Timely dissemination of clinical trial results is essential to advance knowledge, guide practice, and improve outcomes, yet many trials remain unpublished, limiting impact. We examine what drives publication and timelines across three major clinical domains.

We analyzed study design and factors associated with dissemination of interventional trials, focusing on cardiovascular disease (CVD), cancer, and COVID-19. A total of 10,785 trials (CVD: 5929; cancer: 4210; COVID-19: 646) were linked to PubMed publications using National Clinical Trial identifiers. Study design, operational, and transparency-related features were assessed as predictors of time to publication, defined as the interval from study completion to first publication, using Cox proportional hazards model.

COVID-19 trials had the highest publication rate (49.6%), followed by CVD (42.3%) and cancer (32.9%), likely reflecting pandemic-related prioritization. Faster publication was associated with larger enrollment, more sites, result posting, randomization, DMC presence, and higher blinding levels (all p < 0.05). Slower publication was linked to supportive care or diagnostic trials (CVD), basic science (cancer), and later COVID-19 trial completion. In subgroups, U.S. facility presence (CVD) and phase 3 design (cancer) predicted faster publication, while healthy volunteer inclusion (CVD) predicted slower publication. Among DMC trials, more secondary outcomes were linked to faster publication across all disease areas.

Key study design and operational factors consistently predict whether and when trials are published. Strengthening methodological rigor, result reporting, and multi-site collaboration may accelerate timely dissemination into peer-reviewed literature.

Susan G. Komen® (Komen) has invested nearly $1.1 billion in ground-breaking breast cancer research since 1982. As a patient-centered organization, Komen measures research funding impact beyond academic metrics in favor of economic value and societal effects. Here, we highlight an innovative approach to assessing the real-world impact of Komen-funded research by showing how Komen funding for pivotal studies and key personnel conducting research contributed to discovery and development of targeted therapy drugs approved to treat breast cancer by the United States Food and Drug Administration (FDA) between 2012 and 2023.

We utilized bibliometric analysis to work backwards through citations within pivotal Phase III clinical trial publications to identify earlier clinical trials, pre-clinical research, and basic research publications that supported development of each drug, evaluating each published study and contributing authors for Komen funding support.

All 19 targeted therapy drugs approved by the FDA between 2012 and 2023 were impacted at multiple phases along the drug development pipeline by Komen funding, including direct impacts in basic research (i.e., investments in projects) that supported target discovery, and impacts in support of key personnel who contributed to pivotal studies and clinical trials (i.e., investments in people) that led to approval.

Nonprofit and public sector research funding provide the foundation for the drug development pipeline. This paper highlights an innovative approach to assess the impact of research investments beyond traditional academic measures and underscores the significance of nonprofit, patient-centered organizations like Komen in driving drug development through supporting basic and applied research.

To successfully recruit and retain faculty members from underrepresented backgrounds (URBs), we need to understand the factors that attract them to research careers in the first place. However, scholarship in this area has focused largely on students who are contemplating research careers rather than faculty members who are currently in such careers.

This study explores the career motivations of early-career health researchers (faculty members and postdoctoral fellows) from URBs. It was conducted as part of a cluster randomized trial across 25 academic institutions investigating a support intervention. We conducted 1-hour semi-structured qualitative interviews with scholars from URBs in both the intervention and control arms of the trial. To our knowledge, this is the largest qualitative study of early-career faculty members from URBs to date.

Seventy-eight individuals were interviewed. Our analysis revealed six key themes pertinent to participants’ motivations to pursue research careers: (1) love of science; (2) making a larger impact; (3) happenstance and economic considerations; (4) family, community, and a path out of poverty; (5) the role of mentors and role models; and (6) support programs for scholars from URBs.

Our results align with prior studies while offering new insights into the motivations of URB faculty members in research careers. These insights can and should inform the design of programs to both recruit and retain URM faculty members in research careers.

In team science, invitation to writing groups can be subjective and secretive. Confronted with this challenge in the ISCHEMIA trial, with 320 participating sites, 4 coordinating centers, 6 core laboratories, and numerous committees, we adapted an existing model to develop a transparent, objective, and equitable method for determining authorship eligibility.

We developed a scoring system based on site performance of tasks critical to trial success that meet the ICJME criteria for authorship. Sites were ranked according to points earned, and points required for potential authorship were communicated to all sites. Site investigators were surveyed for their manuscript topic preferences for writing groups. Beyond the point-based system, authorship positions were also reserved for trial contributors who were not site investigators.

