ResearchMatch on FHIR: Development and evaluation of a recruitment registry and electronic health record system interface for volunteer profile completion.

Background: Obtaining complete and accurate information in recruitment registries is essential for matching potential participants to research studies for which they qualify. Since electronic health record (EHR) systems are required to make patient data available to external systems, an interface between EHRs and recruitment registries may improve accuracy and completeness of volunteers' profiles. We tested this hypothesis on ResearchMatch (RM), a disease- and institution-neutral recruitment registry with 1357 studies across 255 institutions. Methods: We developed an interface where volunteers signing up for RM can authorize transfer of demographic data, medical conditions, and medications from the EHR into a registration form. We obtained feedback from a panel of community members to determine acceptability of the planned integration. We then developed the EHR interface and performed an evaluation study of 100 patients to determine whether RM profiles generated with EHR-assisted adjudication included more conditions and medications than those without the EHR connection. Results: Community member feedback revealed that members of the public were willing to authenticate into the EHR from RM with proper messaging about choice and privacy. The evaluation study showed that out of 100 participants, 75 included more conditions and 69 included more medications in RM profiles completed with the EHR connection than those without. Participants also completed the EHR-connected profiles in 16 fewer seconds than non-EHR-connected profiles. Conclusions: The EHR to RM integration could lead to more complete profiles, less participant burden, and better study matches for many of the over 148,000 volunteers who participate in ResearchMatch.

Decentralized clinical trials in the trial innovation network: Value, strategies, and lessons learned.

New technologies and disruptions related to Coronavirus disease-2019 have led to expansion of decentralized approaches to clinical trials. Remote tools and methods hold promise for increasing trial efficiency and reducing burdens and barriers by facilitating participation outside of traditional clinical settings and taking studies directly to participants. The Trial Innovation Network, established in 2016 by the National Center for Advancing Clinical and Translational Science to address critical roadblocks in clinical research and accelerate the translational research process, has consulted on over 400 research study proposals to date. Its recommendations for decentralized approaches have included eConsent, participant-informed study design, remote intervention, study task reminders, social media recruitment, and return of results for participants. Some clinical trial elements have worked well when decentralized, while others, including remote recruitment and patient monitoring, need further refinement and assessment to determine their value. Partially decentralized, or "hybrid" trials, offer a first step to optimizing remote methods. Decentralized processes demonstrate potential to improve urban-rural diversity, but their impact on inclusion of racially and ethnically marginalized populations requires further study. To optimize inclusive participation in decentralized clinical trials, efforts must be made to build trust among marginalized communities, and to ensure access to remote technology.

"Send My Information": Increasing public accessibility to clinical trials by facilitating participant expression of interest.

Introduction: The process of identifying and connecting with clinical trial study teams can be challenging and difficult for members of the public. The national volunteer community registry, ResearchMatch, and the public clinical trials search tool, Trials Today, work in tandem to bridge this connection by providing a streamlined process for potential participants to identify clinical trials which may be of interest. Methods: Building on the existing infrastructure of ResearchMatch and Trials Today, we created a mechanism by which the public can request that their basic contact information (e.g., email/phone) be securely shared with any actively recruiting clinical trial, including trials with no existing relationship with ResearchMatch. Results: Within the first 2 years of use (July 2019-July 2021), ResearchMatch Volunteers sent 12,251 requests to study teams. On average, 20% of these requests were accepted by the study teams. Conclusions: The utilization of this tool indicates that there is active interest among members of the public to independently contact study teams about trials of interest. Additionally, research teams unaffiliated with ResearchMatch are willing to at minimum accept contact information. This allows ResearchMatch to successfully serve as a medium, connecting members of the public with actively recruiting trials.

The Recruitment Innovation Center: Developing novel, person-centered strategies for clinical trial recruitment and retention.

Clinical trials continue to face significant challenges in participant recruitment and retention. The Recruitment Innovation Center (RIC), part of the Trial Innovation Network (TIN), has been funded by the National Center for Advancing Translational Sciences of the National Institutes of Health to develop innovative strategies and technologies to enhance participant engagement in all stages of multicenter clinical trials. In collaboration with investigator teams and liaisons at Clinical and Translational Science Award institutions, the RIC is charged with the mission to design, field-test, and refine novel resources in the context of individual clinical trials. These innovations are disseminated via newsletters, publications, a virtual toolbox on the TIN website, and RIC-hosted collaboration webinars. The RIC has designed, implemented, and promised customized recruitment support for 173 studies across many diverse disease areas. This support has incorporated site feasibility assessments, community input sessions, recruitment materials recommendations, social media campaigns, and an array of study-specific suggestions. The RIC's goal is to evaluate the efficacy of these resources and provide access to all investigating teams, so that more trials can be completed on time, within budget, with diverse participation, and with enough accrual to power statistical analyses and make substantive contributions to the advancement of healthcare.

