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In the Interim...

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by Berry

4.9(12 reviews)

68 episodes

Updated Daily

Accepts GuestsHas Sponsors

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FairBased on show quality, social media presence, reviews, charts, and more

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Engagement51

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Podcast Overview

A podcast on statistical science and clinical trials. Explore the intricacies of Bayesian statistics and adaptive clinical trials. Uncover methods that push beyond conventional paradigms, ushering in data-driven insights that enhance trial outcomes while ensuring safety and efficacy. Join us as we dive into complex medical challenges and regulatory landscapes, offering innovative solutions tailored for pharma pioneers. Featuring expertise from industry leaders, each episode is crafted to provide clarity, foster debate, and challenge mainstream perspectives, ensuring you remain at the forefront of clinical trial excellence.

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Publishing Since

2/18/2025

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Beta

FairBased on show quality, social media presence, reviews, charts, and more

Quality98

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Engagement51

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Recent Episodes

July 6, 2026

Bias in Stopping Trials Early

On the latest episode of "In the Interim...", Dr. Scott Berry and Dr. Kert Viele deliver a focused, technical analysis of statistical bias when stopping trials early. This episode clarifies the definition of bias, detailed within the context of interim analyses, emphasizing the empirical consequences of different stopping rules. The discussion addresses common misconceptions around interpretation as well as including the mathematical rationale for averaging across all trial outcomes, and the error of restricting bias estimates to only successful (early-stopped) trials. The hosts present a detailed critique of Bassler et al. (JAMA 2010), highlighting methodological flaws and misinterpretations of comparisons between truncated and non-truncated studies. Simulation is positioned as the primary tool for quantifying bias, with contextual examples illustrating the manageable magnitude of bias. Regulatory expectations are summarized, referencing formal FDA and ICH guidance on adaptive design bias assessment. The DAWN trial is cited as a real-world example where early stopping accelerated patient benefit. Key Highlights<ul><li>Definition and quantification of bias in early-stopped clinical trials</li><li>Mathematical examples demonstrating bias magnitude in fixed and adaptive group sequential designs</li><li>Detailed critique of the methodology and conclusions in Bassler et al. (JAMA 2010)</li><li>Discussion correcting common misunderstandings in bias estimation and selective reporting</li><li>Simulation as a decisive tool for precise bias estimation</li><li>Regulatory context including FDA guidance and ICH E20 draft guidance</li><li>Reference to DAWN trial as evidence of practical benefits of early stopping</li></ul>For more, visit us at <a href="https://www.berryconsultants.com/">https://www.berryconsultants.com/</a>

June 22, 2026

A Statistician Reads JAMA: A Futile Issue

On the latest episode of "In the Interim…", Dr. Scott Berry provides an empirical examination of two recent JAMA trials: TRACK (low-dose rivaroxaban in advanced kidney disease) and VICTORY (IV vitamin C in severe burn injury). The TRACK trial lacked any pre-specified futility criteria, with a DSMB-initiated stop based on conditional power calculations. Scott argues that conditional power, especially in this interim context, is a poor, misleading tool—contrasting it against a Bayesian predictive probability calculation that produced a much lower and more realistic estimate of success. In VICTORY, a pre-specified risk ratio threshold for futility was incorporated, with simulation confirming minimal effect on bias and statistical power. Scott underscores the practical and ethical importance of rigorously pre-specified, simulation-based futility rules and operationalizes the case for Bayesian predictive probability as a decision metric in interim monitoring. He reiterates that responsibility for defining futility belongs to trial designers, not left to ad hoc DSMB judgment, and calls for precise statistical planning in adaptive trial protocols.Key Highlights<ul><li>TRACK: No pre-specified futility rule; DSMB stopped for futility using conditional power post hoc.</li><li>Technical critique of conditional power as misguided at interim, supporting Bayesian predictive probability instead.</li><li>VICTORY: Pre-specified futility threshold, with simulation confirming minimal operational bias and power reduction.</li><li>Emphasizes pre-specified, simulation-based futility planning and predictive probability monitoring as standards for all trials.</li></ul>For more, visit us at <a href="https://www.berryconsultants.com/">https://www.berryconsultants.com/</a>

June 15, 2026

Response-Adaptive Randomization in Clinical Trials

In this episode of "In the Interim…", Dr. Scott Berry and Dr. Kert Viele examine response-adaptive randomization (RAR) in clinical trials, dissecting its statistical rationale, common criticisms, and implementation challenges. Drawing on extensive experience with trials such as BAN2401 (lecanemab), ICECAP, dulaglutide seamless Phase 2/3, I-SPY2, REMAP-CAP, PROSPECT, and the historical ECMO trial, they discuss the scientific advantages and disadvantages and ethical impact. RAR reallocates patient assignments during interim analyses to direct more patients to better-performing arms, but this can reduce power in two-arm trials, introduce complexity from temporal trends, and create operational complexity. The ECMO trial and "play-the-winner" approaches are discussed as cautionary examples emphasizing the need for thorough simulation before deployment. The hosts highlight RAR’s strengths for dose-finding, multi-arm, and some platform designs, but underscore its limitations in confirmatory two-arm settings. Operational demands, data reliability, simulation across scenarios, and resistance to overgeneralization are recurrent themes. The episode concludes by situating RAR within the broader context of adaptive platform trials and learning healthcare systems.Key Highlights<ul><li>Definition and mechanics of RAR, with interim analysis guiding allocation updates</li><li>Multi-arm adaptive and platform trial experiences (BAN2401, ICECAP, dulaglutide, I-SPY2, REMAP-CAP, PROSPECT)</li><li>Critique of RAR in two-arm trials (power loss), temporal trends, unblinding, and overgeneralized literature</li><li>ECMO/play-the-winner: risks of poorly simulated RAR</li><li>Necessity for rigorous pre-trial simulation and robust data flows</li><li>Contextualization of RAR’s role in both traditional and learning healthcare environments</li></ul>For more, visit us at <a href="https://www.berryconsultants.com/">https://www.berryconsultants.com/</a>

68 total episodes available with 1 transcripts

Recent guests on In the Interim...

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Jenny Devenport

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Dr Scott Berry

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Dr Kaspar Rufibach

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Dr Don Berry

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Dr Lindsay Berry

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Dr Nick Berry

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Dr Jeff Saver

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Scott Berry

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Don Berry

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Dr Jim Albert

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Dr Andrew Thomson

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Dr Kert Viele

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What is In the Interim...?: A podcast on statistical science and clinical trials.

Explore the intricacies of Bayesian statistics and adaptive clinical trials. Uncover methods that push beyond conventional paradigms, ushering in data-driven insights that enhance trial outcomes while ensuring safety and efficacy. Join us as we dive into complex medical challenges and regulatory landscapes, offering innovative solutions tailored for pharma pioneers. Featuring expertise from industry leaders, each episode is crafted to provide clarity, foster debate, and challenge mainstream perspectives, ensuring you remain at the forefront of clinical trial excellence.
How often does this podcast release new episodes?: This podcast updates daily.
Where can I listen to this podcast?: This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
Does this podcast accept guests?: Yes, this podcast regularly features guests.

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