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PRONA: an R-package for Patient Reported Outcomes Network Analysis
Brandon H Bergsneider1,2, Orieta Celiku1
1Neuro-Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, United States.
Bioinformatics (Oxford, England)
|November 9, 2024
Summary
Network analysis (NA) models complex illness symptoms. PRONA, a new R-package, unifies NA tools and identifies patient subgroups for improved cancer care.
Area of Science:
- Oncology
- Computational Biology
- Data Science
Background:
- Network analysis (NA) is a novel approach to model complex illness symptom patterns.
- Graph theory methods in NA reveal symptom interplays crucial for patient quality of life.
Purpose of the Study:
- To address limitations in clinical NA application, specifically the lack of unified software platforms and methods for cohort heterogeneity.
- To introduce PRONA, an R-package designed to streamline Patient Reported Outcomes Network Analysis.
Main Methods:
- PRONA is an R-package consolidating existing NA software into a unified pipeline.
- It incorporates unsupervised methods for discovering patient subgroups with distinct symptom profiles.
- Implementation details and source code are available on GitHub.
Main Results:
- PRONA provides a unified, user-friendly platform for network analysis of patient-reported outcomes.
- The package enables the identification of critical symptoms impacting quality of life in complex illnesses.
- It facilitates the discovery of patient heterogeneity through unsupervised subgroup analysis.
Conclusions:
- PRONA enhances the clinical applicability of network analysis for complex diseases like cancer.
- The R-package offers a unified solution for NA, addressing current research and clinical gaps.
- PRONA's ability to identify patient subgroups with unique symptom patterns can inform personalized treatment strategies.
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