Citations

Abstract Background Traumatic brain injury (TBI) in older adults is associated with high mortality and poor functional outcomes. However, optimal management remains uncertain, as evidence comparing surgical and medical strategies is limited, heterogeneous, and extrapolated from younger populations. We conducted a systematic review and meta-analysis to compare outcomes between surgical and medical management in this population. Methods PubMed, Embase, and Web of Science were searched from database inception to December 8, 2025. Studies including adults aged ≥60 years with TBI comparing surgical versus medical management were included. The primary outcome was favorable neurological outcome, while secondary outcomes included hospital length of stay (LOS) and mortality. Pooled estimates were calculated as risk ratios (RR) and mean differences (MD) using random-effects models with restricted maximum likelihood and Hartung–Knapp adjustment. Results Sixteen cohort studies comprising 132,823 patients were included. Surgical management was not associated with improved favorable neurological outcomes at discharge, 3, 6, or 12 months. However, it was associated with longer LOS (MD = 6.35 days, 95% CI: 2.55 to 10.14; p < 0.01). No differences were observed in in-hospital, 30-day, 3-month, 12-month, or 24-month mortality. Notably, surgical management was associated with a reduction in 6-month mortality (RR = 0.68, 95% CI: 0.51–0.92; p = 0.02). Conclusions In older adults with TBI, surgical management was associated with reduced 6-month mortality and longer hospital LOS, but not with improved functional outcomes, highlighting a dissociation between survival and recovery. This dissociation has implications for clinical decision-making and patient and family counseling. Individualized decision-making that incorporates frailty, comorbidities, and potential reversibility of injury is essential, rather than relying solely on age. While this study represents the best available comparative evidence to date on surgical versus non-surgical management in older adults with TBI, findings should be interpreted with caution due to heterogeneity and low to very low certainty of the evidence. High-quality randomized controlled trials are needed to better define the role of surgery in this population.

Introduction: Although the role of cardiometabolic risk factors (CMRF) has been characterized in steatotic liver disease, their role in the severity of alcohol-associated hepatitis (AH) remains unclear. We aimed to evaluate the impact of CMRF on mortality. Methods: Multinational prospective cohort study (2015–2024) including hospitalized patients with severe AH across 32 centers in 14 countries. Diagnosis of AH was made using the NIAAA criteria. Analyses included adjusted competing-risk models by age, sex, ethnicity, history of cirrhosis, CMRF, corticosteroid use, MELD, and ACLF grade, with liver transplantation as a competing risk. Results: 936 participants were included; mean age 48±11.2 years, and 88.9% were male. At least one CMRF was present in 46.6%; median body mass index (BMI) was 24.2 kg/m 2 [IQR: 22.8–28.2], prevalence of diabetes 17.6%, hypertension 16.5%, and dyslipidemia 5.8%. Median MELD was 24.4 [19.3–31.4], 86.7% had severe AH, and 180-day survival was 72.9%. Survival did not differ by CMRF status (log-rank p =0.453). In adjusted competing-risk models, higher age (sHR 1.02; 95%CI:1.01–1.04), greater alcohol intake (per g/day; sHR 1.001; 95%CI:1.000–1.002), MELD (sHR 1.04; 95%CI:1.01–1.06), and ACLF grade 2–3 (sHR 2.34 and 4.34) predicted mortality. However, no individual CMRF independently increased mortality. A prespecified non-linear BMI analysis showed modestly lower mortality between 25–40 kg/m², with a higher risk above 40 kg/m². Conclusion: Among patients with severe AH, metabolic dysfunction was not associated with increased mortality. Although a higher BMI was associated with slightly lower mortality in AH, this may reflect better nutritional status rather than a true protective effect.

