Bayesian adaptive two-stage design for determining person-time in Phase II clinical trials with Poisson data

Hand, Austin L.; Scott, John; Young, Phil D.; Stamey, James D.; Young, Dean M.

doi:10.1080/02664763.2015.1117588

Cited by 2 publications

(6 citation statements)

References 17 publications

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“…The study confirmed the validity of using this statistical technique to end a clinical trial early due to either treatment futility or efficacy, an approach that can save developers of novel medical products both time and money (29). …”

Section: Improving Clinical Evaluation Pre- and Post-licensure Througsupporting

confidence: 52%

“…In another project, CBER statisticians used a novel version of a Bayesian two-stage adaptive design to analyze a hypothetical Phase II trial of immune globulin (intravenous; IGIV)—an antibody-based product used as replacement therapy in patients with humoral immunodeficiencies. The study confirmed the validity of using this statistical technique to end a clinical trial early due to either treatment futility or efficacy, an approach that can save developers of novel medical products both time and money ( 29 ).…”

Section: Improving Clinical Evaluation Pre- and Post-licensure Througsupporting

confidence: 52%

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Advancing Public Health Using Regulatory Science to Enhance Development and Regulation of Medical Products: Food and Drug Administration Research at the Center for Biologics Evaluation and Research

Kusinitz¹,

Braunstein²,

Wilson³

2017

Front. Med.

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Center for Biologics Evaluation and Research enhances and supports regulatory decision-making and policy development. This work contributes to our regulatory mission, advances medical product development, and supports Food and Drug Administration’s regulatory response to public health crises. This review presents some examples of our diverse scientific work undertaken in recent years to support our regulatory and public health mission.

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Section: Improving Clinical Evaluation Pre- and Post-licensure Througsupporting

confidence: 52%

Section: Improving Clinical Evaluation Pre- and Post-licensure Througsupporting

confidence: 52%

Advancing Public Health Using Regulatory Science to Enhance Development and Regulation of Medical Products: Food and Drug Administration Research at the Center for Biologics Evaluation and Research

Kusinitz¹,

Braunstein²,

Wilson³

2017

Front. Med.

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“…(2009), and Hand et al. (2016), who assume that the number of infections is a Poisson distributed variable.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Furthermore, for phase II single‐arm trials, Hand et al. (2016) extended the standard scheme to conduct a two‐stage design to the case of a Poisson‐distributed response variable and constructed a Bayesian predictive two‐stage design.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, Zaslavsky (2012) determined the sample size for the estimation of a Poisson rate using the concept of conditional power and reformulating the Type I and II error probabilities in terms of confidence and credible limits. Furthermore, for phase II single-arm trials, Hand et al (2016) extended the standard scheme to conduct a two-stage design to the case of a Poisson-distributed response variable and constructed a Bayesian predictive two-stage design.…”

Section: Introductionmentioning

confidence: 99%

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Exact sample size determination for a single Poisson random sample

Gentile

Sambucini

2023

Biometrical J

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Classical power analysis for sample size determination is typically performed in clinical trials. A “hybrid” classical Bayesian or a “fully Bayesian” approach can be alternatively used in order to add flexibility to the design assumptions needed at the planning stage of the study and to explicitly incorporate prior information in the procedure. In this paper, we exploit and compare these approaches to obtain the optimal sample size of a single‐arm trial based on Poisson data. We adopt exact methods to establish the rejection of the null hypothesis within a frequentist or a Bayesian perspective and suggest the use of a conservative criterion for sample size determination that accounts for the not strictly monotonic behavior of the power function in the presence of discrete data. A Shiny web app in R has been developed to provide a user‐friendly interface to easily compute the optimal sample size according to the proposed criteria and to assure the reproducibility of the results.

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Bayesian adaptive two-stage design for determining person-time in Phase II clinical trials with Poisson data

Cited by 2 publications

References 17 publications

Advancing Public Health Using Regulatory Science to Enhance Development and Regulation of Medical Products: Food and Drug Administration Research at the Center for Biologics Evaluation and Research

Advancing Public Health Using Regulatory Science to Enhance Development and Regulation of Medical Products: Food and Drug Administration Research at the Center for Biologics Evaluation and Research

Exact sample size determination for a single Poisson random sample

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