Journal of Clinical and Translational Science最新文献

There is increasing recognition of the crucial need for robust community engagement in health research and clinical trials. Despite this awareness, challenges persist in bridging the gap between researchers and communities. Much of the current discourse focuses on addressing issues such as cultural humility and equitable partnerships. To expand this conversation, we conducted community engagement studios, following the model by Joosten et al. We wanted to gather perspectives on research involvement across New Mexico. This process and resultant findings offer valuable insights into effective community engagement practices and advance clinical and translational science by amplifying community voices and needs.

Introduction: Demonstrating the impact of implementation science presents a new frontier for the field, and operationalizing downstream impact is challenging. The Translational Science Benefits Model (TSBM) offers a new approach for assessing and demonstrating research impact. Here we describe integration of the TSBM into a mentored training network.

Methods: Washington University's Clinical and Translational Science Awards TSBM team collaborated with a National Institute of Mental Health-supported training program, the Implementation Research Institute (IRI), a 2-year training institute in mental health implementation science. This partnership included three phases: (1) introductory workshop on research impact, (2) workshop on demonstrating impact, and (3) sessions to guide dissemination, including interactive tools and consultation with the TSBM research team. Fifteen IRI alumni were invited to participate in the pilot; six responded agreeing to participate in the training, develop TSBM case studies, and provide feedback about their experiences. Participants applied the tools and gave feedback on design, usability, and content. We present their case studies and describe how the IRI used the results to incorporate TSBM into future trainings.

Results: The case studies identified 40 benefits spanning all four TSBM domains, including 21 community, 11 policy, five economic, and three clinical benefits. Participants reported that TSBM training helped them develop a framework for talking about impact. Selecting benefits was challenging for early-stage projects, suggesting the importance of early training.

Conclusions: The case studies showcased the institute's impact and the fellows' work and informed refinement of tools and methods for incorporating TSBM into future IRI training.

Introduction: Seattle Children's Research Institute is identifying the amount and type of health equity scholarship being conducted institution wide. However, methods for categorizing how scholarship is equity-focused are lacking. We developed and evaluated the reliability of a health equity scholarship coding schema applied to Seattle Children's affiliated scholarship.

Methods: A 2021-2022 Ovid MEDLINE affiliation search yielded 3551 affiliated scholarship records, with 1079 records identified via an existing filter as scholarship addressing social determinants of health. Through reliability testing and examining concordance and discordance across three independent coders of these records, we developed a coding schema to classify health equity scholarship (yes/no). When health equity scholarship proved positive/Yes, the coders assigned a one through five maturity rating of the scholarship towards addressing inequities. Subsequent reliability testing including a new coder was conducted for 992 subsequent affiliated scholarship records (Oct 2022-June 2023), with additional testing of the sensitivity and specificity of the existing filter relative to the new coding schema.

Results: Reliability for identifying health equity scholarship was consistently high (Fleiss kappas ≥ .78) and categorization of health equity scholarship into maturity levels was moderate (Fleiss kappas ≥ .47). The coding schema identified additional health equity scholarship not captured in an existing filter for social determinants of health scholarship. Based on the new schema, 23.3% of Seattle Childrens' affiliated scholarship published October 2002-June 2023 was health equity focused.

Conclusions: This new coding schema can be used to identify and categorize health equity scholarship to help quantitate the health equity focus of portfolios of human-focused research.

Introduction: The proportion of physician-investigators involved in biomedical research is shrinking even as the need for high-quality, interdisciplinary research is growing. Building the physician-investigator workforce is thus a pressing concern. Flexible, "light-weight" training modalities can help busy physician-investigators prepare for key stages of the research life cycle and personalize their learning to their own needs. Such training can also support researchers from diverse backgrounds and lighten the work of mentors.

