biostatistics

May 28, 2020: New Updates to Design and Analysis Plan Chapters in the Living Textbook

Posted on by Damon Seils

The annual update of the Living Textbook has brought new content and organization to the Experimental Designs and Analysis Plan chapters. We invite you to explore these chapters and the external resources linked from the resources sidebar in each section.

The NIH Collaboratory Coordinating Center regularly refreshes content in the Living Textbook to improve the robust collection of resources it offers to the wider research community about how to plan and implement pragmatic clinical trials.

Sections of the Experimental Designs and Randomization Schemes chapter include:

  • Statistical Design Considerations
  • Cluster Randomized Trials
  • Randomization Methods
  • Choosing Between Cluster and Individual Randomization
  • Alternative Cluster Randomized Designs
  • Concealment and Blinding
  • Designing to Avoid Identification Bias
  • Additional Resources

Sections of the Analysis Plan chapter include:

  • Intraclass Correlation
  • Unequal Cluster Sizes
  • Accounting for Residual Confounding in the Analysis
  • Missing Data and Intention-to-Treat Analyses
  • EHR Data Extraction
  • Unanticipated Changes
  • Case Study: STOP CRC Trial

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 6, 2020: EHR Workshop Grand Rounds Series Continues With Future Directions in Real-World Evidence

Posted on by Damon Seils

The NIH Collaboratory is using its ePCT Grand Rounds platform for a special webinar series on electronic health records (EHRs). The series, Advances at the Intersection of Digital Health, Electronic Health Records and Pragmatic Clinical Trials, is highlighting advances in digital health, new approaches and evolving standards for EHRs, and implications for researchers conducting pragmatic trials.

In this week’s EHR workshop session, Dr. Jacqueline Corrigan-Curay of the US Food and Drug Administration and Dr. Joshua Denny of the National Institutes of Health will discuss “Real World Evidence: Contemporary Experience and Future Directions.” NIH Collaboratory investigator Dr. Patrick Heagerty of the University of Washington School of Public Health will facilitate the discussion. The Grand Rounds session will be held on Friday, May 8, at 1:00 pm eastern. Join the online meeting.

Other upcoming sessions in the EHR workshop series include:

  • May 29, 2020: Experiences From the Collaboratory PCTs (Jeffrey [Jerry] G. Jarvik, MD, MPH; Lynn DeBar, PhD; Doug Zatzick, MD; Vince Mor, PhD; Moderator: Wendy Weber, ND, PhD, MPH)
  • June 26, 2020: Keys to Success in the Evolving EHRs Environment (Teresa Zayas-Cabán, PhD; George [Holt] Oliver, MD, PhD; Christopher A. Longhurst, MD, MS; Rachel Richesson, PhD, MPH; Moderator: Keith Marsolo, PhD)
  • Recording June 30, Available July 7, 2020: Podcast: Summary Expert Panel Discussion (Patrick J. Heagerty, PhD; Keith Marsolo, PhD; Wendy Weber, ND, PhD, MPH; Moderator: Lesley H. Curtis, PhD)

April 23, 2020: New Workshop Summary on the Design and Analysis of Pragmatic Clinical Trials

Posted on by Karen Staman

In 2019, NIH Health Care Systems Research Collaboratory held a comprehensive workshop to explore and discuss statistical issues encountered with embedded pragmatic clinical trials (ePCTs). The new Workshop Summary describes panel discussions with the principal investigators and statisticians of NIH Collaboratory Trials and the challenges and solutions encountered during the design and analysis of their trials.

The 4 panel discussions covered the following topics:

  • Measurement and Data: Outcomes, Exposures, and Subgroups Based on EHR Data
  • To Cluster or Not to Cluster?
  • Choosing a Parallel Group or Stepped-Wedge Design
  • Unique Complications

This Workshop Summary also provides lessons learned and recommends tools to help others design and analyze future ePCTs. For more on the design and analysis of pragmatic clinical trials, see the tools provided by the Biostatistics and Study Design Core and Living Textbook chapters on Experimental Designs and Randomization Schemes and Analysis Plans.

