Sensitivity Analysis of Causal Inference in Clinical Trial Subject to Crossover

• Activity Number: 179
• Type: Contributed
• Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Hui Xie*+ and Daniel F. Heitjan+
• Companies: Columbia University and University of Pennsylvania
• Keywords: nonignorable ; crossover ; clinical trial ; causal inference

Abstract

In randomized clinical trials some subjects may cross over between treatment arms. To evaluate the effect of such crossover on key inferences, one can model this phenomenon as a missing-data problem. The as-treated estimate of the treatment effect is biased if the crossover is nonignorable. Troxel, Ma, and Heitjan (2002) developed a method for measuring the sensitivity of inferences to nonignorability in the missing-data mechanism. We apply their method to measure sensitivity to nonignorable crossover in randomized clinical trials. A drawback of their approach is that it assumes a single nonignorable selection model that applies equally to all patients, whereas in clinical trials we might expect each arm to have its own nonignorable selection mechanism. Accordingly, we extend the Troxel method to account for the possibility of multiple nonignorability mechanisms. We conclude that with our method one can delineate circumstances under which the as-treated analysis may be more or less sensitive to nonignorable crossover. We apply our method to the evaluation of sensitivity to nonignorable crossover in a clinical trial of chemotherapy for the treatment of multiple sclerosis.