On the Use of Local Assessments for Monitoring Centrally Reviewed Endpoints with Missing Data in Clinical Trials

Sean S. Brummel, Daniel L. Gillen

Department of Statistics, University of California, Irvine, USA.
Harvard School of Public Health, Center for Biostatistics in AIDS Research, Cambridge, USA.

DOI: 10.4236/ojs.2013.34A005                

Abstract

Due to ethical and logistical concerns it is common for data monitoring committees to periodically monitor accruing clinical trial data to assess the safety, and possibly efficacy, of a new experimental treatment. When formalized, monitoring is typically implemented using group sequential methods. In some cases regulatory agencies have required that primary trial analyses should be based solely on the judgment of an independent review committee (IRC). The IRC assessments can produce difficulties for trial monitoring given the time lag typically associated with receiving assessments from the IRC. This results in a missing data problem wherein a surrogate measure of response may provide useful information for interim decisions and future monitoring strategies. In this paper, we present statistical tools that are helpful for monitoring a group sequential clinical trial with missing IRC data. We illustrate the proposed methodology in the case of binary endpoints under various missingness mechanisms including missing completely at random assessments and when missingness depends on the IRC’s measurement.

Keywords

Group Sequential; Information; Independent Review; Endpoint; Missing Data

Conflicts of Interest

The authors declare no conflicts of interest.

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