Citations

ABSTRACT Commercial antimicrobial susceptibility testing (AST) systems for gram-negative bacteria provide operational advantages over reference broth microdilution (BMD) testing, but the results produced by commercial AST systems might not be as accurate as the reference method. Assessing and comparing the performance of AST systems can be informative for clinical microbiology practice. In total, 280 clinical isolates and 100 isolates from the U.S. Centers for Disease Control and Prevention Antimicrobial Resistance Isolate Bank, including Enterobacterales and Pseudomonas aeruginosa, were intended to be tested using disk diffusion (DD) and automated commercial AST systems, such as Selux AST System (Selux Diagnostics), MicroScan (Beckman Coulter), Phoenix (Becton, Dickinson and Company), and Vitek 2 (bioMérieux). These results were compared to BMD as the reference standard. In total, 372 isolates were assessed. For Enterobacterales, the greatest frequency of very major errors was identified with cefepime by Vitek 2 (29.0%) and ertapenem by DD (9.1%); essential agreement less than 90% was identified with the following combinations: aztreonam by MicroScan (86.4%), aztreonam by Vitek 2 (88.9%), cefepime by Selux (86.3%), cefepime by Vitek 2 (76.8%), ceftazidime by Vitek 2 (89.9%), and levofloxacin by MicroScan (83.4%). For P. aeruginosa , essential agreement less than 90% was identified with the following combinations: gentamicin by Selux (87.2%), tobramycin by Selux (86.6%), and ciprofloxacin by Phoenix (88.4%). Overall, antimicrobials that had low demonstrable bias across all automated commercial AST systems included ampicillin, amoxicillin-clavulanate, ceftazidime-avibactam, ertapenem, and trimethoprim-sulfamethoxazole. Comparing commercial testing systems head-to-head against a reference standard provides insight into the strengths and weaknesses of the performance of these test systems, and these insights can subsequently inform local decisions regarding further investigations and potential operational mitigation strategies. IMPORTANCE This study assessed and compared the performance of multiple commercial antimicrobial susceptibility testing (AST) systems and disk diffusion methods. The accuracy of determining minimum inhibitory concentrations or zone diameters of antimicrobials and the associated interpretive categories were studied for 372 isolates of Enterobacterales and Pseudomonas aeruginosa . Performance of the evaluated systems revealed that multiple antimicrobial-organism combinations were below the standards typically required by regulatory agencies and clinical laboratories. These deficiencies varied across the commercial platforms and disk diffusion methods, highlighting the importance of benchmarking studies that compare the performance using identical isolates. These identified performance weaknesses may warrant further study and/or the implementation of mitigation strategies in clinical laboratory operations to prevent the reporting of errant results.

Abstract Cancer outcomes vary widely between individual patients, each accumulating an irregular record of treatments, diagnoses, measurements, and complications. Current prognostic models reduce this complexity into a single snapshot, focus on narrow clinical settings, and rarely generalize across hospitals. Here we introduce Chronicle , an explainable transformer that learns from entire patient trajectories to predict diverse clinical outcomes throughout the disease course while capturing both short- and long-term temporal dependencies. Trained on 53.7 million longitudinal data points from 51,711 patients spanning 67 cancer types, Chronicle operates natively on irregular data without imputation and jointly predicts eight endpoints within a flexible framework adaptable to additional outcomes. Chronicle outperformed cross-sectional models for overall survival prediction (C-index 0.84 vs 0.76-0.79), stratified patients more accurately than established prognostic systems, including TNM stage, and predicted seven adverse event and transfusion endpoints (AUC 0.80-0.92). Applied without retraining to 69,341 patients in Germany, Switzerland, and the United States, Chronicle generalized across healthcare systems and improved further with local fine-tuning. Integrated explainability traced each risk update to patient-specific clinical factors, revealing distinct temporal persistence of prognostic information, with relevance half-lives ranging from weeks for therapies to nearly one year for baseline characteristics. These findings demonstrate that learning from hospital-wide patient trajectories enables interpretable and continuously updated predictions, providing a scalable framework to support individualized treatment decisions.

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.

