Transforming the #Enzian classification into a four-stage system: A feasibility study by comparison with the 2021 AAGL endometriosis classification.

Abstract

Study objective: To develop a translation model of the #Enzian classification into a 4-stage system and to evaluate its performance in a retrospective endometriosis cohort.

Design: Feasibility study consisting of 2 parts: First, the allocation of points for the translation model of the #Enzian classification into a 4-stage system. Second, the comparison between the AAGL2021 stages and the new #Enzian stages in a retrospective cohort of patients with endometriosis surgery.

Setting: Tertiary center in Europe.

Participants: 222 endometriosis patients who underwent laparoscopic surgery with perioperative documentation of both classifications.

Interventions: The basic structure of the translation model was defined according to the point values used in the AAGL2021 classification for different anatomical locations. In the absence of a direct translation option, the corresponding points for the #Enzian compartments were determined in a survey of 3 experienced endometriosis surgeons. The final 4-stage system was then tested against the AAGL2021 classification in a retrospective dataset.

Results: The distribution of endometriosis stages was similar between the 2 classifications, with a comparable percentage of patients in each stage (stage 1: 43% and 44%, stage 2: 20% and 24%, stage 3: 11% and 9%, stage 4: 27% and 21% for the #Enzian and AAGL2021 classifications, respectively). However, the composition of the stages differed slightly, especially in stages 2 and 3, which was shown in a sankey diagram. Certain deep endometriotic lesions in compartment B and adenomyosis are not respected in the AAGL2021 classification.

Conclusion: The #Enzian classification can be easily converted to a 4-stage scoring system similar to the AAGL2021 classification. Perhaps future research could help to determine appropriate point values based on different outcome parameters (e.g., pain, infertility, surgical complexity, …).