Conference proceeding
A Network-based Modeling Approach to Identify the Common Disease Classes in Patients with Late-stage Prostate Cancer
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings
01 Jan 2022
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Conference Title: 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI) Conference Start Date: 2022, June 11 Conference End Date: 2022, June 14 Conference Location: Rochester, MN, USAProstate cancer (PCa) is one of the most common non-cutaneous cancers, and the second major cause of cancer death among men in the United States. The comorbidities study of PCa patients can inform treatment priority management and patient-oriented care. In this study, using the SEER-Medicare database, we adopt a network-based modeling approach to identify the most common disease classes among male with late-stage (stage D) PCa. The dataset comprises patients diagnosed with stage D PCa between January 1, 2010, and December 31, 2015, and a control group consisted of an equal size random sample of men without cancer. For both stage D PCa and control subpopulations, we created a set of 116 networks. Each network in the set represents a disease category identified using subsections of ICD-9 disease codes. In these networks, diseases and complications (identified using ICD-9 codes) are used as networks' nodes. Two nodes are connected if their related diseases' co-occurrences are observed in the dataset. Furthermore, the edges are weighted by the co-occurrence probability of complication pairs. A statistical approach was adopted to compare the differences between corresponding networks in the two groups. Out of 116 subsections, 59 had more than 30 distinct pairs, from which 51 subsections were statistically different between the control and the stage D PCa subpopulations (p - value
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Details
- Title
- A Network-based Modeling Approach to Identify the Common Disease Classes in Patients with Late-stage Prostate Cancer
- Creators
- Ali Jazayeri - Drexel UniversityMichal Monselise - Drexel UniversityNiusha Jafari - Drexel UniversityNikita Nikita - Thomas Jefferson UniversityChristopher C. Yang - Drexel UniversityGrace Lu-Yao - Thomas Jefferson University
- Publication Details
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Conference Proceedings
- Publisher
- The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science; Information Science (Informatics) (2013-2026)
- Web of Science ID
- WOS:000864170400016
- Scopus ID
- 2-s2.0-85139025280
- Other Identifier
- 991019173903704721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Health Care Sciences & Services
- Medical Informatics