Citations

Abstract Background Recent studies suggested that treating obesity and its comorbidities with glucagon-like peptide-1 (GLP-1) receptor agonists may improve outcomes in patients with heart failure with preserved ejection fraction (HFpEF). The randomized SUMMIT trial found that tirzepatide use was associated with a lower risk of heart failure (HF) events or cardiovascular death in adults with HFpEF and obesity compared with placebo. Purpose We aimed to examine whether tirzepatide use in clinical practice was associated with risks of HF events and all-cause mortality among adults with HFpEF and obesity. Methods This was a retrospective cohort study leveraging the Optum Labs Data Warehouse (OLDW), a de-identified administrative claims database of commercial and Medicare Advantage enrollees across the United States. We identified all adults with HFpEF and obesity from January 1, 2022, to December 31, 2024. Our primary exposure was tirzepatide use, and our primary outcome was a composite of a HF event (ED visits or hospitalization for HF) or mortality. Secondary outcomes included hospitalization for angina, atrial fibrillation or atrial flutter (AF/AFL), acute myocardial infarction (MI), cardiac arrest, and cardiogenic shock. Patients were followed from the index date, defined as the tirzepatide treatment start date after HFpEF diagnosis or pseudo-index date in tirzepatide non-users, to the end of enrollment or death using the intention-to-treat framework. Inverse probability of treatment weighting (IPTW) was used to balance groups. Fracture, conjunctivitis, ear infection, and fungal skin infection were used as falsification endpoints. Cox-proportional and Fine-Gray subdistribution hazard models were used to estimate a hazard ratio (HR) and subdistribution hazard ratio (SHR), respectively. Results Among our total cohort of 99,270 patients, the mean age was 73 years, 58,616 (59.1%) were female, 8,839 (8.9%) used tirzepatide, and the mean follow-up time was about 385 days. Patients using tirzepatide had a significantly lower risk of a HF event or mortality (HR=0.73; 95% confidence interval [CI]=0.66–0.80; p<0.001) compared to patients not using tirzepatide. Patients using tirzepatide had a lower risk of a HF event (SHR=0.80; 95% CI=0.73–0.88; p<0.001) and all-cause mortality (HR=0.48; 95% CI=0.38–0.60; p<0.001). Tirzepatide use was associated with lower risks of hospitalization for acute MI (SHR=0.67; 95% CI=0.52–0.85; p=0.001) and cardiogenic shock (SHR=0.56; 95% CI=0.38–0.83; p=0.003), but not angina, AF/AFL, or cardiac arrest (Figure 1). Conclusion Among adults with HFpEF and obesity, tirzepatide use in real-world clinical practice was associated with a lower risk of HF events, hospitalizations for acute cardiovascular disease, and all-cause mortality.For image description, please refer to the figure legend and surrounding text.

Abstract Current genomic assays provide prognostic information and guide chemotherapy decisions in early-stage hormone receptor–positive/human epidermal growth factor receptor 2–negative (HR+/HER2−) breast cancer, but limited tissue sampling may incompletely capture tumor heterogeneity. We developed and validated an image-based artificial intelligence (AI) model integrating dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and clinicopathologic features to predict recurrence risk in early-stage HR+/HER2 − breast cancer. In this retrospective multi-institutional study, the model was trained using pre-treatment imaging and clinicopathologic data from 522 patients and independently validated in 550 additional patients treated between 2010 and 2023. By analyzing spatial tumor characteristics, the model generated individualized recurrence risk scores that outperformed clinicopathologic features alone. In the validation cohort, median age was 53 years (range, 24–90), 15.6% of patients self-identified as African American, 89.7% had clinical T1–T2 disease, and 34.4% had 1–3 positive lymph nodes. Five-year recurrence-free survival was 93.8% (95% CI, 90.0–96.2%) among patients classified as low risk compared with 82.6% (95% CI, 74.8–88.1%) among those classified as high risk, corresponding to an adjusted hazard ratio of 2.28. Prognostic performance was maintained across clinically relevant subgroups, including age and nodal status. These findings support the potential of a noninvasive image-based AI approach for real-time prognostication and treatment personalization in early-stage HR+/HER2 − breast cancer.