ABSTRACT Bispecific T cell engagers (BTEs) induce MHC‐independent cytotoxicity by bridging T cells to tumor cells via binding a T cell–activating receptor and a tumor‐associated antigen. BTEs have proven effective in hematologic malignancies and some solid tumors, yet their potential in glioblastoma (GBM) is largely unexplored. We developed a fully humanized BTE (hBTE) targeting interleukin‐13 receptor alpha 2 (IL13RA2), a tumor‐associated antigen widely expressed in GBM and associated with poor prognosis. In vitro, hBTE activated T cells and induced antigen‐dependent cytokine release and cytotoxicity against IL13RA2‐positive GBM cells. In vivo, hBTE showed robust target‐specific activity and markedly prolonged survival in primary and recurrent GBM xenograft models, without detectable off‐target local or systemic toxicity. Beyond GBM, hBTE also exhibited antitumor activity in IL13RA2‐expressing solid tumors, demonstrating selective tumor accumulation and therapeutic efficacy in models of breast cancer brain metastases and extracranial lung cancer. This work highlights the therapeutic potential of BTEs in IL13RA2‐expressing tumors and establishes a strong preclinical rationale for advancing hBTE therapy toward clinical translation in GBM and other tumors.

Abstract Spatial transcriptomics links gene expression to tissue architecture, providing a mechanistic view of cellular organization. Yet existing datasets cover few donors and miss the complexity of human disease. Experimental costs remain prohibitive, and large-scale profiling is impractically slow for population-level studies. Accurate computational methods are urgently needed. Predicting gene expression from standard histology, however, remains an open problem, as current approaches transfer poorly to unseen cohorts and diseases. Here, we present Phoenix, a (latent) flow matching generative model that infers pan-cancer spatially resolved single-cell gene expression with high accuracy. Phoenix analyzes treatment response in silico: Applied to 763 head and neck cancer patients, it identified three new spatial biomarkers that we validated across two cancers (breast cancer, n = 84; ovarian cancer, n = 157) and treatment regimens (platinum, trastuzumab). Phoenix generalizes beyond carcinomas: In a large sarcoma cohort (802 tissue microarray cores), it accurately predicted cell-type-specific signatures in held-out samples and captured chemotherapy-induced immune remodeling. Phoenix also extends across species: In a mouse model, it accurately predicted the expression of pancreatic cancer lineage markers and the mutant mKras^G12D allele in silico. In total, we evaluated Phoenix on over 10,000 patients. Our results establish virtual spatial transcriptomics as a scalable framework for studying tissue organization, therapeutic response, and disease mechanisms.

INTRODUCTION: Nosocomial infections (NIs) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have failed to identify high-risk patients. We aimed to develop machine learning (ML) models to predict NI. METHODS: The CLEARED consortium consists of prospectively enrolled cirrhosis inpatients from >120 centers. Using day-of-admission clinical data, 3 ML approaches (random forest [RF], extreme gradient boosting, and neural networks [NNs]) were used to predict NI. Data were split 80:20 for training and testing stratified by the outcome. Models were compared using area under the receiver operating characteristic curve (AUC). RESULTS: In total, 8,263 patients (55.90 ± 13.34 years; 64.1% men) from 127 centers in 37 countries were included. NI developed in 869 (10.5%), a median of 6 (4–11) days of postadmission. Major NIs were respiratory (29.6%) and urinary tract infection (15.7%), and spontaneous bacterial peritonitis (13.5%). NIs occurred more frequently in patients from low/low-middle income countries and those with severe liver disease, alcohol etiology, and admission infections. NIs were associated with inpatient mortality (31.9% vs 8.1%, P < 0.001) and liver transplantation (4.8% vs 1.9%, P < 0.001). Although the RF model (AUC 0.69) showed good calibration (Brier score 0.09), outperforming extreme gradient boosting, neural network, and LR models (AUC 0.66 for all; LR comparison P = 0.043), no model achieved AUC ≥0.80 for clinical utility. At 10% predicted probability threshold, the RF model demonstrated only 75.4% sensitivity, 52.9% specificity, and 15.9% positive predictive value (PPV). DISCUSSION: NIs cannot be accurately predicted from day-of-admission data using ML models, even in a large, prospective, global cirrhosis cohort. Every hospitalized patient with cirrhosis should receive protocolized infection control measures.

