title: Studies reporting ROC curves of diagnostic and prediction data can be incorporated into meta-analyses using corresponding odds ratios.
abstract: OBJECTIVE
  To develop an approach by which studies describing the accuracy of diagnostic tests or clinical predictions can be combined in a meta-analysis, even though studies may report their results using different summary measures.
  
  
  METHODS
  A method is proposed to allow algebraic and numerical conversion of values of the Receiver Operating Characteristic Area Under the Curve (AUC) summary statistic into corresponding odds ratios (OR). A similar conversion is demonstrated for the standard errors (SEs) of these summary statistics.
  
  
  RESULTS
  The conversion of the AUC values into OR values was achieved using a logit-threshold model. The delta method was used to convert the associated SEs. An example concerning predictions of mortality in the intensive care unit illustrates the calculations.
  
  
  CONCLUSIONS
  This paper provides an accessible method that permits the meta-analyst to overcome some of the difficulties implied by incomplete and inconsistent reporting of research studies in this area. It allows all studies to be included on the same metric, which in turn more easily permits exploration of issues such as heterogeneity. The method can readily be used for meta-analyses of diagnostic or screening tests, or for prediction data.
authors.affiliation: Department of Clinical Epidemiology and Biostatistics, McMaster University, 1200 Main Street West, HSC-2C16, Hamilton, Ontario, Canada L8N 3Z5. walter@mcmaster.ca
authors.forename: S D
authors.initials: SD
authors.lastname: Walter
authors.forename: T
authors.initials: T
authors.lastname: Sinuff
mesh_terms: D019540:Area Under Curve; D016638:Critical Illness / Q000401:mortality; D003627:Data Interpretation, Statistical; D006801:Humans; D008433:Mathematics; D015201:Meta-Analysis as Topic; D016017:Odds Ratio; D011237:Predictive Value of Tests; D012372:ROC Curve