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ABSTRACT: Introduction
To facilitate the initial clinical decision regarding whether to use esophagectomy alone or neoadjuvant therapy in surgical care for individual patients with adenocarcinoma of the esophagus and esophagogastric junction-information not available from randomized trials-a machine-learning analysis was performed using worldwide real-world data on patients undergoing different therapies for this rare adenocarcinoma.Methods
Using random forest technology in a sequential analysis, we (1) identified eligibility for each of four therapies among 13,365 patients: esophagectomy alone (n = 6649), neoadjuvant therapy (n = 4706), esophagectomy and adjuvant therapy (n = 998), and neoadjuvant and adjuvant therapy (n = 1022); (2) performed survival analyses incorporating interac
SUBMITTER: Rice TW
PROVIDER: S-EPMC6876319 | biostudies-literature | 2019 Dec
REPOSITORIES: biostudies-literature