Related Experiment Video
Updated: Jul 5, 2026
Establishment of an Experimental Mouse Model of Endometrioma to Study its Related Infertility
Published on: April 5, 2024
A logistic model for the prediction of endometriosis
Barbara J Stegmann1, Michele Jonsson Funk, Ninet Sinaii
1Reproductive Biology and Medicine Branch, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland 20892-1109, USA.
Objective:
To develop a model that uses individual and lesion characteristics to help surgeons choose lesions that have a high probability of containing histologically confirmed endometriosis.
Design:
Secondary analysis of prospectively collected information.
Setting:
Government research hospital in the United States.
Patient(S):
Healthy women 18-45 years of age, with chronic pelvic pain and possible endometriosis, who were enrolled in a clinical trial.
Intervention(S):
All participants underwent laparoscopy, and information was collected on all visible lesions. Lesion data were randomly allocated to a training and test data set.
Main Outcome Measure(S):
Predictive logistic regression, with the outcome of interest being histologic diagnosis of endometriosis.
Result(S):
After validation, the model was applied to the complete data set, with a sensitivity of 88.4% and specificity of 24.6%. The positive predictive value was 69.2%, and the negative predictive value was 53.3%, equating to correct classification of a lesion of 66.5%. Mixed color; larger width; and location in the ovarian fossa, colon, or appendix were most strongly associated with the presence of endometriosis.
Conclusion(S):
This model identified characteristics that indicate high and low probabilities of biopsy-proven endometriosis. It is useful as a guide in choosing appropriate lesions for biopsy, but the improvement using the model is not great enough to replace histologic confirmation of endometriosis.
