Prevention and Treatment of Missing Data in Clinical Trials

摘要

Randomized clinical trials are the primary tool for evaluating new medical interventions. More than $7 billion is spent every year in evaluating drugs, devices, and biologics. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, a substantial percentage of the measurements of the outcome or outcomes of interest is often missing. This missingness reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. In light of this problem, the Panel on the Handling of Missing Data in Clinical Trials was created at the request of the U.S. Food and Drug Administration (FDA) to prepare a report with recommendations that would be useful for FDAs development of a guidance for clinical trials on appropriate study designs and follow-up methods to reduce missing data and appropriate statistical methods to address missing data for analysis of results. The panels work focused primarily on Phase III confirmatory clinical trials that are the basis for the approval of drugs and devices. For these trials, the bar of scientific rigor is set high; however, many of our recommendations are applicable to all randomized trials. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participantsdiscontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The panel concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (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 miss-ing data underlying estimates of treatment effects. In addition to the highest priority recommendations here, in the body of the report the panel offers additional recommendations on the conduct of clinical trials and techniques for analysis of trial data.