clinical trials

June 19, 2020: Living Textbook Grand Rounds Series: Part 4-Demystifying Biostatistical Concepts for Embedded Pragmatic Clinical Trials (Elizabeth Turner, PhD; Patrick Heagerty, PhD; David Murray, PhD)

Posted on by Gina Uhlenbrauck

Speakers

Elizabeth Turner, PhD
Associate Professor
Department of Biostatistics & Bioinformatics
Duke Global Health Institute
Duke University  

Patrick Heagerty, PhD
Professor Department of Biostatistics
University of Washington  

David Murray, PhD
Associate Director for Prevention
Director, Office of Disease Prevention National Institutes of Health

Topic

Demystifying Biostatistical Concepts for Embedded Pragmatic Clinical Trials

Keywords

Embedded PCTs; Biostatistics; Trial design; Cluster-randomized trial (CRT); Stepped-wedge; Intraclass correlation coefficient; NIH Collaboratory Trial; Sample size; Individually randomized group treatment

Key Points

  • Focus on the research question, because that will drive the design, and the design will drive the analysis.
  • Select design features with analysis in mind, and collaborate early with a statistician. Weigh statistical choices against the challenges of implementation.
  • If possible, choose individual randomization. However, sometimes there is a strong rationale for choosing cluster/group randomization. Clustering must be accounted for in both design and analysis for CRTs and individually randomized group treatment (IRGT) trials.
  • The intraclass correlation coefficient (ICC) is a common measure of outcome clustering. Estimating the ICC is needed for study planning and power.
  • Increasing the number of clusters has more impact on power than increasing the number of patients per cluster.

Discussion Themes

With the move to virtual healthcare, the boundaries between clinic-based clusters have become more fluid. What approaches should trials use to describe contamination and estimate the impact of contamination on outcomes?

Read more about ICC in a Living Textbook resource and visit the Training Resources page for practical help on how to plan and conduct ePCTs.

Learn more in the Living Textbook about considerations for trial design and analysis for ePCTs.

Visit the NIH Collaboratory’s Biostatistics and Study Design Core webpage for more resources around design and analysis issues in ePCTs.

The NIH hosts a Research Methods Resources website with materials on this topic.

Tags

#pctGR, @Collaboratory1

June 22, 2020: NIH Offers Methods Webinar on Stepped-Wedge Cluster Randomized Trials

Posted on by Damon Seils

The NIH Office of Disease Prevention will continue its Methods: Mind the Gap webinar series on July 14 with “Overview of Statistical Models for the Design and Analysis of Stepped Wedge Cluster Randomized Trials.” Dr. Fan Li of Yale University, a longtime participant in the NIH Collaboratory’s Biostatistics and Study Design Core Working Group, will lead the webinar.

The Methods: Mind the Gap series explores research design, measurement, intervention, data analysis, and other methods of interest in prevention science. The July 14 session will address the stepped-wedge cluster randomized design, which has received increasing attention in pragmatic clinical trials (PCTs) and implementation science research. Since the design’s introduction, a variety of mixed-effects model extensions have been proposed for the design and analysis of PCTs. Dr. Li will provide a general model representation and discuss model extensions as alternative ways to characterize secular trends, intervention effects, and sources of heterogeneity. He will also review key model ingredients and clarify their implications for the design and analysis of stepped-wedge cluster randomized trials.

Register in advance to join the online presentation. Registration is required.

June 17, 2020: Living Textbook Grand Rounds Series Continues With “Demystifying Biostatistical Concepts”

Posted on by Damon Seils

Join us Friday, June 19, for “Demystifying Biostatistical Concepts for Embedded Pragmatic Clinical Trials,” the fourth session in our special 5-part Grand Rounds series focused on the Living Textbook. NIH Collaboratory investigators Drs. Liz Turner, Patrick Heagerty, and David Murray will discuss statistical design considerations, choosing the right design, and implications for the analysis. Topics covered will include:

  • RCTs, CRTs, and IRGTs: selecting the right trial design
  • Clustering and statistical power
  • Other analytical issues

See below for the full schedule of Living Textbook sessions and a special message from Dr. Kevin Weinfurt.

