title: Bias, underestimation of risk, and loss of statistical power in patient-level analyses of lesion detection.
abstract: OBJECTIVE
  Sensitivity and the false positive rate are usually defined with the patient as the unit of observation, i.e., the diagnostic test detects or does not detect disease in a patient. For tests designed to find and diagnose lesions, e.g., lung nodules, the usual definitions of sensitivity and specificity may be misleading. In this paper we describe and compare five measures of accuracy of lesion detection.
  
  
  METHODS
  The five levels of evaluation considered were patient level without localization, patient level with localization, region of interest (ROI) level without localization, ROI level with localization, and lesion level.
  
  
  RESULTS
  We found that estimators of sensitivity that do not require the reader to correctly locate the lesion overstate sensitivity. Patient-level estimators of sensitivity can be misleading when there is more than one lesion per patient and they reduce study power. Patient-level estimators of the false positive rate can conceal important differences between techniques. Referring clinicians rely on a test's reported accuracy to both choose the appropriate test and plan management for their patients. If reported sensitivity is overstated, the clinician could choose the test for disease screening, and have false confidence that a negative test represents the true absence of lesions. Similarly, the lower false positive rate associated with patient-level estimators can mislead clinicians about the diagnostic value of the test and consequently that a positive finding is real.
  
  
  CONCLUSIONS
  We present clear recommendations for studies assessing and comparing the accuracy of tests tasked with the detection and interpretation of lesions...
authors.affiliation: Department of Quantitative Health Sciences/JJN3 and the Imaging Institute, Cleveland Clinic Foundation, 9500 Euclid Ave, Cleveland, OH 44195, USA. obuchon@ccf.org
authors.forename: Nancy A
authors.initials: NA
authors.lastname: Obuchowski
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Mazzone
authors.forename: Abraham H
authors.initials: AH
authors.lastname: Dachman
mesh_terms: D000465:Algorithms; D015982:Bias; D003627:Data Interpretation, Statistical; D003952:Diagnostic Imaging / Q000706:statistics & numerical data*; D005188:False Negative Reactions; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D015994:Incidence; D009369:Neoplasms / Q000175:diagnosis* / Q000453:epidemiology*; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012680:Sensitivity and Specificity