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<p>Endometriosis is one of the most common causes of chronic pelvic or lower-abdominal pain, yet mechanisms, predictors, and patient-centered treatment pathways remain insufficiently defined. This article summarizes the situation in Germany and presents two complementary research consortia: StEPP-UPP and ENDO-PAIN.</p><p>StEPP-UPP addresses the clinical heterogeneity of endometriosis pain via a&#xa0;prospective multicenter cohort, standardized patient-reported outcomes, quantitative sensory testing, and multi-omics from blood, stool, and lesions. Explainable artificial intelligence and machine-learning models aim to estimate risk and trajectories of persistent pain, define mechanism-informed subgroups, and support treatment decisions. Preclinical mouse models with non-evoked behavioral metrics plus multiparametric MRI and single-cell analyses provide mechanistic anchoring for clinical signatures.</p><p>ENDO-PAIN focuses on neuroinflammation and fibrosis as drivers of pain and chronification. Using patient samples, cell cultures, and 3D organoids, it maps immune–stroma interactions, syndecan signaling, and hormone–inflammation axes (for example P4–TGFβ–NFκB–COX-2) to derive biomarker networks and therapeutic targets.</p><p>Both consortia integrate patient advocacy structurally to ensure patient-relevant endpoints and accessible information. Together they point to three priorities: standardization of data collection and biobanking; stratification along bio-psycho-social profiles and molecular signatures; and interdisciplinary shared decision-making across research, clinics, and people with endometriosis, aiming for mechanistically grounded, data-driven, patient-centered pain medicine.</p>

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Endometrioseschmerz-Forschung in Deutschland

  • 期刊论文

  • 发表日期：

    2026年7月20日

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  • Renata Voltolini Velho,
  • Bruno Pradier,
  • Franziska Werner,
  • Esther M. Pogatzki-Zahn,
  • Sylvia Mechsner

摘要

Endometriosis is one of the most common causes of chronic pelvic or lower-abdominal pain, yet mechanisms, predictors, and patient-centered treatment pathways remain insufficiently defined. This article summarizes the situation in Germany and presents two complementary research consortia: StEPP-UPP and ENDO-PAIN.

StEPP-UPP addresses the clinical heterogeneity of endometriosis pain via a prospective multicenter cohort, standardized patient-reported outcomes, quantitative sensory testing, and multi-omics from blood, stool, and lesions. Explainable artificial intelligence and machine-learning models aim to estimate risk and trajectories of persistent pain, define mechanism-informed subgroups, and support treatment decisions. Preclinical mouse models with non-evoked behavioral metrics plus multiparametric MRI and single-cell analyses provide mechanistic anchoring for clinical signatures.

ENDO-PAIN focuses on neuroinflammation and fibrosis as drivers of pain and chronification. Using patient samples, cell cultures, and 3D organoids, it maps immune–stroma interactions, syndecan signaling, and hormone–inflammation axes (for example P4–TGFβ–NFκB–COX-2) to derive biomarker networks and therapeutic targets.

Both consortia integrate patient advocacy structurally to ensure patient-relevant endpoints and accessible information. Together they point to three priorities: standardization of data collection and biobanking; stratification along bio-psycho-social profiles and molecular signatures; and interdisciplinary shared decision-making across research, clinics, and people with endometriosis, aiming for mechanistically grounded, data-driven, patient-centered pain medicine.