Materials and methods: The University of Pittsburgh's Institute for Clinical Research Education designed the Stackables Microcredentials in Clinical and Translational Research (Stackables) program to provide flexible, online training to supplement and enhance formal training programs. This training utilizes a self-paced, just-in-time format along with an interactive, storytelling approach to sustain learner engagement. Learners earn badges for completing modules and certificates for completing "stacks" in key competency areas. In this paper, we describe the genesis and development of the Stackables program and report the results of a pilot study in which we evaluated changes in confidence in key skill areas from pretest to posttest, as well as engagement and perceived effectiveness.

Results: Our Stackables pilot study showed statistically significant gains in learner confidence in all skill areas from pretest to posttest. Pilot participants reported that the module generated high levels of engagement and enhanced their skills, knowledge, and interest in the subject.

Conclusions: Stackables provide an important complement to formal coursework by focusing on discrete skill areas and allowing learners to access the training they need when they need it.

Given the dramatic growth in the financial burden of cancer care over the past decades, individuals with cancer are increasingly susceptible to developing social needs (e.g., housing instability and food insecurity) and experiencing an adverse impact of these needs on care management and health outcomes. However, resources required to connect individuals with needed social and community services typically exceed the available staffing within clinical teams. Using input from focus groups, key informant interviews, user experience/user interface testing, and a multidisciplinary community advisory board, we developed a new technology solution, ConnectedNest, which connects individuals in need to community based organizations (CBOs) that provide services through direct and/or oncology team referrals, with interfaces to support all three groups (patients, CBOs, and oncology care teams). After prototype development, we conducted usability testing, with participants noting the importance of the technology for filling a current gap in screening and connecting individuals with cancer with needed social and community services. We employ a patient-empowered approach that engages the support of an individual's healthcare team and community organizations. Future work will examine the integration and implementation of ConnectedNest for oncology patients, oncology care teams, and cancer-focused CBOs to build capacity for effectively addressing distress in this population.

Background: Phase I clinical trials aim to find the highest dose of a novel drug that may be administrated safely without having serious adverse effects. Model-based designs have recently become popular in dose-finding procedures. Our objective is to provide an overview of phase I clinical trials in oncology.

Methods: A retrospective analysis of phase I clinical trials in oncology was performed by using the PubMed database between January 1, 2020, and December 31, 2022. We extracted all papers with the inclusion of trials in oncology and kept only those in which dose escalation or/ and dose expansion were conducted. We also compared the study parameters, design parameters, and patient parameters between industry-sponsored studies and academia-sponsored research.

Result: Among the 1450 papers retrieved, 256 trials described phase I clinical trials in oncology. Overall, 71.1% of trials were done with a single study cohort, 56.64% of trials collected a group of at least 20 study volunteers, 55.1% were sponsored by industry, and 99.2% of trials had less than 10 patients who experienced DLTs.The traditional 3 + 3 (73.85%) was still the most prevailing method for the dose-escalation approach. More than 50% of the trials did not reach MTDs. Industry-sponsored study enrolled more patients in dose-escalation trials with benefits of continental cooperation. Compared to previous findings, the usage of model-based design increased to about 10%, and the percentage of traditional 3 + 3 design decreased to 74%.

Conclusions: Phase I traditional 3 + 3 designs perform well, but there is still room for development in novel model-based dose-escalation designs in clinical practice.

Objective: The progression of long-term diabetes complications has led to a decreased quality of life. Our objective was to evaluate the adverse outcomes associated with diabetes based on a patient's clinical profile by utilizing a multistate modeling approach.

Methods: This was a retrospective study of diabetes patients seen in primary care practices from 2013 to 2017. We implemented a five-state model to examine the progression of patients transitioning from one complication to having multiple complications. Our model incorporated high dimensional covariates from multisource data to investigate the possible effects of different types of factors that are associated with the progression of diabetes.

