Diversity, Equity, and Inclusion in Clinical Research: A Path Toward Precision Health for Everyone

Novel clinical trial designs emerging from the molecular reclassification of cancer

Next-generation sequencing has revealed the disruptive reality that advanced/metastatic cancers have complex and individually distinct genomic landscapes, necessitating a rethinking of treatment strategies and clinical trial designs. Indeed, the molecular reclassification of cancer suggests that it is the molecular underpinnings of the disease, rather than the tissue of origin, that mostly drives outcomes. Consequently, oncology clinical trials have evolved from standard phase 1, 2, and 3 tissue-specific studies; to tissue-specific, biomarker-driven trials; to tissue-agnostic trials untethered from histology (all drug-centered designs); and, ultimately, to patient-centered, N-of-1 precision medicine studies in which each patient receives a personalized, biomarker-matched therapy/combination of drugs. Innovative technologies beyond genomics, including those that address transcriptomics, immunomics, proteomics, functional impact, epigenetic changes, and metabolomics, are enabling further refinement and customization of therapy. Decentralized studies have the potential to improve access to trials and precision medicine approaches for underserved minorities. Evaluation of real-world data, assessment of patient-reported outcomes, use of registry protocols, interrogation of exceptional responders, and exploitation of synthetic arms have all contributed to personalized therapeutic approaches. With greater than 1 × 1012 potential patterns of genomic alterations and greater than 4.5 million possible three-drug combinations, the deployment of artificial intelligence/machine learning may be necessary for the optimization of individual therapy and, in the near future, also may permit the discovery of new treatments in real time.

Underrepresented populations in genomic research: a qualitative study of researchers' perspectives

BACKGROUND

The lack of diversity in genomic data limits researchers' ability to investigate the relationships between genetic profiles, disease manifestations, and responses to new therapies. As a result, innovations in treatment could have potentially harmful effects on a significant portion of the population due to incomplete or inaccurate genomic data. In addition, the lack of harmonization in the use of population descriptors in genomic studies raises both ethical and scientific concerns regarding which descriptors should be used to study and recruit underrepresented populations. Therefore, understanding the factors contributing to the lack of diversity in genomic research is an urgent scientific, clinical, and public health priority. This study aims to explore the social and contextual factors influencing the participation of underrepresented populations in genomic research, from the perspective of researchers in the field.

METHODS

A total of 13 semi-structured interviews were conducted with researchers experienced in genomic research in Canada and fluent in either French or English. The interview transcripts were analyzed using thematic analysis.

RESULTS

Researchers identified several factors contributing to the low participation of underrepresented populations in genomic research, with one key factor being the geographic distribution of research institutions and the disconnect between research efforts and the communities being studied. To address this issue, participants stressed the importance of moving away from colonial practices, such as conducting research on a community without consulting its members in the design phase. Furthermore, it was suggested that existing diversity, equity, and inclusion policies alone were insufficient to effectively address the challenge. Lastly, the study also highlighted a potential link between how study populations are categorized and the willingness of underrepresented groups to participate in genomic research.

CONCLUSION

Although researchers are generally aware of the literature on the causes, consequences, and potential solutions for increasing participation, confusion remains regarding the use of population descriptors. Our findings highlight the need for improved education, greater consensus, and expanded dialogue within the genomic research community to promote the harmonization of population descriptors.

Using Social Media to Engage and Enroll Underrepresented Populations: Longitudinal Digital Health Research

BACKGROUND

Emerging digital health research poses roadblocks to the inclusion of historically marginalized populations in research. Exclusion of underresourced communities in digital health research is a result of multiple factors (eg, limited technology access, decreased digital literacy, language barriers, and historical mistrust of research and research institutions). Alternative methods of access and engagement may aid in achieving long-term sustainability of diversified participation in digital health research, ensuring that developed technologies and research outcomes are effective and equitable.

OBJECTIVE

This study aims to (1) characterize socioeconomic and demographic differences in individuals who enrolled and engaged with different remote, digital, and traditional recruitment methods in a digital health pregnancy study and (2) determine whether social media outreach is an efficient way of recruiting and retaining specific underrepresented populations (URPs) in digital health research.

METHODS

The Better Understanding the Metamorphosis of Pregnancy (BUMP) study was used as a case example. This is a prospective, observational, cohort study using digital health technology to increase understanding of pregnancy among 524 women, aged 18-40 years, in the United States. The study used different recruitment strategies: patient portal for genetic testing results, paid/unpaid social media ads, and a community health organization providing care to pregnant women (Moses/Weitzman Health System).