Abstract Background The Charlson comorbidity index (CCI) is a validated weighted measure of comorbidity burden, but has an unclear role in heart failure (HF). Objectives To characterize age-adjusted CCI (ACCI) in HF, its association with the use of guideline-directed medical therapy (GDMT) and with outcomes. Methods In the Swedish HF registry, patients were divided into 3 groups based on ACCI scores (low 1-3, intermediate 4-6, and high ≥7). We studied its association with clinical characteristics and GDMT use. Multivariable multinominal and Cox regressions were used to analyze ACCI and its association with ejection fraction (EF) category (reduced [HFrEF], mildly reduced [HFmrEF], preserved [HFpEF]), and with outcomes up to 3 years. Results Among 117,419 patients (age 75 [66-82], 36% women, 53% HFrEF, 24% HFmrEF, 23% HFpEF, median ACCI was 5, 6 and 6 respectively. ACCI ≥7 was present in 31% with HFrEF, 35% with HFmrEF and 42% with HFpEF. A higher ACCI score was associated with higher EF category, NYHA class, serum NT-proBNP, diuretic use, and lower quality of life and GDMT use (p<0.05 for all). The risk of composite CV mortality/first HF hospitalization was higher with intermediate (adjusted HR 1.34, 95% CI 1.29-1.39) and high vs low ACCI (1.76, 1.69-1.83). High ACCI category (vs low) was significantly associated with non-CV (adjusted HR 6.36, 95% CI 5.75-7.04), but also, CV mortality (4.35, 3.99-4.74), and total hospitalizations (adjusted IRR 2.16, 2.11-2.22) but also HF hospitalizations 1.23 (1.17-1.28) Conclusion The ACCI discriminates well in HF, with higher ACCI being associated with greater severity of HF, lesser GDMT use and worse quality of life. Higher ACCI was more strongly associated with death than hospitalization. Higher ACCI was more strongly associated with non-CV outcomes but also with CV and HF outcomes.

Abstract Purpose: Fibroblast activation protein (FAP) is an attractive target for radiopharmaceutical therapy. Phase I of the LuMIERE study (ClinicalTrials.gov, NCT04939610) investigated the safety of [177Lu]Lu-FAP-2286 (177Lu-FAP-2286) in heavily pretreated patients with advanced solid tumors and identified the recommended phase II dosage (RP2D). Patients and Methods: LuMIERE is a prospective, open-label, nonrandomized, phase I/II, multicenter study. Phase I followed a Bayesian optimal interval design evaluating four escalating activity levels of 177Lu-FAP-2286 (3.70, 5.55, 7.40, and 9.25 GBq). Patients were selected by positive [68Ga]Ga-FAP-2286 (68Ga-FAP-2286, also known as [68Ga]Ga-HKG301) PET/CT imaging on all target lesions [maximum standardized uptake value (SUVmax) ≥1.5× SUVmean of mediastinal blood pool]. 177Lu-FAP-2286 was administered intravenously every 6 weeks for ≤6 cycles. The primary endpoint was dosage-limiting toxicities (DLT) and treatment-emergent adverse events (TEAE). Results: Of 35 patients imaged with 68Ga-FAP-2286, 27 received 177Lu-FAP-2286 (3.70 GBq, n = 3; 5.55 GBq, n = 6; 7.40 GBq, n = 7; 9.25 GBq, n = 11). Two DLTs were observed: one patient who received 5.55 GBq of 177Lu-FAP-2286 experienced grade 4 lymphopenia, and one patient who received 9.25 GBq experienced grade 3 hemoptysis; these were the only treatment-related grade ≥3 TEAEs. All-cause grade ≥3 TEAEs were reported for 11 patients (40.7%). The RP2D for 177Lu-FAP-2286 monotherapy was determined to be 9.25 GBq. Preliminary Response Evaluation Criteria in Solid Tumors efficacy findings demonstrated a partial response in 1 patient and stable disease in 10 patients (maintained for at least two assessments in 6 patients). Conclusions: 177Lu-FAP-2286 was well tolerated in patients with advanced solid tumors. The safety and preliminary efficacy findings support its continued development in phase II.

Abstract Severe neuropathies with predominant involvement of motor fibres can resemble lower motor neuron disease (LMND) phenotypes. Given the fatal prognosis of LMND, identifying underlying autoimmune syndromes is crucial to provide treatment options to patients. We investigated a novel autoantibody binding pattern observed on murine teased sciatic nerve fibres. Target antigens were identified using immunoprecipitation combined with mass spectrometry. Target specificity of these autoantibodies was validated in cell-based assays, neutralization assays and knock-out models. A retrospective study cohort consisting of different neuropathies (chronic inflammatory demyelinating polyradiculopathy n = 86, Guillain–Barré syndrome n = 37, multifocal motor neuropathy n = 18, diabetic neuropathy n = 30, other inflammatory neuropathies n = 10), amyotrophic lateral sclerosis (n = 50), multiple sclerosis (n = 50) and healthy controls (n = 50) was negative for septin multimer autoantibodies. Histopathological analysis of skin and the sural nerve including electron microscopy was performed in one seropositive patient, and autoantibody binding was characterized in vitro. Extensive immunotherapy was initiated in one patient, with clinical and serological follow-up over 4 years. Among 3543 total samples tested, three patients (two male, one female)—diagnosed with the LMND variant of amyotrophic lateral sclerosis (aged 65, 72 and 79 years, respectively)—showed a novel and distinct autoantibody binding pattern of indirect immunofluorescence staining on peripheral nerves, targeting Schmidt–Lanterman incisures (SLIs), paranodes and the abaxonal myelin. Target identification and validation revealed septin multimers as autoantibody epitopes. Despite the primarily intracellular location of septins, autoantibody binding was evident in living myelinated dorsal root ganglia, primarily at SLIs (‘incisuropathy’). Septin multimer autoantibodies further initiated complement deposition on fixed and permeabilized cell-based assays. Sural nerve and skin biopsies showed inflammation, myelin and axonal pathology. Extensive immunotherapy in one patient was followed by disease stabilization over 3 years. The other two patients died of rapid disease progression: one of them received no immunotherapy while the other had ineffective treatments with single administrations of intravenous immunoglobulin and rituximab. Our data suggest that septin multimer autoimmunity occurs in severe motor-predominant neuropathies which can clinically resemble a neurodegenerative LMND. Screening for septin multimer autoantibodies should be considered in patients presenting with this phenotype. Follow-up studies need to determine the direct pathogenicity of septin multimer autoantibodies, their potential as a biomarker of an autoimmune syndrome and responses to immunotherapy in larger cohorts.

