Clinical trial design during and beyond the pandemic: the I-SPY COVID trial

Using Bayesian statistics in confirmatory clinical trials in the regulatory setting: a tutorial review

Bayesian statistics plays a pivotal role in advancing medical science by enabling healthcare companies, regulators, and stakeholders to assess the safety and efficacy of new treatments, interventions, and medical procedures. The Bayesian framework offers a unique advantage over the classical framework, especially when incorporating prior information into a new trial with quality external data, such as historical data or another source of co-data. In recent years, there has been a significant increase in regulatory submissions using Bayesian statistics due to its flexibility and ability to provide valuable insights for decision-making, addressing the modern complexity of clinical trials where frequentist trials are inadequate. For regulatory submissions, companies often need to consider the frequentist operating characteristics of the Bayesian analysis strategy, regardless of the design complexity. In particular, the focus is on the frequentist type I error rate and power for all realistic alternatives. This tutorial review aims to provide a comprehensive overview of the use of Bayesian statistics in sample size determination, control of type I error rate, multiplicity adjustments, external data borrowing, etc., in the regulatory environment of clinical trials. Fundamental concepts of Bayesian sample size determination and illustrative examples are provided to serve as a valuable resource for researchers, clinicians, and statisticians seeking to develop more complex and innovative designs.

SARS-CoV-2 resistance to monoclonal antibodies and small-molecule drugs

Over four years have passed since the beginning of the COVID-19 pandemic. The scientific response has been rapid and effective, with many therapeutic monoclonal antibodies and small molecules developed for clinical use. However, given the ability for viruses to become resistant to antivirals, it is perhaps no surprise that the field has identified resistance to nearly all of these compounds. Here, we provide a comprehensive review of the resistance profile for each of these therapeutics. We hope that this resource provides an atlas for mutations to be aware of for each agent, particularly as a springboard for considerations for the next generation of antivirals. Finally, we discuss the outlook and thoughts for moving forward in how we continue to manage this, and the next, pandemic.

Using the 'Leapfrog' Design as a Simple Form of Adaptive Platform Trial to Develop, Test, and Implement Treatment Personalization Methods in Routine Practice

The route for the development, evaluation and dissemination of personalized psychological therapies is complex and challenging. In particular, the large sample sizes needed to provide adequately powered trials of newly-developed personalization approaches means that the traditional treatment development route is extremely inefficient. This paper outlines the promise of adaptive platform trials (APT) embedded within routine practice as a method to streamline development and testing of personalized psychological therapies, and close the gap to implementation in real-world settings. It focuses in particular on a recently-developed simplified APT design, the 'leapfrog' trial, illustrating via simulation how such a trial may proceed and the advantages it can bring, for example in terms of reduced sample sizes. Finally it discusses models of how such trials could be implemented in routine practice, including potential challenges and caveats, alongside a longer-term perspective on the development of personalized psychological treatments.

How Electronic Medical Record Integration Can Support More Efficient Critical Care Clinical Trials

Large volumes of data are collected on critically ill patients, and using data science to extract information from the electronic medical record (EMR) and to inform the design of clinical trials represents a new opportunity in critical care research. Using improved methods of phenotyping critical illnesses, subject identification and enrollment, and targeted treatment group assignment alongside newer trial designs such as adaptive platform trials can increase efficiency while lowering costs. Some tools such as the EMR to automate data collection are already in use. Refinement of data science approaches in critical illness research will allow for better clinical trials and, ultimately, improved patient outcomes.

Trend in Clinical Trial Participation During COVID-19: A Secondary Analysis of the I-SPY COVID Clinical Trial

To analyze the temporal trend in enrollment rates in a COVID-19 platform trial during the first three waves of the pandemic in the United States.

DESIGN

Secondary analysis of data from the I-SPY COVID randomized controlled trial (RCT).

SETTING

Thirty-one hospitals throughout the United States.

PATIENTS

Patients who were approached, either directly or via a legally authorized representative, for consent and enrollment into the I-SPY COVID RCT.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Among 1,338 patients approached for the I-SPY COVID trial from July 30, 2020, to February 17, 2022, the number of patients who enrolled (n = 1,063) versus declined participation (n = 275) was used to calculate monthly enrollment rates. Overall, demographic and baseline clinical characteristics were similar between those who enrolled versus declined. Enrollment rates fluctuated over the course of the COVID-19 pandemic, but there were no significant trends over time (Mann-Kendall test, p = 0.21). Enrollment rates were also comparable between vaccinated and unvaccinated patients. In multivariable logistic regression analysis, age, sex, region of residence, COVID-19 severity of illness, and vaccination status were not significantly associated with the decision to decline consent.

