study design

February 25, 2022: The Next Generation of Patient-Centered Trials – No Site Visits, Home-delivery of Meds and Patient-reported Outcomes – The CHIEF-HF Trial (John Spertus, MD, MPH, FACC, FAHA)

Posted on by terren.green@duke.edu

Speaker

John Spertus, MD, MPH, FACC, FAHA
Daniel Lauer/Missouri Endowed Chair and Professor
University of Missouri – Kansas City
Clinical Director of Outcomes Research
Saint Luke’s Mid America Heart Institute

Keywords

Heart failure; Canagliflozin; INVOKANA; Kansas City Cardiomyopathy Questionnaire (KCCQ); tele-health; tele-trials

Key Points

  • The CHIEF-HF trial (Canagliflozin: Impact on Health Status, Quality of Life and Functional Status in Heart Failure) was a double blind randomized clinical trial of the medication Canagliflozin for heart failure.
  • CHIEF-HF was designed to learn if patients have fewer symptoms after 3 months of treatment with Canagliflozin.
  • CHIEF-HF used a novel trial design that involved no site-visits and electronic monitoring of patient engagement. The follow up rate for this study was over 97%.
  • The Total Symptom Score on the KC Cardiomyopathy Questionnaire was the key outcome measure in the CHIEF-HF Trial.
  • Heart failure patients treated with Canagliflozin experienced a statistically significant improvements in symptoms.
  • Sites in the study chose recruitment methods that worked best for them. More personalized recruitment strategies were most successful.
  • Difficulties of electronic trials include the technology limitations of the participants, and electronic consent concerns from regulatory agencies. Positives of electronic trials are high enrollment and completion rates.

Discussion Themes

How do technology heavy studies enroll diverse and underserved populations who may not have access to smartphones and wearable technology?

Virtual studies such as this that enrolled at 6 to 8 times the rate on a traditional trial can save quite a bit of money on overhead expenses.

 

Read more about the CHIEF-HF trial.

 

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#pctGR, @Collaboratory1

February 18, 2022: Building a Resource: The Process of Developing a Trans-stakeholder Framework to Enable Pediatric Drug Development (Perdita Taylor-Zapata, MD)

Posted on by terren.green@duke.edu

Speaker

Perdita Taylor-Zapata, MD
Best Pharmaceuticals for Children Act (BPCA) Program Lead and NICHD Program Officer
Obstetric and Pediatric Pharmacology and Therapeutics Branch
National Institute of Child Health and Human Development

Keywords

NIH Best Pharmaceuticals for Children Act; Pediatric Trial Network; Trial design; Pediatric drug development

Key Points

  • The current model for pediatric drug development can be slow and neglect neonates and rare pediatric conditions.
  • The NIH Best Pharmaceuticals for Children Act (BPCA) allows the NIH to conduct clinical trials with off-patent drugs in children.
  • Goals of the BPCA program include developing novel trial designs and including diverse and understudied populations.
  • A new framework to enable pediatric drug development could identify resources to assist in drug development, identify areas in need of further research, provide a pathway for integrating approaches, and connect pediatric researchers.
  • The BPCA went through a rigorous systematic approach to develop a comprehensive resource listing for best practices for pediatric drug trials.

Discussion Themes

Most data collected through the opportunistic model presented is PK data to determine dosing so that a more traditional drug trial can be conducted in the future.

With the right infrastructure in place, such as the Pediatric Trials Network, can substantially improve time to conduct trials.

 

Read more about the BPCA and their commitment to diversity in pediatric drug trials.

