title: PCR based high risk HPV testing is superior to neural network based screening for predicting incident CIN III in women with normal cytology and borderline changes.
abstract: OBJECTIVE
  To improve the accuracy of conventional cytology in cervical cancer screening, high risk human papillomavirus (HPV) testing and neural network based screening have been developed. This study assessed the power of both techniques to detect women at risk of developing incident CIN III; that is, CIN III detected during the follow up of women with normal cytology and borderline nuclear changes.
  
  
  METHODS
  A cohort of 2250 women, 34-54 years of age, who attended population based cervical cancer screening from 1988 to 1991 and had normal smears or borderline nuclear changes was followed. All smears were tested for high risk HPV and the smears were rescreened using neural network based screening. The value of neural network based screening for predicting incident CIN III during a mean follow up period of 6.4 years was compared with that of high risk HPV testing. In addition, morphological markers presumed to be related to HPV were correlated with HPV status.
  
  
  RESULTS
  Thirteen (0.6%) women had incident CIN III. Both high risk HPV positivity and abnormal cytology were associated with an increased risk for incident CIN III (odds ratio, 240 and 22, respectively) and high risk HPV positivity was associated with abnormal cytology. The sensitivity of high risk HPV testing for predicting incident CIN III was much higher than that of neural network based screening (92% and 46%, respectively). None of the morphological markers assessed, including koilocytosis, was correlated with high risk HPV status.
  
  
  CONCLUSIONS
  High risk HPV testing is superior to neural network based screening in identifying women at risk of developing CIN III. For women with normal cytology and borderline changes and a negative high risk HPV test, the screening interval can be considerably prolonged.
authors.affiliation: Department of Pathology, Academic Hospital Vrije Universiteit, Amsterdam, The Netherlands.
authors.forename: L
authors.initials: L
authors.lastname: Rozendaal
authors.forename: J
authors.initials: J
authors.lastname: Westerga
authors.forename: J C
authors.initials: JC
authors.lastname: van der Linden
authors.forename: J M
authors.initials: JM
authors.lastname: Walboomers
authors.forename: F J
authors.initials: FJ
authors.lastname: Voorhorst
authors.forename: E K
authors.initials: EK
authors.lastname: Risse
authors.forename: M E
authors.initials: ME
authors.lastname: Boon
authors.forename: C J
authors.initials: CJ
authors.lastname: Meijer
mesh_terms: D000328:Adult; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D016571:Neural Networks, Computer; D027383:Papillomaviridae / Q000302:isolation & purification*; D011237:Predictive Value of Tests; D012307:Risk Factors; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis* / Q000821:virology; D014626:Vaginal Smears; D002578:Uterine Cervical Dysplasia / Q000175:diagnosis* / Q000821:virology