Episodes
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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/
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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
Definition and mechanics of RAR, with interim analysis guiding allocation updatesMulti-arm adaptive and platform trial experiences (BAN2401, ICECAP, dulaglutide, I-SPY2, REMAP-CAP, PROSPECT)Critique of RAR in two-arm trials (power loss), temporal trends, unblinding, and overgeneralized literatureECMO/play-the-winner: risks of poorly simulated RARNecessity for rigorous pre-trial simulation and robust data flowsContextualization of RAR’s role in both traditional and learning healthcare environmentsFor more, visit us at https://www.berryconsultants.com/
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Missing episodes?
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In this episode of "In the Interim…", Dr. Scott Berry explores the origins of REMAP-CAP with Prof. Steve Webb, former chair of the REMAP-CAP International Trial Steering Committee. This episode examines how pandemic preparedness efforts after 2009 H1N1 shaped the design of an international, adaptive platform trial to be able to respond rapidly to new infectious threats. Steve and Scott explain the sequence of strategy meetings, the role of the PREPARE consortium in securing EU funding and subsequent federation across Australia and Canada. The discussion details REMAP-CAP’s technical foundations: a modular master protocol, domain architecture, Bayesian adaptive methods, and frequent interim analyses. When COVID-19 emerged, these core elements permitted immediate platform activation to combat the pandemic infection with assessment of treatments across multiple domains—including steroids, immune modulation, and anticoagulation—generating actionable evidence in weeks. The episode also addresses international data harmonization, multi-platform trial collaboration, and the capacity to adapt trial structure as infectious disease threats evolve.
Key Highlights
Response to H1N1 and feckless pandemic trialsInternational strategy meetings—origins of platform conceptPREPARE consortium and cross-continental fundingModular master protocol, factorial allocation, and domain-specific appendicesBayesian triggers and response adaptive randomizationPivot to COVID-19 and rapid data generationMulti-platform international collaborationFor more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry explores the challenge of protracted endpoint timelines in adaptive clinical trials and the statistical strategies used to increase the rate of actionable information gain. Drawing on detailed case studies from breast cancer (I-SPY 2), Alzheimer’s disease (BAN 2401), diabetes (AWARD-5/Trulicity), and cardiac arrest, Scott addresses the technical demands of longitudinal modeling and interim data imputation for accelerating learning. The discussion prioritizes a critical, empirical perspective of demonstrating how carefully constructed statistical models, simulation, and Bayesian methods can convert interim patient data into more robust estimates of delayed outcomes and support key design adaptations. The episode is a direct account of the methods, uncertainties, and real-world impact of fighting time in adaptive trials.
Key Highlights
Analyzes how delayed primary endpoints challenge adaptive trial efficiency, and how adaptive trial designs use accumulating in-trial data to inform adaptive allocation, arm graduation, and early trial conclusions.Dissects the use of longitudinal models in I-SPY 2, in which interim MRI measurements at one and three months are mapped to predicted six-month pathologic complete response, through an ordinal stratified, pre-specified modeling approach—illustrating both the strengths and limits of interim forecasting.Reviews the BAN 2401 adaptive Alzheimer’s trial, where early cognitive assessments were modeled to forecast 12-month outcomes enabling response adaptive randomization and sample size adaptation based on projections from interim data.Details the AWARD-5 seamless trial for dulaglutide (Trulicity), where strategic enrollment pacing, predictive modeling of early HbA1c and weight loss, and a utility function across four endpoints supported both dose selection and seamless transition to phase 3 without requiring full cohort maturation.Summarizes recent cardiac arrest trial (ICECAP), using 30-day ordinal scales and multiple imputation to predict 90-day outcomes and improve interim decision-making.Unpacks the importance of prior-data-driven modeling, simulation, and strict robustness checks in the construction of all predictive models used for interim adaptation.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry is joined by Dr. Will Meurer, professor of Emergency Medicine and Neurology at the University of Michigan, for an in-depth discussion of the ICECAP trial’s adaptive Bayesian design. The discussion breaks down the scientific rationale for hypothermia after cardiac arrest, critiques legacy studies, and explores the justification for including both shockable and non-shockable rhythm types. The episode provides a detailed account of ICECAP’s methodological strategies: a weighted mRS primary endpoint, Bayesian adaptive trial structure, response-adaptive randomization (governed by strict allocation guardrails), a unique Bayesian model for duration-response, and futility rules. The trial’s development is described in the context of the ADAPT-IT initiative, an FDA/NIH partnership, and the operational leadership of the MUSC Data Coordinating Center. Results are pending publication which will be highlighted in a future episode of “In the interim…”.