Background: There is growing evidence that social determinants of health (SDOH) are associated with disparities in access to care and hand and upper extremity health. Quality measures represent an opportunity to evaluate disparities in access and outcomes that can inform improvement interventions. We performed a systematic review of evidence regarding health disparities within hand surgery and aimed to develop suitable quality measures that are clinically important, feasible, usable, and scientifically acceptable. Methods: We performed a systematic review including common hand surgery terms to identify health disparities in hand surgery related to SDOH. Candidate quality measures were constructed based upon evidence from the systematic review. A consortium of 11 US-based hand and upper extremity surgeons completed a modified RAND/UCLA Delphi Appropriateness process to evaluate the importance, feasibility, usability, and scientific acceptability of the candidate quality measures. Panelists rated each measure on a scale of 1 ( definitely not important/feasible/usable/scientifically acceptable ) to 9 ( definitely important/feasible/usable/scientifically acceptable ) in 2 voting rounds separated by a face-to-face discussion. Agreement among panelists and validity were assessed using predetermined criteria. Results: Fourteen candidate quality measures addressing health disparities were identified based on evidence from the systematic review, including time to surgery and emergency department use after hand surgery based on insurance type, clinical outcomes based on social deprivation, among others. All 14 measures were accepted. Conclusions: Fourteen candidate quality measures were identified and accepted based upon consensus to address health disparities in hand surgery, although future investigation will be needed to evaluate their effectiveness.

Diffuse large B-cell lymphoma (DLBCL), the most common type of lymphoma, arises from various pathogenic mechanisms including gene translocations and fusions. Detection of gene rearrangements using fluorescence in situ hybridization (FISH) is a standard practice for DLBCL diagnosis and guides treatment decisions. High-throughput chromosome conformation capture (Hi-C) DNA sequencing is a next-generation sequencing-based technology to identify genome-wide rearrangements using a single assay. In this study, Hi-C sequencing was performed using FFPE tissues from 159 patients with DLBCL, and identified 746 cancer genes at or proximal to the rearrangement breakpoints with a total of 1903 occurrences. Focusing on clinically important rearrangements, Hi-C detected 102 rearrangements of MYC, BCL2, and/or BCL6 in 92 patients and revealed the fusion partners, including 25 rearrangements missed by FISH. Causes of FISH negative results included FISH-cryptic breakpoints, complex or faint FISH signals, low percentage of FISH positivity, and issues related to tissue fixation. Moreover, in 20 patients (12.6%), Hi-C sequencing detected 22 rearrangements characteristic of other lymphoma types, including CCND1 rearrangements that could lead to reclassification as mantle cell lymphoma. Survival analysis for genome-wide rearrangements using machine learning models identified MYC, PD-L1, CCND1, BCL2, NTRK1/PRCC, RRAS, and FANCE rearrangements with significant prognostic effects in the DLBCL cohort. In conclusion, Hi-C sequencing detects gene rearrangements crucial for diagnosis in an unbiased and molecular manner and showed high sensitivity and specificity in our study. These advantages of Hi-C sequencing offer help to improve the workflow of clinical pathology laboratories, diagnostic precision, and treatment of large B-cell lymphoma.

Abstract Pathogenic variants in cardiomyopathy genes confer substantial disease risk, yet clinical penetrance varies widely. The population-level prevalence, age-specific penetrance, and the extent to which polygenic susceptibility modifies disease risk across diverse ancestries remain poorly defined. This population-based cohort study leveraged genome sequencing and linked electronic health record data from the All of Us Research Program (n=414,830). This study found that P/LP variants in cardiomyopathy-associated genes were present in 0.91% of participants (95% CI, 0.88%–0.94%), with similar prevalence across ancestry groups. Compared with non-carriers, variant carriers had significantly higher odds of all-cause heart failure (ACHF, OR, 2.58; 95% CI, 2.31–2.89), non-ischemic heart failure (NIHF, OR, 2.74; 95% CI, 2.42–3.10), and non-ischemic cardiomyopathy (NICM, OR, 4.99; 95% CI, 4.44–5.63). Among carriers, by age 50 years, 24.5% (95% CI, 14.5%–33.4%) developed ACHF, 17.2% (95% CI, 8.8%–24.8%) developed NIHF, and 30.1% (95% CI, 19.5%–40.2%) developed NICM. Higher polygenic risk for heart failure was independently associated with increased risk of ACHF (OR, 1.81; 95% CI, 1.74–1.89), NIHF (OR, 1.66; 95% CI, 1.58–1.75), and NICM (OR, 1.69; 95% CI, 1.59–1.80). Among carriers with elevated polygenic risk, odds of disease were substantially higher than among non-carriers at average polygenic risk (ACHF: OR, 4.71; 95% CI, 4.17–5.32; NIHF: OR, 4.56; 95% CI, 3.99–5.22; NICM: OR, 8.51; 95% CI, 7.44–9.73). Results showed that P/LP variants in cardiomyopathy genes were relatively common in this large, ancestrally diverse cohort, and conferred increased risk of cardiomyopathy and HF, with incomplete but clinically meaningful penetrance. Polygenic risk for HF independently and additively increased disease risk across ancestries. Integrating both may improve risk stratification and enable more precise, equitable care.

