Efficiency of study designs in diagnostic randomized clinical trials

Abstract

From the patients' management perspective, a good diagnostic test should contribute to both reflecting the true disease status and improving clinical outcomes. The diagnostic randomized clinical trial is designed to combine both diagnostic tests and therapeutic interventions. Evaluation of diagnostic tests is carried out with therapeutic outcomes as the primary endpoint rather than test accuracy. We lay out the probability framework for evaluating such trials. We compare two commonly referred designs-the two-arm design and the paired design-in a formal statistical hypothesis testing setup and identify the causal connection between the two tests. The paired design is shown to be more efficient than the two-arm design. The efficiency gains vary depending on the discordant rates of test results. We derive sample size formulas for both binary and continuous endpoints. We derive estimation of important quantities under the paired design and also conduct simulation studies to verify the theoretical results. We illustrate the method with an example of designing a randomized study on preoperative staging of bladder cancer.