Citations

Importance Allogeneic hematopoietic cell transplant (HCT) is curative for hematologic cancers, yet access remains inequitable for racially and ethnically underrepresented and socioeconomically disadvantaged populations, making the goal of having a suitable donor for every patient who needs a transplant challenging. The ACCESS trial broadened access by enrolling patients without matched donors, who instead received an HCT from a mismatched unrelated donor. Objective To compare baseline characteristics of ACCESS trial participants with participants enrolled in a similar clinical trial and a patient-reported outcome (PRO) protocol cohort. Design, Setting, and Participants This cross-sectional study included adult participants (aged ≥18 years) from 3 cohorts—the ACCESS trial (2021-2024), BMT CTN 1703 trial (2019-2021), and Center for International Blood and Marrow Transplant Research (CIBMTR) PRO Protocol observational study (2020-2025)—who completed a baseline PRO survey. The ACCESS and PRO Protocol cohorts were stratified by conditioning intensity (myeloablative [MAC] vs reduced-intensity and nonmyeloablative [RIC/NMA]); all BMT CTN 1703 participants received RIC/NMA. Exposure Hematopoietic cell transplant. Main Outcomes and Measures Racial and ethnic diversity, insurance type, education, and income were compared among cohorts using counts and percentages, and socioeconomic and structural disadvantage were measured using the Social Vulnerability Index and Comprehensive Score for Financial Toxicity–Functional Assessment of Chronic Illness Therapy. Results Baseline surveys were completed by 208 participants in the ACCESS trial (median [range] age at transplant, 62.3 [20.4-78.9] years; 108 male [51.9%]), 122 participants in the PRO Protocol study (median [range] age at transplant, 63.9 [21.1-78.0] years; 67 male [54.9%]), and 342 participants in the BMT CTN 1703 trial (median [range] age at transplant, 66.9 [20.7-78.6] years; 218 male [63.7%]). Participants in ACCESS were more racially and ethnically diverse, with 15 (7.2%), 25 (12.1%), 46 (22.2%), 110 (53.1%), and 11 (5.3%) of Asian, Black or African American, Hispanic or Latino, White, and other race and ethnicity, respectively, compared with 4 (3.3%), 2 (1.6%), 8 (6.6%) 104 (85.2%), and 4 (3.3%), respectively, in the PRO Protocol and 10 (3.0%), 0, 16 (4.8%), 302 (91.0%), and 4 (1.2%), respectively, in the BMT CTN 1703 trial. Participants in ACCESS were more likely to have Medicaid (36 [18.1%]) vs PRO Protocol (8 [6.7%]) and BMT CTN 1703 (16 [5.1%]) participants and reported lower education (some college or an associate’s degree: 103 [49.5%] vs 73 [59.8%] in the PRO Protocol; postcollege education: 34 [17.3%] vs 35 [29.2%] in the PRO Protocol) and household income (<$40 000 annually: 25 [24.0%] vs 8 [11.6%] in the PRO Protocol and 7 [38.9%] in the BMT CTN 1703 trial). Median Social Vulnerability Index scores were highest among participants in the ACCESS MAC group (median [range], 0.72 [0.01-0.97] vs 0.61 [0.16-0.78] in the PRO Protocol MAC group), and 16 participants [27.6%] in the ACCESS MAC group reported moderate to severe financial toxicity. The ACCESS participants lived closer to transplant centers, especially in the RIC/NMA group (median [IQR], 28 [14-75] miles vs 47 [16-96] miles for BMT CTN 1703 participants and 49 [21-104] miles for PRO Protocol participants). Conclusions and Relevance This cross-sectional study of clinical trial participants and a clinical cohort found that the ACCESS trial enrolled a more racially and ethnically diverse and socioeconomically disadvantaged population. Trial designs that broaden eligibility could expand access to HCT, highlighting the need for systemic interventions to ensure equity.

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.

Objective Meaningful assessments of how large language models (LLMs) incorporate clinical guidelines require large-scale testing over many queries. Here, we evaluate the prevalence of clinical guideline omissions and hallucinations in a large sample of diagnostic LLM outputs. Methods We used simulated case vignettes and zero-shot prompting to generate diagnostic outputs and rationales from GPT-4.1 and DeepSeek-V3. English case vignettes were created for hypercholesterolaemia and type-2 diabetes mellitus. Each vignette contained identical medical information, while sociodemographic characteristics varied in terms of sex, ethnicity and location. We calculated the prevalence of existing and hallucinated clinical guidelines in LLM outputs across disease, LLM and sociodemographic characteristics. Results We analysed a total of 12 197 LLM outputs, which quantifies three hazard areas: omissions (up to 97% for DeepSeek-V3 and 46% for GPT-4.1), hallucinations (up to 9%) and inconsistencies (guideline citation rate ranging from 0% to 78.39% across sociodemographic vignettes). Omission and hallucination rates were generally similar across vignettes with different sex or ethnicity data, yet were particularly sensitive to patient location. Discussion This study highlights significant variability in clinical guideline prediction across two different diseases, three different sociodemographic variables and two LLMs, even when the LLMs were instructed by identical prompts, establishing clinical guideline prediction in LLM outputs as a stochastic event. Conclusion The stochastic nature of LLMs creates a unique challenge for evidence generation and clinical deployment. Being able to measure and capture this stochasticity within high-quality research designs will be a prerequisite to advancing the responsible deployment of LLMs in healthcare.