ABSTRACT Myelodysplastic syndrome (MDS) and chronic myelomonocytic leukemia (CMML) are clonal myeloid neoplasms shaped by genetic lesions and immune dysregulation, both of which contribute to disease progression and poor outcomes. Existing prognostic systems, such as IPSS‐R and IPSS‐M, do not incorporate immune alterations. We assessed the biological and clinical relevance of an immune dysfunction signature (IDS) across multi‐center MDS and CMML cohorts. IDS scores, derived from bulk transcriptomic data, were significantly associated with inferior leukemia‐free and overall survival. In multivariable analyses, IDS retained independent prognostic value alongside IPSS‐R, IPSS‐M, and bi‐allelic TP53 inactivation. Incorporation of IDS into existing models improved prognostic discrimination and time‐dependent predictive accuracy. Longitudinal analyses revealed that rising IDS scores paralleled disease progression and acute transformation, whereas declining scores were observed in remission. Biologically, IDS‐high cases demonstrated reduced cytotoxic T‐cell activity, expansion of regulatory T cells, enrichment of primitive progenitor signals, and increased expression of checkpoint pathway genes. These findings were validated across multiple independent MDS cohorts and consistently reproduced in CMML, where IDS also stratified risk and tracked disease evolution. Finally, integration with drug response signatures from the BeatAMLv2 cohort suggested potential therapeutic vulnerability of IDS‐high cases to multikinase and NF‐κB pathway inhibitors. These results establish IDS as a robust and dynamic biomarker in MDS and CMML, with applications in refined risk stratification, longitudinal disease monitoring, and guiding personalized therapeutic strategies targeting immune dysfunction. Trial Registration: #201709072RINC, #202109078RINB, #202207050RINB

Abstract Prognostic indices such as the CLL International Prognostic Index (CLL-IPI) and the International Prognostic Score for Early-stage CLL (IPS-E) can predict time to first treatment (TTFT) in patients with early-stage CLL. Their ability to predict risk of infection - a leading contributor to morbidity and mortality in CLL - remains uncertain. The CLL-TIM is a machine-learning model developed in Europe that integrates clinical, laboratory, and infection-related data to predict TTFT or infection risk within 2-years of diagnosis, Receiver Operating Characteristic - Area Under the Curve (ROC-AUC) 0.74; Agius et al., Nat Comm 11, 363 2020. We conducted the first validation of CLL-TIM in a US cohort of newly diagnosed CLL patients and compared its performance with the CLL-IPI and IPS-E indices. Adults with newly diagnosed CLL (2000-2020) were identified through the Rochester Epidemiology Project using International Classification of Disease (ICD) codes; all diagnoses were confirmed. We replicated the variable selection from the original CLL-TIM model and applied it to our cohort. The primary endpoint was a 2-year composite of either TTFT or incident infection (defined as having blood cultures drawn). Model performance was evaluated using ROC-AUC consistent with the original CLL-TIM methods. CLL-IPI and IPS-E performance was assessed using time-dependent ROC-AUC; pairwise differences in discrimination were tested using DeLong. We identified 454 CLL patients with a median age of 72 years [range, 30-97], 166 (37%) were female, Rai Stage was 0-II in 399 (92%) patients. IGHV genes were unmutated in 130/305 (42%) patients and TP53 disruption (either del17p by FISH or TP53 mutation) was present in 24/329 (8%) patients. At 2-years, 55 (12%) patients received CLL therapy, and 56 (12%) patients had an infection. The 2-year composite endpoint was observed in 94 (21%) patients. The ROC-AUC was 0.74 (95% CI 0.68-0.80) for CLL-TIM, 0.69 for CLL-IPI (95% CI 0.63-0.75, p=0.11 compared to CLL-TIM) , and 0.68 for IPS-E (95% CI 0.62-0.74, p=0.02 compared to CLL-TIM). We also evaluated the ROC-AUC using all the prognostic models for each individual endpoints. The corresponding ROC-AUC for TTFT at 2 years were 0.79, 0.74, and 0.76 for CLL-TIM, CLL-IPI, and IPS-E, respectively; and for infection at 2 years were 0.68, 0.57, and 0.52, respectively. This is the first validation of the CLL-TIM in a US-based cohort of newly diagnosed CLL patients. Although the CLL-TIM model exceeded the minimally meaningful discrimination threshold (AUC >0.7) for individual patient-level risk prediction, there was no statistical difference in AUC between CLL-TIM and CLL-IPI, suggesting either model can predict the composite endpoint at 2 years. Most of the observed discrimination was driven by prediction of TTFT rather than infection, underscoring the need to develop more infection-specific risk models for newly diagnosed CLL. Citation Format: Raphael Mwangi, Tait D. Shanafelt, Soren Basnet, Emily L. West, Owen Keegan, Timothy G. Call, Yao Yuan, Bryan Alexis Vallejo, Paul J. Hampel, Lindsey E. Roeker, Yucai Wang, Saad J. Kenderian, Sara J. Achenbach, Aaron D. Norman, Kari G. Rabe, Neil E. Kay, James R. Cerhan, Curtis A. Hanson, Susan L. Slager, Sameer A. Parikh. Validation of the CLL treatment infection model (CLL-TIM) in patients with newly diagnosed chronic lymphocytic leukemia (CLL) [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 4228.

