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Potentially missing data are considerably more frequent than definitely missing data: a methodological survey of 638
Lara A Kahale1, Batoul Diab1, Assem M Khamis1
1Clinical Epidemiology Unit, American University of Beirut, Beirut, Lebanon.
Journal of Clinical Epidemiology
|October 10, 2018
Summary
Missing data in randomized controlled trials (RCTs) is common, with potentially missing data being more frequent than definitely missing data. Improved reporting standards are needed for risk of bias assessment in clinical research.
Area of Science:
- Clinical Trials
- Biostatistics
- Evidence-Based Medicine
Background:
- Missing outcome data is crucial for risk of bias assessment in randomized controlled trials (RCTs).
- Reporting clarity on participant follow-up and handling of missing data in RCTs is often insufficient.
- Authors' methods for addressing missing data and assessing bias are not consistently described.
Purpose of the Study:
- To evaluate how RCT authors report on participant categories with potential missing data.
- To analyze the methods RCT authors use to handle missing data in their analyses.
- To determine how RCT authors assess the risk of bias associated with missing data.
Main Methods:
- A survey of 400 eligible RCT reports from 100 clinical intervention systematic reviews was conducted.
- Eleven reviewers independently extracted data on 19 predefined categories of participants with potential missing data.
- Participants were classified based on follow-up status: explicitly followed-up, explicitly not followed-up, or unclear follow-up.
Main Results:
- 63% of RCTs reported on predefined categories of participants with missing data.
- Median percentages for explicitly not followed-up and unclear follow-up were 5.8% and 9.7%, respectively.
- Complete case analysis was common (54%) when participants were explicitly not followed-up; most RCTs (99%, 95%) did not report outcome-specific missing data or bias assessment methods.
Conclusions:
- Potentially missing data is more prevalent than definitely missing data in RCTs.
- Current reporting practices for missing data in RCTs are inadequate.
- Development and adherence to explicit reporting standards by authors and editors are necessary for accurate risk of bias assessment.
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