Less medical intervention after sharp demarcation of grade 1-2 cervical intraepithelial neoplasia smears by neural network screening

BACKGROUND. Neural network technology has been used for the daily screening of cervical smears in The Netherlands since 1992. The authors believe this method might have the potential to demarcate diagnoses of Grade 1-2 cervic al intraepithelial neoplasia (CIN 1-2). METHODS. Of 133,196 women who were screened between 1992-1995, there were 2 236 CIN 1-2 smears; 1128 of which were detected by means of neural network screening (NNS) (n = 83,404 women) and 1108 of which were diagnosed by conv entional screening (n = 49,792 women). Cytologic and clinical outcomes (fir st cytologic or histologic follow-up diagnosis) were retrieved for all the women in the study population (n = 1920). Stratification based on clinical outcome resulted in the cases being grouped as overdiagnosed, concordant, o r underdiagnosed. The smears were performed by general practitioners, where as the biopsies were obtained by gynecologists. RESULTS. The prevalence rate for CIN 1-2 was 1.15% (95% confidence interval [95% CI], 1.08-1.23%) for NNS and 1.92% (95% CI, 1.80-2.04%) for conventio nal diagnosis (P < 0.001). Concordance with histology was significantly hig her for NNS (53.9%; 95% CI, 50.7-57.0%) compared with conventional screenin g (29.2%; 95% CI, 26.4-32.2%). In addition, overdiagnosis was significantly lower for cases diagnosed by NNS (39.4%; 95% CI, 36.3-42.4%) compared with cases diagnosed by conventional screening (62.4%; 95% CI, 59.3-65.5%). CONCLUSIONS. Neural network-based screening can lead to fewer women being b urdened unnecessarily with a cytologic diagnosis of CIN 1-2 by resulting in a sharp demarcation in these diagnoses and a corresponding reduction in un necessary medical interventions. [See editorial on pages 171-172, this issu e.] Cancer (Cancer Cytopathol) 2001;93:173-178. (C) 2001 American Cancer So ciety.