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Health Economics | Center for Health Policy | Journal

Development of Machine Learning Algorithms for the Prediction of Financial Toxicity in Localized Breast Cancer Following Surgical Treatment

March 26, 2021 | Anaeze C. Offodile II, Chris Sidey-Gibbons, André Pfob, Malke Assad, Stefanos Boukovalas, Yu-Li Lin, Jesse Creed Selber, Charles Butler
A stethoscope on American paper currency.

Table of Contents

Author(s)

Anaeze C. Offodile II

Former Nonresident Scholar

Chris Sidey-Gibbons

André Pfob

Malke Assad

Stefanos Boukovalas

Yu-Li Lin

Jesse Creed Selber

Charles Butler

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Abstract

Financial burden caused by cancer treatment is associated with material loss, distress, and poorer outcomes. Financial resources exist to support patients but identification of need is difficult. The authors sought to develop and test a tool to accurately predict an individual's risk of financial toxicity based on clinical, demographic, and patient-reported data prior to initiation of breast cancer treatment.

Access the full journal article in JCO Clinical Cancer Informatics.

https://doi.org/10.1200/CCI.20.00088
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