 

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#pctGR, @Collaboratory1

February 11, 2022: Great Power and Great Responsibility: Machine Learning in Clinical Research (E. Hope Weissler, MD, MHS; Erich Huang, MD, PhD)

Posted on by terren.green@duke.edu

Speakers

E. Hope Weissler, MD, MHS
Resident, Vascular and Endovascular Surgery
Duke University School of Medicine

Erich Huang, MD, PhD
Chief Science and Innovation Officer, Onduo

Topic

Great Power and Great Responsibility: Machine Learning in Clinical Research

Keywords

Machine Learning; Artificial Intelligence; Data Liquidity; Data Storage; HL7FHIR

Key Points

  • Machine learning may address issues that have reduced the efficiency and effectiveness of clinical research and help clinical research projects reach their full potential.
  • Machine learning may improve the pragmatism of research, decreasing costs and time it takes to conduct a research study.
  • Machine learning can be used to canvas the literature, hypothesize drug-target interactions, propose new therapeutics, and analyze highly dimensional research output.
  • Effects of machine learning are up to us and could potentially reduce the pragmatism of research if applied indiscriminately. Machine learning could produce overly selected study participant groups, too closely managing adherence, and using ultra-high-touch follow-up methods.
  • Data Liquidity refers to the ease with which data can be transferred or exchanged. This depends largely on the manner in which the data is stored.
  • Some forms of data are liquid than others due to privacy, security, and ethical concerns.

Discussion Themes

A lot of emphasis is currently being placed on the mobile/wearable device area, but an equally important area to develop in machine learning is patient identification and recruitment.

Is data ever really de-identified? Should data be owned by the patient? Why is health data treated differently than consumer data? Privacy regulation is difficult and needs to be addressed further by Congress in the future.

 

Read more about Dr. Weissler and Dr. Huang’s machine learning in clinical research.

 

Tags

#pctGR, @Collaboratory1

February 4, 2022: SPIRRIT-HFpEF: Opportunities and Challenges in a Large Registry-Based Randomized Clinical Trial(Adam DeVore, MD, MHS; Lars Lund, MD, PhD)

Posted on by terren.green@duke.edu

Speakers

Adam DeVore, MD, MHS
Associate Professor of Medicine
Duke University Medical Center
Duke Clinical Research Institute

Lars Lund, MD, PhD
Professor of Cardiology
Karolinska Institutet
Karolinska University Hospital

Topic

SPIRRIT-HFpEF: Opportunities and Challenges in a Large Registry-based Randomized Clinical Trial

Keywords

Heart Failure; SPIRRIT-HFpEF; Randomized clinical trial; Spironolactone; Eplerenone; Swedish Heart Failure Registry (SwedeHF)

Key Points

  • The SPIRRIT-HFpEF trial, conducted Sweden and the US, was a randomized pragmatic clinical trial of spironolactone or eplerenone in heart failure.
  • Death from heart disease is decreasing while death from Heart Failure is increasing.
  • The SPIRRIT-HFpEF trial focused on improving the trajectory for the growing heart failure population.
  • Patients treated with Spironolactone had a modest but not statistically significant improvement over placebo, but total hospitalizations were less.
  • Patients with a lower ejection fraction were more likely to benefit than patients with a higher ejection fraction.
  • The Swedish Heart Failure Registry (SwedeHF) has been collecting data from HF patients since 2000.’

Discussion Themes

The hardest aspect of a clinical trial is recruitment and enrollment. Patients are spread out over the health care system. The challenge is getting staff and personnel to do the work of screening and prescreening.

In the SPIRRIT-HFpEF, the drawbacks of not blinding were small and the costs of blinding would have been huge.

 

Learn more about the SPIRRIT-HFpEF trial and the Swedish Heart Failure Registry.  Read about the SPIRRIT-HFpEF trial results.

 

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#pctGR, @Collaboratory1

January 27, 2022: Grand Rounds Podcast Now Available, Featuring Dr. Chris Lindsell on Selecting Outcomes for Outpatient Trials

Posted on by terren.green@duke.edu

Headshot of Dr. Christopher John LindsellIn the latest episode of the NIH Collaboratory Grand Rounds podcast, Dr. Christopher Lindsell and Dr. Adrian Hernandez continue the discussion about research outcomes and the importance of understanding stakeholder perspectives in choosing the correct outcomes for outpatient trials.

