A Mechanism-Informed Symptom Pattern Framework for Endometriosis-Associated Supportive Care: A Narrative Synthesis and Conceptual Hypothesis

Background: Endometriosis is a heterogeneous condition in which symptom profiles, pain phenotypes, and responses to non-pharmacological care vary substantially between patients. Existing classification systems describe lesion distribution but do not organise the functional and symptomatic variation relevant to supportive-care planning. Hypothesis: We propose a literature-derived conceptual framework organising endometriosis symptom heterogeneity into four mechanism-informed patterns — pain sensitisation, gut–immune interaction, neuroendocrine sensitivity, and estrogen clearance burden — overlaid by two cross-cutting modifier axes: immune-inflammatory activity and progesterone responsiveness. Methods: Targeted narrative synthesis of peer-reviewed literature on endometriosis pathophysiology. Pattern boundaries were defined by two operational criteria: mechanistic distinctness and meaningful differentiation in the emphasis on non-pharmacological supportive care. The framework's mechanistic vocabulary was cross-referenced against the 2026 multi-ancestry GWAS of endometriosis (Koller et al., ~1.4M women, 105,869 cases). Discussion: The framework is hypothesis-generating and not a diagnostic or treatment-selection tool. It occupies a supportive-care stratification layer complementary to anatomical and molecular classification systems. Convergence with GWAS-identified loci supports the mechanistic architecture but does not confirm cluster boundaries. Prospective validation using structured longitudinal symptom phenotyping aligned with WERF EPHect standards is required. Conclusion: This conceptual framework provides a structured vocabulary for mechanism-informed supportive-care planning in endometriosis and a testable hypothesis for future cohort research.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-24
DOI
https://doi.org/10.5281/zenodo.20825919
Primary Topic
Endometriosis Research and Treatment
Type
article
Field-Weighted Citation Impact
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article

A Mechanism-Informed Symptom Pattern Framework for Endometriosis-Associated Supportive Care: A Narrative Synthesis and Conceptual Hypothesis

Anna Kreimes
Zenodo (CERN European Organization for Nuclear Research)
Endometriosis Research and Treatment
article

A Mechanism-Informed Symptom Pattern Framework for Endometriosis-Associated Supportive Care: A Narrative Synthesis and Conceptual Hypothesis

Anna Kreimes
article en

Abstract

Background: Endometriosis is a heterogeneous condition in which symptom profiles, pain phenotypes, and responses to non-pharmacological care vary substantially between patients. Existing classification systems describe lesion distribution but do not organise the functional and symptomatic variation relevant to supportive-care planning. Hypothesis: We propose a literature-derived conceptual framework organising endometriosis symptom heterogeneity into four mechanism-informed patterns — pain sensitisation, gut–immune interaction, neuroendocrine sensitivity, and estrogen clearance burden — overlaid by two cross-cutting modifier axes: immune-inflammatory activity and progesterone responsiveness. Methods: Targeted narrative synthesis of peer-reviewed literature on endometriosis pathophysiology. Pattern boundaries were defined by two operational criteria: mechanistic distinctness and meaningful differentiation in the emphasis on non-pharmacological supportive care. The framework's mechanistic vocabulary was cross-referenced against the 2026 multi-ancestry GWAS of endometriosis (Koller et al., ~1.4M women, 105,869 cases). Discussion: The framework is hypothesis-generating and not a diagnostic or treatment-selection tool. It occupies a supportive-care stratification layer complementary to anatomical and molecular classification systems. Convergence with GWAS-identified loci supports the mechanistic architecture but does not confirm cluster boundaries. Prospective validation using structured longitudinal symptom phenotyping aligned with WERF EPHect standards is required. Conclusion: This conceptual framework provides a structured vocabulary for mechanism-informed supportive-care planning in endometriosis and a testable hypothesis for future cohort research.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Endometriosis Research and Treatment
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