A logistic model for the prediction of endometriosis

Barbara J. Stegmann, Michele Jonsson Funk, Ninet Sinaii, Katherine E. Hartmann, James Segars, Lynnette K. Nieman, Pamela Stratton

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)51-55
Number of pages5
JournalFertility and Sterility
Volume91
Issue number1
DOIs
StatePublished - Jan 2009
Externally publishedYes

Fingerprint

Endometriosis
Logistic Models
Biopsy
Pelvic Pain
Appendix
Chronic Pain
Laparoscopy
Colon
Color
Outcome Assessment (Health Care)
Clinical Trials
Sensitivity and Specificity
Research

Keywords

  • Endometriosis
  • logistic regression modeling
  • prediction

ASJC Scopus subject areas

  • Obstetrics and Gynecology
  • Reproductive Medicine

Cite this

Stegmann, B. J., Funk, M. J., Sinaii, N., Hartmann, K. E., Segars, J., Nieman, L. K., & Stratton, P. (2009). A logistic model for the prediction of endometriosis. Fertility and Sterility, 91(1), 51-55. https://doi.org/10.1016/j.fertnstert.2007.11.038

A logistic model for the prediction of endometriosis. / Stegmann, Barbara J.; Funk, Michele Jonsson; Sinaii, Ninet; Hartmann, Katherine E.; Segars, James; Nieman, Lynnette K.; Stratton, Pamela.

In: Fertility and Sterility, Vol. 91, No. 1, 01.2009, p. 51-55.

Research output: Contribution to journalArticle

Stegmann, BJ, Funk, MJ, Sinaii, N, Hartmann, KE, Segars, J, Nieman, LK & Stratton, P 2009, 'A logistic model for the prediction of endometriosis', Fertility and Sterility, vol. 91, no. 1, pp. 51-55. https://doi.org/10.1016/j.fertnstert.2007.11.038
Stegmann, Barbara J. ; Funk, Michele Jonsson ; Sinaii, Ninet ; Hartmann, Katherine E. ; Segars, James ; Nieman, Lynnette K. ; Stratton, Pamela. / A logistic model for the prediction of endometriosis. In: Fertility and Sterility. 2009 ; Vol. 91, No. 1. pp. 51-55.
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