Abstract
BACKGROUND: Minimally invasive esophagectomy (MIE) is commonly applied in the treatment of esophageal squamous cell carcinoma (ESCC). The preoperative immune prognostic index (IPI) is considered a potential indicator for ESCC. In this study, we attempted to establish and validate a comprehensive clinical risk staging toward predicting the long-term outcome in ESCC patients after MIE through the combined application of IPI and clinicopathological features based on nomogram. METHODS: Patients diagnosed with ESCC and who were treated with MIE at our center were randomly assigned in a 7:3 ratio to two cohorts: training (n=425) and validation (n=188). Nomograms were then established according to the Cox multivariate results for the training cohort. To evaluate the predictive value and the clinical benefit rate of the nomogram, we employed the calibration curve, decision curve analysis (DCA), and time-dependent area under the curve (t-AUC). The best cut-off value obtained was applied to develop the survival nomogram-scoring (SNS) staging. RESULTS: Patients with ESCC and who underwent MIE exhibited the worse overall survival (OS) and disease-free survival (DFS) with an IPI=2 relative to IPI=0 or 1 (all P < 0.001) in the training and validation cohorts, respectively. According to the multivariate Cox analysis, we established nomograms that combined IPI with the clinicopathological features to predict the OS and DFS. The t-AUC and DCA demonstrated that the nomograms had a better predictive value and clinical benefit rate than the American Joint Committee on Cancer (AJCC) staging. Accordingly, we developed the SNS staging and found that the OS and DFS were significantly different among patients at different stages (all P < 0.001). The dynamic mortality risk rate revealed a double peak in the high-risk patients (12 and 48 months) and a single peak in the low-risk patients (24 months) and middle-risk patients (12 months), which gradually decreased over time. CONCLUSION: The SNS staging based on IPI and clinicopathological features can thus be applied to effectively evaluate the OS and DFS of ESCC patients after MIE. Our findings may facilitate the development of clinical follow-up strategies.