To date, 50 original, peer-reviewed ISCHEMIA trial manuscripts have been published. In total, 208 authors from 33 countries participated in at least one publication. Of the 87 sites that randomized at least 15 participants over a mean of 5 years, 72% had authorship positions across published manuscripts. Surveys were sent to 334 site investigators and 27% responded. Among respondents, 61% indicated that ISCHEMIA was the first trial they had worked on with performance-based criteria for authorship invitation. Respondents agreed the system was transparent (81%), objective (83%), and equitable for early career researchers (70%) and underrepresented minorities in research (57%).

ISCHEMIA employed a point-based authorship eligibility system that most authors found objective, merit-based, transparent, and equitable. Implementation of such a system should be considered for team science publications.

Fidelity – ensuring interventions are implemented as intended – is a key focus in implementation science. Despite its benefits in research and practice, data on the fidelity of implementation are often overlooked, measured inconsistently, or underreported. In 2024, we proposed a preliminary guideline for one component of fidelity – the fidelity of delivery in parenting interventions. This study builds upon that work, refining the guideline for psychosocial and behavioral interventions.

Using a modified Delphi technique, we refined the Fidelity of Intervention delivery in Psychosocial and behavioral Programs (FIPP) guideline. The process included survey responses (n = 34), two panel consensus meetings (n = 10), and email feedback (n = 5) resulting in six rounds of iterative revisions to produce the final FIPP.

The modified Delphi technique resulted in a final FIPP with 35 items across six categories: intervention, facilitator, fidelity measure, and fidelity assessor characteristics; fidelity assessment method; and fidelity results and discussion. The final FIPP was produced based on engagement and data from the survey participants, consensus meeting panelists, and email panelists.

This study advances reporting on fidelity of delivery in psychosocial and behavioral interventions by refining the FIPP guideline through a rigorous, consensus-driven process. The FIPP provides a comprehensive structure to improve the consistency and transparency of fidelity of delivery assessment. By promoting standardized reporting, the FIPP enhances the quality of implementation science, ultimately supporting more effective interventions and better participant outcomes. Researchers and practitioners are encouraged to adopt the FIPP to strengthen intervention fidelity and drive meaningful progress in the field.

Narcolepsy type 1 (NT1) is a chronic neurological disorder with a genetic predisposition, yet its precise molecular pathogenesis remains unclear. Despite increasing recognition of its clinical and genetic basis, the precise molecular mechanisms remain unclear. This study aimed to identify NT1-associated hub genes and investigate their biological functions and interactions through comprehensive bioinformatics analysis, followed by experimental validation.

NT1-related microarray data (GSE21592) were retrieved from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using integrated analysis with R software and the GEO2R platform. Functional enrichment analyses for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were conducted using Database for Annotation, Visualization, and Integrated Discovery online tool. Protein–protein interaction (PPI) networks were constructed using STRING database and visualized with Cytoscape. Quantitative real-time PCR (qRT-PCR) was used to experimentally validate the expression of identified hub genes in NT1 patients.

A total of 148 DEGs were identified. GO analysis revealed involvement primarily in biosynthesis, humoral immune response, viral gene expression, oxidoreductase activity, cytoplasmic translation, etc. KEGG analysis showed enrichment in oxidative phosphorylation, ribosomal pathways, thermogenesis, and glutathione metabolism pathways. Five hub genes – CREB1, PIK3R1, MED1, GATA3, and KDM5A – were identified from the PPI network. qRT-PCR validation confirmed significantly reduced expression of these genes in NT1 patients compared to healthy controls.

Our study identified and experimentally validated five critical hub genes associated with NT1, providing new insights into its molecular mechanisms and highlighting potential therapeutic targets for future research and clinical intervention strategies.

Inflammatory bowel disease (IBD), encompassing ulcerative colitis (UC) and Crohn’s disease (CD), presents increasing global health burdens. Despite advancements in therapy, disparities in mortality trends across demographic and geographic lines persist in the United States.

To analyze IBD-associated mortality trends in the U.S. from 2018 to 2023 using CDC WONDER data, highlighting demographic, regional, and sex-based disparities.

A retrospective analysis of death certificate data from the CDC WONDER database was performed. Age-adjusted mortality rates (AAMRs) were calculated and stratified by sex, race/ethnicity, and region. Trends were evaluated via join-point regression, with the annual percentage change (APC) and average annual percentage change (AAPC) calculated to assess statistical significance.

