Study designs for comparative diagnostic test accuracy: A methodological review and classification scheme

Bada Yang, Maria Olsen, Yasaman Vali, Miranda W. Langendam, Yemisi Takwoingi, Christopher J. Hyde, Patrick M. M. Bossuyt, Mariska M. G. Leeflang

Research output: Contribution to journalReview articleAcademicpeer-review

19 Citations (Scopus)

Abstract

Objectives: (1) To identify and classify comparative diagnostic test accuracy (DTA) study designs; (2) to describe study design labels used by authors of comparative DTA studies. Methods: We performed a methodological review of 100 comparative DTA studies published between 2015 and 2017, randomly sampled from studies included in 238 comparative DTA systematic reviews indexed in MEDLINE in 2017. From each study report, we extracted six design elements characterizing participant flow and the labels used by authors. Results: We identified a total of 46 unique combinations of study design features in our sample, based on six design elements characterizing participant flow. We classified the studies into five study design categories based on how participants were allocated to receive each index test: ‘fully paired’ (n=79), ‘partially paired, random subset’ (n=0), ‘partially paired, nonrandom subset’ (n=2), ‘unpaired randomized’ (n=1) and ‘unpaired nonrandomized’ (n=3). The allocation method used in 15 studies was unclear. Sixty-one studies reported, in total, 29 unique study design labels but only four labels referred to specific design features of comparative studies. Conclusion: Our classification scheme can help systematic review authors define study eligibility criteria, assess risk of bias, and communicate the strength of the evidence. A standardized labelling scheme could be developed to facilitate communication of specific design features.
Original languageEnglish
Pages (from-to)128-138
Number of pages11
JournalJournal of Clinical Epidemiology
Volume138
DOIs
Publication statusPublished - 1 Oct 2021

Keywords

  • Bias
  • Comparative accuracy studies
  • Diagnostic accuracy
  • Study design
  • Test comparison

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