Literature DB >> 17886243

Incorporating intermediate binary responses into interim analyses of clinical trials: a comparison of four methods.

Anne Whitehead1, Marina Roshini Sooriyarachchi, John Whitehead, Kim Bolland.   

Abstract

In clinical trials with a long period of time between randomization and the primary assessment of the patient, the same assessments are often undertaken at intermediate times. When an interim analysis is conducted, in addition to the patients who have completed the primary assessment, there will be those who have till then undergone only intermediate assessments. The efficiency of the interim analysis can be increased by the inclusion of data from these additional patients. This paper compares four methods of increasing information based on model-free estimates of transition probabilities to incorporate intermediate assessments from patients who have not completed the trial. It is assumed that the observations are binary and that there is one intermediate assessment. The methods are the score and Wald approaches, each with the log-odds ratio and probability difference parameterizations. Simulations show that all four approaches have good properties in moderate to large sample sizes.

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Year:  2008        PMID: 17886243     DOI: 10.1002/sim.3046

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  Interim analysis incorporating short- and long-term binary endpoints.

Authors:  Julia Niewczas; Cornelia U Kunz; Franz König
Journal:  Biom J       Date:  2019-01-29       Impact factor: 2.207

2.  Interim analysis for binary outcome trials with a long fixed follow-up time and repeated outcome assessments at pre-specified times.

Authors:  Sameer Parpia; Jim A Julian; Chushu Gu; Lehana Thabane; Mark N Levine
Journal:  Springerplus       Date:  2014-06-26

3.  A comparison of methods for treatment selection in seamless phase II/III clinical trials incorporating information on short-term endpoints.

Authors:  Cornelia Ursula Kunz; Tim Friede; Nicholas Parsons; Susan Todd; Nigel Stallard
Journal:  J Biopharm Stat       Date:  2015       Impact factor: 1.051

  3 in total

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