4.6 Article

Development of practical recommendations for diagnostic accuracy studies in low-prevalence situations

Journal

JOURNAL OF CLINICAL EPIDEMIOLOGY
Volume 114, Issue -, Pages 38-48

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jclinepi.2019.05.018

Keywords

Diagnostic accuracy studies; Low prevalence; Primary care

Funding

  1. Ter Meulen Grant of the Royal Netherlands Academy of Arts and Sciences
  2. National Institute for Health Research (NIHR) Community Healthcare Medtech and In Vitro Diagnostics Cooperative (MIC)
  3. NIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust
  4. University of Birmingham

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Objective: Low disease prevalence poses challenges for diagnostic accuracy studies because of the large sample sizes that are required to obtain sufficient precision. The aim is to collate and discuss designs of diagnostic accuracy studies suited for use in low-prevalence situations. Study Design and Setting: We conducted a literature search including backward citation tracking and expert consultation. Two reviewers independently selected studies on designs for estimating diagnostic accuracy in a low-prevalence situation. During a 1-day expert meeting, all designs were discussed and recommendations were formulated. Results: We identified six designs for diagnostic accuracy studies that are suitable in low-prevalence situations because they reduced the total sample size or the number of patients undergoing the index test or reference standard depending on which poses the highest burden. We described the advantages and limitations of these designs and evaluated efficiencies in sample sizes, risk of bias, and alignment with the clinical pathway for applicability in routine care. Conclusion: Choosing a study design for diagnostic accuracy studies in low-prevalence situations should depend on whether the aim is to limit the number of patients undergoing the index test or reference standard, and the risk of bias associated with a particular design type. (C) 2019 Elsevier Inc. All rights reserved.

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