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Link to original content: https://pubmed.ncbi.nlm.nih.gov/38256490/
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Review
. 2024 Jan 8;13(2):356.
doi: 10.3390/jcm13020356.

Endometriosis Predictive Models Based on Self-Assessment Questionnaire, Evidence from Clinical Examination or Imaging Findings: A Narrative Review

Fani Gkrozou  1 , Orestis Tsonis  2   3 , Felice Sorrentino  4 , Luigi Nappi  4 , Anastasia Vatopoulou  1 , Chara Skentou  1 , Suruchi Pandey  3 , Minas Paschopoulos  1 , Angelos Daniilidis  5
Affiliations
Review

Endometriosis Predictive Models Based on Self-Assessment Questionnaire, Evidence from Clinical Examination or Imaging Findings: A Narrative Review

Fani Gkrozou et al. J Clin Med. .

Abstract

Objective: The aim of this narrative review is to evaluate existing questionnaires on predictive models for endometriosis. These symptom-based models have the potential to serve as screening tools for adult women to detect endometriosis.

Data sources: A comprehensive search of PubMed and Embase databases was conducted to identify studies on endometriosis screening.

Selection of studies: The search targeted predictive models for endometriosis localisation, bowel involvement, need for bowel surgery and fertility. Due to the heterogeneity identified, a systematic review was not possible. A total of 23 studies were identified.

Data extraction and synthesis: Among these studies, twelve included measures for general endometriosis, two targeted specific sites, four focused on deep infiltrating endometriosis (DIE), and three addressed the need for endometriosis-related bowel surgery. Many measures combined clinical, imaging and laboratory tests with patient questionnaires. Validation of these models as screening tools was lacking in all studies, as the focus was on diagnosis rather than screening.

Conclusion: This review did not identify any fully validated, symptom-based questionnaires for endometriosis screening in adult women. Substantial validation work remains to establish the efficacy of such tools.

Keywords: chronic pelvic pain; endometriosis; predictive models; pregnancy; self-assessment questionnaire; treatment.

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Conflict of interest statement

The authors declare no conflicts of interest.

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