Addressing missing data in clinical trials

The reliability and interpretability of results from clinical trials can be substantially reduced by missing data. Frequently used approaches to address these concerns, such as upward adjustments in sample sizes or simplistic methods for handling missing data, including last-observation-carried-forward, complete-case, or worst-case anal-yses, are usually inadequate. Although rational imputation methods may be useful to treat missingness after it has occurred, these methods depend on untestable assumptions. Thus, the preferred and often only satisfactory approach to addressing missing data is to prevent it. Procedures should be in place to maximize the like-lihood that outcome data will be obtained at scheduled times of evaluation for all surviving patients who have not withdrawn con-sent. To meaningfully reduce missing data, it is important to rec-ognize and address many factors that commonly lead to higher levels of missingness. Ann Intern Med. 2011;154:113-117. www.annals.or