When treatment failures occur during the course of a clinical trial, the treatment regimen following failure may be changed. This change in therapy complicates comparisons among the original treatment arms. As in some clinical trials with dropouts, intent-to-treat analysis can yield a large bias. We examine the use of multiple imputation to replace observations after treatment failure has occurred. As a sensitivity analysis, this approach is compared to existing methods for handling treatment failures - removing treatment failure subjects, removing data after the onset of treatment failure, and imputation the last observation prior to treatment failure for all subsequent observations - in addition to an analysis of all collected data based on randomized treatment assignment. A data set from the Asthma Clinical Research Network is used to demonstrate the methods.