM (MIDAS, NCT02432560) observational registry was launched in 2015. All adult (≥18 years) women with LAM (treated or untreated) were eligible to enroll at any of the 20 U.S. sites and followed longitudinally with serial assessments of lung function, health-related quality of life, and treatment related adverse event (TRAEs). Baseline cohort characteristics and TRAEs are summarized using descriptive analyses. Marginal structural models (MSMs) with inverse probability of treatment weighting estimated the causal effect of sirolimus on annualized forced expiratory volume in one-second (FEV1) decline, adjusting for age at LAM diagnosis, prior treatment with sirolimus, menopausal status, race, presence of angiomyolipomas, supplemental oxygen use; time-varying covariates included diffusing capacity for carbon monoxide (DLCO) and serum vascular endothelial growth factor-D (VEGF-D) levels. Results Longitudinal data was available in 350 LAM patients, most of whom (246, 70.3%) had sporadic LAM. The median age at the baseline pulmonary function test (PFT) measurement was 46 years (range: 19 - 74) and the median (IQR) number of serial PFTs obtained per patient was 3 (1 - 5). The average follow-up duration per patient was 2.8 years. Over half of the patients (196, 56%) were treated with sirolimus during the MIDAS observation period for a median (IQR) treatment duration of 4.9 (2.4 - 7.5) years. MSM analysis demonstrated that sirolimus treatment was durably effective and reduced FEV₁ decline by 74.36 mL/year (95% CI: 15.87 - 132.85) compared with no treatment (-85.31 mL/year for the untreated group vs. -10.95 mL/year for the treated group, p = 0.01). Sirolimus was generally well tolerated; treatment interruption ≥3 months was observed in 38 (19.4%) of the 196 sirolimus treated patients. Logistic regression analysis showed that higher levels of FEV1 (odds ratio: OR = 3.12 [1.45 - 7.11], p = 0.005), VEGF-D (OR = 1.0007 [1.0004 - 1.001], p < 0.001), and DLCO (OR = 1.023 [1.0053 - 1.0413, p = 0.01]), were associated with treatment interruption. Conclusions In the MIDAS cohort, sirolimus treatment resulted in durable stabilization of lung function with a favorable safety profile over a 5-year period. These real-world data support sirolimus as a chronic suppressive therapy for LAM, demonstrating durable efficacy in slowing lung disease progression and tolerability with long-term use. This abstract is funded by: National Institutes of Health

PURPOSE External beam radiation therapy (EBRT) has gained delayed acceptance as a recommended first-line treatment modality for patients with hepatocellular carcinoma (HCC), given limited evidence that it improves overall survival (OS). We analyzed individual patient data (IPD) from an international cohort to assess OS among patients with HCC treated with EBRT. METHODS We performed a systematic review of publications that assessed EBRT, met prespecified technical standards for HCC, and reported OS (search date December 15, 2022). Corresponding authors were invited to submit IPD for the study. We performed Kaplan-Meier survival analyses to determine OS and restricted mean survival time (RMST) stratified by Barcelona Clinic Liver Cancer (BCLC) stage and treatment status (ie, treatment-naïve and experienced). We performed random effects Cox proportional hazards modeling to assess clinical characteristics associated with OS. RESULTS Data were provided on 4,913 patients treated with EBRT with a median follow-up time of 5.0 years. The median OS was 6.8 years (95% CI, 5.7 to 8.7) for BCLC-0 and 4.6 years (95% CI, 4.1 to 5.1) for BCLC-A. Among treatment-naïve patients, the median OS was not reached (95% CI, 8.6 to not reached) for BCLC-0 and was 5.4 years (95% CI, 4.5 to 6.7) for BCLC-A. In multivariable models, more advanced BCLC stage, higher tumor burden, worse performance status, and Child-Pugh class B or C were associated with a higher risk of mortality. Ablative radiation dose and more recent year of treatment were associated with a reduced risk of death. CONCLUSION To our knowledge, this study represents the largest multinational cohort of patients with HCC treated with EBRT. OS outcomes with EBRT for very early- and early-stage HCC appear to be comparable with resection, thermal ablation, and other ablative locoregional therapies. These data support the inclusion of EBRT in the BCLC HCC clinical decision-making process.

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.

