Background: Current the number of examined LNs are controversial in predicting the survival of ESCC. We aimed to develop an alternative LN-classification-based nomogram to individualize ESCC prognosis.Methods: Using the data of patients diagnosed with ESCC from SEER database between 2004 and 2015, we determined the cut-off values for the number of LNs examined via the K-adaptive partitioning (KAPS) algorithm. A nomogram predicting the survival of ESCC was performed, internally and externally

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... idated, and evaluated by calibration plot, C-index, and decision curve analysis, and compared to the 7th TNM stage.Results: Totally, we included 3629 patients with detailed information. The optimal cut-off for examined LN number was 8. The C-index for the nomogram was higher than the 7th TNM staging (internal: 0.708; 95%CI, 0.678-0.753 vs 0.601; 95%CI, 0.573-0.656, P<0.001; external: 0.687; 95%CI, 0.601-0.734 vs 0.605; 95%CI, 0.563-0.659, P<0.001). Additionally, the nomogram showed good agreement between internal and external validation. DCA analysis showed no matter in the internal cohort or external cohort, the nomogram showed a greater benefit across the period of follow-up compared to 7th TNM stage.Conclusion: We found examining LNs that was more than 8 benefited for prognosis of patients. Based on these, a nomogram with greater benefit for predicting survival of EC patients than TNM staging was constructed.