Living Textbook Grand Rounds Series
Date Title Speakers
January 31, 2020 Pragmatic Clinical Trials: How Do I Start?
  • Greg Simon, MD, MPH, Kaiser Permanente Washington Health Research Institute
  • Lesley H. Curtis, PhD, Duke University
February 28, 2020 Preparing for the Unknown: Conducting Pragmatic Research in Real-World Contexts
  • Jerry Jarvik, MD, MPH, University of Washington
  • Vince Mor, PhD, Brown University
  • Leah Tuzzio, MPH, Kaiser Permanente Washington Health Research Institute
March 27, 2020 Tips for Putting Together a Successful PCT Grand Application
  • Wendy Weber, ND, PhD, MPH, National Center for Complementary and Integrative Health
June 19, 2020 Demystifying Biostatistical Concepts for Embedded Pragmatic Clinical Trials
  • Liz Turner, PhD, Duke University
  • Patrick Heagerty, PhD, University of Washington
  • David M. Murray, PhD, National Institutes of Health
July 17, 2020 Choosing What to Measure and Making It Happen: Your Keys to Pragmatic Trial Success
  • Rachel Richesson, PhD, MPH, Duke University
  • Emily O’Brien, PhD, Duke University

 

June 12, 2020: A Cluster Randomized Pragmatic Trial of an Advance Care Planning Video Intervention in Long-Stay Nursing Home Residents: Main Findings from the PROVEN Trial (Susan Mitchell, MD, MPH)

Posted on by Gina Uhlenbrauck

Speaker

Susan L. Mitchell, MD, MPH
Senior Scientist
Hebrew SeniorLife
Hinda and Arthur Marcus Institute for Aging Research
Professor of Medicine
Harvard Medical School

Topic

A Cluster Randomized Pragmatic Trial of an Advance Care Planning Video Intervention in Long-Stay Nursing Home Residents: Main Findings from the PROVEN Trial

Keywords

Embedded pragmatic trial; PROVEN; Advance care planning; Nursing homes; Video intervention; Medicare; Care preferences; Decision support tool; Minimum data set; Intention to treat

Key Points

  • The PROVEN trial was the first large-scale embedded pragmatic trial conducted in nursing homes.
  • The advance care planning (ACP) video intervention in PROVEN was meant as an adjunct to first-person discussions with the clinical care provider.
  • The levels of care preferences described in the ACP videos were life prolongation, limited care, and comfort care.
  • PROVEN’s primary outcome was the number of transfers to the hospital from the nursing home.

Discussion Themes

Widely adoptable, effective interventions to improve ACP in nursing homes remain elusive.

Of the challenges of conducting PCTs embedded in nursing homes, it is important not to overlook the real-world priorities of stakeholders. A high level of endorsement, from C-suite to frontline care providers, is needed before attempting such a trial.

While a priority for nursing home administrators is the number of residents who transfer to the hospital, an essential question for patients and palliative care experts is whether patients receive care that matches their goals and preferences. This is hard to ascertain in a pragmatic way.

Read more about the PROVEN trial, and learn about a new research initiative built on the success of the NIH Collaboratory: the National Institute on Aging’s IMPACT Collaboratory, which is directly funding pilots of embedded PCTs across diverse healthcare settings to improve the care of patients with dementia and their caregivers.

