{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T23:49:50Z","timestamp":1783468190707,"version":"3.55.0"},"reference-count":37,"publisher":"Wiley","issue":"3","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2023,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Postoperative radiotherapy (PORT) is beneficial in the improvement of local\u2010regional 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\u2010inflammation index to predict distant metastasis\u2010free survival (DMFS) of major SGCs.<\/jats:p><\/jats:sec><jats:sec><jats:title>Patients and Methods<\/jats:title><jats:p>A total of 418 patients with major SGCs following PORT were randomly divided into a training (<jats:italic>n<\/jats:italic>\u00a0=\u00a0334) and validation set (<jats:italic>n<\/jats:italic>\u00a0=\u00a084). The pre\u2010radiotherapy neutrophil\u2010to\u2010lymphocyte ratio (NLR), and platelet\u2010to\u2010lymphocyte 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\u2010rank 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.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The estimated 3\u2010, 5\u2010, and 10\u2010year DMFS were 79.4%, 71.8%, and 59.1%, respectively. The multivariate analysis revealed that age (<jats:italic>p<\/jats:italic>\u00a0=\u00a00.033), advanced T stage (<jats:italic>p<\/jats:italic>\u00a0=\u00a00.003), positive <jats:italic>N<\/jats:italic> stage (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001), high\u2010risk pathology (<jats:italic>p<\/jats:italic>\u00a0=\u00a00.011), and high PLR (<jats:italic>p<\/jats:italic>\u00a0=\u00a00.001) were significantly associated with worse DMFS. The nomogram showed good calibration and discrimination in the training (AUC\u00a0=\u00a080.9) and validation set (AUC\u00a0=\u00a087.9). Furthermore, the DCA demonstrated favorable applicability, and a significant difference (<jats:italic>p<\/jats:italic>\u2009&lt;\u20090.001) was observed for the DMFS between the subgroups based on the nomogram points.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>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.<\/jats:p><\/jats:sec>","DOI":"10.1002\/cam4.5167","type":"journal-article","created":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T06:27:20Z","timestamp":1662100040000},"page":"2772-2781","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A nomogram involving immune\u2010inflammation index for predicting distant metastasis\u2010free survival of major salivary gland carcinoma following postoperative radiotherapy"],"prefix":"10.1002","volume":"12","author":[{"given":"Wenbin","family":"Yan","sequence":"first","affiliation":[{"name":"Department of Radiation Oncology Fudan University Shanghai Cancer Center  Shanghai China"},{"name":"Department of Oncology Shanghai Medical College  Shanghai China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaomin","family":"Ou","sequence":"additional","affiliation":[{"name":"Department of 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