Key Highlights
Rationale for exploring duration of hypothermia after cardiac arrest with review of prior evidence.Enrollment of shockable and non-shockable populations to address clinical uncertainty.Primary endpoint: weighted mRS, independently developed for ICECAP.Bayesian adaptive design with response-adaptive randomization, interim analyses, and allocation guardrails.Management of missing data with multiple imputation from 30-day outcomes.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry details the design, execution, and results of the multi-platform randomized clinical trial (mpRCT) pioneered during the COVID-19 pandemic. He describes how REMAP-CAP, ATTACC, and ACTIV-4a—each developed independently—pooled data prospectively for joint analysis to address therapeutic anticoagulation in hospitalized COVID-19 patients. Scott outlines the operational rigor required to harmonize endpoints, establish monthly adaptive analyses, and stratify patients by disease severity and D-dimer level. He examines the unified Bayesian hierarchical modeling approach, dynamic borrowing across strata, and the process for simultaneous DSMB reviews coordinated across all platforms. The mpRCT framework enabled real-time, evidence-based adaptations and rigorous distinction of treatment effect by patient subgroup. Results were incorporated into clinical guidelines because prospectively specified analysis revealed benefit for moderate patients and futility or harm for severe patients—findings that would have been missed by standard post hoc pooling.
Key Highlights
Integration of REMAP-CAP, ATTACC, and ACTIV-4a under a prospectively unified analysis plan.Primary endpoint and stratified patient subgroups defined in advance.Monthly adaptive analyses using a shared Bayesian hierarchical model.Simultaneous oversight by joint statistical and DSMB committees.Superiority of therapeutic anticoagulation in moderate, non-critically ill groups; futility and possible harm in severe patients.mpRCT model established a framework for future global multi-platform trials.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry examines the analytical challenges of comparing performance across eras in both sports and clinical research. Drawing from statistically robust family debates and published research, Scott details how overlapping competitors—such as athletes who played with both Babe Ruth, played with the next generation, who played with … all the way to playing with Aaron Judge—enable the estimation of temporal effects and allow for objective comparisons between generations. He translates this approach directly into platform clinical trials, demonstrating how overlapping trial arms or shared control groups make it possible to quantify and adjust for time trends. Scott distinguishes between observable, model-based comparisons and subjective judgments, rigorously addressing limitations such as interactions between treatments and era, and emphasizing the foundational importance of empirical overlap over speculative claims.
Key Highlights
Deconstruction of time-machine thought experiments: analyzing how teams like the 1927 Yankees or athletes such as Johnny Weissmuller and Jesse Owens compare to present-day counterparts using statistical benchmarks.Technical explanation of connecting eras empirically through players or trial arms who span multiple time periods, thereby supporting quantitative estimation of temporal shifts.Detailed account of linear and hierarchical modeling strategies, with covariate adjustment for player age, period effects, and evolving population composition across baseball, hockey, and golf data.Translation of these statistical constructs to adaptive and platform clinical trials, exemplified by I-SPY 2, where overlapping treatment and control arms permit rigorous assessment of evolving treatment effects over a trial’s lifespan.Critical discussion of the rare but important possibility of treatment-by-era interactions, and the necessity of data-driven assessment rather than assumption.Consideration of how these methods inform not just debates about athletic greatness and Hall of Fame inclusion, but also robust interpretation of treatment effects in longitudinal clinical studies.For more, visit us at https://www.berryconsultants.com/
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In the 60th episode of “In the Interim…”, Dr. Scott Berry, Dr. Nick Berry, and Dr. Joe Marion discuss how Berry Consultants uses AI in clinical trial design and software development. The conversation addresses current applications, limitations, implications for productivity, and the ongoing need for human expertise in clinical trial design. The team examines both promising use cases and the risks associated with security, compliance, and AI-generated statistical work.