April 10, 2020: Hydroxychloroquine for the Early Treatment of COVID-19 in Hospitalized Adults: A Multicenter Randomized Clinical Trial (Sean Collins, MD, MSc)

Posted on by Gina Uhlenbrauck

Speaker

Sean Collins, MD, MSc
Professor and Executive Vice Chair
Department of Emergency Medicine
Director, Center for Emergency Care Research and Innovation
Vanderbilt University Medical Center

Topic

Hydroxychloroquine for the Early Treatment of COVID-19 in Hospitalized Adults: A Multicenter Randomized Clinical Trial

Keywords

Coronavirus; Virus pandemic; COVID-19; Randomized controlled trial; Acute respiratory distress syndrome (ARDS); Hydroxychloroquine; FDA; Emergency Use Authorization; ORCHID study

Key Points

  • Hydroxychloroquine is a biologically plausible agent for early treatment of acute respiratory distress syndrome in patients with COVID-19, but its effects remain to be evaluated in a high-quality, multicenter, blinded, placebo-controlled trial.
  • In an Emergency Use Authorization, the FDA has encouraged the conduct and participation in randomized controlled clinical trials that may produce evidence concerning the effectiveness of hydroxychloroquine in treating patients with COVID-19.
  • Trial results of the effects of this agent will be informative, whether showing benefit or harm.

Discussion Themes

The study team for this trial determined that one-to-one randomization would yield the best data quickly.

Efficacy and safety of hydroxychloroquine must be closely monitored in a health setting.

This is not the only study of chloroquine going on around the world; is there any collaboration with other studies?

Because of the urgency of the pandemic, people are collaborating on a level never seen before. We have a common goal and must maintain momentum through accelerating clinical trials with large teams of parallel studies.

Read more about this COVID-19 study at NCT04332991.

Tags
#pctGR, @Collaboratory1

April 9, 2020: Biostatistics Core Brings Experience to PRISM Challenges: An Interview With Dr. Patrick Heagerty and Dr. Liz Turner

Posted on by Damon Seils

The NIH Collaboratory’s Biostatistics and Study Design Core Working Group supports the Demonstration Projects by offering guidance on their statistical plans and study designs during the planning phase and documenting new statistical and methodological issues that arise during planning and implementation.

At the NIH Collaboratory PRISM kickoff meeting in November, we spoke with the leaders of the Biostatistics and Study Design Core, Dr. Patrick Heagerty and Dr. Liz Turner, to learn more about how the Core is supporting the new PRISM Demonstration Projects.

“Conducting these studies in living health systems is fraught with challenges and opportunities—things changing in the healthcare system that will affect a planned design that’s no longer possible to conduct, and building partnerships with the systems so that it’s possible to flexibly react in terms of the study design along the way,” said Dr. Turner. “We’ll be there to help support [the PRISM projects] and identify some of those challenges,” she said.

The new Demonstration Projects are part of the PRISM program (Pragmatic and Implementation Studies for the Management of Pain to Reduce Opioid Prescribing), a component of the NIH’s Helping to End Addiction Long-term (HEAL) Initiative. The NIH Collaboratory serves as the PRISM Resource Coordinating Center.

“The Core group meetings bring all these amazing minds together in one spot to listen: What are we hearing that specific projects are thinking about or wrestling with?” said Dr. Heagerty. “What are ideas that we can bring to solve it? And what are new questions that we need to dig a little deeper and learn more about?” he said.

Learn more about the PRISM Demonstration Projects:

  • AcuOA: Pragmatic Trial of Acupuncture for Chronic Low Back Pain in Older Adults
  • FM TIPS: Fibromyalgia TENS in Physical Therapy Study
  • NOHARM: Non-pharmacological Options in Postoperative Hospital-Based and Rehabilitation Pain Management
  • OPTIMUM: Group-based mindfulness for patients with chronic low back pain in the primary care setting

The NIH Collaboratory PRISM Resource Coordinating Center is supported by the National Center for Complementary and Integrative Health. Support is also provided by the NIH Common Fund through a cooperative agreement from the Office of Strategic Coordination within the Office of the NIH Director.

March 17, 2020: Cheat Sheet on the Intraclass Correlation Coefficient

Posted on by Karen Staman

The NIH Collaboratory Biostatistics and Study Design Core has created an Intraclass Correlation Coefficient (ICC) Cheat Sheet to provide an introductory description of the ICC, which is important for the design and analysis of cluster-randomized trials.

“The intraclass correlation coefficient (ICC) is a descriptive statistic that describes the extent to which outcomes 1) within each cluster are likely to be similar or 2) between different clusters are likely to be different from each other, relative to outcomes from other clusters. The ICC is an important tool for cluster-randomized pragmatic trials because this value helps determine the sample size needed to detect a treatment effect.” —from the ICC Cheat Sheet

The tool is a 2-page handout that can be used in trainings or classes regarding pragmatic clinical trials involving cluster randomization.

