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The methods for handling missing data in clinical trials influence sample size requirements.

Guy-Robert Auleley·Bruno Giraudeau·Gabriel Baron·Jean-Francis Maillefert·Maxime Dougados·Philippe Ravaud
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Abstract

OBJECTIVE: Results of studies estimating osteoarthritis progression may be affected by missing values. In clinical trials assessing disease-modifying osteoarthritis drugs, sample sizes should be calculated using close estimates of outcome variables. STUDY DESIGN AND SETTING: Supposing a two-parallel group design in hip osteoarthritis clinical trials, we estimated sample sizes using the joint space width (JSW), number of patients with JSW progression >0.5 mm (JSN), time to total hip arthroplasty (THA), and time to JSN or THA using several approaches to deal with missing data. RESULTS: Three-year clinical trials testing a treatment effect of 50%, with a power of 80%, could require sample sizes of 121 patients for JSW, 57 for JS progression using multiple imputation for handling missing values; 200 for THA; and 47 for JSN or THA. These numbers vary greatly depending on the approach chosen for handling missing data. CONCLUSIONS: These results can help investigators plan clinical trials to select the primary outcome and a priori specify the way missing data will be handled.

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AgedAntirheumatic AgentsData Interpretation, StatisticalDisease ProgressionFemaleHumansMaleMiddle AgedMulticenter Studies as TopicOsteoarthritis, HipRandomized Controlled Trials as TopicResearch DesignSample SizeTreatment OutcomeJournal Article

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Guy-Robert Auleley, Bruno Giraudeau, Gabriel Baron, Jean-Francis Maillefert, Maxime Dougados, Philippe Ravaud. 2004. The methods for handling missing data in clinical trials influence sample size requirements.. https://doi.org/10.1016/j.jclinepi.2003.09.012

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