531: Stratification of Endometriosis-Associated Pain after Surgery: A Prospective Multicenter Study

Topic: Clinical Science
Subtopic: Pain category (ICD-11), Chronic primary visceral / pelvic pain, Omics (Proteomics/Metabolomics/Transcriptomics/Genomics), Quantitative Sensory testing (static and dynamic, e.g., HPT, PPT, CPM, TSP, offset analgesia)

Background and Aims: Endometriosis-associated pain shows marked inter-individual variability with large variations in symptoms, progression over time, and response to treatments including surgery. Mechanistic stratification is still weak because clinical pain trajectories are rarely linked to prospective and longitudinal psycho-social and molecular data. The prospective StEPP-UPP Non-Interventional Trial (NIT) aims to (1) define distinct perioperative pain trajectories and pain phenotypes, (2) build predictive models for certain pain phenotypes based on demographic and biopsychosocial data and (3) identify molecular signatures using an unbiased multi-omics approach to enable innovative diagnostic strategies, novel therapeutic targets in support of mechanism-informed, personalized management for patients after endometriosis surgery.

Methods: StEPP-UPP NIT-1 is a prospective, multicenter, non-interventional longitudinal study enrolling 150 women (18–50 years) with endometriosis undergoing planned surgery. Assessments are made preoperatively and at 3 and 6 months thereafter, including bedside QST (Quantitative Sensory Testing) and different PROMs (Patient-Reported Outcome Measures) assessing pain intensity and pain interference as primary outcomes, and other outcomes like endometriosis-specific quality of life, endometriosis-specific aspects, central sensitization, neuropathic pain, psychological aspects like depression, anxiety and stress, fatigue, including an ecological momentary assessment (EMA) evaluating trajectories over time. Blood, stool, and tissue proteomics are performed and all data are analysed by integrated ML/AI approaches.

Results: Recruitment is ongoing across the three centers; currently, 1/3 of the planned patients have been included and completed baseline assessments; follow-up visits are underway. Postoperative PROMS and EMA responses show >80% compliance, confirming feasibility of longitudinal assessment capture. In parallel, we established an integrative ML/AI pipeline on retrospective data, enabling end-to-end harmonization and reproducible model development. A CatBoost proof-of-concept model was implemented with iterative tuning and probability calibration, with performance estimated via resampling-based internal validation. Early technical linkage of PROMs/QST with molecular features is in place and is being used to refine the pipeline.

Conclusions: Multi-feature data assessment before and after surgery, with high-frequency digital EMA follow-up, combined with standardized perioperative biosampling and multi-platform proteomics in a multicenter endometriosis cohort is feasible. Upon completion, StEPP-UPP NIT-1 will use our ML/AI pipeline to integrate psychosocial, sensory, and molecular features to enable mechanism-based stratification of patients, predict certain pain phenotypes after endometriosis surgery, and provide ideas for an individualized prevention and treatment of endometriosis-related pain, including the identification of novel biomarker candidates as potential new treatment targets.

References: Saunders, P.T.K.; Horne, A.W. Endometriosis: Etiology, pathobiology, and therapeutic prospects. Cell 2021, 184, 2807–2824, doi:10.1016/j.cell.2021.04.041.

Zhang, M.; Xu, T.; Tong, D.; Li, S.; Yu, X.; Liu, B.; Jiang, L.; Liu, K. Research advances in endometriosis-related signaling pathways: A review. Biomed. Pharmacother. 2023,
164, 114909, doi:10.1016/j.biopha.2023.114909.

Presenting Author: Sören Marsmann
Submitting Author: Sören Marsmann

Senior Author: Esther M. Pogatzki-Zahn

IASP 2026 Global Year theme of Neuropathic Pain: No

• Christoph M. Schaefer: Dr. - Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, Muenster, Germany
• Stefan Floren: Dr. - Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, Muenster, Germany
• Sarah Bruun: Mrs. - Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, Muenster, Germany
• Philipp A. Macháček: Mr. - Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, Muenster, Germany
• Jan Vollert: Dr. Sc. Hum. - Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
• Manuela Schmidt: Univ. Prof. PhD - Department of Pharmaceutical Sciences, Division of Pharmacology and Toxicology, Systems Biology of Pain Group, University of Vienna, Austria
• Benedikt Schäfgen: PD Dr. - Department of Gynecology and Obstetrics, University Hospital Muenster, Muenster, Germany
• Lars Hanker: Univ. Prof. Dr. - Department of Gynecology and Obstetrics, University Hospital Muenster, Muenster, Germany
• Sebastian Schäfer: Dr. - Clemenshospital Münster (Ludgerus-Kliniken Münster GmbH), Muenster, Germany
• Christina Kröschel: Mrs. - Clemenshospital Münster (Ludgerus-Kliniken Münster GmbH), Muenster, Germany
• Quang Khoi Le: Mr. - Clemenshospital Münster (Ludgerus-Kliniken Münster GmbH), Muenster, Germany
• Sylvia Mechsner: Prof. Dr. - Department of Gynecology, Charité – Centre of Oncological Surgery, Endometriosis Research Centre Charité, Charité – Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353 Berlin, Germany
• Renata Voltolini Velho: PhD. - Department of Gynecology, Charité – Centre of Oncological Surgery, Endometriosis Research Centre Charité, Charité – Universitätsmedizin Berlin, Campus Virchow Klinikum, Augustenburger Platz 1, 13353 Berlin, Germany
• Bruno Pradier: Dr. - Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, Muenster, Germany
• Daniel Segelcke: Dr. - Department of Anaesthesiology, Intensive Care and Pain Medicine, University Hospital Muenster, Muenster, Germany