RESULTS

Social media as a recruitment tool to engage URPs in a digital health study was overall effective, with a 23.6% (140/594) enrollment rate of those completing study interest forms across 25 weeks. Community-based partnerships were less successful, however, resulting in 53.3% (57/107) engagement with recruitment material and only 8.8% (5/57) ultimately enrolling in the study. Paid social media ads provided access to and enrollment of a diverse potential participant pool of race- or ethnicity-based URPs in comparison to other digital recruitment channels. Of those that engaged with study materials, paid recruitment had the highest percentage of non-White (non-Hispanic) respondents (85/321, 26.5%), in comparison to unpaid ads (Facebook and Reddit; 37/167, 22.2%). Of the enrolled participants, paid ads also had the highest percentage of non-White (non-Hispanic) participants (14/70, 20%), compared to unpaid ads (8/52, 15.4%) and genetic testing service subscribers (72/384, 18.8%). Recruitment completed via paid ads (Instagram) had the highest study retention rate (52/70, 74.3%) across outreach methods, whereas recruitment via community-based partnerships had the lowest (2/5, 40%). Retention of non-White (non-Hispanic) participants was low across recruitment methods: paid (8/52, 15.4%), unpaid (3/35, 14.3%), and genetic testing service subscribers (50/281, 17.8%).

CONCLUSIONS

Social media recruitment (paid/unpaid) provides access to URPs and facilitates sustained retention similar to other methods, but with varying strengths and weaknesses. URPs showed lower retention rates than their White counterparts across outreach methods. Community-based recruitment showed lower engagement, enrollment, and retention. These findings highlight social media's potential for URP engagement and enrollment, illuminate potential roadblocks of traditional methods, and underscore the need for tailored research to improve URP enrollment and retention.

Pediatric Acute Otitis Media Clinical Trials: An Analysis of Diversity

OBJECTIVE

This study aims to assess the diversity and equity of pediatric acute otitis media (AOM) trials using ClinicalTrials.gov, focusing on participant demographics and representation to identify gaps in inclusivity and inform strategies for promoting diversity in future pediatric AOM studies.

STUDY DESIGN

Retrospective analysis.

SETTING

ClinicalTrials.gov.

METHODS

A retrospective analysis was performed on completed clinical trials enrolling pediatric patients with AOM, registered to ClinicalTrials.gov. Only trials that reported results were included. There were 48 trials, excluding duplicates, that matched these criteria. These trials were analyzed for data including study demographics (age, sex, race, ethnicity) and trial characteristics (location, sponsor/funder).

RESULTS

The analysis revealed that of the 48 trials, a significant portion underreported race and ethnicity, with 43.7% of trials reporting race and 25% reporting ethnicity. A majority of the participants identified as white (69.9%), showcasing notable disparities in representation. Domestic trials were more likely to report on race (50%) and ethnicity (30%) compared to international trials (22.3% and 0%, respectively). Privately funded trials reported at higher rates (53.3%) compared to publicly funded ones (38.9%), while the reporting of ethnicity was comparably low between both (20% and 33.3%, respectively).

CONCLUSION

The study highlights the urgent need for more inclusive representation in pediatric clinical research, particularly in AOM trials. Despite guidelines aimed at improving demographic reporting, significant gaps remain. Future research efforts must prioritize the inclusion of diverse populations to ensure clinical trials are generalizable and equitable, thereby advancing toward developing more effective and universally applicable health care solutions for pediatric AOM.

Contextualizing barriers and facilitators to scaling community-engaged research transformation at a historically black medical school

Introduction

Morehouse School of Medicine (MSM) embodies an applied definition of community engagement advanced over four decades. The increased demand for community collaboration requires attention to the institutional contexts supporting community-engaged research. MSM partnered with the University of New Mexico Center for Participatory Research for the Engage for Equity (E2) PLUS Project to assess, ideate, and consider existing and recommended institutional supports for community-engaged research.

Methods

MSM assembled a community-campus Champion Team. The team coordinated virtual workshops with 18 community and academic research partners, facilitated four interviews of executive leaders and two focus groups (researchers/research staff and patients/community members, respectively) moderated by UNM-CPR. Analyses of the transcripts were conducted using an inductive and deductive process. Once the themes were identified, the qualitative summaries were shared with the Champion Team to verify and discuss implications for action and institutional improvements.

Results

Institutional strengths and opportunities for systemic change were aligned with equity indicators (power and control, decision-making, and influence) and contextual factors (history, trust, and relationship building) of The continuum of community engagement in research. Institutional advances include community-engagement added as the fourth pillar of the institution's strategic plan. Action strategies include 1) development a research navigation system to address community-campus research partnership administrative challenges and 2) an academy to build the capacities of community/patient partners to independently acquire, manage, and sustain grants and negotiate equity in dissemination of research.

Conclusions

MSM has leveraged E2 PLUS to identify systems improvements necessary to ensure that community/patient-centered research and partnerships are amplified and sustained.