Using supervised machine learning classifiers to estimate likelihood of participating in clinical trials of a de-identified version of ResearchMatch.

INTRODUCTION: Lack of participation in clinical trials (CTs) is a major barrier for the evaluation of new pharmaceuticals and devices. Here we report the results of the analysis of a dataset from ResearchMatch, an online clinical registry, using supervised machine learning approaches and a deep learning approach to discover characteristics of individuals more likely to show an interest in participating in CTs. METHODS: We trained six supervised machine learning classifiers (Logistic Regression (LR), Decision Tree (DT), Gaussian Naïve Bayes (GNB), K-Nearest Neighbor Classifier (KNC), Adaboost Classifier (ABC) and a Random Forest Classifier (RFC)), as well as a deep learning method, Convolutional Neural Network (CNN), using a dataset of 841,377 instances and 20 features, including demographic data, geographic constraints, medical conditions and ResearchMatch visit history. Our outcome variable consisted of responses showing specific participant interest when presented with specific clinical trial opportunity invitations ('yes' or 'no'). Furthermore, we created four subsets from this dataset based on top self-reported medical conditions and gender, which were separately analysed. RESULTS: The deep learning model outperformed the machine learning classifiers, achieving an area under the curve (AUC) of 0.8105. CONCLUSIONS: The results show sufficient evidence that there are meaningful correlations amongst predictor variables and outcome variable in the datasets analysed using the supervised machine learning classifiers. These approaches show promise in identifying individuals who may be more likely to participate when offered an opportunity for a clinical trial.

Opening doors to clinical trial participation among Hispanics: Lessons learned from the Spanish translation of ResearchMatch.

INTRODUCTION: Clinical trial participation among US Hispanics remains low, despite a significant effort by research institutions nationwide. ResearchMatch, a national online platform, has matched 113,372 individuals interested in participating in research with studies conducted by 8778 researchers. To increase accessibility to Spanish speakers, we translated the ResearchMatch platform into Spanish by implementing tenets of health literacy and respecting linguistic and cultural diversity across the US Hispanic population. We describe this multiphase process, preliminary results, and lessons learned. METHODS: Translation of the ResearchMatch site consisted of several activities including: (1) improving the English language site's reading level, removing jargon, and using plain language; (2) obtaining a professional Spanish translation of the site and incorporating iterative revisions by a panel of bilingual community members from diverse Hispanic backgrounds; (3) technical development and launch; and (4) initial promotion. RESULTS: The Spanish language version was launched in August 2018, after 11 months of development. Community input improved the initial translation, and early registration and use by researchers demonstrate the utility of Spanish ResearchMatch in engaging Hispanics. Over 12,500 volunteers in ResearchMatch self-identify as Hispanic (8.5%). From August 2018 to March 2020, 162 volunteers registered through the Spanish language version of ResearchMatch, and over 500 new and existing volunteers have registered a preference to receive messages about studies in Spanish. CONCLUSION: By applying the principles of health literacy and cultural competence, we developed a Spanish language translation of ResearchMatch. Our multiphase approach to translation included key principles of community engagement that should prove informative to other multilingual web-based platforms.

Dietary sodium restriction decreases insulin secretion without affecting insulin sensitivity in humans.

CONTEXT: Interruption of the renin-angiotensin-aldosterone system prevents incident diabetes in high-risk individuals, although the mechanism remains unclear. OBJECTIVE: To test the hypothesis that activation of the endogenous renin-angiotensin-aldosterone system or exogenous aldosterone impairs insulin secretion in humans. DESIGN: We conducted a randomized, blinded crossover study of aldosterone vs vehicle and compared the effects of a low-sodium versus a high-sodium diet. SETTING: Academic clinical research center. PARTICIPANTS: Healthy, nondiabetic, normotensive volunteers. INTERVENTIONS: Infusion of exogenous aldosterone (0.7 µg/kg/h for 12.5 h) or vehicle during low or high sodium intake. Low sodium (20 mmol/d; n = 12) vs high sodium (160 mmol/d; n = 17) intake for 5-7 days. MAIN OUTCOME MEASURES: Change in acute insulin secretory response assessed during hyperglycemic clamps while in sodium balance during a low-sodium vs high-sodium diet during aldosterone vs vehicle. RESULTS: A low-sodium diet increased endogenous aldosterone and plasma renin activity, and acute glucose-stimulated insulin (-16.0 ± 5.6%; P = .007) and C-peptide responses (-21.8 ± 8.4%; P = .014) were decreased, whereas the insulin sensitivity index was unchanged (-1.0 ± 10.7%; P = .98). Aldosterone infusion did not affect the acute insulin response (+1.8 ± 4.8%; P = .72) or insulin sensitivity index (+2.0 ± 8.8%; P = .78). Systolic blood pressure and serum potassium were similar during low and high sodium intake and during aldosterone infusion. CONCLUSIONS: Low dietary sodium intake reduces insulin secretion in humans, independent of insulin sensitivity.

