Determining qualitative effect size ratings using a likelihood ratio scatter matrix in diagnostic test accuracy systematic reviews

Matthew L. Rubinstein, Colleen S. Kraft, J. Scott Parrott

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Background Diagnostic test accuracy (DTA) systematic reviews (SRs) characterize a test's potential for diagnostic quality and safety. However, interpreting DTA measures in the context of SRs is challenging. Further, some evidence grading methods (e.g. Centers for Disease Control and Prevention, Division of Laboratory Systems Laboratory Medicine Best Practices method) require determination of qualitative effect size ratings as a contributor to practice recommendations. This paper describes a recently developed effect size rating approach for assessing a DTA evidence base. Methods A likelihood ratio scatter matrix will plot positive and negative likelihood ratio pairings for DTA studies. Pairings are graphed as single point estimates with confidence intervals, positioned in one of four quadrants derived from established thresholds for test clinical validity. These quadrants support defensible judgments on "substantial", "moderate", or "minimal" effect size ratings for each plotted study. The approach is flexible in relation to a priori determinations of the relative clinical importance of false positive and false negative test results. Results and conclusions This qualitative effect size rating approach was operationalized in a recent SR that assessed effectiveness of test practices for the diagnosis of Clostridium difficile. Relevance of this approach to other methods of grading evidence, and efforts to measure diagnostic quality and safety are described. Limitations of the approach arise from understanding that a diagnostic test is not an isolated element in the diagnostic process, but provides information in clinical context towards diagnostic quality and safety.

Original languageEnglish (US)
Pages (from-to)205-214
Number of pages10
JournalDiagnosis (Berlin, Germany)
Volume5
Issue number4
DOIs
StatePublished - Nov 27 2018

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All Science Journal Classification (ASJC) codes

  • Medicine(all)

Keywords

  • clinical utility
  • clinical validity
  • diagnostic accuracy
  • diagnostic quality
  • laboratory diagnosis
  • laboratory medicine
  • likelihood ratio
  • systematic review

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