In the Interim...

Berry
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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.

  1. -11 h

    Mammograms: Death Threats, Hillary Clinton and Lead-Time Bias

    In this episode of "In the Interim…", Dr. Don Berry provides a detailed account of co-chairing the 1997 NIH consensus development conference on mammography for women in their 40s. His conversation with Dr. Scott Berry covers the statistical and clinical complexities of breast cancer screening, addressing lead time and length bias, trial design limitations. Don discusses the panel’s finding, based on randomized trials and meta-analysis, that the average benefit of screening women in their 40s is modest (an estimated 1.4-day average life extension and 18% hazard reduction). The panel recommended individualized decision-making rather than universal screening. The episode follows the reaction: heated debate with radiologists, scrutiny from journalists and policymakers, Senate testimony, and personal threats. Don explains how these findings became distilled into soundbites, evidenced by coverage in The New York Times, Chicago Tribune, and a reference in James Patterson’s Murder Games. The conversation addresses overdiagnosis, false positives, and the consequence some called the “Berry effect”—an observed drop in mammogram rates after the panel’s recommendations. Key Highlights Don Berry’s NIH consensus conference leadership and approach to breast cancer screening recommendations.Statistical bias and trial limitations inherent in mammography evidence.Meta-analysis findings: 18% hazard reduction; 1.4-day average life extension.Policy guidance supporting individualized patient decision-making over universal screening.Strong backlash from advocacy, media, radiology, and government—including Senate hearings and personal threats.Enduring debates, public misunderstandings, and continued citation of these events in scientific and popular sources.For more, visit us at https://www.berryconsultants.com/

  2. 10 août

    REMAP-CAP Results: Oseltamivir in Critically-Ill Influenza Patients

    In this episode of "In the Interim…", Dr. Scott Berry speaks with Dr. Srinivas Murthy, Dr. Thomas Hills, and Dr. Lindsay Berry about the REMAP-CAP trial results on oseltamivir in critically ill influenza patients. The trial used a Bayesian covariate-adjusted platform design and found oseltamivir was not effective at reducing 90-day mortality with a “98% and 99% probability of harm in 90-day mortality” compared to control. Covariate adjustment addressed baseline and site variation. Subgroup analyses showed greater harm in patients with higher illness severity. Sensitivity analyses using alternative neutral, optimistic, and pessimistic priors produced important scientific exploration of the results. No evidence was found for benefit over control in any subgroup. The discussion highlights the first randomized, controlled evidence in this patient group, contrasting prior observational studies and clinical guidelines. A mechanism of harm remains unclear. REMAP-CAP is continuing enrollment in moderate severity and pediatric cohorts to further examine population-specific effects. The episode also addresses the broader challenges of trial design and interpretation in acute care research, the limitations of nonrandomized evidence, and the importance of ongoing Bayesian analyses and transparent reporting. Key Highlights Pre-print is available: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7172531REMAP-CAP platform trial, Bayesian logistic regression, covariate adjustmentOseltamivir arms: statistical trigger for inferiority, “98 and 99% probability of harm”Greater harm in sicker subgroups, consistent results across sensitivity analysesOngoing arms: moderate severity and pediatric cohorts, mechanistic questions unresolvedContext: limitations of previous historical data studies, clinical practice impact, future research directionsFor more, visit us at https://www.berryconsultants.com/

  3. 5 août

    ICECAP: The Results

    In this episode of "In the Interim…", Dr. Scott Berry leads a comprehensive discussion of the ICECAP trial results with four Principal Investigators: Dr. Will Meurer (Professor, Emergency Medicine and Neurology, University of Michigan; consultant to Berry Consultants), Dr. Robert Silbergleit (Professor, Emergency Medicine, University of Michigan Medical School), Dr. Romer Geocadin (Professor, Neurology, Neurosurgery, and Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine), and Dr. Sharon Yeatts (Professor of Biostatistics, Public Health Sciences, Medical University of South Carolina). The panel dissects the ICECAP trial’s multi-arm Bayesian adaptive design, response-adaptive randomization, and population-level approach to cooling duration after out-of-hospital cardiac arrest. Emphasis is placed on methodological transparency, direct operational experience, absence of evidence for incremental benefit beyond six hours of cooling, and future direction for neurocritical care trials. Key Highlights Detailed review of adaptive design methodology, Bayesian interim analyses, and stopping criteria for futility based on posterior probabilitiesAnalysis of flat duration-response curve: no clinical benefit seen for extended hypothermia, trial triggered to stop per prespecified ruleCohort discussion: representation of U.S. epidemiology, inclusion of heterogeneous etiologies (notably respiratory and overdose) and bystander CPR ratesOperational challenges: running frequent interim analyses, maintaining trial integrity during COVID-19, site-level differences, statistical reporting timelinesPanel consensus on the need for continued equipoise in temperature management, caution against misinterpretation, and priority for precision subgroups in future researchDirections: implementation lessons, pediatric ICECAP, PRECISE-CAP phenotyping study, ongoing subgroup analysesFor more, visit us at https://www.berryconsultants.com/

