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Efficiency of study designs in diagnostic randomized clinical trials
Author(s) -
Lu Bo,
Gatsonis Constantine
Publication year - 2012
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5655
Subject(s) - sample size determination , randomized controlled trial , research design , clinical study design , statistical hypothesis testing , test (biology) , computer science , clinical endpoint , diagnostic test , medicine , clinical trial , statistics , medical physics , mathematics , surgery , pathology , paleontology , emergency medicine , biology
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. Copyright © 2012 John Wiley & Sons, Ltd.