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), increasing cancer length, decreasing cancer differentiation (G), and more regional lymph nodes resected. Lymphadenectomy necessary to accurately detect pN+ is 60 for shorter, well-differentiated cancers (<2.5 cm) and 20 for longer, poorly differentiated ones.
Conclusions: In esophageal cancer, pN+, increasing number of positive nodes, and increasing pN classification are associated with deeper invading, longer, and poorly differentiated cancers. Consequently, if the goal of lymphadenectomy is to accurately define pN+ status of such cancers, few nodes need to be removed. Conversely, superficial, shorter, and well-differentiated cancers require a more extensive lymphadenectomy to accurately define pN+ status.
Key words: CARCINOMA; TUMOR; FORESTS; NUMBER
引用本文： . . 华西虚拟期刊, 2000, 1(1): 122-129-. doi: 10.1097/SLA.0000000000001594 复制