A Food and Drug Administration advisory committee raised missing data as a serious concern in their review of results from the ATLAS ACS 2 TIMI 51 study, a large clinical trial that assessed rivaroxaban for its ability to reduce the risk of cardiovascular death, myocardial infarction or stroke in patients with acute coronary syndrome (ACS). This case study describes a variety of measures that were taken to address concerns about the missing data.
A range of analyses are described to assess the potential impact of missing data on conclusions. In particular, measures of the amount of missing data are discussed, and the fraction of missing information from multiple imputation is proposed as an alternative measure. The impact of deviations from ignorable censoring is assessed by differentially increasing the hazard of the primary outcome in the treatment groups and multiply imputing events between drop-out and the end of the study. Interestingly, the choice of primary estimand -- Intention to Treat or Modified Intention to Treat -- had a major impact on the missing data analysis. (Joint work with Julia Wang and Xiang Sun)
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