Importance Accurate prediction of patient mortality after kidney transplant is an unmet need. Objective To develop and validate an integrative prediction model that predicts short- and long-term patient mortality for kidney recipients. Design, Setting, and Participants This international cohort study included patients who underwent transplants between 2004 and 2023 from 14 academic medical centers from Europe and the US. The derivation cohort consisted of 1566 consecutive adult kidney recipients in a deeply phenotyped cohort prospectively recruited in 1 French center between 2004 and 2014. External validation cohorts consisted of 10 951 kidney recipients from 7 centers in France, 3 centers in Europe, and 3 centers in North America who underwent kidney transplants between 2006 and 2023. Data were analyzed from January 2023 to June 2025. Main Outcome and Measures All-cause mortality was assessed, and 121 candidate prognostic factors, comprising demographics and clinical, biological, imaging, and immunological parameters, were collected. Results Among 12 517 kidney transplant recipients, including 1566 in the derivation cohort (mean [SD] age, 50.05 [14.31] years; 942 male [60.15%]) and 10 951 in validation cohorts (mean [SD] age, 53.32 [13.97] years; 6766 male [61.78%]), 2486 patients (19.9%) died after a median (IQR) follow-up of 5.08 (2.97-7.00) years. Fourteen prognostic factors (including clinical, biological, and imaging risk factors) were independently associated with patient death (eg, patient age: hazard ratio per 1-year increase in age, 1.07 [95% CI, 1.06-1.08]; P &amp;lt; .001) and were combined into a risk prediction model (mBox). The model exhibited accurate calibration and discrimination in the derivation cohort, with C statistics of 0.82 (95% CI, 0.77-0.87) and 0.80 (95% CI, 0.78-0.82) at 1 and 10 years, respectively, after the transplant. Abbreviated models were developed and validated to ensure model generalizability. Performance of abbreviated models was confirmed in external validation cohorts from France (C statistic, 0.76 [95% CI, 0.73-0.78]), Europe (C statistic, 0.74 [95% CI, 0.72-0.76]), the US (C statistic, 0.74 [95% CI, 0.70-0.78]), the Greater Paris University Hospital database (C statistic, 0.79 [95% CI, 0.77-0.81]), and the University of California at San Francisco database (C statistic, 0.70 [95% CI, 0.65-0.74]). The model was also validated in a series of subpopulations (eg, women vs men: C statistic, 0.81 [95% CI, 0.77-0.84] vs 0.79 [95% CI, 0.77-0.82]) and clinical scenarios (eg, before COVID-19 era: C statistic, 0.79 [95% CI, 0.77-0.81]) with good and stable performance. Conclusions and Relevance In this study, an accurate prediction model for mortality among kidney recipients, computable at the time of transplant, was developed and externally validated. Results suggest that this model may help stratify patient risk of death, allowing for improved medical decisions.

Abstract Pancreatic cancer disproportionately affects Black individuals in the United States, but they have limited representation in genetic studies of pancreatic ductal adenocarcinoma (PDAC). To address this gap, we performed admixture mapping and genome-wide association analysis (GWAS) in genetically inferred African ancestry individuals (1,030 cases and 889 controls). Admixture mapping identified three regions with a significantly higher proportion of African ancestry in cases compared to controls (5q33.3, 10p1, 22q12.3). GWAS identified a genome-wide significant association at 5p15.33 ( CLPTM1L , rs383009:T>C, T Allele Frequency=0.51, OR:1.45, P value=1.24×10 -8 ), a locus previously associated with PDAC. Known loci at 5p15.33, 7q32.3, 8q24.21 and 7q25.1 also replicated (P value <0.01). Multi-ancestral fine-mapping identified two potential causal SNPs (rs3830069 and rs2735940) at 5p15.33. Collectively these findings identified novel PDAC risk loci and expanded our understanding of this deadly cancer in underrepresented populations, emphasizing the multifactorial nature of PDAC risk including inherited genetic and non-genetic factors. Statement of Significance To understand how genetic variation contributes to PDAC risk in Black people in North American, we studied individuals of genetically-inferred African ancestry. We identified novel risk loci and differences in the contribution of known loci. This demonstrates that ancestry-informed genetic analyses improve our understanding of PDAC risk and enhances discovery.

