Prognostic prediction and comparison of three staging programs for patients with advanced (T2-T4) esophageal squamous...

Lymph node-based staging protocols are frequently employed to evaluate the prognosis of esophageal cancer, yet their accuracy remains contentious. The present study was conducted to assess the prognostic significance of three lymph node staging systems, namely N stage, lymph node rate (LNR), and log odds of positive lymph nodes (LODDS), in patients diagnosed with advanced (T2-T4) esophageal squamous cell carcinoma (ESCC).

This cohort comprised 319 eligible patients, with an additional 409 individuals retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, forming the validation cohort. Differences in overall survival (OS) of patients between groups were assessed using the log-rank test. Prognostic independent risk variables were identified, and lymph nodes (LN) prognostic models were built using multivariate Cox regression analysis. Besides, the predictive accuracy of each model was evaluated utilizing the (-2) log-likelihood ratio (-2LLR), the likelihood ratio χ2 score (LRχ2), the Akaike information criterion (AIC), and Harrell's concordance index (C-index). To further evaluate the potential superiority of the model, a nomogram was constructed for comparison with the conventional Tumor Node Metastasis (TNM) staging approach.

Independent prognostic factors for advanced ESCC include the N stage, LNR, and LODDS. Herein, LODDS presented higher values for C-index and LRχ2, and lower values for AIC and -2LLR in OS compared to the others. Consequently, a nomogram was constructed based on LODDS. Calibration curves exhibited strong agreement, and assessment through C-index, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA) demonstrated promising clinical applicability.

LODDS emerges as a promising future prognostic indicator. After surgery, the proposed model holds the potential to provide valuable treatment recommendations for patients with advanced ESCC.