ABSTRACT Background Metabolic dysfunction‐associated steatotic liver disease (MASLD) exhibits marked heterogeneity in fibrosis progression and liver‐related outcomes. Liver biopsy is not feasible for longitudinal risk stratification at scale, creating a need for validated non‐invasive biomarkers, particularly imaging biomarkers, that can predict clinically meaningful disease progression and liver‐related outcomes. Aims To describe the design and rationale of the GOLDMINE study, established to determine whether non‐invasive imaging biomarkers predict MASLD progression and liver‐related clinical outcomes. Methods GOLDMINE is an investigator‐initiated, multi‐centre, international longitudinal cohort enrolling up to 1000 adults with either biopsy‐proven MASLD or MASLD cirrhosis across the full fibrosis spectrum. Participants are recruited from 15 sites in the US and 4 international sites (Japan, Singapore and France). At baseline, participants undergo clinical phenotyping, vibration‐controlled transient elastography, and advanced magnetic resonance imaging (MRI), including proton‐density‐fat‐fraction and magnetic resonance elastography (MRE). MRI (and biospecimen banking) is repeated at 2‐year intervals (years 2 and 4), with annual follow‐up visits for up to 10 years. Baseline liver histology is centrally processed, digitized and reviewed by a single expert hepatopathologist; all MRI/MREs are centrally interpreted. Results The prespecified clinical outcomes include progression to cirrhosis, clinically significant portal hypertension, major adverse liver‐related outcomes (ascites, hepatic encephalopathy, portal hypertensive bleeding, liver transplantation/qualification), hepatocellular carcinoma, major adverse cardiovascular events, and all‐cause mortality, with independent central adjudication of all events. Conclusions GOLDMINE establishes a rigorously phenotyped MASLD cohort integrating centralized histology, advanced MRI‐based biomarkers, longitudinal biobanking, and adjudicated outcomes, providing a platform to validate imaging and blood‐based prognostic biomarkers in MASLD.

Abstract Background: In Part 2 of the phase 2 RELATIVITY-104 study of first-line nivolumab (NIVO) plus relatlimab (RELA) with platinum-doublet chemotherapy (PDCT) vs NIVO + PDCT in patients with metastatic NSCLC, NIVO + RELA + PDCT demonstrated improved clinical benefit, including overall survival, in the prespecified subgroup of tumor PD-L1 expression ≥ 1%, which was further enriched in NSQ tumor histology. Baseline lymphocyte-activation gene 3 (LAG-3) expression was associated with enriched efficacy for both NIVO + RELA + PDCT and NIVO + PDCT. In a comparative transcriptomic analysis, NSQ and squamous tumors demonstrated distinct immune signatures, with NSQ tumors exhibiting higher expression of LAG-3 ligands and greater enrichment for combination therapy benefit by PD-L1 expression. To further elucidate the mechanism of action of NIVO + RELA + PDCT, we report additional exploratory translational data in the PD-L1 ≥ 1% NSQ subgroup for Part 2 of RELATIVITY-104. Methods: Patients with untreated metastatic NSCLC were randomized 1:1 to NIVO 360 mg + RELA 360 mg + PDCT or NIVO 360 mg + PDCT Q3W. Exploratory endpoints included translational analyses in the PD-L1 ≥ 1% NSQ subgroup. Gene expression data from pretreatment tumor RNA sequencing were normalized and analyzed for associations with clinical outcomes. Pre- and on-treatment peripheral blood samples were collected for high-dimensional flow cytometry immunophenotyping using a validated 24-marker LAG-3-specific panel that used drug-tolerant, noncompeting clones for LAG-3, PD-1, and CTLA-4. Statistical associations between biomarkers and clinical outcomes were assessed using logistic regression and Cox proportional hazards models. Data are from the May 2, 2025, database lock. Results: In the NIVO + RELA + PDCT arm, immune signatures demonstrated a significantly lower hazard ratio (HR) in the PD-L1 ≥ 1% NSQ subgroup, while stromal signatures demonstrated a significantly higher HR. T exhausted progenitor signature subsets, as well as ICOS+ CD4+ T cells, at baseline were shown to enrich for survival with NIVO + RELA + PDCT. Clinical benefit was observed across all baseline LAG-3 expression levels (&lt; 1% and ≥ 1%); however, on-treatment increases in LAG-3+ T cells were associated with longer progression-free survival and a higher objective response rate with NIVO + RELA + PDCT. In the NIVO + PDCT arm, increases in LAG-3 cell populations were associated with lower response. Conclusions: In the RELATIVITY-104 study, the on-treatment immune dynamics of LAG-3+ T cells correlated with the benefit of NIVO + RELA + PDCT vs NIVO + PDCT in patients with PD-L1 expression ≥ 1% and NSQ NSCLC. Immune signatures including progenitor T exhausted signatures associated with improved outcomes with NIVO + RELA + PDCT. These data support the mechanistic rationale for adding anti-LAG-3 to anti-PD-1 + PDCT in PD-L1 ≥ 1% NSQ NSCLC. Citation Format: Jaclyn Neely, Annie Yu, Nicolas Girard, Manuel Cobo-Dols, Mauricio Burotto, Luis Paz-Ares, Vamsidhar Velcheti, Martin Reck, Srijata Samanta, Anila Qureshi, Priyanka Kasbekar, Charlie Garnett-Benson. RELATIVITY-104 Part 2: translational analyses in the programmed death ligand 1 (PD-L1) ≥ 1% and non-squamous (NSQ) non-small cell lung cancer (NSCLC) subgroup [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB418.

