Multiplicity issues for platform trials with a shared control arm

Bai, Xiaofei; Deng, Qi; Liu, Dacheng

doi:10.1080/10543406.2020.1821703

Cited by 15 publications

(17 citation statements)

References 9 publications

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“…Furthermore, definition of error rates in the context of a cohort platform trial with a combined decision rule per cohort is not straightforward. 36 , 37 , 41 , 42 , 43 , 44 As an example, whether or not to include simulated platforms that—as a result of random sampling of treatment efficacy from a specified prior distribution—do not contain truly efficacious cohorts in the calculation of the disjunctive power can lead to discrepancies of up to 15% points in our simulations. In terms of type 1 error rates, we defined a type 1 error via a target product profile and focused on interpreting the per‐cohort type 1 error and the family‐wise error rate in this paper.…”

Section: Discussionmentioning

confidence: 99%

Decision rules for identifying combination therapies in open‐entry, randomized controlled platform trials

Meyer

Mesenbrink

Dunger-Baldauf

et al. 2022

Pharmaceutical Statistics

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Platform trials have become increasingly popular for drug development programs, attracting interest from statisticians, clinicians and regulatory agencies.Many statistical questions related to designing platform trials-such as the impact of decision rules, sharing of information across cohorts, and allocation ratios on operating characteristics and error rates-remain unanswered. In many platform trials, the definition of error rates is not straightforward as classical error rate concepts are not applicable. For an open-entry, exploratory platform trial design comparing combination therapies to the respective monotherapies and standard-of-care, we define a set of error rates and operating characteristics and then use these to compare a set of design parameters under a range of simulation assumptions. When setting up the simulations, we aimed for realistic trial trajectories, such that for example, a priori we do not know the exact number of treatments that will be included over time in a specific simulation run as this follows a stochastic mechanism. Our results indicate that the method of data sharing, exact specification of decision rules and a priori assumptions regarding the treatment efficacy all strongly contribute to the operating characteristics of the platform trial. Furthermore, different operating characteristics might be of importance to different stakeholders. Together with the potential flexibility and complexity of a platform trial, which also impact the achieved operating characteristics via, for example, the degree of efficiency of data sharing this implies that utmost care needs to be given to evaluation of different assumptions and design parameters at the design stage.

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Section: Discussionmentioning

confidence: 99%

Decision rules for identifying combination therapies in open‐entry, randomized controlled platform trials

Meyer

Mesenbrink

Dunger-Baldauf

et al. 2022

Pharmaceutical Statistics

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show abstract

“…Practical considerations for platform trials are discussed below, while statistical methods for common designs in umbrella and platform trials are provided in Supplementary Materials 2 [42,[48][49][50][51][52][53][54][55][56][57][58][59]. Throughout the rest of the section, we use the term platform trials for simplicity though most of the discussions here are applicable to both umbrella and platform trials.…”

Section: Practical Considerations For Umbrella/ Platform Trialsmentioning

confidence: 99%

Practical Considerations and Recommendations for Master Protocol Framework: Basket, Umbrella and Platform Trials

Broglio

et al. 2021

Ther Innov Regul Sci

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Master protocol, categorized as basket trial, umbrella trial or platform trial, is an innovative clinical trial framework that aims to expedite clinical drug development, enhance trial efficiency, and eventually bring medicines to patients faster. Despite a clear uptake on the advantages in the concepts and designs, master protocols are still yet to be widely used. Part of that may be due to the fact that the master protocol framework comes with the need for new statistical designs and considerations for analyses and operational challenges. In this article, we provide an overview of the master protocol framework, unify the definitions with some examples, review the statistical methods for the designs and analyses, and focus our discussions on some practical considerations and recommendations of master protocols to help practitioners better design and implement such studies. Supplementary Information The online version contains supplementary material available at 10.1007/s43441-021-00315-7.

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“…When this is the case, the observed treatment difference between candidate A and placebo as well as between candidate B and placebo could be both false positive. Bai et al [ 4 ] provided a detailed discussion on such error rate and showed that such an error rate is not critical based on numerical results obtained from both simulations and numerical integration.…”

Section: Control the Error Rate Of Go/nogo Decisionmentioning

confidence: 99%

Proof of Concept: Drug Selection? Or Dose Selection? Thoughts on Multiplicity Issues

Deng

Ting

2021

Ther Innov Regul Sci

Self Cite

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In new drug development process, one of the most important milestones for a drug candidate is to establish Proof of Concept (PoC) at early Phase II stage. Among many challenges in PoC clinical trial design and analysis, the application of multiplicity comparison procedures (MCP) is frequently discussed when multiple doses or drugs are included in one PoC study. In such discussion, one fundamental question of applying multiplicity adjustment is which error one should consider to control and at what level. Should it be the experiment-wise error or the compound-wise error? In this paper, the multiplicity issues in two cases of PoC studies are used as examples to discuss the concept of different types of error and the level of the error rate control. With a clear understanding of the type of error and error rate control, the debate of applications of the multiplicity adjustment procedures in the PoC studies can be reconciled.

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Multiplicity issues for platform trials with a shared control arm

Cited by 15 publications

References 9 publications

Decision rules for identifying combination therapies in open‐entry, randomized controlled platform trials

Decision rules for identifying combination therapies in open‐entry, randomized controlled platform trials

Practical Considerations and Recommendations for Master Protocol Framework: Basket, Umbrella and Platform Trials

Proof of Concept: Drug Selection? Or Dose Selection? Thoughts on Multiplicity Issues

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