The full January 14 Grand Rounds webinar with Dr. Lindsell is also available.

Podcast January 19, 2022: Searching for a Unicorn: Understanding Stakeholder Perspectives When Selecting Outcomes for Outpatient Trials (Christopher Lindsell, PhD)

Posted on by terren.green@duke.edu

This podcast continues the discussion with Dr. Christopher Lindsell as he discusses research outcomes and the importance of choosing the correct outcome.

Click on the recording below to listen to the podcast.

Want to hear more? View the full Grand Rounds presentation.

For alerts about new episodes, subscribe free on Apple Podcasts or SoundCloud.

Read the transcript.

January 21, 2022: Primary Palliative Care for Emergency Medicine (Corita R. Grudzen, MD, MSHS, FACEP)

Posted on by terren.green@duke.edu

Speaker

Corita R. Grudzen, MD, MSHS, FACEP
Professor, Emergency Medicine and Population Health
Associate Dean, Clinical Sciences
Deputy Director, Clinical and Translational Science Institute
Vice Chair for Research, Emergency Medicine
Ronald O. Perelman Department of Emergency Medicine
NYU Grossman School of Medicine

Keywords

Palliative Care; Stepped-Wedge study design; Emergency Department (ED); Gagne Index; PRIM-ER

 

Key Points

  • The Emergency Department is increasingly seeing older adults with serious illness rather than patients with acute trauma.
  • Primary Palliative Care for Emergency Medicine (PRIM-ER) is a stepped-wedge study partnership of 18 health systems in 33 EDs designed to change the culture and norms of emergency care to promote palliative care at home or hospice rather than admittance to the hospital.
  • The study used the Gagne Index greater than 6 to identify patients at high risk of short-term mortality. Patients with dementia did not need to meet the Gagne Index criteria to be included in the study.
  • A baseline survey, training of 2,470 emergency providers, and study intervention has been completed at all 33 sites.
  • Only .2% of ED patients in the study were admitted to hospice after their ED visit.  At 12 months post ED visit, 30% of dementia patients had died whereas 15.6% of the non-dementia chronic disease patients had died. Data analysis is ongoing.

Discussion Themes

Stepped-wedge studies present timing issues and COVID-19 increased these problems. A cluster randomized design may have been easier to implement.

 

The PRIM-ER study was considered quality improvement by the IRB, so no human subjects approval from the IRB was required.

 

The PRIM-ER next step will be developing tools for patients with dementia regarding palliative care in the ED.

 

Learn more about the PRIM-ER study.

 

Tags

#pctGR, @Collaboratory1

January 7, 2022: D-PRESCRIBE-AD: A Pragmatic Trial to Educate and Sensitize Caregivers and Healthcare Providers to Reduce Inappropriate Prescription Burden in Persons Living with Dementia (Jerry H. Gurwitz, MD; Richard Platt, MD, MSc)

Posted on by terren.green@duke.edu

Speaker

Jerry H. Gurwitz, MD
Chief, Division of Geriatric Medicine
University of Massachusetts Medical School and UMass Memorial Medical Center
Executive Director, Meyers Health Care Institute
A joint endeavor of University of Massachusetts Medical School, Fallon Health, and Reliant Medical Group

Richard Platt, M.D., M.Sc.
President, Harvard Pilgrim Health Care Institute

Topic

D-PRESCRIBE-AD: A Pragmatic Trial to Educate and Sensitize Caregivers and Healthcare Providers to Reduce Inappropriate Prescription Burden in Persons Living with Dementia

Keywords

Distributed Research Network; Dementia; Alzheimer’s Disease; Deprescribing

Key Points

  • The Distributed Research Network, with 45 million members currently accruing new data, facilitates the conduct of multi-center research requiring access to full text medical records and the collection of patient-generated data.
  • Inappropriate prescribing can increase the likelihood of adverse drug events and may have a heightened impact for Alzheimer’s patients.
  • D-PRESCRIBE-AD study is a randomized educational intervention to improve medication safety among Alzheimer patients by discontinuing potentially inappropriate prescriptions.
  • The D-PRESCRIBE-AD study found incidents of prescribing cascades to be less common than expected in the AD population, but prescription of high-risk medications were relatively high.
  • The challenges of the D-PRESCRIBE-AD study are deciding who should receive the provider letter and who is the appropriate caregiver of the patient.

