Journal Article DKFZ-2017-03849

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Blinded versus unblinded covariate selection in confirmatory survival trials.

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2014
Taylor & Francis Philadelphia, PA

Journal of biopharmaceutical statistics 24(2), 398 - 414 () [10.1080/10543406.2013.860158]
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Abstract: Adjustment for covariates and specification of the correct covariate set are important issues in the analysis of clinical trials. Edwards (1999) proposes a model selection approach where the model is chosen on the final data set, which remains blinded for treatment group allocation. We investigate this method for time-to-event endpoints and compare its performance to variable selection within an adaptive design. This adaptive design integrates the methods of Schäfer and Müller (2001) and Keiding et al. (1987) and allows variable selection on the unblinded data during an interim analysis. Monte Carlo simulation shows that Edwards' method-though blinded-outperforms the adaptive method in terms of ability to select the survival relevant covariates and power. The application of the methods is illustrated by a clinical trial example.

Classification:

Contributing Institute(s):
  1. Biostatistik (C060)
Research Program(s):
  1. 313 - Cancer risk factors and prevention (POF3-313) (POF3-313)

Appears in the scientific report 2014
Database coverage:
Medline ; Ebsco Academic Search ; IF < 5 ; JCR ; NCBI Molecular Biology Database ; NationallizenzNationallizenz ; SCOPUS ; Science Citation Index Expanded ; Thomson Reuters Master Journal List ; Web of Science Core Collection
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 Record created 2017-09-29, last modified 2024-02-28



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