Clinical predictive factors for endometriosis in a Portuguese infertile population

C. Calhaz-Jorge*, Ben W. Mol, J. Nunes, A. P. Costa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Citations (Scopus)

Abstract

Background: Endometriosis is an important clinical situation associated with subfertility. It would be very useful to identify patients at increased risk for endometriosis prior to laparoscopy. In the present study, we evaluate the demographic and clinical characteristics in a cohort of Portuguese subfertile women in relation to the presence of endometriosis. Methods: Consecutive subfertile patients scheduled for laparoscopy were interviewed prior to the procedure. At subsequent laparoscopy, the presence of endometriosis was scored according to the revised classification of the American Society for Reproductive Medicine (ASRM). Data available from the medical history were tabulated against the presence or absence of endometriosis. We used logistic regression analysis to evaluate whether data from the patient's medical history could predict the presence of endometriosis. Results: Among the 1079 women that were studied, 358 had minimal/mild endometriosis and 130 had moderate/severe endometriosis. Primary subfertility, regularity of menstrual cycles, dysmenorrhoea, chronic pelvic pain, obesity, ever use of oral contraceptives and smoking were the most important predictors of endometriosis. The prediction model had an area under the receiver operating characteristic curve of 0.71. Conclusions: Both the presence of endometriosis (all stages) and the presence of severe endometriosis per se can be predicted from the medical history. These data should be used in the decision to perform laparoscopy at an early stage or a later stage in the work-up for subfertility.

Original languageEnglish
Pages (from-to)2126-2131
Number of pages6
JournalHuman Reproduction
Volume19
Issue number9
DOIs
Publication statusPublished - Sep 2004

Keywords

  • Endometriosis
  • Epidemiology
  • Infertility
  • Predictive factors

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