The design and conduct of clinical trials to limit missing data

• Published in: Statistics in medicine Vol. 31; no. 28; pp. 3433 - 3443
• Main Authors: Little, R. J., Cohen, M. L., Dickersin, K., Emerson, S. S., Farrar, J. T., Neaton, J. D., Shih, W., Siegel, J. P., Stern, H.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 10.12.2012; Wiley Subscription Services, Inc
• Subjects: Assisted Circulation - instrumentation; Assisted Circulation - methods; Bias; Causality; Chronic Pain - therapy; clinical trial ethics; Clinical trials; Comparative analysis; Credibility; Data Collection - methods; Data Interpretation, Statistical; dropouts; Guidelines as Topic; HIV Infections - drug therapy; HIV Infections - virology; Humans; incomplete data; Informed Consent - standards; Motivation; Outcome Assessment, Health Care - methods; Outcome Assessment, Health Care - standards; Outcome Assessment, Health Care - statistics & numerical data; Patient Dropouts - psychology; Patient Dropouts - statistics & numerical data; Randomized Controlled Trials as Topic - methods; Randomized Controlled Trials as Topic - standards; Randomized Controlled Trials as Topic - statistics & numerical data; randomized withdrawal; Research Design; Research Personnel - education; Research Personnel - standards; Research Subjects; run-in period
• ISSN: 0277-6715; 1097-0258; 1097-0258
• DOI: 10.1002/sim.5519

This article summarizes recommendations on the design and conduct of clinical trials of a National Research Council study on missing data in clinical trials. Key findings of the study are that (a) substantial missing data is a serious problem that undermines the scientific credibility of causal conclusions from clinical trials; (b) the assumption that analysis methods can compensate for substantial missing data is not justified; hence (c) clinical trial design, including the choice of key causal estimands, the target population, and the length of the study, should include limiting missing data as one of its goals; (d) missing‐data procedures should be discussed explicitly in the clinical trial protocol; (e) clinical trial conduct should take steps to limit the extent of missing data; (f) there is no universal method for handling missing data in the analysis of clinical trials – methods should be justified on the plausibility of the underlying scientific assumptions; and (g) when alternative assumptions are plausible, sensitivity analysis should be conducted to assess robustness of findings to these alternatives. This article focuses on the panel's recommendations on the design and conduct of clinical trials to limit missing data. A companion paper addresses the panel's findings on analysis methods. Copyright © 2012 John Wiley & Sons, Ltd.