Conceptualizing, operationalizing, and utilizing equity, diversity, and inclusion in clinical trials: a scoping review

OBJECTIVES

Equity, diversity, and inclusion (EDI) are social constructs which when used in clinical trials, or clinical research broadly help generate the highest quality evidence for interventions in the populations most likely to benefit. However, the incorporation of these constructs is unclear and inconsistent. This scoping review sought to understand how EDI is applied in clinical trials with broader application across clinical research.

METHODS

We reviewed literature from PubMed and Google Scholar, selecting studies 1) published from 2000 to 2023, 2) literature which described concepts, tools, metrics, or frameworks, and 3) provided information on conceptualization, operationalization (measuring) or utilization (analyzing). Additionally, internet searches were conducted to identify websites of research partners such as government institutions, funders, regulators and publishers across the research lifecycle. Websites retrieved were included for our review of EDI consideration (either concepts or statements) outside but impacting upon the published literature.

RESULTS

We reviewed 2385 titles and abstracts and included 75 (3%) in analyses. From gray literature searches of 269 identified key research partners, additional 49 records were included. Studies conceptualized EDI as interconnected rather than distinct constructs. These concepts were often reinforcing, such as efforts to enhance diversity which also promote equity and foster inclusion. Regarding operationalization, 12 frameworks, 20 tools/metrics were identified for EDI assessment across the research lifecycle. These metrics were primarily used for reporting EDI data, and utilization across research lifecycle remains limited. Among research partners, a third of publishers (6 of 20) had any EDI considerations; followed by 2 of 19 trial registries, 12 of 44 research funders, 7 of 60 journals, and none of ethics committee and data repositories reported statements on EDI.

CONCLUSION

This review highlights that a range of EDI relevant tools, frameworks and metrics, each with their unique strengths and limitations. We found a wider adoption of EDI considerations by research partners is still lacking. Future research could explore the impact of different EDI criteria on trial outcomes and the generalizability of trial results.

Racial, ethnic, and socioeconomic disparities in clinical trial reporting for metastatic spine tumors: An exploration of North American studies

PURPOSE

The objective of this study was to evaluate the reporting of racial, ethnic, and socioeconomic data in clinical trials exploring the management of metastatic spine disease (MSD).

METHODS

We undertook a cross-sectional analysis of North American completed and published clinical trials registered on ClinicalTrials.gov exploring the management of patients with MSD. Data on patient demographics, trial characteristics, reporting of race and ethnicity, distribution of racial and ethnic groups, and reporting of socioeconomic measures was extracted from ClinicalTrials.gov and related publications identified through PubMed and Google Scholar searches. An exploratory data analysis was performed, followed by Pearson's Chi-square and binary logistic regression analyses to explore associations of covariates with racioethnic reporting.

RESULTS

Out of 158 completed trials, only 8% (12 of 158) met inclusion criteria with published results. These 12 trials included a total of 1,568 patients with a mean age of 61 years. Almost half (42%; (5 of 12)) of trials did not report race, while only 17% (2 of 12) of trials reported ethnicity. In trials reporting complete racial data (n = 5), 77% (377 of 493) patients were White, 15% (n = 73) Black or African American, and 4% (n = 19) Asian. American Indian/Alaska Native and Native Hawaiian/Other Pacific Islander patients were severely underrepresented (0.4% and 0.2%, respectively). Of the two trials reporting ethnicity, 94% (479 of 514) patients were Not Hispanic or Latino. Sponsoring body of the trial, trial phase, intervention type, number of trial patients, or mean age of patients were not significantly associated with racioethnic reporting. Notably, no trial reported any measures of socioeconomic status.

CONCLUSION

Our review revealed significant gaps in the reporting of racial, ethnic, and socioeconomic data in MSD clinical trials, with substantial underrepresentation of minority groups. This underrepresentation limits the generalizability of trial findings and may perpetuate health disparities. Coordinated efforts from researchers, clinicians, policymakers, and funding bodies are needed to improve diversity in future trials. Strategies such as targeted outreach, community engagement, and more inclusive eligibility criteria should be implemented to ensure that trial populations better reflect the diversity of MSD patients in the general population.

Ethical and academic dilemmas in authorship of clinical research publications: a medical oncologist's perspective

Authorship in clinical research carries significant academic, financial, and social implications. However, determining rightful authorship often introduces ethical and professional dilemmas, particularly in large, multidisciplinary studies, such as those common in oncology. This article explores the ethical complexities surrounding authorship in clinical research from the viewpoint of a medical oncologist. It addresses issues, such as academic jealousy, the inclusion of industry-affiliated researchers, honorary authorship, and the role of patient recruitment in authorship qualification. By examining current guidelines, ethical considerations, and practical cases, this paper aims to offer insights into fostering fair and transparent authorship practices in the field of clinical oncology.

