OBJECTIVE

This study aimed to construct a model based on 23 enrolled molecules to evaluate prognoses of pT2/3N0M0 esophageal squamous cell carcinoma (ESCC) patients with up to 20 years of follow-up.

METHODS

The lasso-Cox model was used to identify the candidate molecule. A nomogram was conducted to develop the survival model (molecular score, MS) based on the molecular features. Cox regression and Kaplan-Meier analysis were used in this study. The concordance index (C-index) was measured to compare the predicted ability between different models. The primary endpoint was overall survival (OS).

RESULTS

A total of 226 patients and 23 proteins were enrolled in this study. Patients were classified into high-risk (MS-H) and low-risk (MS-L) groups based on the MS score of 227. The survival curves showed that the MS-L cohort had better 5-year and 10-year survival rates than the MS-H group (5-year OS: 51.0% vs. 8.0%; 10-year OS: 45.0% vs. 5.0%, all p < 0.001). Furthermore, multivariable analysis confirmed MS as an independent prognostic factor after eliminating the confounding factors (Hazard ratio 3.220, p < 0.001). The pT classification was confirmed to differentiate ESCC patients' prognosis (Log-rank: p = 0.029). However, the combination of pT and MS could classify survival curves evidently (overall p < 0.001), which showed that the prognostic prediction efficiency was improved significantly by the combination of the pT and MS than by the classical pT classification (C-index: 0.656 vs. 0.539, p < 0.001).

CONCLUSIONS

Our study suggested an MS for significant clinical stratification of T2/3N0M0 ESCC patients to screen out subgroups with poor prognoses. Besides, the combination of pT staging and MS could predict survival more accurately for this cohort than the pT staging system alone.