Abstract Background and Aims Stroke and systemic embolism are recognized but poorly characterized complications of atrial fibrillation (AF) and left atrial flutter (AFL) catheter ablation. Their incidence, outcomes, and procedural associations remain insufficiently defined. Methods Retrospective global registry was initiated by the European Heart Rhythm Association Scientific Committee. A secure database captured data from ablation centres worldwide on general AF and left AFL ablation activity, as well as detailed information on patients with symptomatic embolic events between 2017 and 2024. Results Overall, 204 centres reported 335 743 ablation procedures and 550 embolic events (incidence 0.16%). Centre-level rate ranged from 0% to 3.1%. Most events were cerebral (94%), followed by peripheral (5%), and combined (1%). Coronary air embolism accounted for 62% of all peripheral events. Intraprocedural events occurred in 93 patients (17%), within 72 h in 357 (78%) and beyond 72 h in 100 (22%); 128 cases (23%) were diagnosed after hospital discharge. Nonparoxysmal AF (0.23% vs 0.15%; P &lt; .001), centre experience, and ablation energy source (radiofrequency, 0.16%; cryoballoon, 0.16%; pulsed field ablation, 0.25%; laserballoon, 0.88%; P &lt; .001) were associated with embolic risk. Median NIHSS score after stroke was 4 (interquartile range, 2–9). Three-month follow-up was available for 518 patients with embolism (95%): 181 (35%) had sequelae and 16 (3%) died. Conclusions Symptomatic embolic events are infrequent but associated with significant morbidity and mortality. Most events occur early, though a substantial proportion arise later. Higher event rates were observed with laser and possibly with pulsed field ablation. A greater centre experience was associated with a lower embolism incidence.

Abstract Background Robotic left pancreatectomy (RLP) is increasingly adopted worldwide. Current guidelines suggest a learning curve of 21 cases, yet its impact on major morbidity and oncological quality remains uncertain. Methods A retrospective multicentre international study was undertaken across 10 centres in the UK, Spain, Germany, the USA, and Australia (2014–2025). Consecutive patients undergoing RLP were categorised into competency (first 21 cases per centre) or proficiency phase (&gt;21). The primary outcome was major morbidity (Clavien–Dindo grade ≥ IIIa), and secondary outcome was the R1-margin rate. Mixed-effects logistic regression and risk-adjusted cumulative sum (RA-CUSUM) analyses were performed. Results 521 patients underwent RLP, including 200 (38.4%) in the competency phase and 321 (61.6%) in the proficiency phase. Median age was 63 years (IQR 54–73), and 56.4% were female. Rates of major morbidity were similar between phases (14.5% versus 14.0%, P = 0.981), as were R1 margin rates (21.6% versus 19.7%, P = 0.092). Independent predictors of major morbidity included male sex (OR 1.76, P = 0.037), preoperative pancreatitis (OR 2.23, P = 0.031), and multivisceral resection (OR 2.29, P = 0.034). Among patients with adenocarcinoma (n = 110), prolonged operative time (OR 1.39 per hour, P = 0.004) and nodal positivity (OR 2.62, P = 0.047) predicted R1 resection, while learning phase was not associated with margin status. RA-CUSUM demonstrated no excess morbidity over time in any centre. Conclusions In this first multicentre international analysis, the learning phase of RLP did not increase the risk of major morbidity or compromise oncological quality. These findings support the safe global adoption of RLP with appropriate training and case selection.