Predictive and Interpretable Machine Learning of Economic Burden: The Role of Chronic Conditions Among Elderly Patients with Incident Primary Merkel Cell Carcinoma (MCC)
Among older adults with MCC, cardiac and renal conditions were the leading drivers of total expenditures and OOP expenditures. Our findings suggest that managing cardiac and renal conditions may be important for cost containment efforts.
Authors
- Joanna Kolodney
- Zasim Azhar Siddiqui (ORCID: https://orcid.org/0000-0002-6719-3228)
- George A. Kelley (ORCID: https://orcid.org/0000-0003-0595-4148)
- Murtuza Bharmal (ORCID: https://orcid.org/0000-0001-7689-5769)
- Khalid M. Kamal (ORCID: https://orcid.org/0000-0003-4269-3370)
- Usha Sambamoorthi (ORCID: https://orcid.org/0000-0001-8311-1360)
- Yves Paul Vincent Mbous (ORCID: https://orcid.org/0000-0002-6642-1073)
- Traci LeMasters (ORCID: https://orcid.org/0000-0002-6998-2650)
Institutions
- West Virginia University (US)
- University of North Texas (US)
- University of North Texas Health Science Center (US)
- AstraZeneca (United States) (US)
Publication Details
- Journal
- ClinicoEconomics and Outcomes Research
- Published
- 2024-12-01
- DOI
- https://doi.org/10.2147/ceor.s456968
- Citations
- 1
- Primary Topic
- Polyomavirus and related diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.28
Funders
- EMD Serono