In this episode of "In the Interim...", Dr. Scott Berry investigates the practical meaning of fairness by connecting a controversial World Cup soccer ruling to foundational questions in clinical trial statistics. Scott scrutinizes FIFA’s unusual reversal of a red card suspension for US striker Folarin Balogun, referencing reports of US presidential influence, and draws explicit parallels between the enforcement of rules in international sport and the necessity for rigorously defined procedures in science. He references how systems thrive, or fail, on clear, consistently applied standards. Using Sherlock Holmes’ “Silver Blaze” and Abraham Wald’s WWII aircraft analysis, Scott revisits core statistical ideas about inference and missing data, survivorship bias, and the difference between prespecified versus post-hoc analyses. This episode affirms that adaptive and Bayesian approaches, when built on sound pre-specification and methodological discipline, represent scientific progress, offering a measured perspective on how standards and expectations of fairness continue to evolve.

Key Highlights:

• FIFA’s red card reversal, reports of external influence, and ramifications for procedural legitimacy
• Analogies from soccer, golf, baseball, and wrestling on the societal role of rules and enforcement
• Classic statistics lessons on missing data, inference, and survivorship bias
• Discussion of post-hoc versus prespecified analysis and its implications in trial integrity
• Defense of adaptive and Bayesian methodology as scientifically valid through pre-specification and covariate adjustment
• Reflection on the ongoing evolution of fairness and rigor in sport and science

For more, visit us at https://www.berryconsultants.com/

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

• Definition and quantification of bias in early-stopped clinical trials
• Mathematical examples demonstrating bias magnitude in fixed and adaptive group sequential designs
• Detailed critique of the methodology and conclusions in Bassler et al. (JAMA 2010)
• Discussion correcting common misunderstandings in bias estimation and selective reporting
• Simulation as a decisive tool for precise bias estimation
• Regulatory context including FDA guidance and ICH E20 draft guidance
• Reference to DAWN trial as evidence of practical benefits of early stopping

For more, visit us at https://www.berryconsultants.com/

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

• TRACK: No pre-specified futility rule; DSMB stopped for futility using conditional power post hoc.
• Technical critique of conditional power as misguided at interim, supporting Bayesian predictive probability instead.
• VICTORY: Pre-specified futility threshold, with simulation confirming minimal operational bias and power reduction.
• Emphasizes pre-specified, simulation-based futility planning and predictive probability monitoring as standards for all trials.

For more, visit us at https://www.berryconsultants.com/