Machine Learning-Guided Adjuvant Treatment of Head and Neck Cancer

JAMA Network Open
Frederick Matthew HowardAlexander T Pearson

Abstract

Postoperative chemoradiation is the standard of care for cancers with positive margins or extracapsular extension, but the benefit of chemotherapy is unclear for patients with other intermediate risk features. To evaluate whether machine learning models could identify patients with intermediate-risk head and neck squamous cell carcinoma who would benefit from chemoradiation. This cohort study included patients diagnosed with squamous cell carcinoma of the oral cavity, oropharynx, hypopharynx, or larynx from January 1, 2004, through December 31, 2016. Patients had resected disease and underwent adjuvant radiotherapy. Analysis was performed from October 1, 2019, through September 1, 2020. Patients were selected from the National Cancer Database, a hospital-based registry that captures data from more than 70% of newly diagnosed cancers in the United States. Three machine learning survival models were trained using 80% of the cohort, with the remaining 20% used to assess model performance. Receipt of adjuvant chemoradiation or radiation alone. Patients who received treatment recommended by machine learning models were compared with those who did not. Overall survival for treatment according to model recommendations was the primary ...Continue Reading

References

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Citations

Mar 6, 2021·Current Opinion in Otolaryngology & Head and Neck Surgery·Vincent Vander PoortenPierre Delaere

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Software Mentioned

DeepSurv
IPTW
PySurvival
Python

Related Concepts

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Carcinoma, Squamous Cell

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