Addressing the Reality of Missing Data

Missing-Data-Clinical-Trials-thumb-220pxwiValid statistical interpretation of most clinical trials relies on results of statistical analyses which require randomized samples of data.

Usually, not all randomized patients contribute complete data to these analyses. Missing data can bias analysis results in unknown ways, thus, making interpretation of trials with missing data difficult.

The Atmosphere

The National Academy of Medicine recently assembled an expert panel on missing data in clinical trials. Read the panel's published report:


[fa icon="thumb-tack"]   The Prevention and Treatment of Missing Data in Clinical Trials

The panel's recommendations include two key principles:

  • (1) "careful design and conduct to limit the amount and impact of missing data, and
  • (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects.”

Our Team

Cytel Consulting's clinical trial statisticians have extensive knowledge and experience in clinical trial methodology. They understand when to limit missing data and when to deploy methods to deal with missing data issues in the analysis stage.

This includes, but is not limited to:

  • Single imputation, when appropriate
  • Multiple imputation techniques
  • Methods for assessing assumptions regarding missing data
  • Assessment of patterns of missingness
  • Sample size calculations accounting for missing data

Our Experience

Cytel has extensive experience designing and implementing better clinical trials in every conceivable therapeutic area. Our help has been instrumental to sponsor companies in oncology, cardio-vascular, CNS, gastro-intestinal, Diabetes, metabolic disorders, inflammation, skin, pain, psychiatry, rare/orphan diseases, and medical devices.