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LECTURE 19 2011 - Missing Data in Clinical Trials Jims...

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Missing Data in Clinical Trials
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Jim’s Latest Venture A Gourmet Health Food Spa
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Weight Loss Trial Results No. randomized 100 100 Weight change -15.0 -30.0 (12 months) Weight Watchers Jim’s Gourmet Spa Jim is very happy!
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More Trial Results No. seen at 12 76/100 13/100 months Lost to Follow-up (%) 24% 87% Weight Watchers Jim’s Gourmet Spa
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Threats to the Interpretation of Clinical Trials Inadequately powered studies Surrogate markers and short follow-up Poor follow-up (missing data) Absence of pre-specified monitoring plans
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Key Points Advantages of randomization are threatened when major outcomes are missing – no longer comparing like with like on average. Missing data can lead to biased estimates of treatment differences. Models for handling missing data involve unverifiable assumptions since reasons for missing data may not be known. Therefore, focus must be on preventing missing data (losses).
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References National Research Council (2010). The prevention and treatment of missing data in clinical trials. Panel on Handling Missing Data in Clinical Trials. Committee on National Statistics. The National Academies Press Wood AM et al. Are missing outcome data adequately handled? A review of published randomized controlled trials in major medical journals. Clin Trials 2004; 1:368-376.n
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Missing Data (definition) An outcome that is meaningful for analysis that was not collected. A participant who cannot be followed for a meaningful outcome is considered lost to follow-up for that outcome.
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Reporting Missing Data in Clinical Trials 66% of 519 trials published in December 2000 did not report how they handled missing data. Of 71 trials published by the BMJ, JAMA, Lancet or N Engl J Med between July and December in 2001, 89% had partly missing outcome data. In 34 trials with repeated outcome measurements, 50% performed complete case analysis Only 21% reported sensitivity analysis. Lancet 2005 365: 1159-1162 and Clin Trials 2004; 1:368-376.
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In order to carry out a proper intention-to-treat analysis all patients must be followed Intention-to-treat - an analysis which includes all randomized patients in the groups to which they were randomly assigned, regardless of their compliance with the entry criteria, regardless of the treatment they actually received, and regardless of subsequent withdrawal from treatment or deviation from protocol. Def: Fisher L, et al., 1990, in Peace et al. Statistical Issues in Drug Development , Mercel Dekker.
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SMART Study Design Drug Conservation (DC) Strategy [Stop or defer ART until CD4+ < 250; then episodic ART based on CD4+ cell count to increase counts to > 350] Virologic Suppression (VS) Strategy [Continuous ART use] Participants with CD4 count > 350 n = 2720 n = 2752 N Engl J Med 2006
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Primary Endpoint Findings of SMART DC AIDS/death No AIDS/death 3000 VS 3000 6000 5090 910 What does “no” mean?
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