ArticlePloS one2025
Quality of life identification by unsupervised cluster analysis: A new approach to modelling the burden of endometriosis.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Selected Parameters of the Mental State of Women with Endometriosis-A Systematic Review.Journal of clinical medicine · 2026Review
- Using artificial intelligence to predict sexual health outcomes in endometriosis: a decision tree model algorithm.Sexual medicine · 2026Article
- Association of body mass index on sexual function in women with endometriosis: A cross-sectional study.PloS one · 2026Article
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4 authors.
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Abstract
backgroundSymptoms frequently associated with endometriosis affect quality of life (QoL). Our aim investigated the hypothesis that cluster analysis can be used to identify homogeneous phenotyping subgroups of women according to the burden of the endometriosis for their QoL, and then to investigate the phenotype differences observed between these subgroups.
methodsWe developed an anonymous online survey, which received responses from 1,586 French women with endometriosis. K-means, a major clustering algorithm, was performed to show structure in data and divide women into groups based on the burden of endometriosis. This was defined using 9 dimensions. Multivariable logistic regression was performed to highlight the association between QoL and several factors. Covariables were age, BMI, smoking, education, children, marital status and surgery.
resultsK-means clustering was implemented with 8 clusters (optimal CCC value of 17.2162). In one cluster, women presented a high level of QoL and represented 234 women for 60% of women with a high level of QoL, and another with 410 women for 34% of women with worse QoL. Independent factors determining high QoL were age (over 45 years compared to below 25 years, OR = 0.17 [0.07-0.46], p<0.001), BMI (high vs low, OR = 0.47 [0.28-0.80], p = 0.005), having children (OR = 0.30 [0.18-0.48], p<0.001), having surgery for endometriosis (OR = 0.55 [0.32-0.94], p = 0.029), and education (high vs low, OR = 2.75 [1.75-4.31], p<0.001).
conclusionCluster analysis identifies homogeneous women phenotypes for QoL with endometriosis. Implementing new methodological approaches improves QoL of endometriosis women and allows appropriate preventive strategies.
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