Differential effects of nebivolol and metoprolol on insulin sensitivity and plasminogen activator inhibitor in the metabolic syndrome.

Early-generation ß-blockers lower blood pressure and reduce cardiovascular morality in coronary artery disease and congestive heart failure but worsen glucose homeostasis and fibrinolytic balance. Nebivolol is a third-generation ß-blocker that increases the bioavailability of nitric oxide. We compared the effect of nebivolol (5 mg/d) and the ß(1)-selective antagonist metoprolol (100 mg/d) on glucose homeostasis and markers of fibrinolysis in 46 subjects with metabolic syndrome. Subjects underwent a frequently sampled IV glucose tolerance test after 3-week washout and placebo treatment and after randomized treatment with study drug. After 12-week treatment, nebivolol and metoprolol equivalently decreased systolic blood pressure, diastolic blood pressure, and heart rate. Neither drug affected ß-cell function, disposition index, or acute insulin response to glucose. Metoprolol significantly decreased the insulin sensitivity index. In contrast, nebivolol did not affect insulin sensitivity, and the decrease in sensitivity was significantly greater after metoprolol than after nebivolol (-1.5±2.5×10(-4)×min(-1) per milliunit per liter versus 0.04±2.19×10(-4)×min(-1) per milliunit per liter after nebivolol; P=0.03). Circulating plasminogen activator inhibitor also increased after treatment with metoprolol (from 9.8±6.8 to 12.3±7.8 ng/mL) but not nebivolol (from 10.8±7.8 to 10.5±6.2 ng/mL; P=0.05 versus metoprolol). Metoprolol, but not nebivolol, increased F(2)-isoprostane concentrations. In summary, treatment with metoprolol decreased insulin sensitivity and increased oxidative stress and the antifibrinolytic plasminogen activator inhibitor 1 in patients with metabolic syndrome, whereas nebivolol lacked detrimental metabolic effects. Large clinical trials are needed to compare effects of nebivolol and the ß(1) receptor antagonist metoprolol on clinical outcomes in patients with hypertension and the metabolic syndrome.

Interactive hemodynamic effects of dipeptidyl peptidase-IV inhibition and angiotensin-converting enzyme inhibition in humans.

Dipeptidyl peptidase-IV inhibitors improve glucose homeostasis in type 2 diabetics by inhibiting degradation of the incretin hormones. Dipeptidyl peptidase-IV inhibition also prevents the breakdown of the vasoconstrictor neuropeptide Y and, when angiotensin-converting enzyme (ACE) is inhibited, substance P. This study tested the hypothesis that dipeptidyl peptidase-IV inhibition would enhance the blood pressure response to acute ACE inhibition. Subjects with the metabolic syndrome were treated with 0 mg of enalapril (n=9), 5 mg of enalapril (n=8), or 10 mg enalapril (n=7) after treatment with sitagliptin (100 mg/day for 5 days and matching placebo for 5 days) in a randomized, cross-over fashion. Sitagliptin decreased serum dipeptidyl peptidase-IV activity (13.08±1.45 versus 30.28±1.76 nmol/mL/min during placebo; P≤0.001) and fasting blood glucose. Enalapril decreased ACE activity in a dose-dependent manner (P<0.001). Sitagliptin lowered blood pressure during enalapril (0 mg; P=0.02) and augmented the hypotensive response to 5 mg of enalapril (P=0.05). In contrast, sitagliptin attenuated the hypotensive response to 10 mg of enalapril (P=0.02). During sitagliptin, but not during placebo, 10 mg of enalapril significantly increased heart rate and plasma norepinephrine concentrations. There was no effect of 0 or 5 mg of enalapril on heart rate or norepinephrine after treatment with either sitagliptin or placebo. Sitagliptin enhanced the dose-dependent effect of enalapril on renal blood flow. In summary, sitagliptin lowers blood pressure during placebo or submaximal ACE inhibition; sitagliptin activates the sympathetic nervous system to diminish hypotension when ACE is maximally inhibited. This study provides the first evidence for an interactive hemodynamic effect of dipeptidyl peptidase-IV and ACE inhibition in humans.

