Quantitative assessment of the impact of standard agreement templates on multisite clinical trial start up time.

Contracting delays remain a challenge to the successful initiation of multisite clinical research in the US. The Clinical and Translational Science Awards (CTSA) Contracts Processing Study showed average contract negotiation duration of > 100 days for industry-sponsored or investigator-initiated contracts. Such delays create enormous costs to sponsors and to patients waiting to use new evidence-based treatments. With support from the National Institutes of Health's National Center for Advancing Translational Sciences, the Accelerated Clinical Trial Agreement (ACTA) was developed by 25 major academic institutions and medical centers engaged in clinical research in collaboration with the University-Industry Demonstration Partnership and with input from pharmaceutical companies. The ACTA also informed the development of subsequent agreements, including the Federal Demonstration Partnership Clinical Trial Subaward Agreement (FDP-CTSA); both ACTA and the FDP-CTSA are largely non-negotiable agreements that represent pre-negotiated compromises in contract terms agreed upon by industry and/or medical center stakeholders. When the involved parties agree to use the CTSA-developed and supported standard agreement templates as a starting point for negotiations, there can be significant time savings for trials. Use of the ACTA resulted in an average savings of 48 days and use of the FDP-CTSA saved an average of 57 days of negotiation duration.

Development and Validation of an Emergency Department Electronic Medical Record Gout Flare Alert.

OBJECTIVE: Patients with acute gout are frequently treated in the emergency department (ED) and represent a typically underresourced and understudied population. A key limitation for gout research in the ED is the timely ability to identify acute gout patients. Our goal was to refine a multicriteria, electronic medical record alert for gout flares and to determine its diagnostic characteristics in the ED. METHODS: The gout flare alert used electronic medical record data from ED nursing notes and was triggered by the term 'gout' preceding past medical history in the chief complaint, the term 'gout' and a musculoskeletal problem in the chief complaint, or the term 'gout' in the problem list and a musculoskeletal chief complaint. We validated its diagnostic properties to assess presence/absence of gout through manual medical record review using adjudicated expert consensus as the gold standard. RESULTS: In January 2020, we analyzed 202 patient records from 2 university-based EDs; from these records, 57 patients were identified by our gout flare alert, and 145 were identified by other means as potentially having an acute gout flare. The gout flare alert's positive predictive value was 47% (95% confidence interval [95% CI] 34-60%), negative predictive value was 94% (95% CI 90-98%), sensitivity was 75% (95% CI 61-89%), and specificity was 82% (95% CI 76-88%). The diagnostic properties were similar at both institutions. CONCLUSION: Our multicomponent gout flare alert had reasonable sensitivity and specificity, albeit a modest positive predictive value. An electronic gout flare alert may help enable the conduct of gout research in the ED setting.

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.

Development of a multi-component intervention to promote participation of Black and Latinx individuals in biomedical research.

INTRODUCTION: Barriers to research participation by racial and ethnic minority group members are multi-factorial, stem from historical social injustices and occur at participant, research team, and research process levels. The informed consent procedure is a key component of the research process and represents an opportunity to address these barriers. This manuscript describes the development of the Strengthening Translational Research in Diverse Enrollment (STRIDE) intervention, which aims to improve research participation by individuals from underrepresented groups. METHODS: We used a community-engaged approach to develop an integrated, culturally, and literacy-sensitive, multi-component intervention that addresses barriers to research participation during the informed consent process. This approach involved having Community Investigators participate in intervention development activities and using community engagement studios and other methods to get feedback from community members on intervention components. RESULTS: The STRIDE intervention has three components: a simulation-based training program directed toward clinical study research assistants that emphasizes cultural competency and communication skills for assisting in the informed consent process, an electronic consent (eConsent) framework designed to improve health-related research material comprehension and relevance, and a "storytelling" intervention in which prior research participants from diverse backgrounds share their experiences delivered via video vignettes during the consent process. CONCLUSIONS: The community engaged development approach resulted in a multi-component intervention that addresses known barriers to research participation and can be integrated into the consent process of research studies. Results of an ongoing study will determine its effectiveness at increasing diversity among research participants.

A REDCap-based model for online interventional research: Parent sleep education in autism.

INTRODUCTION: The use of online platforms for pediatric healthcare research is timely, given the current pandemic. These platforms facilitate trial efficiency integration including electronic consent, randomization, collection of patient/family survey data, delivery of an intervention, and basic data analysis. METHODS: We created an online digital platform for a multicenter study that delivered an intervention for sleep disorders to parents of children with autism spectrum disorder (ASD). An advisory parent group provided input. Participants were randomized to receive either a sleep education pamphlet only or the sleep education pamphlet plus three quick-tips sheets and two videos that reinforced the material in the pamphlet (multimedia materials). Three measures - Family Inventory of Sleep Habits (FISH), Children's Sleep Habits Questionnaire modified for ASD (CSHQ-ASD), and Parenting Sense of Competence (PSOC) - were completed before and after 12 weeks of sleep education. RESULTS: Enrollment exceeded recruitment goals. Trial efficiency was improved, especially in data entry and automatic notification of participants related to survey completion. Most families commented favorably on the study. While study measures did not improve with treatment in either group (pamphlet or multimedia materials), parents reporting an improvement of ≥3 points in the FISH score showed a significantly improved change in the total CSHQ (P = 0.038). CONCLUSION: Our study demonstrates the feasibility of using online research delivery platforms to support studies in ASD, and more broadly, pediatric clinical and translational research. Online platforms may increase participant inclusion in enrollment and increase convenience and safety for participants and study personnel.