Measuring Representativeness in Clinical Trials

Representativeness in randomized clinical trials remains a critical concern, affecting the external validity of trial results, equitable access to the risks and benefits of research participation, and public trust in clinical research. Although representative participation by members of groups traditionally underrepresented in clinical trials is just a surrogate for true diversity, equity, inclusion, and belonging in clinical trials, it can be quantified, allowing stakeholders to add empirical rigor to diversity, equity, inclusion, and belonging efforts. Multiple ways to measure representativeness have been proposed, including the participation-to-prevalence ratio, raw participation proportions or numbers for relevant subgroups, and enrollment fraction for relevant subgroups. These methods have strengths and weaknesses and may be appropriate to report in certain circumstances, depending on why stakeholders seek to assess representativeness. Stakeholders-including regulatory agencies, journal editors, clinical trial investigators, and trial sponsors-may use quantitative measures of representativeness to establish trial enrollment standards, monitor equitable participation in ongoing trials, and condition funding or drug or device approval on achieving specific representativeness targets. However, using quantitative measures of representativeness in this way could have unintended consequences, including researchers "gaming" recruitment strategies to meet target numbers, overlooking nuanced variations within communities, and potentially incentivizing problematic and exploitative recruitment strategies. Although no single method of measuring representativeness offers a comprehensive solution for increasing diversity, equity, inclusion, and belonging in all randomized clinical trials, a carefully designed, multifaceted approach to measuring representativeness may provide stakeholders with useful perspectives for measuring progress in increasing the diversity of clinical trial participation. For stakeholders seeking a single number to assess the representativeness of a trial enrolling patients with a disease state with well-delineated demographics, the participation-to-prevalence ratio is ideal; however, for a more nuanced view of representativeness, the combination of enrollment fraction in subgroups of relevance plus a full report of the demographics of patients approached for enrollment may be more appropriate.

Inclusion of people with multiple long-term conditions in pregnancy research: patient, public and stakeholder involvement and engagement in a randomised controlled trial

BACKGROUND

Both pregnant women and those with multiple long-term conditions are under-served groups in clinical research. Informing and improving research through patient and public involvement, including pregnant women with two or more long-term health conditions, is critical to increasing their inclusion in maternity research. Giant PANDA is a randomised controlled trial, evaluating the effect of a treatment initiation strategy with nifedipine versus labetalol on severe maternal hypertension and a composite outcome of fetal/neonatal death, or neonatal unit admission. We aimed to undertake a mixed methods study-within-a-project within the Giant PANDA trial to understand barriers and facilitators to participation, understand and optimise current representativeness of clinical trial delivery of those with multiple long-term conditions and co-create a checklist to support their inclusion in pregnancy research.

METHODS

We undertook online workshops with women with lived experience and hybrid workshops with healthcare professionals who look after women with multiple long-term conditions. A site audit of Giant PANDA sites provided insights into research delivery capacity and health system set-up, and how this influences inclusion. An extension to the Giant PANDA screening log captured data on multiple long-term conditions enabling analysis of the impact of these health conditions on women's inclusion in the trial. We co-created a checklist of recommendations for those designing and recruiting to similar clinical trials.

RESULTS

Five key recommendations were identified including a need to (1) involve women with multiple long-term conditions as partners in maternity research and (2) minimise barriers that stop them from taking part through (3) designing and delivering research that is flexible in time and place (4) consider research as part of care for everyone, including those with multiple long-term conditions and (5) measure and report inclusion of those with two or more health conditions in maternity research. Multiple long-term conditions were not a barrier to recruitment or randomisation in the Giant PANDA trial.

CONCLUSION

Women with multiple long-term conditions would like opportunities to find out about and participate in research which accounts for their needs. Our checklist aims to support those designing and delivering maternity research to optimise inclusion of individuals with multiple-long term conditions.

TRIAL REGISTRATION

Giant PANDA: EudraCT number: 2020-003410-12, ISRCTN: 12,792,616.

Remote data collection of infant activity and sleep patterns via wearable sensors in the HEALthy Brain and Child Development Study (HBCD)

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. Wearable and remote sensing technologies have advanced data collection outside of laboratory settings to enable exploring, in more detail, the associations of early experiences with brain development and social and health outcomes. In the HBCD Study, the Novel Technology/Wearable Sensors Working Group (WG-NTW) identified two primary data types to be collected: infant activity (by measuring leg movements) and sleep (by measuring heart rate and leg movements). These wearable technologies allow for remote collection in the natural environment. This paper illustrates the collection of such data via wearable technologies and describes the decision-making framework, which led to the currently deployed study design, data collection protocol, and derivatives, which will be made publicly available. Moreover, considerations regarding actual and potential challenges to adoption and use, data management, privacy, and participant burden were examined. Lastly, the present limitations in the field of wearable sensor data collection and analysis will be discussed in terms of extant validation studies, the difficulties in comparing performance across different devices, and the impact of evolving hardware/software/firmware.

