title: Correctly using sensitivity, specificity, and predictive values in clinical practice: how to avoid three common pitfalls.
abstract: OBJECTIVE
  Radiology is the specialty of imaging-based diagnostic tests. Understanding the science behind evaluating diagnostic test performance is essential for radiologists because we provide care to patients and interact with our colleagues.
  
  
  CONCLUSIONS
  Here, we review the key terminology used and common pitfalls encountered in the literature and in day-to-day discussions of diagnostic test performance.
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Ave, M-391, Box 0628, San Francisco, CA 94143-0628, USA. david.naeger@radiology.ucsf.edu
authors.forename: David M
authors.initials: DM
authors.lastname: Naeger
authors.forename: Maureen P
authors.initials: MP
authors.lastname: Kohi
authors.forename: Emily M
authors.initials: EM
authors.lastname: Webb
authors.forename: Andrew
authors.initials: A
authors.lastname: Phelps
authors.forename: Karen G
authors.initials: KG
authors.lastname: Ordovas
authors.forename: Thomas B
authors.initials: TB
authors.lastname: Newman
mesh_terms: D016022:Case-Control Studies; D003952:Diagnostic Imaging / Q000592:standards*; D005188:False Negative Reactions; D005189:False Positive Reactions; D006801:Humans; D011237:Predictive Value of Tests; D011871:Radiology / Q000592:standards*; D012107:Research Design; D018570:Risk Assessment; D012680:Sensitivity and Specificity