Prediction of lymph node metastasis in early esophageal cancer

• Published in: World journal of gastrointestinal surgery 2023-10, Vol.15 (10), p.2294-2304
• Main Authors: Li, Yan, Wang, Jun-Xiong, Yibi, Ran-Hen
• Format: Article
• Language: English
• Subjects: Systematic Reviews
• ISSN: 1948-9366; 1948-9366
• DOI: 10.4240/wjgs.v15.i10.2294

Given the poor prognosis of patients with lymph node metastasis, estimating the lymph node status in patients with early esophageal cancer is crucial. Indicators that could be used to predict lymph node metastasis in early esophageal cancer have been reported in many recent studies, but no recent studies have included a review of this subject. To review indicators predicting lymph node metastasis in early esophageal squamous cell carcinoma (ESCC) and early esophageal adenocarcinoma (EAC). We searched PubMed with "[early esophageal cancer (Title/Abstract)] and [lymph node (Title/Abstract)]" or "[early esophageal carcinoma (Title/Abstract)] and [lymph node (Title/Abstract)]" or "[superficial esophageal cancer (Title/Abstract)] and [lymph node (Title/Abstract)]." A total of 29 studies were eligible for analysis. Preoperative imaging (size), serum markers (microRNA-218), postoperative pathology and immunohistochemical analysis (depth of invasion, tumor size, differentiation grade, lymphovascular invasion, neural invasion, expression of PIM-1 < 30%) were predictive factors for lymph node metastasis in both early ESCC and EAC. Serum markers (thymidine kinase 1 ≥ 3.38 pmol/L; cytokeratin 19 fragment antigen 21-1 > 3.30 ng/mL; stathmin-1) and postoperative pathology and immunohistochemical analysis (overexpression of cortactin, mixed-lineage leukaemia 2, and stanniocalcin-1) were predictive for lymph node metastasis in early ESCC. Transcription of CD69, myeloid differentiation protein 88 and toll-like receptor 4 and low expression of olfactomedin 4 were predictive of lymph node metastasis in early EAC. A total of 6 comprehensive models for early ESCC, including logistic regression model, nomogram, and artificial neural network (ANN), were reviewed. The areas under the receiver operating characteristic curve of these models reached 0.789-0.938, and the ANN performed best. As all these models relied on postoperative pathology, further models focusing on serum markers, imaging and immunohistochemical indicators are still needed. Various factors were predictive of lymph node metastasis in early esophageal cancer, and present comprehensive models predicting lymph node metastasis in early ESCC mainly relied on postoperative pathology. Further studies focusing on serum markers, imaging and immunohistochemical indicators are still in need.