title: Predicted Interval Plots (PIPS): A Graphical Tool for Data Monitoring of Clinical Trials.
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.
authors.affiliation: Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA.
authors.forename: Lingling
authors.initials: L
authors.lastname: Li
authors.forename: Scott R
authors.initials: SR
authors.lastname: Evans
authors.forename: Hajime
authors.initials: H
authors.lastname: Uno
authors.forename: L J
authors.initials: LJ
authors.lastname: Wei