Missing Data Imputation
SECONDARY
Missing values in part 1 were imputed for the primary and key secondary end points using a prespecified multiple imputation (a total of 100 imputed data sets) washout model. The washout model can be thought of as a modified control-based pattern–mixture model. This was used to explore the possibility of data missing not at random for patients who discontinued the study early. For patients who discontinued the study early in the inclisiran group, their missing values for day 150 were imputed under the assumption that their outcome would be similar to those in the placebo group with similar background characteristics. For patients in the placebo group, their missing values over all visits after early termination were imputed based on the missing at random assumption. Multiple imputation was used to account for uncertainty in the imputation process and results from the imputed data sets were combined using the Rubin method.