| Literature DB >> 21423789 |
Lingling Li1, Scott R Evans, Hajime Uno, L J Wei.
Abstract
Group sequential designs are often used in clinical trials to evaluate efficacy and/or futility. Many methods have been developed for different types of endpoints and scenarios. However, few of these methods convey information regarding effect sizes (e.g., treatment differences) and none uses prediction to convey information regarding potential effect size estimates and associated precision, with trial continuation. To address these limitations, Evans et al. (2007) proposed to use prediction and predicted intervals as a flexible and practical tool for quantitative monitoring of clinical trials. In this article, we reaffirm the importance and usefulness of this innovative approach and introduce a graphical summary, predicted interval plots (PIPS), to display the information obtained in the prediction process in a straightforward yet comprehensive manner. We outline the construction of PIPS and apply this method in two examples. The results and the interpretations of the PIPS are discussed.Entities:
Year: 2009 PMID: 21423789 PMCID: PMC3059316 DOI: 10.1198/sbr.2009.0041
Source DB: PubMed Journal: Stat Biopharm Res ISSN: 1946-6315 Impact factor: 1.452