Milken Institute

Circulating microRNAs are promising biomarkers of acute cellular rejection (ACR) and antibody-mediated rejection (AMR) in heart transplantation. The study objective was to assess the characteristics and diagnostic performance of previously identified microRNAs and clinical rejection scores (CRS) in distinct blood samples obtained at the time of an endomyocardial biopsy (EMB). In the 5-center, prospective, longitudinal cohort study, GRAfT (Genomic Research Alliance for Transplantation), microRNA sequencing was performed on blood samples. The previously identified microRNAs associated with ACR (n=12) and AMR (n=17) were used to fit a logistic regression model to the current cohort, and the scores were scaled from 0 to 100. Diagnostic performance of ACR and AMR microRNA panels was assessed by the area under the receiver-operating characteristic curve. An adjusted Cox proportional hazard model evaluated the effect of CRS on long-term outcomes. In 173 heart transplant recipients (29% female sex, 41% Black race, median follow-up 374 days after transplant), 922 blood samples were sequenced, 720 paired with EMB. Among 14 episodes of ACR, the median ACR CRS was 78 compared with 42 without ACR, P<0.001. Among 25 episodes of AMR, median AMR CRS was 75 compared with 53 without AMR, P<0.001. The area under the receiver-operating characteristics curve for the CRS was 0.93 for ACR and 0.92 for AMR. Using a CRS threshold of 65, the ACR CRS had 79% sensitivity, 97% specificity, and 100% negative predictive value; the AMR CRS had 84% sensitivity, 86% specificity, and 99% negative predictive value. The ACR and AMR CRS were both <65 in 589 (82%) of the tests. After adjustment, a 10-point increase in CRS was associated with >40% increase in the hazard of the composite outcome: subsequent ACR or AMR by EMB, allograft dysfunction, or death (ACR hazard ratio, 1.42 [95% CI, 1.20-1.69]; P<0.001; AMR hazard ratio, 1.45 [95% CI, 1.14-1.86]; P=0.003). Circulating microRNAs reliably identified ACR and AMR on EMB. An elevated microRNA CRS was associated with an increased risk of subsequent rejection, allograft dysfunction, or death. This biomarker, with further validation, can serve as a noninvasive test to screen and diagnose ACR and AMR without the need for an EMB. URL: https://www.clinicaltrials.gov; Unique identifier: NCT02423070.

Malnutrition among hospitalized older adults in the United States is a growing public health concern associated with poor quality of life, increased mortality, higher readmission rates, and loss of independence. Addressing malnutrition is hindered by limited continuity of nutrition care from hospital to home and a shortage of community-based registered dietitian nutritionists (RDNs). To address these gaps, the Academy of Nutrition and Dietetics developed an enhanced referral model that supports coordinated, data-driven nutrition care after hospital discharge by securely sharing electronic health record data through the Academy's Health Informatics Infrastructure (ANDHII) with community RDNs for medical nutrition therapy and meal provision. The present study aims to: (1) assess implementation feasibility of the enhanced referral model; (2) identify barriers to and facilitators for implementing the model; (3) determine if there is an increase in the proportion of patients ≥ 60 years with malnutrition being offered MNT and meal provision in the community compared to baseline; (4) evaluate whether the enhanced referral model is effective in improving participants' quality of life, food security, and measures of malnutrition compared to usual care. This study will use a hybrid type 2, implementation effectiveness, pre-post study design. Eight acute care hospitals and community meal provision organization pairs will participate. Over 35 months, sites will enroll a total of 1,120 participants; each site will enroll participants under usual care (routine clinical care and practices provided to patients at each site as the control), then transition to the enhanced referral intervention model using a step-wedge schedule. Quantitative data of descriptive statistics and effectiveness outcomes will be analyzed using SPSS. Qualitative data will be analyzed using a coding reliability approach to thematic analysis, guided by validated implementation framework, to identify barriers, facilitators, and feasibility. We hypothesize that adopting the enhanced referral model will improve the continuity of nutrition care, increase the utilization of MNT and meal provision, improve food security, reduce malnutrition-related characteristics, and improve quality of life in older adults. The results could provide evidence to expand RDN care for older adults in the community setting.

Patient navigation is an evidence-based intervention to improve access to cancer screenings, time to diagnostic resolution, adherence to treatment and improved survivorship. Given the diversity of lived experiences and educational backgrounds of navigators, standardized foundational training that aligns with standards of practice and reimbursement requirements is critical. To address this need, in 2015 the George Washington University (GW) Cancer Center launched the Oncology Patient Navigator Training: The Fundamentals (Patient Navigator Training), an accessible, no cost, evidence-based training for patient navigators. To understand its reach and impact after 10 years, the GW Cancer Center Technical Assistance and Training team analyzed data using paired t-tests in SPSS v29.02.02. Across all lessons, statistically significant improvements in learner confidence for all learning objectives were reported. In sum, the freely available Patient Navigator Training developed by the GW Cancer Center provides a strong foundation to prepare oncology patient navigators for practice. It may also be adapted to train navigators in other disease areas or geographies.