Key Highlights
AI is used to develop user interfaces and code modules, notably expediting tasks like R Shiny app development and software prototyping.Statistical coding for complex modeling and simulation—such as numerical integration and predictive probability calculations—remains unreliable when delegated to AI and still requires direct oversight and manual review.Attention to security and confidentiality is central; Berry prohibits the use of client-sensitive or patient data within AI tools.Generative AI assists with drafting and editing documents, but the output tends to be non-specific, generic, and sometimes imprecise, requiring expert editorial input before use.While embracing AI to improve efficiency, the discussion is critical of current AI hype, especially around black-box modeling and pushes back against the perception that current AI can replace domain-specific statistical design or strategic judgment.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry and Dr. Nick Berry investigate how futility in clinical trials and stopping rules in sports illuminate very similar decision problems, albeit with very different consequences. Drawing from baseball’s 10-run rule, tournament cuts in golf, the discussion confronts traditional and Bayesian strategies for interim decisions. The episode explains why simulation, not historical trial review, provides the empirical backbone for futility boundaries in clinical trials, and details the mechanics and consequences of aggressive stopping criteria. Using the Biogen aducanumab Alzheimer’s trials, the conversation exposes how a futility rule based on 20% predictive probability halted trials even when meaningful probability of success remained. Scott and Nick address the influence of ethical considerations, cost, regulatory priorities, and statistical rigor, and contrast Bayesian predictive probability’s strengths over conditional power.
Key Highlights
Dissects sports futility rules (10-run rule, golf cuts, Bill James heuristic) and their application to clinical trial designArgues for prospective simulation to define adaptive futility thresholdsExplains how Bayesian predictive probability provides a more robust framework than conditional probability for interim adaptive decisionsDetails how aggressive futility criteria may prematurely stop trials and risk missing beneficial treatments, as in the aducanumab caseExplores the intersection of ethics, patient safety, operational efficiency, regulatory standards, and trial cost -
In this episode of "In the Interim…", host Dr. Scott Berry undertakes a detailed, methodical critique of ICH-E20 draft guidance language as applied to adaptive clinical trial design. Focusing on an innocuous but corruptible paragraph in Section 3.1, Scott scrutinizes the logic behind regulatory reluctance to appreciate multiple or complex adaptations in confirmatory trials. Drawing on extensive experience, he highlights how such restrictive interpretations do not reflect practical development realities, instead setting up “false choices” where alternative designs desired by regulators are infeasible. Through operational scenarios—including the SEPSIS-ACT trial, an enrichment design, and sample size re-estimation examples—Scott illustrates the empirical benefits of seamless and multi-adaptive trials for sponsors, patients, and regulators. Technical discussion addresses misconceptions about complexity and bias and stresses the value of presenting realistic alternatives when engaging with regulatory authorities. The episode ultimately encourages a more nuanced dialogue to advance efficient and scientifically robust clinical trials.
Key Highlights
Discussion of ICH-E20 section 3.1 guidance and its operational impact on adaptive designs.Dissection of “false choice” dilemmas in regulatory interactions, referencing real adaptive trial submissions.Case-based examples: SEPSIS-ACT, enrichment, and sample size adaptation trials.Highlighting myths regarding bias and operational burden from multiple interim analyses.Emphasis on practical strategies for more effective regulatory communication about adaptive trials and realistic alternatives.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…" Dr. Scott Berry is joined by Professors Victoria Cornelius, Danny McAuley, and Anthony Gordon, for a technical review of the PANTHER trial—an international, Phase 2 adaptive platform evaluating pharmacologic interventions for ARDS. The trial is open-label and does not employ blinding, as discussed in the episode. The primary endpoint is 28-day organ support-free days (death as -1, survivors 0–28 days), analyzed with a Bayesian proportional odds model. PANTHER uses stratification by hyper- and hypoinflammatory subphenotypes, with fixed, equal randomization within each stratum. Analyses for treatments are separated by stratum, reflecting the potential of differential treatment effects. Quarterly interim analyses allow early stopping by stratum for efficacy or futility. Content includes explicit discussion of infrastructure: rapid device deployment, centralized data for trial and future biological discovery, and governance challenges in multinational collaboration. Funding is provided by NIHR (UK), US Department of Defense, CIHR (Canada), NHMRC and MRFF (Australia), HRB (Ireland), and additional support from Germany and Japan. PANTHER is positioned to streamline Phase 2 critical care drug testing and facilitate graduation to larger platforms such as REMAP-CAP, with potential to expedite pharmaceutical evaluation and accelerate ARDS therapeutic development.
