Detailed Description of Derivation and Display of Delinquent and Delayed Data

• Activity Number: 321
• Type: Contributed
• Date/Time: Tuesday, August 6, 2013 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): William Coar and David Kerr*+
• Companies: Axio Research and Axio Research

Abstract

Important questions for data cleaning and interim analyses for clinical trials are "How current is the data?" and "Are there patients that are overdue for visits?" Missing and delayed data is correctly an important topic in clinical trials and close monitoring of data can help ensure maximal data completion. The answer to these questions can help a Data Monitoring Committee know if they are looking at timely data, and let the study team know if more aggressive monitoring or other additional site oversight is needed. The solution proposed is to first determine if patients are overdue for visits and, if so, estimate how long they are overdue. This is not necessarily trivial and depends on the visit structure of the study and allowable time windows for each visit. Once this information is computed, the data are presented in a non-traditional but highly informative way, as a Kaplan-Meier figure. This figure quickly informs viewers of both the quantity of patients overdue for visits and the length of time overdue.