Navigating Strategies for Comparative Effectiveness From Trials to Real-World Evidence

Moderator

Priti Jhingran, PhD, Genesis Research Group, Hoboken, NJ, United States

Speakers

Craig Parzynski, MS, Genesis Research Group, Hoboken, NJ, United States; Alexandra Z Sosinsky, MSc, Genesis Research Group, Hoboken, NJ, United States

How do you choose the right approach and timing to generate comparative effectiveness evidence? How is your strategy shaped by limited head-to-head evidence, differences in study populations, or situations where fit-for-purpose real-world data may be available? What practical and strategic considerations should be taken into context in building this strategy? This theater session examines how to assess an evidence base and translate its strengths and gaps into a comparative effectiveness approach that aligns with the decision context.
Framed by the pragmatic needs of regulatory/HTA bodies for comparative data, as well as commercial implications, the speakers will discuss how existing trial and real-world evidence can be used to generate comparative effectiveness through indirect treatment comparisons (ITC), such as network meta-analyses (NMA) and matching-adjusted indirect comparisons (MAIC), and external control arm (ECA) studies. The session will focus on when each is most defensible, what assumptions drive validity, and how tradeoffs in bias and feasibility shape evidence strategy. The discussion will also address considerations related to the scrutiny these approaches may face from regulators/HTA bodies.
Through examples, speakers will describe how different evidence base scenarios lead to different methodological approaches and how those choices may be justified as part of a broader evidence package for stakeholders. Attendees will gain insight into sizing up an evidence base and strategy for selecting comparative effectiveness methods that are scientifically sound and decision relevant.
Sponsored by Corporate Partner, Genesis Research Group

Topic

Health Technology Assessment, Methodological & Statistical Research, Study Approaches

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