The Prevention and Treatment of Missing Data in Clinical Trials (2010) / Chapter Skim
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1 Introduction and Background
1 Introduction and Background
Pages 7-20
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From page 7... ...
. At the request of FDA, the National Research Council convened the Panel on the Handling of Missing Data in Clinical Trials, under the Committee on National Statistics, to prepare "a report with recommendations that would be useful for FDA's 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 charge further specified:
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Such guidance would usefully distinguish between types of clinical trials and missingness situations. For example, it could be useful to provide guidance on such questions as: (1)
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Some of the aspects of clinical trials that can affect the amount of missing data include whether data collection continues for participants who discontinue study treatment, the use of outcomes that are at risk of being undefined for some patients, the rate of attrition, and the use of composite outcomes. Missing Data Due to Discontinuation of Study Treatment It is common for some participants in a clinical trial to discontinue study treatment because of adverse events or lack of efficacy.
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Such knowledge could be related to whether the participant discontinues treatment. Use of Outcomes That Are at Risk of Being Undefined for Some Patients Some clinical trials use outcomes that may not be ascertainable for all participants.
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Two general lines of attack have been employed to address the problem of missing values in clinical trials. The first is simply to design and carry out the clinical trial in a manner that limits the amount of missing data.
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Our goal is to improve the quality of estimates of treatment effects and their associated estimates of uncertainty in randomized clinical trials.1 THREE KINDS OF TRIALS AS CASE STUDIES In this report, we use three types of trials to illustrate how clinical trial design and other aspects of trial conduct can be modified to limit the impact of missing data on regulatory decisions; trials for chronic pain, trials for the treatment of HIV, and trials for mechanical circulatory devices for severe symptomatic heart failure. These examples are chosen both because they are important in their own right and because they share many characteristics with a wide variety of other types of clinical trials.
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Patients who stop study treatment usually switch to a proven (approved) effective therapy, and the trial sponsors typically stop collecting pain response data on those patients who discontinue study treatment.
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Trials for Mechanical Circulatory Devices for Severe Symptomatic Heart Failure For patients with advanced heart failure, heart implantable left ventricular assist devices (LVADs) have been shown to be effective when used as a bridge to heart transplants.2 Furthermore, because many patients are not eligible candidates for transplantation, the use of LVADs as destination therapy has been shown to be effective, and its use is increasing.
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As a case study, we consider a superiority design trial in which the goal is to determine whether an LVAD is superior to optimal medical management for prolonging patients' survival and optimizing their health status. In many device trials, blinding of patients and investigators is not possible.
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CLINICAL TRIALS IN A REGULATORY SETTING This report focuses primarily on issues concerning the treatment of missing data in randomized controlled clinical trials that are intended to support regulatory applications for drugs, medical devices, and biologics. Several aspects of the regulatory setting have particular bearing on how missing data issues are handled.
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As there are many potential approaches to handling missing data, pretrial specification of an approach to be used in the primary analysis is particularly important to help ensure predictability. However, because the assumptions underlying any one approach to handling missing data may be invalid, prospective definition of sensitivity analyses with different underlying assumptions will help assess the robustness of the conclusions and help support effective decision making.
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3. Statistical Principles for Clinical Trials; Step : Note for Guidance on Statistical Principles for Clinical Trials, from the European Medicines Evaluation Agency (EMEA)
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More particularly, the focus of this report is the treatment of missing data in confirmatory randomized controlled trials of drugs, devices, and biologics, although, as noted above, we believe the material is also relevant for other types of clinical trials, including those carried out by academics and NIHfunded trials, and more generally for various biostatistical investigations. We note that no further mention is made in this report about methods for the treatment of missing data for biologics because they raise no issues that are not already raised in drug trials.
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Chapters 4 and 5 describe methods of analysis for data from clinical trials in which some of the values for the outcome or outcomes of interest are missing: Chapter 4 considers drawing inferences when there are missing data, and Chapter 5 considers sensitivity analyses. The final chapter presents the panel's recommendations.
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