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Phase III Precision Medicine Clinical Trial Designs That Integrate Treatment and Biomarker Evaluation.

ABSTRACT: Recent advances in biotechnology and cancer genomics have afforded enormous opportunities for development of more effective anticancer therapies. A key thrust of this modern drug development paradigm is successful identification of predictive biomarkers that can distinguish patients who might be sensitive to new targeted therapies. To respond to this challenge, a number of phase III cancer trial designs integrating biomarker-based objectives have been proposed and implemented in oncology drug development. In this article, we provide an updated review of commonly used biomarker-based randomized clinical trial designs, with a particular focus on design efficiency. When the efficacy of a new therapy may be limited to a biomarker-defined subgroup, the choice of an appropriate randomized clinical trial design should be guided by the strength of the biomarker's credentials. If compelling evidence indicates that a targeted therapy is beneficial only in a particular biomarker-defined subgroup, an enrichment design should be used. If there is strong evidence that the treatment is likely to be more beneficial in the biomarker-positive patients but a meaningful benefit is also possible in the biomarker-negative patients, then a properly powered biomarker-stratified design (eg, a subgroup-specific or Marker Sequential Test strategy) would provide the most rigorous determination of the sensitive populations. If the evidence supporting the predictive value of the biomarker is weak and the treatment is expected to work in the overall population, then a fallback design could be used. Careful selection of an appropriate phase III design strategy that integrates evaluation of a new anticancer therapy and its companion diagnostic is critical to the success of precision medicine in oncology.

SUBMITTER: Polley MC

PROVIDER: S-EPMC7446320 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Phase III Precision Medicine Clinical Trial Designs That Integrate Treatment and Biomarker Evaluation.

Polley Mei-Yin C MC Korn Edward L EL Freidlin Boris B

JCO precision oncology 20191024

Recent advances in biotechnology and cancer genomics have afforded enormous opportunities for development of more effective anticancer therapies. A key thrust of this modern drug development paradigm is successful identification of predictive biomarkers that can distinguish patients who might be sensitive to new targeted therapies. To respond to this challenge, a number of phase III cancer trial designs integrating biomarker-based objectives have been proposed and implemented in oncology drug de ...[more]

PMID: 32923845

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Project description:BackgroundPhase III trials often require large sample sizes, leading to high costs and delays in clinical decision-making. Group sequential designs can improve trial efficiency by allowing for early stopping for efficacy and/or futility and thus may decrease the sample size, trial duration and associated costs. Bayesian approaches may offer additional benefits by incorporating previous information into the analyses and using decision criteria that are more practically relevant than those used in frequentist approaches. Frequentist group sequential designs have often been used for phase III studies, but the use of Bayesian group sequential designs is less common. The aim of this work was to explore how Bayesian group sequential designs could be constructed for phase III trials conducted in emergency medicine.MethodsThe PARAMEDIC2 trial was a phase III randomised controlled trial that compared the use of adrenaline to placebo in out-of-hospital cardiac arrest patients on 30-day survival rates. It used a frequentist group sequential design to allow early stopping for efficacy or harm. We constructed several alternative Bayesian group sequential designs and studied their operating characteristics via simulation. We then virtually re-executed the trial by applying the Bayesian designs to the PARAMEDIC2 data to demonstrate what might have happened if these designs had been used in practice.ResultsWe produced three alternative Bayesian group sequential designs, each of which had greater than?90% power to detect the target treatment effect. A Bayesian design which performed interim analyses every 500 patients recruited produced the lowest average sample size. Using the alternative designs, the PARAMEDIC2 trial could have declared adrenaline superior for 30-day survival with approximately 1500 fewer patients.ConclusionsUsing the PARAMEDIC2 trial as a case study, we demonstrated how Bayesian group sequential designs can be constructed for phase III emergency medicine trials. The Bayesian framework enabled us to obtain efficient designs using decision criteria based on the probability of benefit or harm. It also enabled us to incorporate information from previous studies on the treatment effect via the prior distributions. We recommend the wider use of Bayesian approaches in phase III clinical trials.Trial registrationPARAMEDIC2 Trial registration ISRCTN, ISRCTN73485024. Registered 13 March 2014, http://www.isrctn.com/ISRCTN73485024.

Project description:Despite advances in pharmacotherapy, diabetic kidney disease (DKD) remains associated with a high burden of micro- and macrovascular complications often leading to premature mortality. New therapies are highly desirable to mitigate the burden of this disease. However, there are a number of barriers that hamper drug development in DKD. These include, amongst others, the lengthy and complex clinical trials required to prove drug efficacy and safety, inefficiencies in clinical trial conduct, and the high costs associated with these development programs. In this review a number of aspects are discussed, aiming to identify opportunities to transform and innovate drug development for DKD. Many clinical trials in DKD, as well as in other areas, face difficulties in timely and efficient enrolment of participants. To address this issue a network of sites should be created that are continuously recruiting individuals with DKD and collecting crucial information that can be used to understand prognosis and prognostic factors, and more importantly to serve as a pool of participants for recruitment to randomized trials. Second, the current clinical endpoints are late events in the progression of DKD. Endpoints based on lesser declines in estimated glomerular filtration rate (eGFR) or changes in albuminuria can shorten follow-up and/or lead to smaller and cheaper trials. Enrichment by enrolling clinical trial populations based on biomarker profiles is another approach that may facilitate clinical trial efficiency and conduct. Biomarkers can be used to individualize treatment by targeting populations more likely to respond leading to smaller and more efficient trials. Finally, using new trial design such as basket, umbrella or more broadly platform trials to assess a number of therapies simultaneously offers the potential to transform the drug development process in DKD. There are a number of opportunities to transform development approaches for new therapies for DKD. Platform trials along with appropriate biomarker-based enrichment strategies offer the possibility to foster drug development in a precision medicine era.

Dataset Information

Phase III Precision Medicine Clinical Trial Designs That Integrate Treatment and Biomarker Evaluation.

Publications

Phase III Precision Medicine Clinical Trial Designs That Integrate Treatment and Biomarker Evaluation.

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