Limiting the Problem of Missing Data Urged for Clinical Trials
Special report: analysis methods can not compensate for missing data, simple fixes ruled out
WEDNESDAY, Oct. 3 (HealthDay News) -- Missing data compromise inferences from clinical trials, and due to the problematic nature of compensation with analysis methods, the importance of avoiding missing data in clinical trials is paramount, according to a special report published in the Oct. 4 issue of the New England Journal of Medicine.
Roderick J. Little, Ph.D., from the University of Michigan in Ann Arbor, and colleagues summarized some of the main findings from the National Research Council report on how to address the problem of missing data from clinical trials.
The report primarily focused on phase 3 confirmatory clinical trials that assessed the safety and efficacy of drugs, biologic products, and some medical devices. The authors report that the issue of missing data is a serious problem which questions the scientific integrity of conclusions from clinical trials. Analysis methods cannot compensate for missing data and consequently an important objective should be to limit missing data. Specific aspects of trial design as well as components of clinical-trial conduct can limit the extent of missing data. Analysis methods based on plausible scientific assumptions should be used in studies with missing data, ruling out simple fixes such as imputation by the last observation carried forward.
"In summary, there is no easy fix for missing data at the analysis stage. Too many current analyses of clinical trials apply naive methods for missing-data adjustment that make unjustified assumptions," the authors write. "The key is to design and carry out the trial in a way that limits the problem of missing data."
Several authors disclosed financial ties to the pharmaceutical industry.