Background
Postoperative radiotherapy (PORT) is beneficial in the improvement of localâregional 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 immuneâinflammation index to predict distant metastasisâfree 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
=Â 334) and validation set (
n
=Â 84). The preâradiotherapy neutrophilâtoâlymphocyte ratio (NLR), and plateletâtoâlymphocyte 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 Logârank 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 3â, 5â, and 10âyear DMFS were 79.4%, 71.8%, and 59.1%, respectively. The multivariate analysis revealed that age (
p
=Â 0.033), advanced T stage (
p
=Â 0.003), positive
N
stage (
p
<â0.001), highârisk pathology (
p
=Â 0.011), and high PLR (
p
=Â 0.001) were significantly associated with worse DMFS. The nomogram showed good calibration and discrimination in the training (AUCÂ =Â 80.9) and validation set (AUCÂ =Â 87.9). Furthermore, the DCA demonstrated favorable applicability, and a significant difference (
p
<â0.001) 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.