A Novel Classification of Endometriosis Based on Clusters of Comorbidities

Author:

Sarria-Santamera Antonio1ORCID,Yemenkhan Yerden2ORCID,Terzic Milan345ORCID,Ortega Miguel A.678ORCID,Asunsolo del Barco Angel7910ORCID

Affiliation:

1. Department of Biomedical Sciences, Nazarbayev University School of Medicine, Astana 010000, Kazakhstan

2. Department of Medicine, Nazarbayev University School of Medicine, Astana 010000, Kazakhstan

3. Department of Surgery, Nazarbayev University School of Medicine, Astana 010000, Kazakhstan

4. Clinical Academic Department of Women’s Health, National Research Center for Maternal and Child Health, University Medical Center, Astana 010000, Kazakhstan

5. Department of Obstetrics, Gynecology and Reproductive Sciences, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA

6. Department of Medicine and Medical Specialties, Faculty of Medicine and Health Sciences, University of Alcalá, 28801 Alcalá de Henares, Spain

7. Ramón y Cajal Institute of Sanitary Research (IRYCIS), 28034 Madrid, Spain

8. Cancer Registry and Pathology Department, Hospital Universitario Principe de Asturias, 28805 Alcalá de Henares, Spain

9. Department of Surgery, Medical and Social Sciences, Faculty of Medicine and Health Sciences, University of Alcala, 28801 Alcalá de Henares, Spain

10. Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, The City University of New York, New York, NY 10017, USA

Abstract

Endometriosis is a heterogeneous, complex, and still challenging disease, due to its epidemiological, etiological and pathogenic, diagnostic, therapeutic, and prognosis characteristics. The classification of endometriosis is contentious, and existing therapies show significant variability in their effectiveness. This study aims to capture and describe clusters of women with endometriosis based on their comorbidity. With data extracted from electronic records of primary care, this study performs a hierarchical clustering with the Ward method of women with endometriosis with a subsequent analysis of the distribution of comorbidities. Data were available for 4055 women with endometriosis, and six clusters of women were identified: cluster 1 (less comorbidity), cluster 2 (anxiety and musculoskeletal disorders), cluster 3 (type 1 allergy or immediate hypersensitivity); cluster 4 (multiple morbidities); cluster 5 (anemia and infertility); and cluster 6 (headache and migraine). Clustering aggregates similar units into similar clusters, partitioning dissimilar objects into other clusters at a progressively finer granularity—in this case, groups of women with similarities in their comorbidities. Clusters may provide a deeper insight into the multidimensionality of endometriosis and may represent diverse “endometriosis trajectories” which may be associated with specific molecular and biochemical mechanisms. Comorbidity-based clusters may be important to the scientific study of endometriosis, contributing to the clarification of its clinical complexity and variability. An awareness of those comorbidities may help elucidate the etiopathogenesis and facilitate the accurate earlier diagnosis and initiation of treatments targeted toward particular subgroups.

Publisher

MDPI AG

Subject

General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)

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