17 – Missing Data in Neuroscience Clinical Trials: Truth or Consequences
Choosing Estimands in Clinical Trials with Missing Data
Craig H. Mallinckrodt
Eli Lilly & CO, Lilly Corporate Center
Consensus exists that in preventing and treating missing data clear objectives should be defined along with the causal estimands, trial design and conduct should maximize adherence to the protocol specified interventions, and a sensible primary analysis should be paired with plausible sensitivity analyses. Two general categories of estimands are: effects of the drug as actually taken (effectiveness, de-facto) and effects of the drug if taken as directed (efficacy, de-jure). Examples are used to illustrate how maximizing adherence reduces sensitivity to missing data assumptions for de-jure estimands, but may also reduce generalizability of results for de-facto estimands if the methods used to maximize adherence in the trial are not feasible in clinical practice.