Literature DB >> 19127460

Some controversial multiple testing problems in regulatory applications.

H M James Hung1, Sue-Jane Wang.   

Abstract

Multiple testing problems in regulatory applications are often more challenging than the problems of handling a set of mathematical symbols representing multiple null hypotheses under testing. In the union-intersection setting, it is important to define a family of null hypotheses relevant to the clinical questions at issue. The distinction between primary endpoint and secondary endpoint needs to be considered properly in different clinical applications. Without proper consideration, the widely used sequential gate keeping strategies often impose too many logical restrictions to make sense, particularly to deal with the problem of testing multiple doses and multiple endpoints, the problem of testing a composite endpoint and its component endpoints, and the problem of testing superiority and noninferiority in the presence of multiple endpoints. Partitioning the null hypotheses involved in closed testing into clinical relevant orderings or sets can be a viable alternative to resolving the illogical problems requiring more attention from clinical trialists in defining the clinical hypotheses or clinical question(s) at the design stage. In the intersection-union setting there is little room for alleviating the stringency of the requirement that each endpoint must meet the same intended alpha level, unless the parameter space under the null hypothesis can be substantially restricted. Such restriction often requires insurmountable justification and usually cannot be supported by the internal data. Thus, a possible remedial approach to alleviate the possible conservatism as a result of this requirement is a group-sequential design strategy that starts with a conservative sample size planning and then utilizes an alpha spending function to possibly reach the conclusion early.

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Year:  2009        PMID: 19127460     DOI: 10.1080/10543400802541693

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  15 in total

1.  Graphical approaches for multiple comparison procedures using weighted Bonferroni, Simes, or parametric tests.

Authors:  Frank Bretz; Martin Posch; Ekkehard Glimm; Florian Klinglmueller; Willi Maurer; Kornelius Rohmeyer
Journal:  Biom J       Date:  2011-08-12       Impact factor: 2.207

Review 2.  Design, data monitoring, and analysis of clinical trials with co-primary endpoints: A review.

Authors:  Toshimitsu Hamasaki; Scott R Evans; Koko Asakura
Journal:  J Biopharm Stat       Date:  2017-10-30       Impact factor: 1.051

3.  Group-Sequential Strategies in Clinical Trials with Multiple Co-Primary Outcomes.

Authors:  Toshimitsu Hamasaki; Koko Asakura; Scott R Evans; Tomoyuki Sugimoto; Takashi Sozu
Journal:  Stat Biopharm Res       Date:  2015       Impact factor: 1.452

4.  A logrank test-based method for sizing clinical trials with two co-primary time-to-event endpoints.

Authors:  Tomoyuki Sugimoto; Takashi Sozu; Toshimitsu Hamasaki; Scott R Evans
Journal:  Biostatistics       Date:  2013-01-10       Impact factor: 5.899

5.  Sample size determination in group-sequential clinical trials with two co-primary endpoints.

Authors:  Koko Asakura; Toshimitsu Hamasaki; Tomoyuki Sugimoto; Kenichi Hayashi; Scott R Evans; Takashi Sozu
Journal:  Stat Med       Date:  2014-03-27       Impact factor: 2.373

6.  Sizing clinical trials when comparing bivariate time-to-event outcomes.

Authors:  Tomoyuki Sugimoto; Toshimitsu Hamasaki; Scott R Evans; Takashi Sozu
Journal:  Stat Med       Date:  2017-01-24       Impact factor: 2.373

7.  Sample Size Considerations in Clinical Trials when Comparing Two Interventions using Multiple Co-Primary Binary Relative Risk Contrasts.

Authors:  Yuki Ando; Toshimitsu Hamasaki; Scott R Evans; Koko Asakura; Tomoyuki Sugimoto; Takashi Sozu; Yuko Ohno
Journal:  Stat Biopharm Res       Date:  2015-06-24       Impact factor: 1.452

8.  Interim evaluation of efficacy or futility in group-sequential trials with multiple co-primary endpoints.

Authors:  Koko Asakura; Toshimitsu Hamasaki; Scott R Evans
Journal:  Biom J       Date:  2016-10-19       Impact factor: 2.207

9.  Closed Testing in Pharmaceutical Research: Historical and Recent Developments.

Authors:  Kevin S S Henning; Peter H Westfall
Journal:  Stat Biopharm Res       Date:  2015       Impact factor: 1.452

10.  Interim Monitoring for Futility in Clinical Trials with Two Co-primary Endpoints Using Prediction.

Authors:  Koko Asakura; Scott R Evans; Toshimitsu Hamasaki
Journal:  Stat Biopharm Res       Date:  2019-11-04       Impact factor: 1.452

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