Results: The cohort consisted of 10,596 patients diagnosed with diabetes and no previous complications associated with the disease. Most of the patients in our study were female, White, and had type 2 diabetes. During our study period, 5928 did not develop complications, 3323 developed microvascular complications, 1313 developed macrovascular complications, and 1129 developed both micro- and macrovascular complications. From our model, we determined that patients had a 0.1334 [0.1284, .1386] rate of developing a microvascular complication compared to 0.0508 [0.0479, .0540] rate of developing a macrovascular complication. The area deprivation index score we incorporated as a proxy for socioeconomic information indicated that patients who reside in more disadvantaged areas have a higher rate of developing a complication compared to those who reside in least disadvantaged areas.

Conclusions: Our work demonstrates how a multistate modeling framework is a comprehensive approach to analyzing the progression of long-term complications associated with diabetes.

Background: Central venous lines (CVLs) are frequently utilized in critically ill patients and confer a risk of central line-associated bloodstream infections (CLABSIs). CLABSIs are associated with increased mortality, extended hospitalization, and increased costs. Unnecessary CVL utilization contributes to CLABSIs. This initiative sought to implement a clinical decision support system (CDSS) within an electronic health record (EHR) to quantify the prevalence of potentially unnecessary CVLs and improve their timely removal in six adult intensive care units (ICUs).

Methods: Intervention components included: (1) evaluating existing CDSS' effectiveness, (2) clinician education, (3) developing/implementing an EHR-based CDSS to identify potentially unnecessary CVLs, (4) audit/feedback, and (5) reviewing EHR/institutional data to compare rates of removal of potentially unnecessary CVLs, device utilization, and CLABSIs pre- and postimplementation. Data was evaluated with statistical process control charts, chi-square analyses, and incidence rate ratios.

Results: Preimplementation, 25.2% of CVLs were potentially removable, and the mean weekly proportion of these CVLs that were removed within 24 hours was 20.0%. Postimplementation, a greater proportion of potentially unnecessary CVLs were removed (29%, p < 0.0001), CVL utilization decreased, and days between CLABSIs increased. The intervention was most effective in ICUs staffed by pulmonary/critical care physicians, who received monthly audit/feedback, where timely CVL removal increased from a mean of 18.0% to 30.5% (p < 0.0001) and days between CLABSIs increased from 17.3 to 25.7.

Conclusions: A significant proportion of active CVLs were potentially unnecessary. CDSS implementation, in conjunction with audit and feedback, correlated with a sustained increase in timely CVL removal and an increase in days between CLABSIs.

Purpose: This study assesses the feasibility of biomedical informatics resources for efficient recruitment of rural residents with cancer to a clinical trial of a quality-of-life (QOL) mobile app. These resources have the potential to reduce costly, time-consuming, in-person recruitment methods.

Methods: A cohort was identified from the electronic health record data repository and cross-referenced with patients who consented to additional research contact. Rural-urban commuting area codes were computed to identify rurality. Potential participants were emailed study details, screening questions, and an e-consent link via REDCap. Consented individuals received baseline questionnaires automatically. A sample minimum of n = 80 [n = 40 care as usual (CAU) n = 40 mobile app intervention] was needed.

Results: N = 1298 potential participants (n = 365 CAU; n = 833 intervention) were screened for eligibility. For CAU, 68 consented, 67 completed baseline questionnaires, and 54 completed follow-up questionnaires. For intervention, 100 consented, 97 completed baseline questionnaires, and 58 completed follow-up questionnaires. The CAU/intervention reached 82.5%/122.5% of the enrollment target within 2 days. Recruitment and retention rates were 15.3% and 57.5%, respectively. The mean age was 59.5 ± 13.5 years. The sample was 65% women, 20% racial/ethnic minority, and 35% resided in rural areas.

Conclusion: These results demonstrate that biomedical informatics resources can be highly effective in recruiting for cancer QOL research. Precisely identifying individuals likely to meet inclusion criteria who previously indicated interest in research participation expedited recruitment. Participants completed the consent and baseline questionnaires with zero follow-up contacts from the research team. This low-touch, repeatable process may be highly effective for multisite clinical trials research seeking to include rural residents.