Adaptive trial designs in diagnostic accuracy research

Antonia Zapf*, Maria Stark, Oke Gerke, Christoph Ehret, Norbert Benda, Patrick Bossuyt, Jon Deeks, Johannes Reitsma, Todd Alonzo, Tim Friede

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

The aim of diagnostic accuracy studies is to evaluate how accurately a diagnostic test can distinguish diseased from nondiseased individuals. Depending on the research question, different study designs and accuracy measures are appropriate. As the prior knowledge in the planning phase is often very limited, modifications of design aspects such as the sample size during the ongoing trial could increase the efficiency of diagnostic trials. In intervention studies, group sequential and adaptive designs are well established. Such designs are characterized by preplanned interim analyses, giving the opportunity to stop early for efficacy or futility or to modify elements of the study design. In contrast, in diagnostic accuracy studies, such flexible designs are less common, even if they are as important as for intervention studies. However, diagnostic accuracy studies have specific features, which may require adaptations of the statistical methods or may lead to specific advantages or limitations of sequential and adaptive designs. In this article, we summarize the current status of methodological research and applications of flexible designs in diagnostic accuracy research. Furthermore, we indicate and advocate future development of adaptive design methodology and their use in diagnostic accuracy trials from an interdisciplinary viewpoint. The term “interdisciplinary viewpoint” describes the collaboration of experts of the academic and nonacademic research.

Original languageEnglish
Pages (from-to)591-601
Number of pages11
JournalStatistics in Medicine
Volume39
Issue number5
DOIs
Publication statusPublished - 28 Feb 2020

Keywords

  • adaptive designs
  • diagnostic accuracy
  • diagnostic studies
  • group sequential designs
  • sample size reestimation

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