A new validated screening method for endometriosis diagnosis based on patient questionnaires. 

Abstract

Background: The time between symptoms onset and endometriosis diagnosis is usually long. The negative impacts of delayed endometriosis diagnosis can affect patients and health outcomes.

Methods: We conducted a case-control study using clinical symptoms and epidemiological data extracted from a prospective pre-operative patient questionnaire compared between patients with histologically proven endometriosis and patients with no endometriosis at surgical exploration from 2005 to 2018, in a French referral center. We used the beta coefficients of the significant variables introduced in a multiple regression model to devise a score (score 1), evaluated by the area under the curve (or C-index), with three levels, defined by a score between 1 and ≥ 25: (i) highly specific, identifying correctly the patients without the disease; (ii) highly sensitive, identifying the patients with the disease; and (iii) a level maximizing sensitivity and specificity for the best classification of the whole population. To minimize patient self-evaluation of pain, we devised a second score (score 2) with the same method and levels and scores definition, excluding visual analog scale pain scores, except for dysmenorrhea. These scores were validated on an internal and external population.

Findings: Score 1 had a C-index of 0.81 (95% CI [0.79-0.83]). Results for the three score 1 levels were: ≥ 25: specificity of 91% (95% CI [89-93]); < 11: sensitivity of 91% (95% CI [89-93]); ≥ 18: specificity of 75% (95% CI [72-78]) and sensitivity of 73% (95% CI [70-76]). Score 2 had a C-index of 0.75 (95% CI [73-77]). The three levels of score 2 were: ≥ 24: specificity of 82% (95% CI [80-85]); < 7: sensitivity of 92% (95% CI [90-94]); ≥ 17: specificity of 62% (95% CI [58-65]) and sensitivity of 78% (95% CI [75-81]). The two scores were internally and externally validated.

Interpretation: A score based only on a patient questionnaire could allow identification of a population at high risk of endometriosis. This strategy might help referral to specialized radiologists for a non-surgical endometriosis scan.