Menstrual Effluent in the Pathogenesis and Diagnosis of Endometriosis—A Systematic Review

TL;DR

This review explores menstrual effluent as a non-invasive biospecimen for understanding and diagnosing endometriosis, highlighting its potential for capturing disease mechanisms and diagnostic accuracy.

Contribution

The study systematically evaluates the pathophysiological relevance and diagnostic potential of menstrual effluent in endometriosis for the first time.

Findings

Menstrual effluent reflects key pathophysiological mechanisms of endometriosis, including immune dysregulation and progesterone resistance.

Aromatase mRNA showed the highest diagnostic accuracy (AUC 0.977) in detecting endometriosis.

Diagnostic assessments were based on case–control studies, with no prospective validation conducted.

Abstract

Background: The individual and social burden of endometriosis is high, and the diagnosis is usually delayed by 7–10 years. Menstrual effluent (ME) represents an accessible and uniquely informative biofluid. This systematic review evaluated the pathophysiological relevance and diagnostic potential of ME in endometriosis. Methods: Following PRISMA 2020 guidelines, we systematically searched PubMed/MEDLINE, EBSCOhost (Academic Search Premier, APA PsycArticles, APA PsycInfo, CINAHL, and MEDLINE), Semantic Scholar, and Google Scholar from inception to 30 November 2025. Original studies analyzing human ME or ME-derived cells in women with endometriosis versus controls were eligible. We extracted study design, analytic methods, diagnostic accuracy metrics (AUC, sensitivity, and specificity), mechanistic pathways, and risk of bias (QUADAS-2 for diagnostic, and NIH tools for mechanistic studies). Results: Thirty-five studies were included. ME consistently captured key pathophysiological mechanisms of endometriosis, including impaired decidualization and progesterone resistance, immune dysregulation with diminished cytotoxic clearance, pro-angiogenic and invasive phenotypes, heightened stem/progenitor cell survival, cellular senescence and DNA damage, and altered extracellular-vesicle signaling. Diagnostic accuracy was reported in nine studies. Aromatase mRNA showed the highest performance (AUC 0.977), followed by TGF-β1 (AUC 0.973) and IGFBP1 (AUC 0.92). A lipidomic two-marker model achieved an AUC of 0.87. All diagnostic assessments were based on case–control studies; none conducted prospective validation. Conclusions: ME is a biologically relevant, non-invasive, and patient-acceptable biospecimen reflecting core endometriosis mechanisms and yielding promising diagnostic accuracy. The highest diagnostic performance was achieved for assays reflecting steroidogenic and growth-factor pathways (e.g., aromatase and TGF-β1). Standardization and prospective validation are needed before clinical adoption.

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