Literature DB >> 20183459

Missing data in confirmatory clinical trials.

Paul Flyer1, Joseph Hirman.   

Abstract

Missing data for key efficacy and safety endpoints in clinical trials have the potential to undermine the scientific integrity of the study and prevent definitive conclusions regarding the safety and efficacy of an experimental product. Much of the missing data is the result of poor protocol design and a lack of agreement in the scientific community regarding the collection of study data after treatment discontinuation instead of an inability to collect the data. Rather than dealing with the fundamental causes of missing data, the statistical community has traditionally attempted to explicitly impute the missing data based upon observed data or more recently through the use of statistical models that implicitly impute the missing data. In this article, the causes for missing data are described and a number of approaches to maintain the integrity of the studies are described.

Mesh:

Year:  2009        PMID: 20183459     DOI: 10.1080/10543400903242746

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


  3 in total

1.  A multiple imputation method for sensitivity analyses of time-to-event data with possibly informative censoring.

Authors:  Yue Zhao; Amy H Herring; Haibo Zhou; Mirza W Ali; Gary G Koch
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2.  Intention-to-treat analysis when only a baseline value is available.

Authors:  Jos Wr Twisk; Judith Jm Rijnhart; Trynke Hoekstra; Noah A Schuster; Marieke M Ter Wee; Martijn W Heymans
Journal:  Contemp Clin Trials Commun       Date:  2020-11-26

3.  Methodological Issues on a Clinical Trial to Test Tapentadol Prolonged release vs. Oxycodone/Naloxone Prolonged release.

Authors:  Jorge Bacallao; Alfonso J Casado
Journal:  Pain Pract       Date:  2016-03       Impact factor: 3.183

  3 in total

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