Improving the Efficiency of Randomized Trials: The DYNAGITO Example

A traditional principle of the randomized controlled trial is that the p-value comparing treatment groups should be computed from the simple crude data. This assumes that the size of the study is sufficiently large for an accurate and precise estimation of the difference between groups. There are situations where the accuracy and precision of the study can be improved by statistical adjustment for baseline covariates, including when the outcome is continuous and available at baseline. The European Medicines Agency (EMA) and the Food and Drug Administration (FDA) recommend covariate adjustment in trials as a tool to improve the efficiency of the analysis and to avoid conditional bias from chance covariate imbalance. The recent DYNAGITO randomized controlled trial compared the effectiveness of the single inhaler tiotropium-olodaterol combination for the treatment of COPD with tiotropium alone in reducing the rate of exacerbations over 52 weeks. The pre-specified crude analysis produced a rate ratio of 0.93 (p-value > 0.01, not significant) comparing the tiotropium-olodaterol combination with tiotropium alone. However, a sensitivity analysis adjusted for the baseline rate of exacerbations and other factors produced a rate ratio of 0.89 (p-value 0.001, significant). The DYNAGITO trial is an example where statistical adjustment was justified but not used. Future trials of COPD therapy could be designed more efficiently, be made less costly, while improving the accuracy and precision of their data and the resulting conclusions.