Cost-benefit analysis of selective screening criteria for Chlamydia trachomatis infection in women attending Colorado family planning clinics

Sex Transm Dis. Jan-Feb 1992;19(1):47-53. doi: 10.1097/00007435-199201000-00010.

Abstract

Women attending family planning clinics in Colorado during 1988 were screened for Chlamydia trachomatis infection by enzyme immunoassay (EIA, Chlamydiazyme, Abbott Laboratories; Abbott Park, IL). Cervical specimens from 11,793 women attending 22 family planning clinics were analyzed. Patient history and physical exams were used to assess risk factors for infection. A total of 913 individuals (7.7%) had positive culture results for C. trachomatis. Multivariate analysis showed that infection was significantly related to endocervical bleeding, cervical mucopurulent discharge, a new sexual partner in the last 3 months or multiple previous sexual partners (greater than 3) in the last year, pregnancy, the use of oral contraceptives, and age. Increased odd ratios were observed for the combination of endocervical bleeding and mucopurulent discharge and sexual history that included partners over the previous year as well as the most recent 3 months. A combination of these criteria was used to selectively screen women attending Colorado family planning clinics on an ongoing basis. A cost-benefit analysis employing a model reported previously showed a significant financial benefit associated with universal screening over either selective screening or no screening for C. trachomatis in this population.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Ambulatory Care Facilities
  • Child
  • Chlamydia Infections / economics
  • Chlamydia Infections / epidemiology
  • Chlamydia Infections / prevention & control*
  • Chlamydia trachomatis*
  • Colorado / epidemiology
  • Cost-Benefit Analysis
  • Family Planning Services
  • Female
  • Humans
  • Mass Screening / economics*
  • Mass Screening / methods
  • Mass Screening / statistics & numerical data
  • Middle Aged
  • Risk Factors