Literature DB >> 14584711

An adaptive approach to implementing bivariate group sequential clinical trial designs.

Susan Todd1.   

Abstract

In clinical trials, situations often arise where more than one response from each patient is of interest; and it is required that any decision to stop the study be based upon some or all of these measures simultaneously. Theory for the design of sequential experiments with simultaneous bivariate responses is described by Jennison and Turnbull (Jennison, C., Turnbull, B. W. (1993). Group sequential tests for bivariate response: interim analyses of clinical trials with both efficacy and safety endpoints. Biometrics 49:741-752) and Cook and Farewell (Cook, R. J., Farewell, V. T. (1994). Guidelines for monitoring efficacy and toxicity responses in clinical trials. Biometrics 50:1146-1152) in the context of one efficacy and one safety response. These expositions are in terms of normally distributed data with known covariance. The methods proposed require specification of the correlation, rho between test statistics monitored as part of the sequential test. It can be difficult to quantify rho and previous authors have suggested simply taking the lowest plausible value, as this will guarantee power. This paper begins with an illustration of the effect that inappropriate specification of rho can have on the preservation of trial error rates. It is shown that both the type I error and the power can be adversely affected. As a possible solution to this problem, formulas are provided for the calculation of correlation from data collected as part of the trial. An adaptive approach is proposed and evaluated that makes use of these formulas and an example is provided to illustrate the method. Attention is restricted to the bivariate case for ease of computation, although the formulas derived are applicable in the general multivariate case.

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Year:  2003        PMID: 14584711     DOI: 10.1081/BIP-120024197

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


  3 in total

1.  Assessing the impact of safety monitoring on the efficacy analysis in large Phase III group sequential trials with non-trivial safety event rate.

Authors:  Yanqiu Weng; Yuko Y Palesch; Stacia M DeSantis; Wenle Zhao
Journal:  J Biopharm Stat       Date:  2015-05-26       Impact factor: 1.051

2.  Adjustment on the Type I Error Rate for a Clinical Trial Monitoring for both Intermediate and Primary Endpoints.

Authors:  Susan Halabi
Journal:  J Biom Biostat       Date:  2012-05-19

3.  Impact of safety monitoring on error probabilities of binary efficacy outcome analyses in large phase III group sequential trials.

Authors:  Yanqiu Weng; Wenle Zhao; Yuko Palesch
Journal:  Pharm Stat       Date:  2012-05-16       Impact factor: 1.894

  3 in total

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