Panel count data is common in cancer screening. In the context of colorectal cancer screening, our work focuses on the prediction of the probability of advanced adenoma conditional on patient-level risk factors and/or event history. We implement the joint frailty model proposed by Huang et al. which involves a non-stationary Poisson process for recurrent adenoma events and informative screening time using semi-parametric Cox models correlated by a latent frailty variable, where coefficients and baseline intensity functions are estimated by estimating equations. Subject-specific frailty value is estimated by the borrow-strength method. In addition, marginal models for the adenoma and screening events are also applicable when average covariate effects on the population level are of interest. Predictions based on the marginal model and predictions based on the frailty models for patients with or without a screening history are compared. When a patient's screening history is available and sufficient adenoma events are observed, the predictions based on the frailty model with estimated subject-specific frailty are superior. However, in the cases of early censoring when adenoma events are not observed for most patients and screening history is not available, the prediction based on the marginal model has better performance. Furthermore, for patients' future screening, the individualized screening intervals derived from the dynamic predictions of advanced adenoma risks will detect adenoma events earlier with shorter lag time between the adenoma state transition and the screening compared to the current practice of regular screening intervals.

Background & aimsIn the United States, Non-Hispanic Black (Black) people are 2–threefold more likely than Non-Hispanic White (White) people to have pregnancy complications, such as a baby with low birthweight. Multi-level, community-based interventions aimed at mitigating the impacts of interpersonal and structural racism may decrease bias, improve the quality of care, and improve pregnancy outcomes. The Accountability for Cancer Care through Undoing Racism and Equity and the Heart Health Now studies reduced disparities in cancer treatment and cardiovascular risk, respectively. The Accountability for Care through Undoing Racism and Equity for Moms Study (ACURE4Moms) was modified from these successful interventions and designed to test the impact of multi-level, community-engaged antiracism interventions delivered on disparities in low birth weight (LBW) (Aim 1), experiences with perinatal depression and experiences with discrimination in medical settings (Aim 2) and other patient-centered outcomes. We will also measure implementation barriers and facilitators (Aim 3).MethodsACURE4Moms is a 4-arm, cluster-randomized trial which has enrolled 39 prenatal practices randomized to implement the following interventions for 2 years: Arm 1–Standard Care; Arm 2—Data Accountability and Transparency; Arm 3—Community-Based Doula linkages; and Arm 4—Data and Doula interventions combined. Practice staff in Arms 2–4 will also receive quarterly Maternal Healthcare Equity Education and Training. A subgroup of 100 Black patients from each practice will participate in a longitudinal survey that measures mental health symptoms and experiences with discrimination during pregnancy and postpartum. A stakeholder advisory board including doulas, community members, and policymakers helps to make decisions regarding study design, implementation, and dissemination.Multi-level mixed models will be used to evaluate outcomes using administrative, vital records and survey data. The primary outcome is a reduction in low birth weight for Black infants. Secondary outcomes include reductions in hospitalizations and emergency department use, mental health symptoms, and experiences with discrimination during pregnancy and postpartum. Intermediate outcomes include implementation barriers and facilitators.DiscussionThe findings of the ACURE4Moms study will inform policy makers, health systems, clinicians and communities about the effectiveness of multi-level, practice-based interventions to reduce maternal health disparities and provide information regarding scalability.Trial RegistrationThis trial has been prospectively registered as (7/29/2022) with clinicaltrials.gov under the name Accountability for Care Through Undoing Racism & Equity for Moms (ACURE4Moms), Identifier: NCT05484804. URL: https://clinicaltrials.gov/ct2/show/NCT05484804.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13063-026-09514-9.

Global oncology trials face increasing scrutiny over regional enrollment imbalances, as regulatory agencies such as the US Food and Drug Administration, European Medicines Agency, and Pharmaceuticals and Medical Devices Agency demand data reflective of population diversity. This push is grounded in evidence that genetic polymorphisms (eg, UGT1A1*28, CYP2D6), human leukocyte antigen-related toxicities, and biomarker prevalence (eg, epidermal growth factor receptor mutations in approximately 15% of Western v approximately 50% of Asian patients with lung cancer) can significantly influence treatment outcomes. We reviewed scientific literature, regulatory case studies, and methodological innovations addressing regional heterogeneity in oncology trials. Particular focus was given to statistical tools such as adaptive randomization for real-time enrollment balancing, Bayesian hierarchical models for data borrowing across regions, and Multi-Regional Clinical Trial designs for structured consistency assessments. Control arm variability because of regional differences in standard of care and drug access was also examined. Recent regulatory setbacks, especially involving Asia-centric trials, underscore the consequences of insufficient regional planning. Emerging statistical approaches, including adaptive and Bayesian methods, show promise in managing heterogeneity while preserving trial integrity. Persistent challenges include disparities in trial infrastructure, molecular subtype distributions, and comorbidity patterns. Broader regional inclusion and integration of real-world evidence are increasingly critical to overcoming these limitations. Regional enrollment should be viewed not as a regulatory formality, but as a scientific and ethical priority. The future of global oncology trials hinges on proactive regional planning, innovative methodology, and cross-sector collaboration. Aligning global efficiency with local relevance can enhance scientific robustness, support regulatory alignment, and expand equitable access to novel cancer therapies worldwide.