August 16, 2022: Biostatistics Core Develops Tools and Strategies for Common Research Challenges

Head shot of Dr. Patrick HeagertyHead shot of Dr. Liz TurnerIn an interview at the NIH Pragmatic Trials Collaboratory’s annual Steering Committee meeting and 10th anniversary celebration, we asked Dr. Liz Turner and Dr. Patrick Heagerty to reflect on the role of the Biostatistics and Study Design Core Working Group in helping the NIH Collaboratory Trial teams design their trials and analyze the data, and to discuss their focus for the Core's future contributions to pragmatic clinical trials.

Based on your experience working with the NIH Collaboratory Trials, what are some of the common challenges of the Core?

Given the pragmatic nature of the NIH Collaboratory Trials, most use a design that involves some kind of clustering of outcomes. This could be a cluster randomized design or an individually randomized group treatment trial. As a consequence, nearly all projects face the challenge of how to account for clustering in both the design and analysis of the trial.

For the NIH Collaboratory Trials that use a cluster randomized design, one of the most common challenges is deciding between a stepped-wedge design and a standard parallel-arm design. The Core’s recommendation is clear: only use a stepped-wedge design if you have to! Likewise, only use a cluster randomized design if you have to and, if possible, use an individually randomized design. Nevertheless, a cluster randomized design is often the design of choice to address a pragmatic research question, and a stepped-wedge cluster randomized design may be the only way to perform a randomized evaluation of an intervention (for example, when all centers wish to receive the intervention in order to agree to participate in the trial).

From an analysis perspective, common challenges involve how to handle missing outcome data and how to handle longitudinal (that is, repeated) measures data. For both design and analysis, as you can imagine, the COVID-19 pandemic has posed huge challenges, including how to handle the disruption of an ongoing stepped-wedge trial (as in the GGC4H NIH Collaboratory Trial). In short, clustering of outcomes is the biggest theme (and challenge) across the NIH Collaboratory Trials.

What strategies have NIH Collaboratory Trials used to overcome these barriers?

A common strategy used by the NIH Collaboratory Trials to overcome these barriers has been to leverage what we call the “Core group process.” This dynamic process is driven by the NIH Collaboratory Trials and supported by the Core, together with NIH Collaboratory leadership. The process is centered around the monthly Core meeting to which all NIH Collaboratory Trial teams are invited and that involves all Core members. These meetings provide dedicated time for each study team to provide project updates and elicit feedback from the Core and the other NIH Collaboratory Trial teams. In particular, all the study teams are invited to present at least once during the UG3 planning phase and on multiple occasions during the UH3 implementation phase. Core members are also available for ad hoc, smaller group meetings, as requested. What this process allows is for the NIH Collaboratory Trials to present challenges and for us to jointly identify solutions.

How are the NIH Collaboratory Trials’ experiences with the Core helping the field of pragmatic research?

Through the challenges and ideas that have been brought to the Core, the NIH Collaboratory Trials have pushed the field of pragmatic research. In particular, through the Core group process, they have pushed the Core to solve methodological challenges and provide tools to tackle the design issues that arise in the changing research landscape.

Thumbnail image of the COVID-19 checklist

A key example of the Core’s methodological work was inspired by the STOP CRC NIH Collaboratory Trial and is related to the design and analysis choices faced in the unique context of embedded pragmatic trials. This example addresses a common challenge in embedded pragmatic trials, namely how to handle varying cluster sizes, something that arises in so many of the NIH Collaboratory Trials. The research, recently published in Contemporary Clinical Trials, highlights that a seemingly natural analysis in this context may produce a biased inference about intervention effectiveness, which is clearly problematic.

The second example is the Core’s recently published Statistical Analysis Plan Checklist for Addressing COVID-19 Impacts. Development of this tool was inspired by the many challenges faced by the NIH Collaboratory Trials as a result of the COVID-19 pandemic, such as delayed recruitment (as in the BackInAction NIH Collaboratory Trial) and adjustments to how interventions were delivered (as in the ACP PEACE NIH Collaboratory Trial).

What do you think the Core can contribute over the next decade?

The Core has a lot to contribute over the next decade. A key goal is to ensure we are building and diversifying the next generation of statisticians who are experts in pragmatic trials and who can engage deeply in the design and analysis of pragmatic trials embedded in healthcare systems.

To achieve this, we need to continue to bring trainees into the Core, as we have done over the past 6 years, through funded graduate research assistant positions. By doing this, we should be able to not only build the next generation of pragmatic trial experts but also build scholarship in pragmatic trial methodology by identifying methodological gaps needed to be filled so the NIH Collaboratory Trials study teams—and pragmatic trialists in the broader research community—have the best methods available to them.

The opportunity to participate in a cross-institution working group such as ours is surprisingly rare. As a consequence, we are in a unique position to not only build the next generation of experts but also to strength our own collective expertise and knowledge by learning from each other’s perspectives.