title: The diagnostic value of computer-assisted primary cervical smear screening: a longitudinal cohort study.
abstract: OBJECTIVE
  To assess computer-assisted (neural network based) cervical smear screening as a primary tool for the early detection of cervical dysplasia.
  
  
  METHODS
  Longitudinal cohort study.
  
  
  METHODS
  Cytology laboratory reviewing cervical smears taken by general practitioners in a mass screening program in the Netherlands.
  
  
  METHODS
  846 women who developed (pre-)neoplasia of the cervix in the seven years after the baseline smear, and 5217 controls.
  
  
  METHODS
  Cervical smears were evaluated both by conventional light microscopy and with use of the PAPNET Testing System by the same cytotechnologists.
  
  
  METHODS
  Seven year histological and cytological follow-up results were obtained for all women from a nation-wide pathology database.
  
  
  RESULTS
  Conventional screening diagnosed dysplasia or carcinoma in the baseline smears of 458 (54.1%) of the 846 women who were diagnosed with (pre-)neoplasia during follow-up, whereas computer-assisted PAPNET analysis detected such lesions in 462 (54.6%) of these women. In the control population of 5217 (86.0%) women, in whom follow-up revealed no cervical dysplasia, conventional screening gave false positive results in 210 (4.0%) and computer-assisted PAPNET analysis gave false positive results in 207 (4.0%) smears. The areas under the receiver operation curves (AUC) were 80% (95% confidence interval, 78 to 82%) and 79% (95% confidence interval, 77 to 81%) for conventional and PAPNET-assisted screening, respectively.
  
  
  CONCLUSIONS
  The PAPNET Testing System has similar diagnostic value as the conventional screening of Pap smears when used for primary screening.
authors.affiliation: Department of Pathology, University Medical Center Utrecht, The Netherlands. h.doornewaard@lab.azu.nl
authors.forename: H
authors.initials: H
authors.lastname: Doornewaard
authors.forename: Y T
authors.initials: YT
authors.lastname: van der Schouw
authors.forename: Y
authors.initials: Y
authors.lastname: van der Graaf
authors.forename: A B
authors.initials: AB
authors.lastname: Bos
authors.forename: J D
authors.initials: JD
authors.lastname: Habbema
authors.forename: J G
authors.initials: JG
authors.lastname: van den Tweel
mesh_terms: D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008403:Mass Screening / Q000379:methods*; D016571:Neural Networks, Computer; D065006:Papanicolaou Test; D011237:Predictive Value of Tests; D012680:Sensitivity and Specificity; D002578:Uterine Cervical Dysplasia / Q000175:diagnosis*; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis; D014626:Vaginal Smears