Addressing missing data in clinical trials

Ann Intern Med. 2011 Jan 18;154(2):113-7. doi: 10.7326/0003-4819-154-2-201101180-00010.


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 analyses, 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 likelihood that outcome data will be obtained at scheduled times of evaluation for all surviving patients who have not withdrawn consent. To meaningfully reduce missing data, it is important to recognize and address many factors that commonly lead to higher levels of missingness.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Clinical Protocols / standards
  • Clinical Trials as Topic / standards*
  • Clinical Trials as Topic / statistics & numerical data*
  • Data Interpretation, Statistical
  • Humans
  • Informed Consent / standards
  • Patient Dropouts
  • Reproducibility of Results
  • Research Design / standards