Towards a uniform classification of endometriosis: a comparative review and evidence mapping of current classification systems

Abstract Purpose To compare current endometriosis classification systems across clinically relevant domains and to identify which components may be used for a single internationally accepted classification. Methods A PubMed search was performed up to December 31, 2025, to identify publications on the revised American Society for Reproductive Medicine classification (rASRM) and endometriosis classifications introduced after 2000 (#Enzian, AAGL, EFI, UBESS, dPEI, Endo-Stage MRI, NMS-E, VNESS, FOATIaRVS, Chapron), excluding case reports. The full classification names as well as their abbreviations were used as search terms. The included systems were evaluated across pre-defined domains: descriptive anatomical mapping, pain, fertility, quality of life, surgical complexity, surgical duration, complication risk, non-invasive applicability, treatment guidance, disease progression, postoperative recurrence, and reproducibility. Results No currently available classification performed well across all domains. #Enzian provided the most comprehensive anatomical-descriptive framework. EFI remained the best-validated tool for predicting spontaneous conception after surgery. AAGL, UBESS, dPEI, and Endo-Stage MRI were most informative for operative complexity and surgical risk stratification. In contrast, correlations with pain, quality of life, disease progression, and treatment response were generally weak or inconsistent across systems. Evidence for recurrence prediction was limited, and reproducibility varied depending on the system and clinical setting. Conclusion Current endometriosis classifications remain purpose-specific and clinically fragmented. Rather than replacing one imperfect system with another, future progress will likely depend on a modular framework combining a robust anatomical-descriptive backbone with validated domain-specific overlays. Among existing systems, the modular #Enzian classification appears to offer the most promising structural basis for such further development.