Tags

#pctGR, @Collaboratory1

June 5, 2020: PCORnet COVID-19 Common Data Model Design and Results (Thomas Carton, PhD, MS; Keith Marsolo, PhD; Jason Perry Block, MD, MPH)

Posted on by Gina Uhlenbrauck

Speakers

Thomas W. Carton, PhD, MS
Chief Data Officer
Louisiana Public Health Institute

Keith Marsolo, PhD
Associate Professor
Department of Population Health Sciences
Duke Clinical Research Institute
Duke University School of Medicine

Jason Perry Block, MD, MPH
Associate Professor of Population Medicine
Department of Population Medicine Harvard
Pilgrim Health Care Institute
Harvard Medical School

Topic

PCORnet COVID-19 Common Data Model Design and Results

Keywords

COVID-19; PCORnet; Common Data Model; CDM; Data query; Health disparities; Distributed data network

Key Points

  • For data to be useful in research, they have to be standardized across systems. The PCORnet Common Data Model standardizes data into a single language, enabling fast insights.
  • All the core data elements needed to support COVID-19 research and surveillance have a home in the PCORnet CDM. The goal for PCORnet is to characterize the cohort of COVID-19 patients and provide detailed information on demographics and pre-existing conditions.

Discussion Themes

Can PCORnet partners stand up a version of the CDM with more up-to-date information to allow for a faster characterization of the PCORnet COVID-19 population?

Is there a query to discover and address COVID-19 health disparities and social determinants of health?

Can PCORnet and NCATS’ National COVID Cohort Collaborative (N3C) work together?

Read more about PCORnet’s code lists and case definitions on GitHub.

Tags

#COVID19, #pctGR, @Collaboratory1

May 19, 2020: New Updates to What is a Pragmatic Clinical Trial Chapter in the Living Textbook

Posted on by Gina Uhlenbrauck

The NIH Collaboratory regularly refreshes content in the Living Textbook in order to offer a robust collection of resources to the wider research community about how to plan and implement a pragmatic clinical trial. We invite you to explore recent additions to the introductory chapter What Is a Pragmatic Clinical Trial?

Highlights include information on the broader embedded PCT (ePCT) ecosystem, an updated table describing the 19 NIH Collaboratory Trials, a new illustration of the PRECIS-2 continuum, webinars on how to start a PCT, and more.

“The Living Textbook reflects a collection of expert consensus regarding special considerations, standard approaches, and best practices in the design, conduct, and reporting of PCTs.” – Dr. Kevin Weinfurt, Editor-in-Chief of the Living Textbook

Sections in What is a Pragmatic Clinical Trial include:

  1. Why Are We Talking About Pragmatic Trials?
  2. The Embedded Pragmatic Clinical Trial Ecosystem
  3. Differentiating Between RCTs, PCTs, and Quality Improvement Activities
  4. Pragmatic Elements: An Introduction to PRECIS-2
  5. Key Considerations for PCTs
  6. Additional Resources

May 15, 2020: Optimized Learning While Doing: The REMAP-CAP Adaptive Platform Trial (Derek Angus, MD, MPH)

Posted on by Gina Uhlenbrauck

Speaker

Derek C. Angus, MD, MPH, FRCP
Distinguished Professor and Mitchell P. Fink Endowed Chair
Department of Critical Care Medicine
University of Pittsburgh and UPMC Health System

Topic

Optimized Learning While Doing: The REMAP-CAP Adaptive Platform Trial

Keywords

Adaptive study design; REMAP-CAP; Community-acquired pneumonia; Embedded research; Learning health system; Pandemic; Response-adaptive randomization; Global adaptive platform; COVID-19

Key Points

  • The Randomised, Embedded, Multifactorial, Adaptive Platform Trial for Community-Acquired Pneumonia (REMAP-CAP) aims to determine and continuously update the optimal set of treatments for community-acquired pneumonia.
  • An important aspect of adaptive trial designs is that already accrued data are used to increase the likelihood that patients within the trial are randomized to treatments that are beneficial.
  • With the onset of the COVID-19 pandemic, the REMAP study made use of an adaptive sub-platform called REMAP-COVID, which is studying multiple questions around COVID treatment simultaneously.

Discussion Themes

The COVID-19 pandemic requires us to do two things at once: learn and do. An integrated approach finds the optimal balance to treat patients as well as possible and learn as fast as possible.

Adaptive randomization is potentially more comfortable for physicians, where patients are preferentially assigned to the best therapy over time.

