National Academies Press: OpenBook

The Prevention and Treatment of Missing Data in Clinical Trials (2010)

Chapter: Committee on National Statistics

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Suggested Citation:"Committee on National Statistics." National Research Council. 2010. The Prevention and Treatment of Missing Data in Clinical Trials. Washington, DC: The National Academies Press. doi: 10.17226/12955.
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COMMITTEE ON NATIONAL STATISTICS

The Committee on National Statistics (CNSTAT) was established in 1972 at the National Academies to improve the statistical methods and information on which public policy decisions are based. The committee carries out studies, workshops, and other activities to foster better measures and fuller understanding of the economy, the environment, public health, crime education, immigration, poverty, welfare, and other public policy issues. It also evaluates ongoing statistical programs and tracks the statistical policy and coordinating activities of the federal government, serving a unique role at the intersection of statistics and public policy. The committee’s work is supported by a consortium of federal agencies through a National Science Foundation grant.

Suggested Citation:"Committee on National Statistics." National Research Council. 2010. The Prevention and Treatment of Missing Data in Clinical Trials. Washington, DC: The National Academies Press. doi: 10.17226/12955.
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Suggested Citation:"Committee on National Statistics." National Research Council. 2010. The Prevention and Treatment of Missing Data in Clinical Trials. Washington, DC: The National Academies Press. doi: 10.17226/12955.
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Page 145
Suggested Citation:"Committee on National Statistics." National Research Council. 2010. The Prevention and Treatment of Missing Data in Clinical Trials. Washington, DC: The National Academies Press. doi: 10.17226/12955.
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Page 146
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Randomized clinical trials are the primary tool for evaluating new medical interventions. 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, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups.

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 participants discontinue 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 Prevention and Treatment of Missing Data in Clinical Trials 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 missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.

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