"I am there just to get on with it": a qualitative study on the labour of the patient and public involvement workforce

BACKGROUND

Workers tasked with specific responsibilities around patient and public involvement (PPI) are now routinely part of the organizational landscape for applied health research in the United Kingdom. Even as the National Institute for Health and Care Research (NIHR) has had a pioneering role in developing a robust PPI infrastructure for publicly funded health research in the United Kingdom, considerable barriers remain to embedding substantive and sustainable public input in the design and delivery of research. Notably, researchers and clinicians report a tension between funders' orientation towards deliverables and the resources and labour required to embed public involvement in research. These and other tensions require further investigation.

METHODS

This was a qualitative study with participatory elements. Using purposive and snowball sampling and attending to regional and institutional diversity, we conducted 21 semi-structured interviews with individuals holding NIHR-funded formal PPI roles across England. Interviews were analysed through reflexive thematic analysis with coding and framing presented and adjusted through two workshops with study participants.

RESULTS

We generated five overarching themes which signal a growing tension between expectations put on staff in PPI roles and the structural limitations of these roles: (i) the instability of support; (ii) the production of invisible labour; (iii) PPI work as more than a job; (iv) accountability without control; and (v) delivering change without changing.

CONCLUSIONS

The NIHR PPI workforce has enabled considerable progress in embedding patient and public input in research activities. However, the role has led not to a resolution of the tension between performance management priorities and the labour of PPI, but rather to its displacement and - potentially - its intensification. We suggest that the expectation to "deliver" PPI hinges on a paradoxical demand to deliver a transformational intervention that is fundamentally divorced from any labour of transformation. We conclude that ongoing efforts to transform health research ecologies so as to better respond to the needs of patients will need to grapple with the force and consequences of this paradoxical demand.

Integrating Machine Learning with Multi-Omics Technologies in Geroscience: Towards Personalized Medicine

Aging is a fundamental biological process characterized by a progressive decline in physiological functions and an increased susceptibility to diseases. Understanding aging at the molecular level is crucial for developing interventions that could delay or reverse its effects. This review explores the integration of machine learning (ML) with multi-omics technologies-including genomics, transcriptomics, epigenomics, proteomics, and metabolomics-in studying the molecular hallmarks of aging to develop personalized medicine interventions. These hallmarks include genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, disabled macroautophagy, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, altered intercellular communication, chronic inflammation, and dysbiosis. Using ML to analyze big and complex datasets helps uncover detailed molecular interactions and pathways that play a role in aging. The advances of ML can facilitate the discovery of biomarkers and therapeutic targets, offering insights into personalized anti-aging strategies. With these developments, the future points toward a better understanding of the aging process, aiming ultimately to promote healthy aging and extend life expectancy.

Is there a relationship between attitudes of general practitioners/family doctors and attitudes of their patients regarding industry-sponsored clinical investigations? A cross-sectional survey in a convenience sample of doctors and patients across nine European countries

AIM

To assess the relationship between the attitudes of general practitioners/family medicine doctors (GP/FD) and of their patients toward industry-sponsored clinical research.

METHODS

A cross-sectional survey included volunteer GPs/FDs who then enrolled and interviewed their patients. Data were analyzed in hierarchical models (patients nested in GPs/FDs, nested in countries/regions).

RESULTS

A total of 201 GPs/FDs from nine European countries responded to the invitation and enrolled 995 of their patients. We observed mild associations between some of the GPs/FDs' attitudes (general opinion on sponsored clinical studies, appreciation of the general values of such studies, views about the importance of participant protection/privacy) and some of the patients' attitudes (appreciation of the general values and of risks associated with sponsored clinical studies, importance assigned to potential personal benefits from participation). We observed no association between GPs/FDs' attitudes and patients' willingness to participate in such studies. However, willingness to participate increased with higher patients' appreciation of the general values of sponsored studies, decreased with higher patients' appreciation of associated risks, and showed a quadratic trend across the levels of importance assigned by patients to potential personal benefits (willingness was higher when the assigned importance was very low or very high). More importance to GP/FD's advice in this respect was assigned by patients who assigned more importance to potential personal benefits, who were better educated, and who resided in rural/suburban dwellings.

CONCLUSIONS

In the present convenience sample, lay-person attitudes about and willingness to participate in industry-sponsored clinical studies were associated with the attitudes of their GPs/FDs.

Utilizing a Virtual Reality Matrix in Medical Education

Virtual reality (VR) is an emerging technology that has demonstrated incredible value within medical education. However, medical institutions adopting VR as a learning tool need to ensure that the immersive technology product they pick possesses standard usability criteria. The current literature is limited in defining what specific criteria institutions should look for, or how to select between various VR products. Since there have been little to no algorithms available to the medical education community to aid in this process, a reproducible matrix has been developed to evaluate multiple VR platforms at once which can help identify the best option for medical education programs. The matrix is a 10-point scoring system that includes what the research team considered to be the 10 most important factors when selecting a VR product for medical education. The scores of any two or more VR products can be quantitatively compared. Therefore, the matrix is to be used as a methodological framework to help objectively select the highest-rated immersive technology platform. The research team involved in the development of the matrix consisted of an associate dean for simulation and technology, a director of simulation and technology, and eight medical students.

