Bias and Incorrect Confidence Interval Coverage in Prescription Drug Labeling

• Activity Number: 305
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Gregory Levin*+
• Keywords: Bias ; Coverage ; Labeling ; Clinical Trials ; Estimation ; Regulatory

Abstract

This research considers the potential bias in point estimates and deviation from nominal coverage in confidence intervals that are reported in the clinical studies section of prescription drug labeling. The primary purpose of labeling is to give healthcare professionals the information needed to prescribe drugs appropriately. Therefore, labeling typically reports the effects that the treatment might be expected to have on several efficacy measures, including not only the primary endpoint used to establish effectiveness, but also a number of key secondary endpoints that are important to the decision-making of practitioners. One possible regulatory approach to labeling is to only include results on important secondary efficacy endpoints if there is statistical evidence of a treatment effect and a clinically meaningful estimated effect size. We evaluate the statistical consequences of this approach and show that it can lead to substantial bias in point estimates (toward spuriously greater effect sizes than the truth) and substantial undercoverage in confidence intervals. These statistical properties may have important and undesirable regulatory and public health implications.