A REDCap-based model for electronic consent (eConsent): Moving toward a more personalized consent.

INTRODUCTION: The updated common rule, for human subjects research, requires that consents "begin with a 'concise and focused' presentation of the key information that will most likely help someone make a decision about whether to participate in a study" (Menikoff, Kaneshiro, Pritchard. The New England Journal of Medicine. 2017; 376(7): 613-615.). We utilized a community-engaged technology development approach to inform feature options within the REDCap software platform centered around collection and storage of electronic consent (eConsent) to address issues of transparency, clinical trial efficiency, and regulatory compliance for informed consent (Harris, et al. Journal of Biomedical Informatics 2009; 42(2): 377-381.). eConsent may also improve recruitment and retention in clinical research studies by addressing: (1) barriers for accessing rural populations by facilitating remote consent and (2) cultural and literacy barriers by including optional explanatory material (e.g., defining terms by hovering over them with the cursor) or the choice of displaying different videos/images based on participant's race, ethnicity, or educational level (Phillippi, et al. Journal of Obstetric, Gynecologic, & Neonatal Nursing. 2018; 47(4): 529-534.). METHODS: We developed and pilot tested our eConsent framework to provide a personalized consent experience whereby users are guided through a consent document that utilizes avatars, contextual glossary information supplements, and videos, to facilitate communication of information. RESULTS: The eConsent framework includes a portfolio of eight features, reviewed by community stakeholders, and tested at two academic medical centers. CONCLUSIONS: Early adoption and utilization of this eConsent framework have demonstrated acceptability. Next steps will emphasize testing efficacy of features to improve participant engagement with the consent process.

Design, analysis, power, and sample size calculation for three-phase interrupted time series analysis in evaluation of health policy interventions.

OBJECTIVE: To discuss the study design and data analysis for three-phase interrupted time series (ITS) studies to evaluate the impact of health policy, systems, or environmental interventions. Simulation methods are used to conduct power and sample size calculation for these studies. METHODS: We consider the design and analysis of three-phase ITS studies using a study funded by National Institutes of Health as an exemplar. The design and analysis of both one-arm and two-arm three-phase ITS studies are introduced. RESULTS: A simulation-based approach, with ready-to-use computer programs, was developed to determine the power for two types of three-phase ITS studies. Simulations were conducted to estimate the power of segmented autoregressive (AR) error models when autocorrelation ranged from -0.9 to 0.9 with various effect sizes. The power increased as the sample size or the effect size increased. The power to detect the same effect sizes varied largely, depending on testing level change, trend changes, or both. CONCLUSION: This article provides a convenient tool for investigators to generate sample sizes to ensure sufficient statistical power when three-phase ITS study design is implemented.

Simulation-based power and sample size calculation for designing interrupted time series analyses of count outcomes in evaluation of health policy interventions.

OBJECTIVE: The purpose of this study was to present the design, model, and data analysis of an interrupted time series (ITS) model applied to evaluate the impact of health policy, systems, or environmental interventions using count outcomes. Simulation methods were used to conduct power and sample size calculations for these studies. METHODS: We proposed the models and analyses of ITS designs for count outcomes using the Strengthening Translational Research in Diverse Enrollment (STRIDE) study as an example. The models we used were observation-driven models, which bundle a lagged term on the conditional mean of the outcome for a time series of count outcomes. RESULTS: A simulation-based approach with ready-to-use computer programs was developed to calculate the sample size and power of two types of ITS models, Poisson and negative binomial, for count outcomes. Simulations were conducted to estimate the power of segmented autoregressive (AR) error models when autocorrelation ranged from -0.9 to 0.9, with various effect sizes. The power to detect the same magnitude of parameters varied largely, depending on the testing level change, the trend change, or both. The relationships between power and sample size and the values of the parameters were different between the two models. CONCLUSION: This article provides a convenient tool to allow investigators to generate sample sizes that will ensure sufficient statistical power when the ITS study design of count outcomes is implemented.

Capecitabine plus erlotinib in gemcitabine-refractory advanced pancreatic cancer.

PURPOSE: The addition of either capecitabine or erlotinib to gemcitabine in the first-line treatment of advanced pancreatic cancer is associated with modest improvements in overall survival. We evaluated an oral regimen of capecitabine and erlotinib in patients with advanced pancreatic cancer who had experienced treatment failure with standard first-line therapy with gemcitabine. PATIENTS AND METHODS: Thirty patients with gemcitabine-refractory metastatic pancreatic cancer were treated with capecitabine, administered at a dose of 1,000 mg/m2 twice daily for 2 weeks, followed by a 1-week break. All patients also received erlotinib 150 mg daily. Patients were observed for evidence of response, toxicity, and survival. EGFR mutational status was assessed in available tumor blocks. RESULTS: Treatment with capecitabine and erlotinib in gemcitabine-refractory patients was associated with an overall objective radiologic response rate of 10% and a median survival duration of 6.5 months. In addition, 17% of the treated patients experienced decreases in tumor marker (CA 19-9) levels of more than 50% from baseline. Common toxicities included diarrhea, skin rash, fatigue, and hand-foot syndrome. EGFR mutations were detected in two of five available tumors; no association between treatment response and EGFR mutational status was evident. CONCLUSION: The combination of capecitabine and erlotinib is active in patients with gemcitabine-refractory pancreatic cancer. This regimen may represent an acceptable treatment option in patients who experience treatment failure with standard first-line therapy with gemcitabine or for whom gemcitabine may not be an appropriate first-line treatment option.