A data-mining framework for large scale analysis of dose-outcome relationships in a database of irradiated head and neck cancer patients.

Purpose: To develop a hypothesis-generating framework for automatic extraction of dose-outcome relationships from an in-house, analytic oncology database.

Methods: Dose-volume histograms (DVH) and clinical outcomes have been routinely stored to the authors' database for 684 head and neck cancer patients treated from 2007 to 2014. Database queries were developed to extract outcomes that had been assessed for at least 100 patients, as well as DVH curves for organs-at-risk (OAR) that were contoured for at least 100 patients.