Discussion Themes

One challenge of a study of this nature is getting buy-in from primary care providers.

Randomization was attempted at the level of Metropolitan Statistical Areas, but challenges with this idea proved too great. Randomization was instead done at an individual level.

Multiple arms of the study were necessary to answer questions about primary care doctor buy-in for this type of study.

 

Learn more about partnering with the DRN.  Read more about. Read more about the D-PRESCRIBE-AD study.

 

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#pctGR, @Collaboratory1

December 16, 2021: NIH Collaboratory Publishes COVID-19 Checklist for Statistical Analysis Plans in Pragmatic Trials

Posted on by Damon Seils

Thumbnail image of the COVID-19 checklistA new tool from the NIH Collaboratory assists investigators in identifying impacts of the COVID-19 public health emergency on ongoing pragmatic clinical trials. The Statistical Analysis Plan Checklist for Addressing COVID-19 Impacts summarizes impacts on trial conduct that study teams should document, measure, analyze, and report.

The new checklist was developed by the NIH Collaboratory’s Biostatistics and Study Design Core Working Group. Since the beginning of the COVID-19 pandemic, many of the NIH Collaboratory Trials have had to postpone recruitment, alter methods of participant engagement, and modify tools for research assessment and intervention delivery.

The leaders of the Biostatistics Core, Dr. Patrick Heagerty and Dr. Liz Turner, spoke in a recent interview about the impacts of the pandemic on the NIH Collaboratory Trials. Early next year, the Coordinating Center will report the results of a survey of the study teams about their experiences with these impacts.

Download the Statistical Analysis Plan Checklist for Addressing COVID-19 Impacts.

December 10, 2021: Decentralized Trials: Naughty or Nice? (Adrian F. Hernandez, MD, MHS)

Posted on by terren.green@duke.edu

Speaker

Adrian F. Hernandez, MD, MHS
Executive Director, Duke Clinical Research Institute
Vice Dean, Duke University School of Medicine

Topic

Decentralized Trials: Naughty or Nice?

Keywords

Decentralized trials; Study design; Implementation; Patient engagement; Patient-reported data

Key Points

  • Decentralized trials have been occurring since the start of the internet and mobile devices to reach people where they are and collect data in places we were not able to in the past.
  • One key problem decentralized trials can help solve is the gap between those who wish to participate in research and those who actually do participate. Clinical trial deserts and lack of broadband widen the gap between those who wish to participate and those who are able.
  • Decentralized trials attempt to capture data remotely instead of at a site and virtually(patient-reported) rather than recorded by study personnel.
  • COVID-19 flipped the model for clinical trial visits from that of site-based visits and care to home based, virtual visits and care.
  • Enrollment can be a challenge for decentralized trials and requires engagement campaigns at various timepoints in the study to achieve desired enrollment numbers.
  • Decentralized trials can help ensure inclusion of diverse communities in your study population.
  • The HeartLine study, CHIEF-HF study, HERO-Together study, and ACTIV-6 study are taking advantage of various technologies to decentralize study design.

Discussion Themes

Decentralized methods may improve recruitment, but may not improve retention. We may need a hybrid model to keep a patient engaged.

Decentralized methods may require decisions about what data we should collect and what we could collect, but don’t need.

 

Read more about decentralized study design in Use of Mobile Devices to Measure Outcomes in Clinical Research, 2010-2016: A Systematic Literature Review and Digitizing Clinical Trials.

 

Tags

#pctGR, @Collaboratory1