Abstract The hallmark of heparin-induced thrombocytopenia (HIT) is the presence of immunoglobulin G (IgG) antibodies against platelet factor 4/heparin (PF4/H) complexes, typically detected by PF4/H enzyme-linked immunosorbent assay (ELISA); thus, negative ELISA results are commonly used to exclude this diagnosis. Here, we report a prevalent yet previously unrecognized subset of antibodies that are undetectable by PF4/H ELISA (ELISA−) but activate platelets in the PF4-dependent P-selectin expression assay (PEA+). In 11 patients with clinically confirmed HIT who tested positive in both PF4/H ELISA and platelet activation assays, ELISA−PEA+ antibodies accounted for 65% ± 19% of total platelet-activating IgG activity and coexisted with ELISA+PEA+ antibodies. Consistent with this finding, single-cell cloning from 7 patients with HIT identified 23 PEA+ antibody-producing B-cell clones, of which 17 were ELISA−, outnumbering the ELISA+ clones. Functionally, ELISA−PEA+ antibodies closely resembled ELISA+PEA+ antibodies: platelet binding and activation required exogenous PF4 and were inhibited by FcγRIIA blockade, high-dose heparin, or Fab fragments made from ELISA+PEA+ antibodies. Importantly, these antibodies induced thrombocytopenia in a humanized mouse model of HIT. Despite lacking PF4/H reactivity in ELISAs, they recognize PF4 on platelets and showed no appreciable binding to neutrophil-activating peptide-2, interleukin-8, or PF4 alone. Structurally, these antibodies were heterogeneous, with a subset sharing heavy-chain features with ELISA+PEA+ antibodies. Collectively, our findings demonstrate that ELISA−PEA+ antibodies are a common, previously unrecognized feature of HIT, with functional relevance, supporting the possibility that they play an important, perhaps even central, role in HIT pathogenesis. Defining their prevalence, kinetics, and clinical impact deserves high priority for further investigation.

Objective This study aims to identify factors associated with patient global assessment (PtGA) and physician global assessment (PhGA) and discordance between them in systemic sclerosis (SSc). Methods Data from adults with early SSc (<5 years) from the Collaborative National Quality and Efficacy Registry were included. PtGA and PhGA (0–10 scale), clinical evaluations, and patient‐reported outcomes (PROs) were collected every six months. Multivariable mixed‐effects linear regression identified factors associated with PtGA and PhGA using (1) clinical variables and (2) clinical variables plus PROs. Relative weight analysis (RWA) determined the relative importance of each variable. Discordance (≥2 points between PtGA and PhGA) was assessed using multinomial mixed‐effects logistic regression. Results Among 956 patients (83% women, 33% limited disease), mean PtGA and PhGA at enrollment were 4.2 (SD 2.6) and 3.4 (SD 2.0), respectively ( P < 0.001). RWA of clinical variables identified modified Rodnan skin score (mRSS) and New York Heart Association (NYHA) functional class as most influential for both global assessments. After including PROs, PtGA was most influenced by measures of pain, skin symptoms, and physical function. Discordance occurred in 53% of patients (35% PtGA worse, 18% PhGA worse). Worse PtGA was associated with higher overall pain and discomfort. Worse PhGA was associated with higher mRSS, worse NYHA class, higher pain interference, and lower diffusing capacity of the lung. Conclusion Discordance between PtGA and PhGA occurs commonly, highlighting the need for comprehensive symptom management and measurement of disease burden in this complex disease. In SSc, differences in PtGA and PhGA reflect dissimilar weighting of data elements.

We previously reported initial results of the pivotal phase II trial of atezolizumab for patients with alveolar soft part sarcoma (ASPS; ClinicalTrials.gov identifier: NCT03141684 ). Here, we report on three additional years of observation. Fifty-three patients with ASPS received atezolizumab. Median duration of response increased to 37.0 months. Objective response rate (ORR) and median progression-free survival (mPFS) remained essentially as previously reported (35.8% [95% CI, 23.1 to 50.2] and 20.8 months [IQR, 7.6-not reached], respectively). ASPSCR1::TFE3 fusion type was determined for 47/53 patients; ORR and mPFS were higher among the 41 patients expressing type 1 (43.9% [95% CI, 28.5 to 60.2] and 28.3 months [IQR, 9.2-not reached], respectively) than the six patients expressing type 2 (0% [95% CI, 0 to 45.9] and 7.5 months [IQR, 3.9-not reached], respectively, PFS HR, 3.2 [95% CI, 1.01 to 10.2]). Eleven patients chose a per-protocol drug holiday (range, 3.5-26.4 months) after ≥2 years of treatment; two experienced disease progression during the holiday. Nine eligible patients elected to receive bevacizumab plus atezolizumab after progressing on monotherapy; ORR was 0% and mPFS was 18.5 months (IQR, 7.9-21.1) in this small cohort. Long-term results support using atezolizumab to treat ASPS, even for several years; a drug holiday with careful monitoring may be an option for some patients.