Association of estimated pulse wave velocity with cognitive function in a multiethnic diverse population: The Northern Manhattan Study

INTRODUCTION

Arterial stiffness is linked to age-related cognitive dysfunction. Estimated pulse wave velocity (ePWV) is associated with cerebrovascular disease. We sought to determine whether ePWV was associated with cognition in a multiethnic population.

METHODS

We included 1257 participants enrolled in a Northern Manhattan Study magnetic resonance imaging MRI-cognitive study (mean age 64 ± 8 years, 61% women, 67% Hispanic, 18% non-Hispanic Black, 15% non-Hispanic white) and analyzed cognitive performance at two time points, at enrollment and on an average 5.0 ± 0.6 years later. ePWV was calculated using baseline age and blood pressure. Cognition and cognitive change scores were regressed on ePWV in multivariable linear regression models.

RESULTS

In adjusted models, ePWV (mean 11 ± 2 m/s) was significantly associated with cognition (b = -0.100, 95% CI, -0.120, -0.080) and cognitive change over time (b = -0.063, 95% CI, -0.082, -0.045). Effect modification by race and sex was found.

DISCUSSION

In this multiethnic population, the associations of ePWV with cognitive performance underline the role of vascular stiffness in age-related cognitive decline.

HIGHLIGHTS

ePWV is a modest but independent predictor of cognitive function and cognitive decline among older individuals. After adjustment, the ePWV measure was inversely associated with performance and decline in global cognition, processing speed, episodic memory, executive function, and semantic memory. After adjustment, modification of the association between ePWV and change in episodic memory and executive function by race and ethnicity was suggested by a significant interaction term. The association between ePWV and episodic memory decline was stronger in females.

Simplifying informed consent as a universal precaution

One barrier to participating in clinical research is that patients with low literacy skills (1 in 5 US adults) may struggle to understand the informed consent document (ICD). Writing consents using health literacy and plain language guidelines including simplified syntax and semantics can increase understandability and facilitate inclusivity of research populations with literacy challenges. Our study aim was to evaluate a simplified ICD for understandability while considering factors known to relate to comprehension (reading skills and working memory). We performed an on-line survey of 192 adults ages 18-77 in Georgia. Participants performed significantly better on the simplified ICD test. We built an additional model with all version x measure interactions (i.e., age, sex, race, urbanicity, GMVT, WM). This model did not significantly improve model fit, F < 1.00, suggesting that individual differences did not moderate the effect of simplification. Our findings suggest that using plain language and simplified syntax and semantics in ICD as a universal precaution may reduce cognitive reading burden for adults regardless of differences in reading skill or working memory. Increasing understandability in ICD may help improve targets for clinical trial enrollment.

Integrating Diversity, Equity, and Inclusion into Preclinical, Clinical, and Public Health Mathematical Models

Mathematical modelling applied to preclinical, clinical, and public health research is critical for our understanding of a multitude of biological principles. Biology is fundamentally heterogeneous, and mathematical modelling must meet the challenge of variability head on to ensure the principles of diversity, equity, and inclusion (DEI) are integrated into quantitative analyses. Here we provide a follow-up perspective on the DEI plenary session held at the 2023 Society for Mathematical Biology Annual Meeting to discuss key issues for the increased integration of DEI in mathematical modelling in biology.

Strategies for improving diversity, equity, and inclusion in cardiovascular research: a primer

This paper aims to empower cardiovascular (CV) researchers by promoting diversity, equity, and inclusion (DE&I) principles throughout the research cycle. It defines DE&I and introduces practical strategies for implementation in recruitment, retention, and team dynamics within CV research. Evidence-based approaches supporting underrepresented populations' participation are outlined for each research phase. Emphasizing the significance of inclusive research environments, the paper offers guidance and resources. We invite CV researchers to actively embrace DE&I principles, enhancing research relevance and addressing longstanding CV health disparities.

More than Just a Number: Perspectives from Black Male Participants on Community-Based Interventions and Clinical Trials to Address Cardiovascular Health Disparities

BACKGROUND

Black Americans remain significantly underrepresented and understudied in research. Community-based interventions have been increasingly recognized as an effective model for reckoning with clinical trial participation challenges amongst underrepresented groups, yet a paucity of studies implement this approach. The present study sought to gain insight into Black male participants' perception of clinical trials before and after participating in a community-based team lifestyle intervention in the United States.

