Prognostic nomogram and risk factors for predicting survival in patients with pT2N0M0 esophageal squamous carcinoma

Sci Rep. 2023 Mar 26;13(1):4931. doi: 10.1038/s41598-023-32171-w.

Abstract

This study analyzed the impact of factors affecting overall survival in patients with pT2N0M0 esophageal squamous carcinoma (ESCC) and developed a nomogram to predict overall survival (OS). We reviewed the clinical data of 413 patients with pathological T2N0M0 ESCC after radical esophagectomy in two hospitals. Data from one institution was used as the training cohort. A nomogram was established using Cox proportional hazard regression for identifying the prognostic factors affecting for OS in ESCC patients. The area under the curve (AUC), calibration curves and decision curve analysis (DCA) were used to evaluate prognostic efficacy, which was validated in an independent validation cohort. In the training cohort (N = 304), the median OS was 69.33 months, and the 3-, 5- and 10-year OS rates were 76.80%, 67.00% and 56.90%, respectively. The median OS of the validation cohort (N = 109) was 73.50 months, and the 3-, 5- and 10-year OS rates were 77.00%, 67.80% and 55.60%, respectively. According to Cox univariate and multivariate analyses, sex, age, tumor length and the number of resected lymph nodes were identified as predictors of OS. We developed nomograms and performed internal and external validation. The time-dependent receiver operating characteristic (ROC) curve and area under the curve (AUC) value, calibration curve and decision curve analysis (DCA) showed good prediction ability of the nomogram. The developed nomogram can effectively predict OS after esophagectomy in patients with pT2N0M0 ESCC.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Carcinoma, Squamous Cell* / pathology
  • Esophageal Neoplasms* / pathology
  • Esophageal Squamous Cell Carcinoma* / pathology
  • Esophageal Squamous Cell Carcinoma* / surgery
  • Humans
  • Neoplasm Staging
  • Nomograms
  • Prognosis
  • Risk Factors