CONCLUSIONS

In this secondary analysis of the I-SPY COVID clinical trial, there was no significant association between the enrollment rate and time period or vaccination status among all eligible patients approached for clinical trial participation. Additional studies are needed to better understand whether the COVID-19 pandemic has altered clinical trial participation and to develop strategies for encouraging participation in future COVID-19 and critical care clinical trials.

Report of the first seven agents in the I-SPY COVID trial: a phase 2, open label, adaptive platform randomised controlled trial

BACKGROUND

An urgent need exists to rapidly screen potential therapeutics for severe COVID-19 or other emerging pathogens associated with high morbidity and mortality.

METHODS

Using an adaptive platform design created to rapidly evaluate investigational agents, hospitalised patients with severe COVID-19 requiring ≥6 L/min oxygen were randomised to either a backbone regimen of dexamethasone and remdesivir alone (controls) or backbone plus one open-label investigational agent. Patients were enrolled to the arms described between July 30, 2020 and June 11, 2021 in 20 medical centres in the United States. The platform contained up to four potentially available investigational agents and controls available for randomisation during a single time-period. The two primary endpoints were time-to-recovery (<6 L/min oxygen for two consecutive days) and mortality. Data were evaluated biweekly in comparison to pre-specified criteria for graduation (i.e., likely efficacy), futility, and safety, with an adaptive sample size of 40-125 individuals per agent and a Bayesian analytical approach. Criteria were designed to achieve rapid screening of agents and to identify large benefit signals. Concurrently enrolled controls were used for all analyses. https://clinicaltrials.gov/ct2/show/NCT04488081.

FINDINGS

The first 7 agents evaluated were cenicriviroc (CCR2/5 antagonist; n = 92), icatibant (bradykinin antagonist; n = 96), apremilast (PDE4 inhibitor; n = 67), celecoxib/famotidine (COX2/histamine blockade; n = 30), IC14 (anti-CD14; n = 67), dornase alfa (inhaled DNase; n = 39) and razuprotafib (Tie2 agonist; n = 22). Razuprotafib was dropped from the trial due to feasibility issues. In the modified intention-to-treat analyses, no agent met pre-specified efficacy/graduation endpoints with posterior probabilities for the hazard ratios [HRs] for recovery ≤1.5 between 0.99 and 1.00. The data monitoring committee stopped Celecoxib/Famotidine for potential harm (median posterior HR for recovery 0.5, 95% credible interval [CrI] 0.28-0.90; median posterior HR for death 1.67, 95% CrI 0.79-3.58).

INTERPRETATION

None of the first 7 agents to enter the trial met the prespecified criteria for a large efficacy signal. Celecoxib/Famotidine was stopped early for potential harm. Adaptive platform trials may provide a useful approach to rapidly screen multiple agents during a pandemic.

FUNDING

Quantum Leap Healthcare Collaborative is the trial sponsor. Funding for this trial has come from: the COVID R&D Consortium, Allergan, Amgen Inc., Takeda Pharmaceutical Company, Implicit Bioscience, Johnson & Johnson, Pfizer Inc., Roche/Genentech, Apotex Inc., FAST Grant from Emergent Venture George Mason University, The DoD Defense Threat Reduction Agency (DTRA), The Department of Health and Human ServicesBiomedical Advanced Research and Development Authority (BARDA), and The Grove Foundation. Effort sponsored by the U.S. Government under Other Transaction number W15QKN-16-9-1002 between the MCDC, and the Government.

Pragmatic platform trials to improve the outcome of patients with acute kidney injury

PURPOSE OF REVIEW

There is an important need for improved diagnostic strategies and treatment among patients with acute kidney injury (AKI). Classical randomized clinical trials have generated relevant results in AKI but are associated with shortcomings, such as high costs and sometimes lack of generalizability. In this minireview, we discuss the value and limits of pragmatic trials and platform trials for AKI research.

RECENT FINDINGS

The implementation of pragmatic and platform trials in critical care settings has generated relevant clinical evidence impacting clinical practice. Pragmatic and platform designs have recently been applied to patients at risk of AKI and represent a crucial opportunity to advance our understanding of optimized treatment and strategies in patients at risk of AKI or presenting with AKI. Trials embedded in electronic health records can facilitate patient enrollment and data collection. Platform trials have allowed for a more efficient study design. Although both pragmatic and platform trials have several advantages, they also come with the challenges and shortcomings discussed in this review.