METHODS

Black Impact, a 24-week community-based lifestyle intervention, applied the American Heart Association's Life's Simple 7 (LS7) framework to assess changes in the cardiovascular health of seventy-four Black male participants partaking in weekly team-based physical activities and LS7-themed education and having their social needs addressed. A subset of twenty participants completed an exit survey via one of three semi-structured focus groups aimed at understanding the feasibility of interventions, including their perceptions of participating in clinical trials. Data were transcribed verbatim and analyzed using a content analysis, which involved systematically identifying, coding, categorizing, and interpreting the primary patterns of the data.

RESULTS

The participants reported a positive change in their perceptions of clinical trials based on their experience with a community-based lifestyle intervention. Three prominent themes regarding their perceptions of clinical trials prior to the intervention were as follows: (1) History of medical abuse; (2) Lack of diversity amongst research teams and participants; and (3) A positive experience with racially concordant research teams. Three themes noted to influence changes in their perception of clinical trials based on their participation in Black Impact were as follows: (1) Building trust with the research team; (2) Increasing awareness about clinical trials; and (3) Motivating participation through community engagement efforts.

CONCLUSIONS

Improved perceptions of participating in clinical trials were achieved after participation in a community-based intervention. This intervention may provide a framework by which to facilitate clinical trial participation among Black men, which must be made a priority so that Black men are "more than just a number" and no longer "receiving the short end of the stick".

Sex, gender, sexual orientation, and more: Sexual diversity in Alzheimer's research needs a new lens to achieve inclusive research and generalizable results

Diversity, Equity, and Inclusion (DEI) efforts in Alzheimer's disease and related dementia (ADRD) research are guiding the adoption of two-step self-report questions that capture research participants' identity based on categories of sex, sexual orientation, and gender identity. The intent is to facilitate inclusion and representation of sexual and gender minoritized (SGM) communities in ADRD research. The data from using these questions are on a collision course with another National Institute of Aging initiative, which is aimed at understanding sex differences in ADRD mechanisms. Here, we critically analyze the goals and methods of the two initiatives. We propose that, in addition to being SGM focused, DEI efforts are needed to expand how scientists consider and measure sexual diversity itself.

Highlights

Sex, sexual orientation, and gender identity (SSOGI) will be asked in ADRD studies.SSOGI data will expand representation of research participant identities.SSOGI data are on a collision course with sex differences research.Both emphasize sexual diversity (SD) largely as SSOGI identity categories.Diversity, Equity, and Inclusion efforts must develop SD methods in ADRD research.

Diversity in Oncology Clinical Trials: Current Landscape for Industry-Sponsored Clinical Trials in Asia

INTRODUCTION

There has been a growing recognition on the importance of diversity in clinical trials. Existing research has highlighted a significant demographic imbalance. Amidst this renewed focus on diversity, it is crucial to acknowledge that Asia comprises over half of the world's population. Given the region's demographic significance, we sought to compare various characteristics and growth rates for trials with sites in Asia against those without any sites in Asia.

METHODS

We performed comprehensive analyses of industry-sponsored phase 2 and 3 oncology trials registered at Clinicaltrials.gov, using drugs or biologics as investigational agents and executed between 1 January 2018 and 31 December 2022. We applied the compound annual growth rate (CAGR) as an analytical tool to track the trial growth rates over this 5-year period.

RESULTS

We identified 894 industry-sponsored phase 2 and 3 cancer studies with available study location data. Out of these, 415 trials (46.42%) had study sites in Asia. Notably, these trials with sites in Asia were also more likely to be phase 3 trials (39.76% vs 6.47%, p < 0.001), include female and paediatric populations, and be randomised trials. Interestingly, lung and stomach cancers were more commonly studied in these trials, while myeloma was less commonly studied. The number of trial sites for liver cancer was not significantly higher for Asia, even though the incidence of the disease is much higher in this region. Despite an overall declining trend in the number of clinical trials in the last 5 years, we observed a transitional positive increase in the CAGR from 2020 to 2021 for trials with sites in Asia. However, East Asia, specifically China, exhibited a disproportionate overrepresentation in these trials.

CONCLUSIONS

There are notable characteristics of clinical trials with sites in Asia. Comprehending these disparities may aid in the strategic planning to enhance a balanced representation of ethnicities in trials.

The landscape of decentralized clinical trials (DCTs): focusing on the FDA and EMA guidance

Decentralized clinical trials (DCTs) consist of off-site trial-related procedures referred to as decentralized elements. We aimed to provide an overview of the landscape of DCTs by comparing regulatory guidance reports and analyzing decentralized elements from clinical trial registries. Two guidance reports on DCTs published by the U.S. Food and Drug Administration and the European Medicines Agencies were summarized and analyzed. Both guidance publications commonly emphasized an assessment of the appropriateness of decentralized elements along 2 axes: patient safety and data integrity. DCT cases were identified from ClinicalTrials.gov by searching with 6 keywords: decentralized, remote, mobile, digital, virtual, and hybrid. Cases where the keyword was used in a non-DCT context, such as digital flexor tendon, were excluded by means of natural language processing. A total of 4,874 trials were identified as DCT cases, with annual increases, especially after 2020. The most common keywords were 'mobile' and 'digital' (36.2% and 24.8%, respectively). Interventions in the DCT cases were analyzed by means of a network analysis. Behavioral and technological tokens were frequently combined, such as 'rehabilitation' and 'app.' Drugs were used in only 1.8% of the DCT cases. Of these, most drugs had been approved previously (96.8%) and were in oral formulation (67.2%). Most of the DCT cases identified in this study involved simple interventions and low-risk drugs. These characteristics were in accordance with the common recommendations in the DCT guidance publications.