Functional BSND variants in essential hypertension.

BACKGROUND: Defects in the handling of renal salt reabsorption may contribute to interindividual differences in blood-pressure regulation and susceptibility to hypertension. Sodium chloride reabsorption in the thick ascending limb (TAL) is dependent in part on the chloride channel, ClC-Kb (encoded by CLCNKB), and its accessory subunit, barttin (encoded by BSND). METHODS: We investigated genetic variations in BSND in a screening population, and genotyped a homogenous cohort of normotensive and hypertensive Ghanaian subjects, in addition to four ethnically defined control populations. Functional consequences of the identified BSND variants were examined using a heterologous expression system. RESULTS: Three novel, nonsynonymous coding-sequence single-nucleotide polymorphisms were identified (V43I, E255Q, and G284D) in the screening population. BSND-V43I was identified in African American, Asian, and Hispanic subjects, with minor allele frequencies of 0.14, 0.18, and 0.01, respectively, but it was absent in the Caucasian population. BSND-E225Q and BSND-G284D were rare variants. Two of these variants (V43I and G284D) exhibited partial loss-of-function phenotypes when heterologously expressed with ClC-Kb chloride channels in cultured cells. In logistic regression analyses, we observed no association between hypertension and BSND-I43 in our study population. However, we did observe significant deviation from Hardy-Weinberg equilibrium in the normotensive population. CONCLUSIONS: We conclude that BSND-V43I, a common variant conferring partial loss of function, exhibits significant deviation from Hardy-Weinberg equilibrium in the Ghanaian normotensive control population. However, it does not independently confer protection against hypertension.

Quantification of the major urinary metabolite of PGE2 by a liquid chromatographic/mass spectrometric assay: determination of cyclooxygenase-specific PGE2 synthesis in healthy humans and those with lung cancer.

Prostaglandin (PG)E2 is a major cyclooxygenase (COX) product that is important in human physiology and pathophysiology. Quantification of systemic PG production in humans is best assessed by measuring excreted urinary metabolites. Accurate and easy-to-perform assays to quantify the major urinary metabolite of PGE2, 11alpha-hydroxy-9,15-dioxo-2,3,4,5-tetranor-prostane-1,20-dioic acid (PGE-M), do not exist. We now report the development of a robust and facile method to measure urinary PGE-M excretion in humans using stable isotope dilution techniques employing liquid chromatography/tandem mass spectrometry (LC/MS/MS). Concentrations of the metabolite in urine from healthy humans are nearly twofold greater in men than in women (10.4+/-1.5 vs. 6.0+/-0.7 ng/mg creatinine). Levels of PGE-M in healthy humans are suppressed significantly not only by the nonselective COX inhibitor ibuprofen but also by the COX-2 selective inhibitor rofecoxib, suggesting that the majority of PGE2 formed in vivo is derived from COX-2. Increased COX-2 expression and increased PGE2 production are associated with malignancy. Levels of PGE-M were found to be greatly increased in humans with unresectable non-small cell cancer of the lung, and this increase is dramatically reduced by administration of the COX-2 inhibitor celecoxib, implying that COX-2 contributes significantly to the overproduction of PGE2. In summary, quantification of PGE-M using LC/MS/MS provides a facile and accurate method to assess PGE2 formation in human physiological and pathophysiological processes.

Comparative genomic hybridization and multiplex-fluorescence in situ hybridization: an appraisal in elderly patients with acute myelogenous leukemia.

Comparative genomic hybridization (CGH) and multiplex-fluorescence in situ hybridization (M-FISH) were used to evaluate the presentation karyotype in 15 and 18 patients respectively, aged >/=60 years, with acute myeloid leukemia (AML). Conventional G-banded analysis was performed in all patients prior to evaluation. Comparative genomic hybridization confirmed the G-banded karyotype fully in 12 patients and partially in two patients. Normal CGH profiles were observed in patients with a normal karyotype and in one patient with a balanced chromosomal translocation as the sole cytogenetic aberration. Multiplex-fluorescence in situ hybridization provided additional information in two patients with a complex karyotype, but failed to detect a telomeric translocation in one patient. Eight patients with normal G-banded karyotypes appeared normal by M-FISH. These results demonstrate that both CGH and M-FISH analysis correlate well with the G-banded karyotype in AML. Furthermore, although additive cytogenetic data was not provided by either technique in cases with normal karyotype, DNA copy number change and cryptic translocations below the resolution of CGH and M-FISH may still be the initiating event for leukemogenesis for these patients.