{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T05:20:37Z","timestamp":1774329637314,"version":"3.50.1"},"reference-count":24,"publisher":"Oxford University Press (OUP)","issue":"11","funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>Network analysis (NA) has recently emerged as a new paradigm by which to model the symptom patterns of patients with complex illnesses such as cancer. NA uses graph theory-based methods to capture the interplay between symptoms and identify which symptoms may be most impactful to patient quality of life and are therefore most critical to treat\/prevent. Despite NA\u2019s increasing popularity in research settings, its clinical applicability is hindered by the lack of a unified platform that consolidates all the software tools needed to perform NA, and by the lack of methods for capturing heterogeneity across patient cohorts. Addressing these limitations, we present PRONA, an R-package for Patient Reported Outcomes Network Analysis. PRONA not only consolidates previous NA tools into a unified, easy-to-use analysis pipeline, but also augments the traditional approach with functionality for performing unsupervised discovery of patient subgroups with distinct symptom patterns.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>PRONA is implemented in R. Source code, installation, and use instructions are available on GitHub at https:\/\/github.com\/bbergsneider\/PRONA.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btae671","type":"journal-article","created":{"date-parts":[[2024,11,9]],"date-time":"2024-11-09T15:04:03Z","timestamp":1731164643000},"source":"Crossref","is-referenced-by-count":1,"title":["PRONA: an R-package for Patient Reported Outcomes Network Analysis"],"prefix":"10.1093","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7013-8150","authenticated-orcid":false,"given":"Brandon H","family":"Bergsneider","sequence":"first","affiliation":[{"name":"Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health , Bethesda, MD 20892,","place":["United States"]},{"name":"School of Medicine, Stanford University , Stanford, CA 94305,","place":["United 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