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ABSTRACT: Objectives
To identify the associations of lymph node metastases (pN+), number of positive nodes, and pN subclassification with cancer, treatment, patient, geographic, and institutional variables, and to recommend extent of lymphadenectomy needed to accurately detect pN+ for esophageal cancer.Summary background data
Limited data and traditional analytic techniques have precluded identifying intricate associations of pN+ with other cancer, treatment, and patient characteristics.Methods
Data on 5806 esophagectomy patients from the Worldwide Esophageal Cancer Collaboration were analyzed by Random Forest machine learning techniques.Results
pN+, number of positive nodes, and pN subclassification were associated with increasing depth of cancer invasion (pT), incre
SUBMITTER: Rice TW
PROVIDER: S-EPMC5405457 | biostudies-literature | 2017 Jan
REPOSITORIES: biostudies-literature