Key Highlights
Real-time phenotyping (Randox device) to stratify ARDS patients.Separate Bayesian analyses by phenotype stratum.Open-label, fixed randomization within stratum.28-day organ support-free days as a composite endpoint.Quarterly interim analyses enable early dropping or graduation of arms by strata.Central data resource and biosample collection for future research.Operational, funding, and device logistics for global trial deployment.Transition of Phase 2 results to established Phase 3 platforms (e.g., REMAP-CAP).For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry connects with Dr. Byron Gajewski, professor of biostatistics and data science at the University of Kansas Medical Center (KUMC), for a detailed discussion on the design, simulation, and operational realities of Bayesian adaptive clinical trials in academic environments. Gajewski discusses his academic background, training at Texas A&M, and progressive adoption of Bayesian principles based on direct experiential advantages in complex data settings. The conversation highlights KUMC’s Fixed and Adaptive Clinical Trial Simulator Working Group, which utilizes FACTS for faculty, staff, and student collaboration, enabling practical simulation, trial protocol development, and in-house applied statistical training. The PAIN-CONTRoLS Trial serves as a practical example of multi-arm Bayesian adaptive design, using response-adaptive randomization for comparative effectiveness in neuropathy research. The NIH-funded HOBIT trial is examined in detail: multi-arm structure, adaptive allocation among investigational arms, fixed control randomization, group-sequential interim analyses, and sliding dichotomy methodology for the Glasgow Outcome Scale Extended. The discussion stresses a shift to probabilistic, evidence-driven interpretation and reporting, shaping operational choices and academic culture for both investigators and trainees.
Key Highlights
Gajewski describes how practical challenges in real-world problems catalyzed his transition to Bayesian modeling.KUMC’s working group integrates FACTS software in collaborative simulation and operational trial planning.The PAIN-CONTRoLS Trial: multi-arm Bayesian adaptive design, response-adaptive randomization, real-time analysis, and endpoint-driven allocation.HOBIT trial: Adaptive allocation, fixed control arm proportion, group-sequential interims, ordinal endpoint modeling.Emphasis on probabilistic, quantitative reporting over binary outcomes in trial analysis and interpretation.Cultural shift observed among academic collaborators and trainees embracing Bayesian adaptive strategies. -
In this episode of "In the Interim...", Dr. Scott Berry hosts Dr. Stephen Senn, award-winning statistician and author, for a discussion on advanced challenges in adaptive and platform trial methodology. Senn draws on experience in academic, pharmaceutical, and regulatory settings to address the recent draft guidance on Bayesian statistics from the FDA and multiple controversies in clinical trial design.
Key Highlights
Emphasizes understanding data origin and regression to the mean as essential for trial interpretation, above adherence to Bayesian or frequentist frameworks.Details methodological considerations for time adjustments and model complexity, highlighting that model specification and parameter handling are critical regardless of statistical school.Identifies the limitations of non-concurrent controls in platform trials, focusing on evolving background therapy, site participation, and protocol changes that reduce validity of historical or pooled control data.Analyzes blinding difficulties in trials with multiple treatments and administration modes, using “veiled” blinding as a case and noting the implications for placebo response comparability.Clarifies that operational efficiencies are the principal advantage of adaptive and platform trials, while purported statistical efficiencies can be exaggerated.Stresses the importance of presenting interim analyses transparently to DSMBs when using complex models for time or covariate adjustment, to ensure oversight and interpretation remain rigorous.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry is joined by statisticians Dr. Amy Crawford, Dr. Cora Allen-Savietta, and Dr. Jessica Overbey for a technical deep dive into hierarchical composite endpoints and the win ratio in clinical trial design. The group addresses clinical and statistical justifications for layered endpoint structures, demonstrates the mechanics of pairwise win ratio analysis, and explores operational and interpretive consequences in both conventional and adaptive trials. The panel scrutinizes analytic limitations, regulatory concerns, and emerging modeling strategies—all grounded in real-world trial examples.