For more on the ICC, see the Intraclass Correlation section in the Living Textbook or this in-depth working document on the ICC from the Biostatistics and Study Design Core. If you have questions, feedback or suggestions regarding this tool, please contact us at nih-collaboratory@dm.duke.edu.

January 8, 2020: Registration Opens for 13th Annual Conference on Statistical Issues in Clinical Trials

Posted on by Damon Seils

Registration opened on January 1 for the 13th Annual University of Pennsylvania Conference on Statistical Issues in Clinical Trials. The theme of this year’s conference is “Cluster Randomized Clinical Trials: Challenges and Opportunities.”

The conference will be held on April 29 at the Smilow Center for Translational Research on the campus of the University of Pennsylvania Perelman School of Medicine in Philadelphia. Cosponsors include the American Statistical Association, the Society for Clinical Trials, and the National Institute of Statistical Sciences.

During the methods portion of the program, NIH Collaboratory investigator David Murray will present “Overview: Innovations in the Design and Analysis of Group- or Cluster-Randomized Trials.” The program also includes presentations on the uses of network- and individual-level information in design and analysis, the complexity introduced by noncompliance, current issues in stepped-wedge designs, and various applications of statistical techniques in cluster randomized studies.

Registration is required for this daylong event.

November 8, 2019: Lumbar Imaging with Reporting of Epidemiology: Initial Results and Some Lessons Learned (Jeffrey Jarvik, MD, MPH, Patrick Heagerty, PhD)

Posted on by Gina Uhlenbrauck

Speakers

Jeffrey (Jerry) G. Jarvik MD MPH
Professor, Radiology, Neurological Surgery and Health Services
Adjunct Professor, Pharmacy and Orthopedics & Sports Medicine
University of Washington

Patrick Heagerty, PhD
Professor and Chair
Department of Biostatistics
University of Washington

Topic

Lumbar Imaging with Reporting of Epidemiology: Initial Results and Some Lessons Learned

Keywords

Embedded pragmatic clinical trials; Radiology imaging; LIRE; Stepped-wedge; Cluster randomization; Epidemiology; Back pain

Key Points

  • The LIRE NIH Collaboratory Trial evaluated whether prevalence benchmark data inserted into lumbar spine imaging reports would reduce overall spine-related healthcare utilization for patients referred from primary care.
  • The inserted intervention text urges caution when interpreting the presence of certain findings that are common in normal, pain-free volunteers.
  • While the study team found no decrease in spine-related healthcare utilization for the overall cohort, there was a small but potentially important effect on reducing opioid prescriptions.

Discussion Themes

A characteristic of stepped-wedge study design is that it yields two comparisons: between-group comparisons (clinic A vs clinic B) and within-group comparisons. But temporal trends can have an impact and must be adjusted for in the analysis.

For what type of intervention would a stepped-wedge design be suitable?

The hope is for a wider dissemination about interventions where radiologic testing is done and incidental findings are common.

Read more about the LIRE NIH Collaboratory Trial.

Tags
#pctGR, #PragmaticTrials, @Collaboratory1

October 30, 2019: Baseline Covariate Imbalance Influences Treatment Effect Bias in Cluster Randomized Trials

Posted on by Damon Seils

In a study supported by the NIH Collaboratory, researchers found that imbalance in individual-level baseline covariates influences bias in the observed treatment effect in cluster randomized trials. Using race as an example, the study highlights the importance of reducing covariate imbalance in the design stage of cluster randomized trials and of using statistical analysis techniques to minimize the resulting bias.

The innovative study, published in Contemporary Clinical Trials, used computer simulation models validated by real-data simulations from a large clinical trial to examine the influence of baseline covariate imbalance on treatment effect bias. They found that bias was proportional to the degree of baseline covariate imbalance and the covariate effect size. In the simulations, trials with larger numbers of clusters had less covariate imbalance. Statistical models that adjusted for important baseline confounders were more effective than unadjusted models in minimizing bias.

The authors recommend several design approaches and statistical analysis techniques for both reducing covariate imbalance and minimizing bias. Using the results of available prior data can help researchers identify important baseline confounders when designing cluster randomized trials.

This work was supported within the NIH Collaboratory by the NIH Common Fund through a cooperative agreement from the Office of Strategic Coordination within the Office of the NIH Director, and by a research supplement from the NIH Common Fund to promote diversity in health-related research.