Leveraging artificial intelligence to advance implementation science: potential opportunities and cautions

BACKGROUND

The field of implementation science was developed to address the significant time delay between establishing an evidence-based practice and its widespread use. Although implementation science has contributed much toward bridging this gap, the evidence-to-practice chasm remains a challenge. There are some key aspects of implementation science in which advances are needed, including speed and assessing causality and mechanisms. The increasing availability of artificial intelligence applications offers opportunities to help address specific issues faced by the field of implementation science and expand its methods.

MAIN TEXT

This paper discusses the many ways artificial intelligence can address key challenges in applying implementation science methods while also considering potential pitfalls to the use of artificial intelligence. We answer the questions of "why" the field of implementation science should consider artificial intelligence, for "what" (the purpose and methods), and the "what" (consequences and challenges). We describe specific ways artificial intelligence can address implementation science challenges related to (1) speed, (2) sustainability, (3) equity, (4) generalizability, (5) assessing context and context-outcome relationships, and (6) assessing causality and mechanisms. Examples are provided from global health systems, public health, and precision health that illustrate both potential advantages and hazards of integrating artificial intelligence applications into implementation science methods. We conclude by providing recommendations and resources for implementation researchers and practitioners to leverage artificial intelligence in their work responsibly.

CONCLUSIONS

Artificial intelligence holds promise to advance implementation science methods ("why") and accelerate its goals of closing the evidence-to-practice gap ("purpose"). However, evaluation of artificial intelligence's potential unintended consequences must be considered and proactively monitored. Given the technical nature of artificial intelligence applications as well as their potential impact on the field, transdisciplinary collaboration is needed and may suggest the need for a subset of implementation scientists cross-trained in both fields to ensure artificial intelligence is used optimally and ethically.

Research and application of artificial intelligence in dentistry from lower-middle income countries - a scoping review

Artificial intelligence (AI) has been integrated into dentistry for improvement of current dental practice. While many studies have explored the utilization of AI in various fields, the potential of AI in dentistry, particularly in low-middle income countries (LMICs) remains understudied. This scoping review aimed to study the existing literature on the applications of artificial intelligence in dentistry in low-middle income countries. A comprehensive search strategy was applied utilizing three major databases: PubMed, Scopus, and EBSCO Dentistry & Oral Sciences Source. The search strategy included keywords related to AI, Dentistry, and LMICs. The initial search yielded a total of 1587, out of which 25 articles were included in this review. Our findings demonstrated that limited studies have been carried out in LMICs in terms of AI and dentistry. Most of the studies were related to Orthodontics. In addition gaps in literature were noted such as cost utility and patient experience were not mentioned in the included studies.

Leveraging the Academic Artificial Intelligence Silecosystem to Advance the Community Oncology Enterprise

Over the last 75 years, artificial intelligence has evolved from a theoretical concept and novel paradigm describing the role that computers might play in our society to a tool with which we daily engage. In this review, we describe AI in terms of its constituent elements, the synthesis of which we refer to as the AI Silecosystem. Herein, we provide an historical perspective of the evolution of the AI Silecosystem, conceptualized and summarized as a Kuhnian paradigm. This manuscript focuses on the role that the AI Silecosystem plays in oncology and its emerging importance in the care of the community oncology patient. We observe that this important role arises out of a unique alliance between the academic oncology enterprise and community oncology practices. We provide evidence of this alliance by illustrating the practical establishment of the AI Silecosystem at the City of Hope Comprehensive Cancer Center and its team utilization by community oncology providers.

An Equity and Justice-Informed Ethical Framework to Guide Incidental Findings in Brain Imaging Research

The handling of incidental findings (IFs) in brain imaging studies has been a source of contention among scientists and bioethicists. A conceptual framework informed by diversity, equity, and inclusion (DEI) and distributive justice approaches, namely EUSTICE, is proposed for the ethical handling and reporting of IFs in brain imaging research. I argue that EUSTICE provides a systematic and inclusive approach to addressing the ethical conundrum around IF disclosure and managing IFs proportionately and sensitively in brain imaging research. The EUSTICE framework may have implications for the field of neurosciences or human studies broadly in guiding ethics of IFs in research.