"How Are Missing Data Addressed? One of the challenges of all trials is how to deal with missing data. Subjects often drop out of a study before the primary endpoint date is reached, fail to show up for appointments, or change their mind and refuse to undergo the scheduled endoscopy at the final evaluation.
There are 2 common methods for handling missing data. The most rigorous method is to consider any subject who has missing data as one who would have failed to meet the endpoint. This method is often called nonresponder imputation. It lowers success rates (and placebo rates), thus making results look less impressive.
Another approach is to use the last observation at which the subject was measured in place of the missing data; this approach is especially common in maintenance studies with repeated measurements. Called the last-observation-carried-forward approach, this method is reasonable, but it may inflate the success rates of both the primary intervention and the control arm, as a common reason patients do not return for visits is that they feel the treatment does not provide a clinical benefit.
Finally, a third approach for addressing missing data is called imputation, in which other data are used to estimate what the missing data would have been. This approach is generally considered appealing but questionable, as it is impossible to check the accuracy of these estimates.
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