title: Negative cervical smears before CIN 3/carcinoma. Reevaluation with the PAPNET Testing System.
abstract: OBJECTIVE
  To test the effectiveness of the PAPNET testing system in identifying false negative smears, using archival cervical cytologic smears from women with histologically proven diagnoses of high grade lesions and carcinoma of the uterine cervix.
  
  
  METHODS
  Forty-six negative smears from women who developed a high grade cervical intraepithelial lesion (CIN 3) or carcinoma of the uterine cervix within three years were retrieved from the archives, plus 20 consecutive control smears for each case. The smears were analyzed with the PAPNET testing system, and the selected cells were reviewed by a cytotechnologist using a strict protocol.
  
  
  RESULTS
  With the PAPNET testing system, 9 of 46 (20%) smears were positive. Seven were reclassified as low grade and two reclassified as high grade squamous intraepithelial lesion (SIL). One of the 31 initially positive smears in the control group of 920 smears was not recognized as such. In the control group of 889 negative smears, 14 newly identified positive cases (1.6%) were detected, all low grade SIL.
  
  
  CONCLUSIONS
  The PAPNET testing system is a good tool for detecting false negative smears and, when used as an adjunct to conventional screening, can reduce the false negative rate.
authors.affiliation: Department of Pathology, Utrecht University, The Netherlands.
authors.forename: H
authors.initials: H
authors.lastname: Doornewaard
authors.forename: H
authors.initials: H
authors.lastname: van de Seijp
authors.forename: J M
authors.initials: JM
authors.lastname: Woudt
authors.forename: Y
authors.initials: Y
authors.lastname: van der Graaf
authors.forename: J G
authors.initials: JG
authors.lastname: van den Tweel
mesh_terms: D001331:Automation; D001706:Biopsy; D002294:Carcinoma, Squamous Cell / Q000175:diagnosis / Q000473:pathology*; D005188:False Negative Reactions; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation*; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation*; D008328:Man-Machine Systems; D008403:Mass Screening; D016571:Neural Networks, Computer; D015588:Observer Variation; D011786:Quality Control; D012189:Retrospective Studies; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis / Q000473:pathology*; D014626:Vaginal Smears / Q000295:instrumentation*; D014741:Video Recording; D002578:Uterine Cervical Dysplasia / Q000175:diagnosis / Q000473:pathology*