A nomogram involving immune-inflammation index for predicting distant metastasis-free survival of major salivary gland carcinoma following postoperative radiotherapy

Abstract

Background: Postoperative radiotherapy (PORT) is beneficial in the improvement of local-regional control and overall survival (OS) for major salivary gland carcinomas (SGCs), and distant metastasis remained the main failure pattern. This study was designed to develop a nomogram model involving immune-inflammation index to predict distant metastasis-free survival (DMFS) of major SGCs. Patients and Methods: A total of 418 patients with major SGCs following PORT were randomly divided into a training (n = 334) and validation set (n = 84). The pre-radiotherapy neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were calculated and transformed as continuous variables for every patient. Associations between DMFS and variables were performed by univariate and multivariable analysis using Log-rank and Cox regression methods. A nomogram was constructed based on the prognostic factors identified by the Cox hazards model. The decision curve analysis (DCA) was conducted with the training and validation set. Results: The estimated 3-, 5-, and 10-year DMFS were 79.4%, 71.8%, and 59.1%, respectively. The multivariate analysis revealed that age (p = 0.033), advanced T stage (p = 0.003), positive N stage (p < 0.001), high-risk pathology (p = 0.011), and high PLR (p = 0.001) were significantly associated with worse DMFS. The nomogram showed good calibration and discrimination in the training (AUC = 80.9) and validation set (AUC = 87.9). Furthermore, the DCA demonstrated favorable applicability, and a significant difference (p < 0.001) was observed for the DMFS between the subgroups based on the nomogram points. Conclusion: The nomogram incorporating clinicopathological features and PLR presented accurate individual prediction for DMFS of the patients with major SGCs following PORT. Further external validation of the model is warranted for clinical utility.