Abstract Background: Prostate cancer (PCa) is the leading cause of cancer-related deaths globally and disproportionately affects men of African ancestry. African men often present at younger ages and with more aggressive disease, and approximately half of the PCa risk has been attributed to genetic factors. Africa is the most genetically diverse region of the world, and even within the continent, populations show important differences in allele frequencies and patterns of pathogenic variation. Despite this diversity, African men remain underrepresented in genomic studies, creating significant gaps in knowledge that limit precision medicine efforts. Methods: A total of 182 prostate cancer patients were recruited from teaching hospitals in Benin, Côte d’Ivoire, Ghana, Kenya and Nigeria. 50 cancer susceptibility genes using the Aviseq ONCO50 panel and the Illumina MiSeq platform. Variant calling was performed using an in-house Snakemake workflow, followed by additional bioinformatic steps to distinguish true PMS2 variants from PMS2CL-related artifacts. Pathogenicity assessment relied on annotations from ClinVar and LOVD databases. Results: Pathogenic and likely pathogenic variants were detected in 31.3% of the study group identified in 26 genes. The five most frequently altered genes were RAD50, PTCH1, MSH6, MUTYH, and NF1. Nigerian patients accounted for 52.6 percent of all pathogenic variants, with recurrent alterations observed in MSH6, MUTYH, NF1, and PTCH1. In contrast, pathogenic BRCA1 and BRCA2 variants were observed primarily in patients from Kenya, Benin, and Côte d’Ivoire. Several frameshift, nonsense, and splice-site variants identified in this study have not been previously reported in African populations.[SR1] Conclusion: This study provides one of the most detailed assessments of inherited cancer susceptibility gene variants in African PCa patients. The findings reveal substantial regional variation in the spectrum of pathogenic variants and highlight population-specific genomic signatures that may contribute to the unequal burden of PCa in men of African ancestry. These data emphasize the importance of expanding genomic research efforts within Africa to strengthen precision oncology and reduce global PCa disparities. Citation Format: Abimbola F. Onyia, Freeman Okwuchi, Opeyemi C. De Campos, Sylvester Divine, Olutola Olasehinde, Ayinde Yahaya, Ayo Salako, Aminu Zakari, Iya Bassey, Nicholas Titiloye, Bernard Petershie, Isidore GANDAHO, Luc Brun, Tore Sanni, Safiatou Coulibaly, Noel Coulibaly, Michael Fakayode, Coulibaly Issoufou, Valérie Gbonon, Kouame Benjamin, Yao Evrard, Peter Coleman, Ayun Cassell, Victor Ajumbo, Lilac Wattanga, Benson Ochieng Nyambega, Folakemi T. Odedina, Solomon Rotimi. Targeted sequencing of common cancer susceptibility genes reveals germline variants in African prostate cancer patients [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 6289.