Automated Rescreening of Pap Smears.

Abstract

The objective of this study was to determine effectiveness and cost of Papnet-assisted rescreening in identifying cervical abnormalities not identified by manual Pap smear rescreening methods. Papnet-assisted rescreening was performed on using 5478 Pap smears previously identified as "within normal limits" or "benign changes" on both initial screening and random rescreening. Cases in which a diagnostic change was considered were reviewed by a panel of three cytotechnologists and three pathologists to obtain a consensus diagnosis. Follow-up was attempted on all patients for whom this panel believed a diagnosis of "atypical squamous cells of undetermined significance," (ASCUS) "atypical glandular cells of undetermined significance," (AGUS) or "squamous intraepithelial neoplasia" was warranted. Papnet-assisted examination identified 5 cases of ASCUS and 1 case of AGUS which had not been previously diagnosed; no additional squamous intraepithelial lesions were identified in these smears; the patient with a diagnosis of AGUS on the smear was diagnosed as having a low-grade squamous intraepithelial lesion on follow-up smear.A cost of $8564-34084 (depending on the Papnet charge) for each additional ASCUS/AGUS diagnosis, and a cost of $25691 - 104410 is expected for each case of low grade SIL identified by Papnet-assisted rescreening and not by traditional manual rescreening.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1996
Accession Number
ADA332970

Entities

People

  • Timothy J. O'leary

Organizations

  • Armed Forces Institute of Pathology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Anti-Bacterial Agents
  • Biomedical Research
  • Cervical Cancers
  • Cost Effectiveness
  • Diseases And Disorders
  • Drug Therapy
  • Ear Diseases
  • Health Services
  • Materials
  • Medical Personnel
  • Military Personnel
  • Neoplasms
  • Nose Diseases
  • Therapy
  • United States

Fields of Study

  • Medicine

Readers

  • Computer Engineering
  • Oncology and Biomarker-Based Cancer Detection.