Key Highlights
Precise definition and use case for hierarchical composite endpoints in cardiovascular and related trials.Stepwise breakdown of win ratio mechanics, tie-handling, and the distinction between effect estimation (win ratio) and hypothesis testing (FS-test).Discussion of endpoint prevalence and dominance, risk of clinical interpretation being tied to lower-order outcomes, the role of patient exposure, and methods to parse component contributions.Overview of statistical power, role of simulation, and comparative advantages over other composite approaches.Identification of core limitations: interpretive complexity, opaque weighting, and mutable meaning of wins with maturing data.Review of predictive probability for adaptive interim analysis and modeling using ordinal regression.Opinions of US and European regulatory perspectives including support, reservations, and expectations for transparency with graphics and complementary analyses.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry interviews Professors Steven Tong and Josh Davis about the SNAP platform trial for Staphylococcus aureus bacteremia. The discussion covers SNAP’s rationale, large-scale adaptive design, methodology, and operational execution at approximately 150 hospitals in 13 countries. Key statistical questions, domain results, pediatric-adult analysis, and global implementation strategy are explored in depth. Listeners will find clear examples of how adaptive platform trials can efficiently address clinically relevant questions in infectious disease, while highlighting the nuances of trial design, statistical thresholds, and network collaboration.
Key Highlights
High and unchanging mortality for Staphylococcus aureus bacteremia—over one million deaths annually.SNAP leverages silo-based structure (MSSA, MRSA, PSSA) and factorial domains for simultaneous, efficient investigation of treatments.Cefazolin shown non-inferior to flucloxacillin for MSSA with lower related acute kidney injury.In PSSA, penicillin demonstrated significantly less toxicity and favorable mortality signal over flucloxacillin; mortality difference did not meet the statistical superiority threshold.Futility reached in the adjunctive clindamycin domain for effect on 90-day mortality.Both adults and children enrolled, with pediatric results using statistical borrowing from adults in line with FDA Bayesian guidance.Ongoing platform expansion includes bacteriophage therapy, antiplatelet domains, and evaluation of diagnostic strategies.Statistical leadership: Dr. Anna McGlothlin (Berry Consultants), Dr. Julie Marsh (statistics lead).For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry and Dr. Kert Viele examine Bayesian borrowing in Phase 3 clinical trials, focusing on statistical handling of prior information and real-world FDA interactions. The episode opens with an analogy, comparing prior probability in Bayesian analysis to interpreting a home pregnancy test, succinctly demonstrating the effect of prior knowledge on trial interpretation. The discussion addresses technical challenges—how borrowing inflates Type I errors and why this is addressed differently under Bayesian operating characteristics. Concrete examples include dynamic versus static borrowing approaches, and formal integration of prior evidence in regulatory submissions. Case studies center on the WATCHMAN device (PROTECT AF and PREVAIL trials) and REBYOTA, illustrating FDA engagement, relevant trial design tactics, and published outcomes. The episode also critiques common pitfalls such as selective data use and improper prior construction, emphasizing the FDA’s focus on comprehensive and unbiased historical sources.
Key Highlights
Pregnancy test analogy used to clarify prior probability in trial interpretation.Bayesian borrowing’s effects on Type I error and statistical thresholds.Case studies: WATCHMAN device (PROTECT AF, PREVAIL) and REBYOTA approvals.Dynamic borrowing versus static borrowing strategies in regulatory settings.Risks of cherry-picking and importance of unbiased, relevant prior data.FDA guidance and review procedures for Bayesian trials.For more, visit us at https://www.berryconsultants.com/
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In Episode 51 of "In the Interim…", Dr. Scott Berry interviews writer, producer, and performer Shaun Cassidy to examine the practical elements of storytelling that matter in scientific and statistical communication. Cassidy draws on his experience in television, music, and live performance—including his role as writer and Executive Producer of New Amsterdam—to present clear parallels between audience engagement in show business and in clinical research. The conversation prioritizes improving narrative precision, emotional resonance, and authenticity when conveying complex topics to varied audiences.
