title: Prospective and randomised public-health trial on neural network-assisted screening for cervical cancer in Finland: results of the first year.
abstract: Our objective was to evaluate the feasibility and relative validity of interactive neural network assisted screening (Papnet) in primary mass screening for cervical cancer as a public health policy (routine screening). A randomized, ongoing trial involved 152,969 invitees and 108,686 attendees in the organized mass screening in Finland in 1999. Drawing invitations from the population registry, women were randomized 2:1 at an individual level to have their smear analyzed either conventionally or with Papnet. The distribution of smears to different cytological categories, detection rates of dysplasias, in situ carcinomas and cancers were estimated with smears analyzed either conventionally (72,461) or by Papnet (36,225). A total of 108,686 smears were screened and 449 were histologically confirmed as dysplasias and carcinomas. The detection rates for histologically verified carcinoma in situ/severe dysplasia, moderate and mild dysplasias were 0.14%, 0.14% and 0.13% with conventional and 0.14%, 0.14% and 0.11% with Papnet, respectively. The detection rate of invasive cancer was 0.06 per thousand (n = 4) with conventional method and 0.08 per thousand (n = 3) with Papnet. None of the differences were statistically significant (p > 0.05). Papnet was able to identify 92.5% of healthy women (normal cytology), and the specificity of conventional smear was 92.9%. The positive predictive value (Pap Classes III-V) of Papnet was slightly but not significantly better (55% vs. 51%). Papnet screening was feasible as a part of routine screening and performed equally well compared to conventional one methods used in Finland. Organized mass screening was practiced very successfully in the last 38 years. We are going to continue the trial to study the potential trends in cervical cancer incidence in both study arms.
authors.affiliation: Department of Obstetrics and Gynaecology, Helsinki University Central Hospital, Finland. pekka.nieminen@hus.fi
authors.forename: Pekka
authors.initials: P
authors.lastname: Nieminen
authors.forename: Matti
authors.initials: M
authors.lastname: Hakama
authors.forename: Merja
authors.initials: M
authors.lastname: Viikki
authors.forename: Jussi
authors.initials: J
authors.lastname: Tarkkanen
authors.forename: Ahti
authors.initials: A
authors.lastname: Anttila
mesh_terms: D000328:Adult; D002278:Carcinoma in Situ / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted; D005260:Female; D005387:Finland / Q000453:epidemiology; D006801:Humans; D008403:Mass Screening / Q000379:methods* / Q000592:standards; D008875:Middle Aged; D009361:Neoplasm Invasiveness / Q000175:diagnosis*; D016571:Neural Networks, Computer; D011446:Prospective Studies; D011634:Public Health; D011786:Quality Control; D012680:Sensitivity and Specificity; D013997:Time Factors; D002578:Uterine Cervical Dysplasia / Q000175:diagnosis*; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis* / Q000382:microbiology / Q000821:virology; D014626:Vaginal Smears / Q000379:methods* / Q000592:standards