A total of 25,153 IBD-related deaths were recorded. The AAMR increased from 8.269 (2018) to 10.761 (2023), with a notable increase until 2022 (APC: +8.91), followed by a decline in 2023 (APC: −7.55). Men presented higher AAMRs than women did (10.882 vs. 9.838). Non-Hispanic White individuals had the highest AAMR (11.401), whereas Non-Hispanic Black and Asian populations presented the steepest increases (APC: 10.49 and 13.45, respectively). Regionally, the Midwest had the highest AAMR (11.531), with Oregon demonstrating the highest state-level mortality.

This study reveals increasing IBD mortality in the U.S., with significant sex, racial, and geographic disparities. These findings highlight systemic inequities in healthcare access, particularly in access to biologic therapy and specialty care. Targeted public health strategies are crucial for reducing disparities and enhancing outcomes in high-risk populations.

DeGAUSS is a privacy-preserving application that ingests addresses and generates output that includes latitude, longitude, census tract, deprivation index and drive times to major hospitals. The application uses a complex command line interface and a container management platform to perform analysis. Our objective was to develop a user-friendly DeGAUSS-based application that simplifies place-based analysis. We also enabled automated geomarker generation by providing an API modality to DeGAUSS.

We developed a self-service platform based on the DeGAUSS application. The application was linked to user authentication platforms. The self-service application can be implemented as an API, enabling high-volume geocoding transactions. We surveyed active users for feedback.

The self-service geomarker application was deployed at Children’s Mercy and the University of Kansas Medical Center. During the period evaluated, more than 2 million addresses were geocoded for 24 users through the user interface and more than 15 million addresses through the API. Users expressed high satisfaction with the system. All respondents used the census block group feature and the core geocoding. Most respondents, 60%, used the deprivation index and 30% used the drive time feature. Population health and social determinants of health were the most common uses (80% each) followed by health equity analyses (70%).

Population health and social determinants of health research require access to precise geographic information about patients or research subjects. The self-service geomarker capability enables users who may not be comfortable with a command line interface to generate geocoded addresses in support of their research and analysis.

Custom transformations of real-world data (RWD) from electronic health record (EHR) systems are necessary to define study variables describing health and disease statuses differently among physicians in multiple specialties and basic scientists from a variety of disciplines . To increase RWD use, we hypothesized that a solution supporting three workflows – discovery, collection, and analysis – using existing rather than novel tools and requiring financial commitment from investigators would scale to meet the needs of clinical and translational research teams and ensure regulatory compliance at an academic medical center.

Weill Cornell Medicine (WCM) implemented custom research data repositories (RDRs) consisting of i2b2 for discovery, REDCap for collection, and Microsoft SQL Server for analysis. WCM subsidized the central information technology (IT) department to manage RDRs and required investigators to commit $50,000 for RDR startup and $7500 for annual maintenance.

From 2013 through 2025, WCM launched more than 17 custom RDRs for pediatrics, myeloproliferative neoplasms, obstetrics and gynecology, pulmonary and critical care, chronic kidney disease, and ophthalmology among other areas. Custom RDRs enabled academic output (e.g., publications, grants) as well as local quality improvement activities.

Custom RDRs facilitated delivery of fit-for-purpose data sets derived from EHR systems and other RWD sources. Over time, RDRs have evolved from an infrastructure product delivered by central IT to a data partnership between investigators and IT.

Custom RDRs and data partnerships may help increase the use of RWD from EHR and other sources by clinical and translational research teams.

Informed consent is a cornerstone of ethical research, but the lack of widely accepted standards for the key information (KI) section in informed consent documents (ICDs) creates challenges in institutional review board (IRB) reviews and participant comprehension. This study explored the use of GPT-4o, a large language model (collectively, AI), to generate standardized KI sections.

An AI tool was developed to interpret and generate KI content from ICDs. The evaluation involved a multi-phased process where IRB subject matter experts, principal investigators (PIs), and IRB reviewers assessed the AI output for accuracy, differentiation between standard care and research, appropriate information prioritization, and structural coherence.

Iterative refinements improved the AI’s accuracy and clarity, with initial assessments highlighting factual errors that decreased over time. Many PIs found the AI-generated sections comparable to their own and expressed a high likelihood of using the tool for future drafts. Blinded evaluations by IRB reviewers highlighted the AI tool’s strengths in describing study benefits and maintaining readability. However, the findings underscore the need for further improvements, particularly in ensuring accurate risk descriptions, to enhance regulatory compliance and IRB reviewer confidence.

The AI tool shows promise in enhancing the consistency and efficiency of KI section drafting in ICDs. However, it requires ongoing refinement and human oversight to fully comply with regulatory and institutional standards. Collaboration between AI and human experts is essential to maximize benefits while maintaining high ethical and accuracy standards in informed consent processes.