| Zhao Min,Liu Kai,Wang Ruozheng.A prognostic nomogram model for locally advanced nasopharyngeal carcinoma in Xinjiang region[J].Chinese Journal of Radiological Medicine and Protection,2021,41(4):259-264 |
| A prognostic nomogram model for locally advanced nasopharyngeal carcinoma in Xinjiang region |
| Received:August 08, 2020 |
| DOI：10.3760/cma.j.issn.0254-5098.2021.04.004 |
| KeyWords:Nasopharyngeal carcinoma Nomogram Epstein-Barr virus Prognosis |
| FundProject:新疆维吾尔自治区科技支疆项目（2020E0265） |
| Author Name | Affiliation | E-mail | | Zhao Min | Affiliated Tumor Hospital of Xinjiang Medical University(Third Clinical Medical College), Key Laboratory of Tumor Immunology and Radiotherapy, Chinese Academy of Medical Sciences, Xinjiang Key Laboratory of Oncology, Urumqi 830011, China | | | Liu Kai | Affiliated Tumor Hospital of Xinjiang Medical University(Third Clinical Medical College), Key Laboratory of Tumor Immunology and Radiotherapy, Chinese Academy of Medical Sciences, Xinjiang Key Laboratory of Oncology, Urumqi 830011, China | | | Wang Ruozheng | Affiliated Tumor Hospital of Xinjiang Medical University(Third Clinical Medical College), Key Laboratory of Tumor Immunology and Radiotherapy, Chinese Academy of Medical Sciences, Xinjiang Key Laboratory of Oncology, Urumqi 830011, China | wrz8526@vip.163.com |
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| Abstract:: |
| Objective To analyze the prognostic factors of patients with locally advanced nasopharyngeal carcinoma after treatment, to develop and validate the prognostic Nomogram model. Methods From July 2010 to June 2017, 317 patients with nasopharyngeal carcinoma who were treated with definitive intensity modulated radiation therapy were selected. The regression method of least absolute shrinkage and selection operator (LASSO) was used for univariate screening, and Cox multivariate regression analysis was performed. The prognostic Nomogram model was constructed for locally advanced nasopharyngeal carcinoma patients. C-index, calibration curve, Net Reclassification Index (NRI), integrated discrimination improvement (IDI) were used to validate and evaluate the model between Nomogram and TNM staging system. The risk evaluated through nomogram was stratified by decision tree algorithm, and the survival rate was calculated by Kaplan-Meier method and compared by Log-rank test. Results T stage, N stage, LDH, GTVnd and pre-treated plasma EBV-DNA copy (EBV-DNA) were correlated with total survival (OS). All the above factors were included in prognostic Nomogram model, and C-index was 0.784 (95%CI:0.736-0.831, P<0.01). The calibration curve showed that the OS probability predicted by Nomogram model was in good agreement with the actual OS, and the result were verified in the validation cohort. Furthermore, the accuracy of the Nomogram model for OS predicting was superior to AJCC 8th version staging system judged by NRI and IDI. According to the Nomogram score, patients can be divided into four subgroups with different risk by decision tree algorithm. K-M survival curve showed that the difference of OS between different groups was statistically significant (χ2=113.21, P<0.01), and patients in high-risk group can benefit from induction chemotherapy combined with concurrent chemoradiotherapy in survival. Conclusions The Nomogram model established by our research group can provide information on diagnosis, treatment and prognosis evaluation for locally advanced nasopharyngeal carcinoma patients in this area. |
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