國家衛生研究院 NHRI:Item 3990099045/14808
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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/14808


    Title: Bayesian hierarchical models for adaptive basket trial designs
    Authors: Chen, C;Hsiao, CF
    Contributors: Institute of Population Health Sciences
    Abstract: Basket trials evaluate a single drug targeting a single genetic variant in multiple cancer cohorts. Empirical findings suggest that treatment efficacy across baskets may be heterogeneous. Most modern basket trial designs use Bayesian methods. These methods require the prior specification of at least one parameter that permits information sharing across baskets. In this study, we provide recommendations for selecting a prior for scale parameters for adaptive basket trials by using Bayesian hierarchical modeling. Heterogeneity among baskets attracts much attention in basket trial research, and substantial heterogeneity challenges the basic assumption of exchangeability of Bayesian hierarchical approach. Thus, we also allowed each stratum-specific parameter to be exchangeable or nonexchangeable with similar strata by using data observed in an interim analysis. Through a simulation study, we evaluated the overall performance of our design based on statistical power and type I error rates. Our research contributes to the understanding of the properties of Bayesian basket trial designs.
    Date: 2023-05
    Relation: Pharmaceutical Statistics. 2023 May-Jun;22(3):531-546.
    Link to: http://dx.doi.org/10.1002/pst.2289
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=1539-1604&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000909626800001
    Cited Times(Scopus): https://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85146183541
    Appears in Collections:[Chin-Fu Hsiao] Periodical Articles

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