Developing symptom-based predictive models of endometriosis as a clinical screening tool: results from a multicenter study.
OBJECTIVE
To generate and validate symptom-based models to predict endometriosis among symptomatic women prior to undergoing their first laparoscopy.


METHODS
Prospective, observational, two-phase study, in which women completed a 25-item questionnaire prior to surgery.


METHODS
Nineteen hospitals in 13 countries.


METHODS
Symptomatic women (n = 1,396) scheduled for laparoscopy without a previous surgical diagnosis of endometriosis.


METHODS
None.


METHODS
Sensitivity and specificity of endometriosis diagnosis predicted by symptoms and patient characteristics from optimal models developed using multiple logistic regression analyses in one data set (phase I), and independently validated in a second data set (phase II) by receiver operating characteristic (ROC) curve analysis.


RESULTS
Three hundred sixty (46.7%) women in phase I and 364 (58.2%) in phase II were diagnosed with endometriosis at laparoscopy. Menstrual dyschezia (pain on opening bowels) and a history of benign ovarian cysts most strongly predicted both any and stage III and IV endometriosis in both phases. Prediction of any-stage endometriosis, although improved by ultrasound scan evidence of cyst/nodules, was relatively poor (area under the curve [AUC] = 68.3). Stage III and IV disease was predicted with good accuracy (AUC = 84.9, sensitivity of 82.3% and specificity 75.8% at an optimal cut-off of 0.24).


CONCLUSIONS
Our symptom-based models predict any-stage endometriosis relatively poorly and stage III and IV disease with good accuracy. Predictive tools based on such models could help to prioritize women for surgical investigation in clinical practice and thus contribute to reducing time to diagnosis. We invite other researchers to validate the key models in additional populations.
Department of Public Health, University of Oxford, Oxford, United Kingdom. nnoaham.kelechi@berkshire.nhs.uk
Kelechi E
KE
Nnoaham
Lone
L
Hummelshoj
Stephen H
SH
Kennedy
Crispin
C
Jenkinson
Krina T
KT
Zondervan
D000293:Adolescent; D000328:Adult; D004715:Endometriosis / Q000175:diagnosis*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D008962:Models, Theoretical; D011446:Prospective Studies