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Analyzing clinical trial outcomes based on incomplete daily diary reports
Neal Thomas1, Ofer Harel2, Roderick J A Little3
1Pfizer, Inc, Groton, CT, U.S.A.
Statistics in Medicine
|February 19, 2016
Summary
This study highlights how missing data significantly impacts insomnia drug trial analysis. Multiple imputation methods improve accuracy for daily diary data, crucial for reliable treatment effect estimation.
Area of Science:
- Biostatistics
- Clinical Trial Methodology
- Pharmaceutical Research
Background:
- Daily diary data in clinical trials often exhibit missing values, complicating analysis.
- Standard methods may overlook complex missing data patterns, potentially biasing results.
- Accurate assessment of treatment effects requires robust handling of missing data.
Purpose of the Study:
- To assess the impact of missing data on the analysis of daily diary data in an insomnia drug trial.
- To evaluate the effectiveness of multiple imputation for handling missing daily diary values.
- To compare standard analysis with methods accounting for complex missing data patterns.
Main Methods:
- A case study analyzing daily diary data from an insomnia drug trial.
- Comparison of standard analysis (ignoring missing values) with multiple imputation.
- Application of longitudinal and landmark analysis models.
- Sensitivity analyses using pattern mixture models to assess missing at random assumption.
Main Results:
- Missing data patterns in daily diaries can be complex and obscure.
- Multiple imputation successfully created complete datasets for analysis.
- Landmark analysis on imputed data provided more reliable treatment effect estimates.
- Sensitivity analyses confirmed the robustness of findings under different assumptions.
Conclusions:
- Handling missing daily diary data using multiple imputation is essential for accurate insomnia drug trial analysis.
- Graphical displays and computational methods aid in understanding and managing missing data.
- Robust statistical approaches are vital for reliable clinical trial outcomes.
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