Non-Invasive Diagnosis of Endometriosis by Questionnaires in Patients Using Contraception

Area of Science:

• Gynecology
• Medical Diagnostics
• Pain Management

Background:

• Assessing endometriosis (EMS)-associated pain is crucial.
• Few studies explore non-invasive prediction methods like questionnaires for EMS.
• Early and accurate diagnosis of EMS remains a significant clinical challenge.

Purpose of the Study:

• To evaluate the efficacy of questionnaires in the non-invasive prediction of endometriosis (EMS).
• To determine if specific pain patterns and questionnaire responses can accurately identify patients with EMS.
• To assess the diagnostic performance of a decision tree model for EMS detection.

Main Methods:

• Prospective observational study (2016-2024) with 228 patients on hormonal contraception.
• Utilized two questionnaires, physical examination, transvaginal ultrasound (TVUS), and MRI when deep infiltrating EMS (DIE) was suspected.
• EMS diagnosis confirmed by histology; statistical analysis included 2x2 contingency tables and a manually created decision tree.

Main Results:

• EMS-positive patients reported ~4-fold higher pain scores (NRS 4.45 vs. 1.15).
• EMS patients had ~3 times more significant parameters (18.5 vs. 5.9).
• A decision tree achieved high diagnostic accuracy: sensitivity 0.924, specificity 0.917, PPV 0.924, NPV 0.917, and a positive likelihood ratio of 11.2.

Conclusions:

• Non-invasive diagnosis of endometriosis (EMS) using questionnaires is feasible and reliable.
• Specific pain patterns, including dysuria and lightning-like pain, are predictive of EMS.
• This questionnaire-based approach can significantly reduce diagnostic delays for EMS.