Proportion of Pelvic Inflammatory Disease caused by Chlamydia trachomatis: consistent picture from different methods

Research output: Contribution to journalArticle

Authors

  • A.E Ades
  • Nicky J Welton
  • Ian Simms
  • John Macleod
  • Paddy J Horner

Abstract

Background. Pelvic inflammatory disease (PID) is a leading cause of both tubal factor infertility and ectopic pregnancy. Chlamydia trachomatis is an important risk factor for PID, but the proportion of PID cases caused by C. trachomatis is unclear. Estimates of this are required to evaluate control measures.

Methods. We consider 5 separate methods of estimating age-group-specific population excess fractions (PEFs) of PID due to C. trachomatis, using routine data, surveys, case-control studies, and randomized controlled trials, and apply these to data from the United Kingdom before introduction of the National Chlamydia Screening Programme.

Results. As they are informed by randomized comparisons and national exposure and outcome estimates, our preferred estimates of the proportion of PID cases caused by C. trachomatis are 35% (95% credible interval [CrI], 11%–69%) in women aged 16–24 years and 20% (95% CrI, 6%–38%) in women aged 16–44 years in the United Kingdom. There is a fair degree of consistency between adjusted estimates of PEF, but all have wide 95% CrIs. The PEF decreases from 53.5% (95% CrI, 15.6%–100%) in women aged 16–19 years to 11.5% (95% CrI, 3.0%–25.7%) in women aged 35–44 years.

Conclusions. The PEFs of PID due to C. trachomatis decline steeply with age by a factor of around 5-fold between younger and older women. Further studies of the etiology of PID in different age groups are required.

Details

Original languageEnglish
Pages (from-to)617-624
JournalThe Journal of Infectious Diseases
Volume214
Issue number4
Early online date3 Jun 2016
Publication statusPublished - 15 Aug 2016

Keywords

  • Chlamydia trachomatis, pelvic inflammatory disease, population attributable fraction, population excess fraction, meta-analysis, Bayesian, evidence synthesis