The impact of lymph node resection and survival prediction by machine learning in esophageal squamous cell carcinoma patients over 60 years old: a clinical trial based on the SEER database and Chinese population

Background: This study aims to investigate the relationship between long-term survival in esophageal squamous cell carcinoma (ESCC) patients and various clinical factors, including age, sex, examined lymph nodes (ELN), tumor size, T stage, N stage, grade, and surgical procedure. These findings aim to provide surgeons with precise information to avoid overtreatment. Materials and Methods: Random forest and Cox proportional hazard models were developed and validated using data from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) database (2013–2018) and Shaanxi Provincial Hospital. A web-based recommendation system was constructed to facilitate the selection of an optimal number of lymph nodes for visualizing survival curves and score trends under different conditions. This study has been registered in the Chinese Clinical Trial Registry (No. ChiCTR2400081083). Results: The optimal number of ELN for two randomly selected ESCC patients was determined to be 33. In the N0 group, patients with 15–33 ELN had a median survival of 55.0 months, significantly longer than those with <15 ELN (30.0 months) or >33 ELN (26.5 months). Statistically significant differences were observed between the 15–33 ELN group and both the <15 ELN (P = 0.02) and >33 ELN groups (P = 0.03) in N0 patients from both the SEER database and our independent cohort (15–33 ELN vs. >33 ELN: 36.0 months vs. 13.0 months, P < 0.001). No significant difference was found in N+ patients, suggesting that the number of retrieved lymph nodes has minimal impact on prognosis in this subgroup. Conclusions: Our findings indicate that examining fewer than 15 or more than 33 lymph nodes increases prognostic risks in ESCC patients over 60 years old.