9524 Background: Unresectable melanoma in-transit metastases (ITM) can pose a significant clinical challenge. Our recently published data comparing first-line treatments for ITM, isolated limb infusion or perfusion (ILI/ILP), immune checkpoint inhibitors (ICI) and intralesional talimogene laherparepvec (TVEC), found superior outcomes with TVEC. However, TVEC was used more often in patients with lower disease burden and earlier stage (IIIB vs. IIIC/D). Therefore, we sought to better investigate these differences with a propensity score-matched (PSM) analysis. Methods: A multi-institutional, international IRB- approved retrospective analysis was conducted for unresectable melanoma ITM from 2016-2022. PSM analysis comparing first-line ILI/ILP, ICI, and TVEC for was performed. Patients were matched for stage, number of ITM, anatomical site, CLND status, gender and age. Kaplan-Meier curves (OS, PFS, DMFS) and Cumulative incidence function (MSS) were used to visualize time-to-event outcomes in the PSM cohort, though both methods do not account for the matched structure. Results: 274 patients were identified, 120 female/154 male; 96 treated with ILI/ILP, 111 with ICI, and 67 with TVEC. Median follow-up was 40 months (range, 1-80). PSM was performed and identified 36 TVEC–ICI pairs and 27 TVEC–ILI pairs. These were combined resulting in a final cohort of 108 observations (45 TVEC, 36 ICI and 27 ILI). The groups were well balanced. No statistical difference was found for metastasis-free survival (DMFS), progression-free survival (PFS), melanoma-specific survival (MSS), and overall survival (OS) between treatment modalities. TVEC was associated with significant improvement in local PFS (median was 2.2 years (y) for ILI/ILP, 1.5y for ICI and not reached for TVEC, p=0.048). While not statistically significant, a clinical benefit was seen in PFS being longer for TVEC (2.1y for TVEC vs. 1.2y for ILI/ILP and 1.1y for ICI; p=0.2) and OS (not reached vs 2.9y for ILI/ILP and 5.2y for ICI; p=0.2). On mixed effect Cox regression proportional hazard model using the matched data set, there were no significant differences in any of the survival and recurrence outcomes. Conclusions: When patients are propensity-matched, there were no significant differences in first-line treatment modalities for unresectable melanoma ITM. Treatment with TVEC did result in clinically meaningful improved overall and local PFS and OS. This supports that selection of ITM therapy should incorporate an individualized approach, incorporating disease distribution, stage, burden, treatment side effects and patient priorities.

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.

Abstract Pain treatments have modest effects. Health outcomes might be improved if treatments are matched to mechanisms underlying the persistence and biopsychosocial impact of an individual's pain. The International Association for the Study of Pain (IASP) defines 3 mechanistic pain descriptors presumed to involve different mechanisms—nociceptive, neuropathic, and nociplastic. Although treatments to address each descriptor have been proposed, there is no consensus on how to assign descriptors to clinical presentations. A recent consensus identified candidate clinical features to discriminate between descriptors in clinical practice and research. These need refinement to progress towards a tool. This study aimed to determine the rank and relative weight of identified clinical features to aid discrimination between mechanistic pain descriptors. Candidate clinical features (n = 196) were refined by the IASP Terminology Task Force to converge similar and remove redundant features. The Task Force (n = 24) and an expert panel (n = 39) ranked features using 1000minds conjoint analysis software and assigned weights based on discrete pairwise choices. Participants nominated from pairs of scenarios, which most likely indicated that pain aligned predominantly to a descriptor. Highest ranked features for neuropathic and nociplastic pain were aligned with IASP Clinical Criteria. Criteria for nociceptive pain have not been established. A ranked list of features shared by 2 mechanisms (indicating mixed mechanisms) was also identified. This study identified expert consensus on the highest ranked clinical features with potential to discriminate between pain descriptors, reflective of different underlying mechanisms. This study extends current frameworks by identifying and refining key discriminators for future operationalisation and validation.