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Published on: September 20, 2019
The methods for handling missing data in clinical trials influence sample size requirements
Guy-Robert Auleley1, Bruno Giraudeau, Gabriel Baron
1Université Paris V-René Descartes, Faculté de Médecine Cochin Port-Royal and Clinique de Rhumatologie, Hôpital Cochin, AP-HP, Paris, France.
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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