Journal of Clinical and Translational Science最新文献

Background: 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.

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

The FIND Integrated Biobank (FIB) network was established to address long-standing barriers in translational research, diagnostic development, and pandemic preparedness, particularly in low- and middle-income countries (LMICs). This article presents the FIB network as an innovative, contract-based model for equitable biobanking partnerships that support rapid, quality-assured access to clinical biospecimens for translational research and diagnostic evaluations. The FIB model offers a replicable and scalable approach to global diagnostic research and preparedness, anchored in equitable, legally binding partnerships. It advances the goals of the WHO Pandemic Agreement and provides a practical pathway for integrating LMIC institutions into global translational research ecosystems.

In 2013, the National Institute of Neurological Disorders and Stroke established National Institutes of Health (NIH) StrokeNet to support multi-site clinical trials focused on stroke prevention, treatment, and recovery. The University of Cincinnati (UC) serves as the National Coordinating Center for StrokeNet. As part of the initiative, the UC StrokeNet Central IRB (SN-CIRB) was established at UC to serve as a single IRB to oversee StrokeNet trials. Since the SN-CIRB approved the first StrokeNet study in 2014, it has reviewed and approved 16 additional studies. Over this period, the UC Human Research Protection Program refined its review processes based on insights from earlier reviews. These improvements have improved efficiency while still ensuring the protection of study participants. The successful implementation and ongoing conduct of the SN-CIRB at UC demonstrate that an academic-based IRB can effectively serve as a Central IRB for a large clinical trial network.

CONTEXTperts (Context and Topic Experts) bring real-world experience in the context of the study topic and setting to enhance research team expertise, capacity, and creativity. They complement but do not replace authentic patient and community engagement, professional consultants, or formal advisory boards. Individual CONTEXTpert consultations or group meetings can help improve research questions, study designs, implementation plans, dissemination, and application of findings. They have added value to a variety of projects with varied research methods and study designs, including research with and without patient or community involvement. CONTEXTperts can bring vision, challenge, and reality checks to a variety of research teams with a practical, affordable model.

Introduction: 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.

Materials and methods: 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.

Results: 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.

Discussion: 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.

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

Introduction: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Introduction: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Background: 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.

Methods: 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.

Results: 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%).

Conclusions: 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.

Background/objective: Chronic pain research studies are important for both finding new treatments and improving existing treatments for individuals with chronic pain. For clinical trials to be effective, participants need to be engaged and willing to participate in treatment groups. Our research applies the theory of planned behavior (TPB) to understand how attitudes, perceived social norms, and perceived control over intervention engagement are associated with willingness to participate in interventions for chronic low back pain (CLBP).

Methods: Adult Michigan Medicine patients were identified using electronic medical records and emailed a link to an online, cross-sectional survey. Participants who self-reported CLBP, ability to read and write in English, and consented to participate were able to complete the survey (N = 405).

Results: The results showed more positive attitudes, positive social norms, and higher perceived behavioral control related to specific chronic low back pain interventions are associated with greater willingness to participate after controlling for demographic and pain-related characteristics.

Conclusion: The findings suggest that TPB constructs may be useful in guiding recruitment efforts for chronic pain intervention trials.