Machine Learning–Guided Adjuvant Treatment of Head and Neck Cancer
TL
TL;DR
Treatment according to 3 machine learning models, trained and validated using the National Cancer Database, was associated with a survival benefit and these models recommended chemoradiation in 44% to 52% of the population.
Abstract
Key Points Question Can machine learning survival models predict which patients with intermediate-risk head and neck squamous cell carcinoma would benefit from adjuvant chemotherapy? Findings In this cohort study of 33 526 patients, treatment according to 3 machine learning models, trained and validated using the National Cancer Database, was associated with a survival benefit. These models recommended chemoradiation in 44% to 52% of the population. Meaning These findings suggest that machine learning models have the potential to better select intermediate-risk patients in need of trimodality therapy, and further study is warranted.
References29 items
1
Transoral robotic surgical resection followed by randomization to low- or standard-dose IMRT in resectable p16+ locally advanced oropharynx cancer: A trial of the ECOG-ACRIN Cancer Research Group (E3311).
2
Deep learning detects virus presence in cancer histology
3
Machine Learning to Predict Delays in Adjuvant Radiation following Surgery for Head and Neck Cancer
4
High-performance medicine: the convergence of human and artificial intelligence
5