Choice of Estimand and Analysis Methods in Diabetes Trials with Rescue Medication

• Activity Number: 699
• Type: Contributed
• Date/Time: Thursday, August 13, 2015 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Mouna Akacha* and Bjoern Holzhauer and Georgina Bermann
• Companies: Novartis and Novartis Pharma AG and Novartis Pharma AG
• Keywords: Estimand ; Rescue medication ; Deterministic missing at random ; Multiple Imputation ; Analyzing HbA1c

Abstract

The analysis of clinical trials aiming to show symptomatic benefits is often complicated by the need for rescue medication when the disease state of patients worsens. In diabetes trials, patients with markers of glycemic control exceeding certain thresholds receive rescue medications. This may mask the difference between two treatment groups, because it will occur more often in less effective treatment groups. Traditionally, the last pre-rescue value was carried forward and analyzed. The deficits of such single imputation approaches are increasingly recognized. We discuss alternative approaches and evaluate them through a simulation study. When the estimand of interest is the effect attributable to the treatments initially assigned at randomization, then one may treat data after intake of rescue as deterministically 'missing' at random. An imputation of the resulting missing values is then possible, but one needs to jointly impute all markers that can lead to the initiation of rescue medication. An alternative for hypothesis testing - but not estimation - is a rank test with "requiring rescue medication" ranked worst and non-rescued patients ranked according to final visit values.