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In the Interim...: Daily Summaries Delivered
by Berry
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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- 6 days ago45 min
The CHIPS Trial: Bayesian Adaptive Trial in JAMA
In this episode of “In the Interim…,” Dr. Scott Berry talks with Dr. Roger Lewis, Dr. Anna McGlothlin, and Dr. Nick Berry — all co-authors on the CHIPS trial results recently published in JAMA (Spinella et al., August 2026) — about the design, implementation, and results. The conversation covers why room-temperature platelets, which can be stored only five to seven days, leave rural hospitals, low-volume centers, and military and disaster settings without a reliable supply, and how a Bayesian adaptive design was used to find the maximum safe cold-storage duration rather than testing a single fixed duration. Roger, Anna, and Nick walk through the monotonic dose-response model that governed escalation, an unplanned mid-trial complication when the FDA independently authorized fourteen-day cold storage, and how the Data Safety Monitoring Board reviewed results within days of each interim. The trial ultimately demonstrated non-inferiority of cold-stored platelets out to twenty-one days with a Bayesian probability greater than 99.9%, offering a path to expanding platelet access in settings where it was previously very challenging.Key HighlightsCold-stored platelets tested as a potential answer to platelet shortages in rural, low-volume, and military/disaster settings.Bayesian adaptive design used to find the maximum safe cold-storage duration, not just test a single fixed duration.A monotonic dose-response model constrained escalation to a pre-specified, safety-first ladder across four interim analyses.Mid-trial complication: an independent FDA decision allowing 14-day cold storage, absorbed into the design without unblinding.Non-inferiority demonstrated out to 21 days of cold storage, with a Bayesian probability greater than 99.9%.Interim data turned around by the unblinded implementation team in five business days, versus the six weeks often assumed for adaptive trials.Implications for platelet access in disaster, military, and low-volume hospital settings, and for how shelf-life-dependent products are tested going forward.For more, visit us at https://www.berryconsultants.com/
- 1 weeks ago38 min
NFL Study of CTE: The Issues
In this episode of "In the Interim…", Dr. Scott Berry examines three recent health-research headlines through a statistician's lens: an Adventist Health Study-2 analysis claiming eggs reduce Alzheimer's risk, an Emory University trial on high-dose vitamin D and cognition (Zhao et al.), and a British Medical Journal study led by Dr. Daniel Danishvar (Harvard, Boston University) reporting that 25 to 97 percent of deceased NFL players showed evidence of chronic traumatic encephalopathy (CTE). After flagging multiplicity and small-sample issues in the first two studies, Scott spends most of the episode on the CTE study's central flaw: because CTE can only be diagnosed after death, the published prevalence is calculated from a sample of deceased players rather than the full population of NFL players — a distinction he illustrates using a thought experiment on sudden infant death syndrome (SIDS) and a breakdown of the study's own age-stratified death data. He traces the resulting bias, a form of differential mortality, to a single caveat buried deep in the study's limitations section.Key HighlightsAdventist Health Study-2's "27% fewer Alzheimer's diagnoses in egg-eaters" finding, and why it's likely multiplicity-driven and observational, not causal.The Emory University vitamin D study (Zhao et al.): a 13% MoCA improvement drawn from roughly eight patients, presented as a headline finding.The British Medical Journal NFL CTE study (Danishvar et al., Harvard / Boston University): a headline prevalence of "25% to 97%" of NFL players.Why 215 of 235 donated brains (97.7%) is a hugely biased numerator — CTE is only diagnosed posthumously, and families of symptomatic players are most likely to donate.The corrected denominator: 878 NFL players who died between 2016 and 2021, yielding roughly 24.5% — still biased, because CTE itself accelerates death.A SIDS thought experiment showing how building a "population" from those who have already died systematically overstates prevalence through a form of differential mortality bias.The key limitation, buried three-quarters of the way through the paper's limitations section, quietly mentions the selection bias behind the headline number.For more, visit us at https://www.berryconsultants.com/
- 2 weeks ago47 min
Talkin' 'bout Sweet Time
In this episode of "In the Interim...", Dr. Scott Berry dissects prevailing concepts of “clinically meaningful difference” in clinical trials focusing on progressive diseases. Through detailed examples from pancreatic cancer (Ben Sasse, Revolution Medicines), emphysema (Elevair), Alzheimer’s disease (lecanemab), and IVF, Scott challenges the adequacy of the population-mean of a continuous outcome in reflecting true patient benefit. The episode discusses inconsistent usage and interpretation of acronyms such as MCID, CSD, and Target Product Profile (TPP). Dr. Berry advises trialists to resist interpreting the mean difference using patient-level minimal effects, and adopt responder analyses and cumulative probability approaches to enhance patient-level relevance. Guidance is offered for analyzing the effect of time-saved instead of a mean differences in a clinical endpoint at a single time for progressive diseases – measuring “sweet time.”Key HighlightsFocus on added time not the change from baseline as the most meaningful outcome for a progressive disease.In-depth evaluation of MCID, CSD, TPP, and risk of misinterpretation.Critique of trying to interpret mean-based endpoints for clinical meaningfulness such as six-minute walk distance and CDR sum of boxes.FDA advisory panel guidance on MCID for IVF live birth endpoints and dichotomous versus continuous endpoints.Advocacy for responder analyses and cumulative probability of achieving thresholds in reporting the clinical effect of a treatment.For more, visit us at https://www.berryconsultants.com/
- Aug 17, 20261h 5m
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 HighlightsDon 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/
- Aug 10, 202651 min
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 HighlightsPre-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/
- Aug 5, 202654 min
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 HighlightsDetailed 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/
- Aug 3, 202640 min
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 HighlightsDISCOUNT 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/
- Jul 27, 202630 min
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 HighlightsDissects 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/
About 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.
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