Machine Learning-Guided Adjuvant Treatment of Head and Neck Cancer

93Citations
Citations of this article
100Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Importance: 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. Objective: To evaluate whether machine learning models could identify patients with intermediate-risk head and neck squamous cell carcinoma who would benefit from chemoradiation. Design, Setting, and Participants: 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. Exposures: Receipt of adjuvant chemoradiation or radiation alone. Main Outcomes and Measures: 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 outcome. Secondary outcomes included frequency of recommendation for chemotherapy and chemotherapy benefit in patients recommended for chemoradiation vs radiation alone. Results: A total of 33527 patients (24189 [72%] men; 28036 [84%] aged ≤70 years) met the inclusion criteria. Median follow-up in the validation data set was 43.2 (interquartile range, 19.8-65.5) months. DeepSurv, neural multitask logistic regression, and survival forest models recommended chemoradiation for 17589 (52%), 15917 (47%), and 14912 patients (44%), respectively. Treatment according to model recommendations was associated with a survival benefit, with a hazard ratio of 0.79 (95% CI, 0.72-0.85; P

Cite

CITATION STYLE

APA

Howard, F. M., Kochanny, S., Koshy, M., Spiotto, M., & Pearson, A. T. (2020). Machine Learning-Guided Adjuvant Treatment of Head and Neck Cancer. JAMA Network Open, 3(11). https://doi.org/10.1001/jamanetworkopen.2020.25881

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free