Read more about REMAP-CAP and Dr. Angus’ research in Optimizing the Trade-off Between Learning and Doing in a Pandemic (JAMA, March 2020).

Tags

#pctGR, @Collaboratory1, @remap_cap

May 14, 2020: Healthcare Workers Invited to Join the HERO Registry

Posted on by Gina Uhlenbrauck

The Healthcare Worker Exposure Response & Outcomes (HERO) Registry invites both clinical and nonclinical healthcare workers to share their life experiences in order to understand the perspectives and problems faced by those on the COVID-19 pandemic frontlines. HERO Registry participants could have the opportunity to participate in future research studies to improve the understanding of COVID-19 and beyond, generating evidence to help healthcare workers stay safe and healthy.

The HERO Registry is open to all healthcare workers, including nurses, therapists, physicians, emergency responders, food service workers, environmental service workers, interpreters, transporters — anyone who works in a setting where people receive health care.

Learn more about the HERO Registry and how to join.

Don’t miss the recent COVID-19 Grand Rounds introducing the HERO Program and get the latest information and resources on COVID-19 for clinical researchers.

May 13, 2020: NIH Collaboratory COVID-19 Grand Rounds Series Continues With the REMAP-CAP Trial

Posted on by Damon Seils

The NIH Collaboratory Coordinating Center is using its popular Grand Rounds platform to share late-breaking research and promote resources in support of clinical researchers affected by the COVID-19 public health emergency.

In this week’s COVID-19 Grand Rounds session, Dr. Derek Angus of the University of Pittsburgh will present “Optimizing Learning While Doing: The REMAP-CAP Adaptive Platform Trial.” The REMAP-CAP trial is an adaptive platform trial of treatments for community-acquired pneumonia. The trial team recently implemented a COVID-19 pandemic appendix to the core protocol. The Grand Rounds session will be held on Friday, May 15, at 1:00 pm eastern. Join the online meeting.

Previous COVID-19 Grand Rounds:

For more news and resources related to the COVID-19 public health emergency, see the COVID-19 Resources page.

May 8, 2020: Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials: Real World Evidence: Contemporary Experience and Future Directions (Patrick Heagerty, PhD, Jacqueline Corrigan-Curay, JD, MD, Joshua C. Denny, MD, MS)

Posted on by Gina Uhlenbrauck

Speakers

Guest Moderator:
Patrick J. Heagerty, PhD
Professor, Department of Biostatistics, University of Washington

Panel:
Jacqueline Corrigan-Curay, JD, MD
Director of CDER’s Office of Medical Policy (OMP)
U.S. Food and Drug Administration (FDA)

Joshua C. Denny, MD, MS, FACMI
Chief Executive Officer, All of Us Research Program, NIH

Topic

Advances at the Intersection of Digital Health, Electronic Health Records, and Pragmatic Clinical Trials: Real World Evidence: Contemporary Experience and Future Directions

Keywords

Electronic health records; Real-world evidence; RWE; Real-world data; RWD; FDA; All of Us; Phenotypes; Regulatory; Fit-for-use data; Digital heath

Key Points

  • To create quality clinical/research records, we must design for multiuse by integrating standards-based tools in the EHR to bring together health care and research. 
  • Quality real-world evidence cannot be built without quality real-world data. With greater efficiencies in data capture, randomization with real-world data provides a pathway for reliable—and persuasive—real-world evidence.

Discussion Themes

Patient-generated health data is part of FDA’s MyStudies Application, designed to facilitate the input of real-world data directly by patients, which can be linked to electronic health data supporting traditional clinical trials, pragmatic trials, observational studies, and registries.

In assessing data quality we can ask, How does a data element travel from clinical care to a research data set?

The NIH’s All of Us program is building a diverse database that can inform thousands of studies on a variety of health conditions.

The All of Us study is tracking COVID-19 in its patients. Sites have identified their COVID-19 participants and relevant labs. Consent is obtained for future sharing of data.

Tags

#pctGR, @Collaboratory1