Abstract
Endometriosis is a systemic and chronic condition in women of childbearing age, yet a highly enigmatic disease with unresolved questions: there are no known biomarkers, nor established clinical stages. We here investigate the use of patient-generated health data and data-driven phenotyping to characterize endometriosis patient subtypes, based on their reported signs and symptoms. We aim at unsupervised learning of endometriosis phenotypes using self-tracking data from personal smartphones. We leverage data from an observational research study of over 4000 women with endometriosis that track their condition over more than 2 years. We extend a classical mixed-membership model to accommodate the idiosyncrasies of the data at hand, i.e., the multimodality and uncertainty of the self-tracked variables. The proposed method, by jointly modeling a wide range of observations (i.e., participant symptoms, quality of life, treatments), identifies clinically relevant endometriosis subtypes. Experiments show that our method is robust to different hyperparameter choices and the biases of self-tracking data (e.g., the wide variations in tracking frequency among participants). With this work, we show the promise of unsupervised learning of endometriosis subtypes from self-tracked data, as learned phenotypes align well with what is already known about the disease, but also suggest new clinically actionable findings. More generally, we argue that a continued research effort on unsupervised phenotyping methods with patient-generated health data via new mobile and digital technologies will have significant impact on the study of enigmatic diseases in particular, and health in general.
Highlights
Endometriosis is a chronic and systemic disease in women of reproductive age with no known cure[1,2,3]
Unsupervised phenotype modeling—Learned endometriosis phenotypes We present a summary of the outputs of the learned model for the whole study cohort in Figs. 2 and 3
We found that participants assigned to phenotype A are most likely to have pelvic inflammatory diseases, with some evidence of high blood pressure associated with phenotypes A and C
Summary
Endometriosis is a chronic and systemic disease in women of reproductive age with no known cure[1,2,3]. Endometriosis is prevalent in women, with estimates of affecting 10% of those in reproductive age, and has high morbidity and impact on quality of life[4,5] It is a highly enigmatic condition, with heterogeneous symptoms documented by patients: stereotypical evidence like pain and infertility are known, but a wide range of other symptoms with systemic effects are reported as well[6]. These variety of symptoms have not been well characterized yet for all endometriosis patients, with unclear associations between some symptoms and the disease: it is still uncertain why some treatments are effective for some patients, and not for others. Several stages of the disease have been proposed, they do not explain the diversity of symptoms experienced by patients, they do not correlate with their severity[7], nor have unequivocal connection with disease progression[8]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