  4. 3 août

    Failure of the Proportional Odds is the Result

    In this episode of "In the Interim…", Dr. Scott Berry and Dr. Elizabeth Lorenzi systematically examine the analytic pitfalls in recent acute ischemic stroke trials, especially the implications of violating the proportional odds assumption on the modified Rankin Scale. The discussion draws on the DISCOUNT, INSTANT, ESCAPE-MeVo, and ORIENTAL-MeVo trials, spotlighting frequent reactive shifts to proportional odds violations. Scott and Liz detail how such approaches obscure clinically relevant heterogeneity and react by creating analysis methods that obscure the clinical relevance of a violation of proportional odds. The episode underscores the necessity for trial designs that explicitly address heterogeneity of treatment effect. Listeners gain an unvarnished critique of prevailing reporting practices and an actionable vision for future stroke trial designs. Key Highlights DISCOUNT trial’s interim analysis and futility stopping.Issues with endpoint dichotomization after proportional odds violations.Comparison across multiple recent stroke trials with inconsistent endpoint definitions.Obscuring of proportional odds violations, which may be the most important result of the trial.Adaptive strategies in STEP platform.For more, visit us at https://www.berryconsultants.com/

  5. 27 juill.

    Adaptive Design Actions Matrix

    In this episode of "In the Interim…", Dr. Scott Berry challenges the widely held belief that any interim look at trial data obligates an alpha adjustment. By constructing a two-by-two matrix: interim data (positive/negative) and adaptive action (increase/decrease sample size), Scott demonstrates that the need for statistical correction depends on precisely what actions are prespecified. He emphasizes that the need for adjustment depends on the action and the data. Technical scenarios examined include group sequential designs, “promising zone” sample size re-estimation (citing the formal results of Mehta and Pocock), and response adaptive randomization. Scott stresses that clear prespecification is required for Type I error control and regulatory compliance. He critiques common missteps, such as unnecessary allocation of alpha to futility boundaries when superiority is not planned, and reiterates that it is the adaptive action, and not mere data review, that determines the statistical impact of interim analyses. Key Highlights Dissects alpha adjustment myths and their historical roots.Details two-by-two matrix: interim data direction and adaptive action.Explores group sequential, futility, promising zone, and response adaptive examples.Clarifies when Type I error is truly affected—action and data matter.Stresses prespecification’s role in trial validity and regulatory acceptance.Identifies pitfalls in common trial design practices.For more, visit us at https://www.berryconsultants.com/

  6. 20 juill.

    A Visit With Tim Berry

    In this episode of "In the Interim…," Dr. Scott Berry interviews Tim Berry, co-founder of Blend360, detailing a career that demonstrates the practical application of statistical and analytical methods within large-scale business environments. Tim outlines his quick shift from earning a master’s at the University of Minnesota to industry positions, starting at AT&T Bell Laboratories, where he built and tested retention models on millions of consumer records. He recounts his time at Rapp Collins, where analytics had limited organizational impact, before joining Merkle and transforming analytics into a key business component through growing a team from two to over eighty, contributing to hundreds of millions in revenue. At Blend360, Tim discusses acquiring Consultants To Go (C2G) to build new capabilities, focusing on hiring and developing young analytics talent through programs like All-Star. The conversation addresses the evolution from traditional statistics to analytics, the rise of AI and agentic AI for workflow automation and calls out media overstatement of AI-driven disruption. He concludes with pointed career advice to his nephew and other quantitative students: prioritize adaptability, industry experience, and continuous learning over chasing credentials. Key Highlights: Graduate thesis using the Bradley-Terry model for baseball outcome predictionMainframe-driven, large-scale retention modeling at AT&TAnalytics as a peripheral function at Rapp Collins versus central driver at MerkleRapid talent expansion and analytics leadership at MerkleFounding Blend360 and institutional talent developmentAI advancements, agentic AI for business, skepticism on AI hypeConcrete advice for quantitative undergraduatesFor more, visit us at https://www.berryconsultants.com/

  7. 13 juill.

    Fairness in Soccer and Clinical Trials

    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 legitimacyAnalogies from soccer, golf, baseball, and wrestling on the societal role of rules and enforcementClassic statistics lessons on missing data, inference, and survivorship biasDiscussion of post-hoc versus prespecified analysis and its implications in trial integrityDefense of adaptive and Bayesian methodology as scientifically valid through pre-specification and covariate adjustmentReflection on the ongoing evolution of fairness and rigor in sport and scienceFor more, visit us at https://www.berryconsultants.com/

  8. 6 juill.

    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 Definition and quantification of bias in early-stopped clinical trialsMathematical examples demonstrating bias magnitude in fixed and adaptive group sequential designsDetailed critique of the methodology and conclusions in Bassler et al. (JAMA 2010)Discussion correcting common misunderstandings in bias estimation and selective reportingSimulation as a decisive tool for precise bias estimationRegulatory context including FDA guidance and ICH E20 draft guidanceReference to DAWN trial as evidence of practical benefits of early stoppingFor more, visit us at https://www.berryconsultants.com/

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À propos

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.

Informations

  • Créateur
    Berry
  • Années d’activité
    2025 - 2026
  • Épisodes
    75
  • Classement
    Tout public
  • Copyright
    © 2025 Berry Consultants
  • Site Web de l’émission
    In the Interim...

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