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by claude@2026-07, 2026-07-03
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This review focuses on endometriosis, examining why the condition is often underdiagnosed, the biological factors contributing to its heterogeneity (including hormonal imbalance, immune dysregulation, chronic inflammation, neuroangiogenesis, and genetic/epigenetic changes), and the consequences of diagnostic delay averaging 6–10 years. It synthesizes evidence for non-invasive diagnostic approaches such as circulating and menstrual biomarkers, microRNAs, advanced imaging, and artificial intelligence tools intended to reduce reliance on surgical diagnosis. The paper highlights key limitations for implementation, including lack of standardized biomarkers, limited validation of AI models, and inequitable access to expert imaging. This paper is centrally about endometriosis — it reviews delayed diagnosis and discusses emerging precision-medicine strategies using non-invasive diagnostics and molecular stratification.
Abstract
Endometriosis is a chronic, estrogen-dependent inflammatory disorder affecting approximately 10% of individuals of reproductive age worldwide and remains one of the most underdiagnosed and heterogeneous conditions in women’s health. Increasing evidence demonstrates that endometriosis is not a single disease entity but a complex, multifactorial spectrum driven by hormonal imbalance, immune dysregulation, chronic inflammation, neuroangiogenesis, and genetic and epigenetic alterations. Profound disease heterogeneity across anatomical presentation, symptom severity, molecular profiles, and treatment response poses major challenges to diagnosis and management. A persistent diagnostic delay averaging 6–10 years from symptom onset continues to result in disease progression, chronic pain, infertility, psychological distress, and substantial socioeconomic burden. This review examines the biological complexity of endometriosis and critically analyzes the causes and consequences of diagnostic delay. We synthesize emerging evidence on non-invasive diagnostic innovations, including circulating and menstrual biomarkers, microRNAs, advanced imaging modalities, and artificial intelligence–based tools, which collectively challenge the historical reliance on surgical diagnosis. We further explore how integrative “omics” approaches and molecular stratification are enabling the transition toward precision medicine, with the potential to predict treatment response and guide personalized therapeutic strategies. Despite significant advances, barriers to clinical translation remain, including lack of standardized biomarkers, limited validation of AI models, and inequitable access to expert imaging. Addressing these challenges through coordinated research, education, and health system reform is essential. The integration of molecular profiling, non-invasive diagnostics, and patient-centered multidisciplinary care offers a transformative opportunity to reduce diagnostic delay and shift endometriosis management from reactive symptom control toward predictive, personalized care.
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Endometriosis: From delayed diagnosis to precision medicine
Authors/Creators
- 1. Department of Obstetrics and Gynaecology, Enugu State University Teaching Hospital, Parklane, Enugu, Nigeria.
- 2. Department of Paediatrics, Alberta Children Hospital Calgary, Canada.
Description
Endometriosis is a chronic, estrogen-dependent inflammatory disorder affecting approximately 10% of individuals of reproductive age worldwide and remains one of the most underdiagnosed and heterogeneous conditions in women’s health. Increasing evidence demonstrates that endometriosis is not a single disease entity but a complex, multifactorial spectrum driven by hormonal imbalance, immune dysregulation, chronic inflammation, neuroangiogenesis, and genetic and epigenetic alterations. Profound disease heterogeneity across anatomical presentation, symptom severity, molecular profiles, and treatment response poses major challenges to diagnosis and management. A persistent diagnostic delay averaging 6–10 years from symptom onset continues to result in disease progression, chronic pain, infertility, psychological distress, and substantial socioeconomic burden.
This review examines the biological complexity of endometriosis and critically analyzes the causes and consequences of diagnostic delay. We synthesize emerging evidence on non-invasive diagnostic innovations, including circulating and menstrual biomarkers, microRNAs, advanced imaging modalities, and artificial intelligence–based tools, which collectively challenge the historical reliance on surgical diagnosis. We further explore how integrative “omics” approaches and molecular stratification are enabling the transition toward precision medicine, with the potential to predict treatment response and guide personalized therapeutic strategies.
Despite significant advances, barriers to clinical translation remain, including lack of standardized biomarkers, limited validation of AI models, and inequitable access to expert imaging. Addressing these challenges through coordinated research, education, and health system reform is essential. The integration of molecular profiling, non-invasive diagnostics, and patient-centered multidisciplinary care offers a transformative opportunity to reduce diagnostic delay and shift endometriosis management from reactive symptom control toward predictive, personalized care.
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