SUMMARY

Pragmatic and platform trials can provide clinical answers in 'real-life' settings, facilitate a significant sample size enrollment at a limited cost, and provide results that can have a faster implementation in clinical practice.

Immune Modulation in Sepsis, ARDS, and Covid-19 - The Road Traveled and the Road Ahead

Immune Modulation in Sepsis, ARDS, and Covid-19Leligdowicz et al. consider the history and future of immunomodulating therapies in sepsis and ARDS, including ARDS due to Covid-19, and remark on the larger challenge of clinical research on therapies for syndromes with profound clinical and biologic heterogeneity.

Acute respiratory distress syndrome in adults: diagnosis, outcomes, long-term sequelae, and management

Acute respiratory distress syndrome (ARDS) is characterised by acute hypoxaemic respiratory failure with bilateral infiltrates on chest imaging, which is not fully explained by cardiac failure or fluid overload. ARDS is defined by the Berlin criteria. In this Series paper the diagnosis, management, outcomes, and long-term sequelae of ARDS are reviewed. Potential limitations of the ARDS definition and evidence that could inform future revisions are considered. Guideline recommendations, evidence, and uncertainties in relation to ARDS management are discussed. The future of ARDS strives towards a precision medicine approach, and the framework of treatable traits in ARDS diagnosis and management is explored.

New Insights into Clinical and Mechanistic Heterogeneity of the Acute Respiratory Distress Syndrome: Summary of the Aspen Lung Conference 2021

Clinical and molecular heterogeneity are common features of human disease. Understanding the basis for heterogeneity has led to major advances in therapy for many cancers and pulmonary diseases such as cystic fibrosis and asthma. Although heterogeneity of risk factors, disease severity, and outcomes in survivors are common features of the acute respiratory distress syndrome (ARDS), many challenges exist in understanding the clinical and molecular basis for disease heterogeneity and using heterogeneity to tailor therapy for individual patients. This report summarizes the proceedings of the 2021 Aspen Lung Conference, which was organized to review key issues related to understanding clinical and molecular heterogeneity in ARDS. The goals were to review new information about ARDS phenotypes, to explore multicellular and multisystem mechanisms responsible for heterogeneity, and to review how best to account for clinical and molecular heterogeneity in clinical trial design and assessment of outcomes. The report concludes with recommendations for future research to understand the clinical and basic mechanisms underlying heterogeneity in ARDS to advance the development of new treatments for this life-threatening critical illness.

Optimizing the Design and Analysis of Future AKI Trials

AKI is a complex clinical syndrome associated with an increased risk of morbidity and mortality, particularly in critically ill and perioperative patient populations. Most AKI clinical trials have been inconclusive, failing to detect clinically important treatment effects at predetermined statistical thresholds. Heterogeneity in the pathobiology, etiology, presentation, and clinical course of AKI remains a key challenge in successfully testing new approaches for AKI prevention and treatment. This article, derived from the "AKI" session of the "Kidney Disease Clinical Trialists" virtual workshop held in October 2021, reviews barriers to and strategies for improving the design and implementation of clinical trials in patients with, or at risk of, developing AKI. The novel approaches to trial design included in this review span adaptive trial designs that increase the knowledge gained from each trial participant; pragmatic trial designs that allow for the efficient enrollment of sufficiently large numbers of patients to detect small, but clinically significant, treatment effects; and platform trial designs that use one trial infrastructure to answer multiple clinical questions simultaneously. This review also covers novel approaches to clinical trial analysis, such as Bayesian analysis and assessing heterogeneity in the response to therapies among trial participants. We also propose a road map and actionable recommendations to facilitate the adoption of the reviewed approaches. We hope that the resulting road map will help guide future clinical trial planning, maximize learning from AKI trials, and reduce the risk of missing important signals of benefit (or harm) from trial interventions.

Redefining critical illness

Research and practice in critical care medicine have long been defined by syndromes, which, despite being clinically recognizable entities, are, in fact, loose amalgams of heterogeneous states that may respond differently to therapy. Mounting translational evidence-supported by research on respiratory failure due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection-suggests that the current syndrome-based framework of critical illness should be reconsidered. Here we discuss recent findings from basic science and clinical research in critical care and explore how these might inform a new conceptual model of critical illness. De-emphasizing syndromes, we focus on the underlying biological changes that underpin critical illness states and that may be amenable to treatment. We hypothesize that such an approach will accelerate critical care research, leading to a richer understanding of the pathobiology of critical illness and of the key determinants of patient outcomes. This, in turn, will support the design of more effective clinical trials and inform a more precise and more effective practice at the bedside.