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 Background Lung cancer is the leading cause of cancer-related death, and the most common cancer diagnosed globally. Approximately 85% of lung cancer cases are non-small cell lung cancer (NSCLC). After initial surgical treatment, adjuvant therapy with conventional or targeted chemotherapy can help optimize survival. These treatments, however, must be tailored to each patients’ problematic situation, including cancer characteristics and goals of care. Shared decision making (SDM) is a method of care by which patients and clinicians work together to form plans of care that advance the patient’s problematic human situation. This method often requires evaluating alternative options, “trying them on” for fit given their practical demands and favorable and unfavorable effects. Tools used within the encounter can facilitate and support SDM conversations, yet none exist for considering care post-surgical treatment of NSCLC. Therefore, we aimed to evaluate the effectiveness of a novel encounter tool for SDM, NSCLC Choice, compared to usual care at improving SDM and reducing decisional conflict for patients with resected early-stage NSCLC considering adjuvant treatment. Methods We will conduct a parallel, patient-level randomized trial comparing NSCLC Choice with usual care. Patients will be eligible if they are adults with stage >1B NSCLC eligible for postsurgical adjuvant chemotherapy. Allocation will be central and post-consent. Patients will be blinded to our trial hypothesis, instead of being invited to evaluate an educational intervention. Our primary outcome is SDM quality, which we will assess using participant reported measures (patient SDM-Q-9) obtained immediately post-encounter and an observer measure estimated from video recording of trial encounters in both arms (OPTION12). With resources to conduct a 100-patient trial, we will have >80% power to detect a 12-point medium difference between arms in patient-reported SDM-Q-9. We will also assess the secondary outcomes of knowledge about the disease and the features of treatment options using an ad hoc questionnaire, decisional conflict using the Decisional Conflict Scale, and patient and clinician satisfaction using the metrics used in prior SDM intervention trials. We will also determine encounter length using video recordings. Discussion In testing NSCLC Choice, we seek to determine the extent to which this intervention can improve care for patients with NSCLC considering adjuvant therapy after surgery. In addition, we expect to determine whether this intervention is satisfactory to participants and feasible in practice. If successful, this study will result in an evidence-based tool for promoting patient-centered conversations around NSCLC and cancer care those fits. Trial Registration: NCT06122064 ClinicalTrials.gov

Abstract Background The Global Bipolar Cohort (GBC) was established to identify existing bipolar disorder (BD) cohorts worldwide and foster collaborations focused on descriptive and analytic outcomes relevant to BD. A distributed analytic framework has been implemented to engage multiple sites without the need for central data pooling. This report describes the GBC endeavor and global functional impairment patterns. Cross-cohort comparisons of functional correlates are limited by heterogeneous measures and data-sharing constraints. Large, culturally diverse comparisons are needed to distinguish broadly reproducible correlates from cohort-specific effects. Participating sites completed a 28-item descriptive survey covering diagnostic methods, cognition, genetics, treatment, functioning, and follow-up strategies. We implemented a harmonized local logistic regression model of dichotomized functional outcome and shared summary statistics only. Results We identified 69 cohorts across five continents. Thirty-seven cohorts contributed functional outcome analyses from 17,130 participants. Outcome measures included clinician-rated disability scales and social indicators such as employment and marital status. The proportion classified with poor functioning ranged from 16% to 77% (mean 50%). In 32 of 37 cohorts, the overall regression model significantly explained variance in functioning. Current depressive symptoms were the most robust and reproducible correlate of poor functional outcome: they were assessed in 29 cohorts, significant in 22 (75.8%), ranked among the top three correlates in 22, and were the top-ranked correlates in 19. Associations between depressive burden and poor functioning were observed across clinician-rated disability scales and work or social indicators, and across geographically diverse cohorts. Comorbid substance use disorder and medication-related variables were associated with poorer functioning in subsets of cohorts, whereas sex, ancestry, bipolar subtype, psychosis history, and premorbid IQ showed weak or inconsistent associations. Cognitive measures, available in a minority of regression models, showed modest and non-uniform effects. Conclusions Across heterogeneous international cohorts, current depressive symptom burden emerged as the most consistent correlate of poor functioning in bipolar disorder. These findings replicate earlier multisite work at a larger scale, show that protocol-based distributed analyses can identify reproducible clinical signals without sharing individual-level data, and support prioritizing detection and treatment of depressive symptoms when aiming to improve real-world functioning. Future work should expand longitudinal harmonization and representation of under-studied populations.