Key Highlights
Cassidy demonstrates that audiences retain emotional impact over factual content, asserting that “people don’t remember what you say, but how you made them feel.”Emphasis on narrative specificity: personal, concrete details foster stronger audience connection than generalized statements, countering assumptions about broad relatability.Effective communication relies on reactive delivery—improvised response to audience cues—rather than rigid, memorized scripts; Cassidy notes this principle applies across disciplines.Role of authenticity and vulnerability: openly stating discomfort or introversion facilitates greater audience trust and personal connection, especially in technical or scientific fields.Anecdotes from Cassidy’s work in television, music, and teaching illustrate the central role of storytelling structure and audience feedback, with parallels drawn to professional scientific presentations.Alan Alda’s illustration of improv for scientists is discussed as an example of bridging technical expertise with adaptive communication skills.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry and Dr. Lindsay Berry investigate the statistical foundations and clinical implications of analyzing ordinal endpoints, drawing on experience from major stroke and COVID-19 trials. Discussion centers on the Modified Rankin Scale, DAWN, MR CLEAN, and REMAP-CAP, demonstrating that methods such as proportional odds, dichotomization, and utility weighting all impose explicit or implicit clinical weights on the outcome categories. The episode presents direct mathematical derivations, exposes the equivalence between proportional odds models and value-weighted analysis, and uses real trial data to explore how statistical and clinical perspectives on endpoint weighting may diverge. Emphasis remains on transparency and the need for clinically relevant weight assignment in trial endpoints.
Key Highlights
Structural overview and clinical significance of the Modified Rankin Scale scores.Illustration that proportional odds models and dichotomized analyses apply hidden, prevalence-driven or threshold-based weights.Utility weighting in DAWN, formulated from EQ-5D patient utilities and economic studies, with observed alignment.MR CLEAN investigators' critique of utility weighting; empirical data demonstrated relative consistency and challenged the claim that statistical approaches resolve variation across patients.REMAP-CAP platform trial: Organ Support Free Days endpoint analyzed with proportional odds imposed weights on the scale from death to free of organ support .Extension of these arguments to win ratio/rank-based approaches, with caution that all methods encode clinical assumptions.For more, visit us at https://www.berryconsultants.com/
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In this episode of "In the Interim…", Dr. Scott Berry marks the podcast’s one-year anniversary, sharing listener metrics, watch data, and regional engagement. He then delivers a step-by-step analysis of the FDA meeting process, detailing the progression from initial sponsor meeting requests and question submission to briefing book preparation, feedback cycles, and in-person logistics for a Type C meeting at the White Oak facility. Drawing from more than 25 years of trial design and regulatory experience, Scott offers precise guidance on technical preparation, sponsor responsibilities, and common errors in sponsor-FDA dialog, emphasizing what works and what wastes time inside the one-hour meeting constraint. His practical approach focuses on clarity, respect for process, and actionable advice.
Key Highlights
Slightly over 30,000 people tuned in during the first year across 45 episodes; about 10,000 via audio, 20,000 via video with a global worldwide reach.FDA meeting workflow: request, submit four to eight questions, draft briefing book, receive written feedback, strict one-hour in-person discussion controlled by sponsor.Advice on briefing book content, avoiding new materials at the meeting, even what not to bring through the White Oak facility.Sponsor pitfalls: disingenuous patient advocacy, asking impossible questions, taking adversarial stance in statistical discussion.For more, visit us at https://www.berryconsultants.com/
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Dr. Nathan O’Hara (University of Maryland), Dr. Gerard Slobogean (UC Irvine), and Dr. Sheila Sprague (McMaster University) describe the launch and design of the Musculoskeletal Adaptive Platform Trial (MAPT)—the first major adaptive platform trial in orthopaedic surgery. The discussion covers MAPT’s master protocol structure, patient-centered endpoint framework, and operational strategies for multinational implementation. Focus areas include the FASTER-HIP domain’s use of Bayesian modeling with a hierarchical clinical endpoint and the standards established for adaptation, data coordination, and future scalability. Listeners gain insight into a trial infrastructure designed to lower barriers for evidence generation and facilitate ongoing evidence generation in musculoskeletal trauma care.
Key Highlights
MAPT as a scalable, master protocol for orthopaedic intervention evaluationHierarchical, patient-centered endpoint (survival, 4-level ambulation, days alive/out of hospital), analyzed with a Bayesian-modeled, non-parametric win ratioDomain-specific adaptation thresholds based on clinical differentiationInterim analyses after 100 patients, then every 50, informing early adaptation40 sites across US, Canada, and Europe, centralized data management at McMasterA unified DSMB structure with capacity for domain-specific expertise as neededTiered protocol access: open sharing, collaboration, direct integrationInfrastructure enables rapid domain addition and multi-investigator participationFor more, visit us at https://www.berryconsultants.com/
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