Yanzi Wan1, Li Tian2, Guoyi Zhang3, Hongyu Xin1, Haojiang Li2, Annan Dong2, Yiqin Liang1, Bingzhong Jing2, Jian Zhou2, Chunyan Cui2, Mingyuan Chen2, Ying Sun2, Chuanbo Xie2, Lizhi Liu4, Yuanzhi Shao5. 1. School of Physics, Sun Yat-sen University, Guangzhou, PR China. 2. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, PR China; Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, PR China. 3. Department of Radiation Oncology, Cancer Center, First People's Hospital of Foshan, PR China. 4. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, PR China; Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, PR China; Department of Radiology, The Third People's Hospital of Shenzhen, PR China. Electronic address: Liulizhidoc@163.com. 5. School of Physics, Sun Yat-sen University, Guangzhou, PR China. Electronic address: stssyz@mail.sysu.edu.cn.
Abstract
PURPOSE: To establish effective prognostic nomograms using clinical features and detailed magnetic resonance imaging (MRI) findings for primary tumor and regional lymph nodes after intensity-modulated radiotherapy (IMRT) in patients with nasopharyngeal carcinoma. METHOD: The nomogram for overall survival (OS) was based on a retrospective study of 595 patients who underwent IMRT at Sun Yat-sen University Cancer Center from 2010 to 2012. The predictive accuracy and discriminative ability of our nomogram models were determined by concordance index and calibration curve, and were compared with the nomogram models combining clinical features with tumor-node-metastasis (TNM) classification. The results were validated using bootstrap resampling and a cohort study of 241 patients. The same data cohort was used to predict the progress-free survival (PFS) of nasopharyngeal carcinoma with 3:1 training cohort (N = 558) and validation cohort (N = 278). RESULTS: The following factors were assembled into our prognostic survival nomogram models: Age, Epstein-Barr virus DNA copy number before treatment (EBV_DNA_CN), tensor veli palatini (TVP) involvement, musculus pterygoideus lateralis (MPL) involvement, prestyloid space (PS) involvement, prevertebral space (PVS) involvement, base of sphenoid bone (BOSB) involvement, paranasal sinus (PNS) involvement, the laterality of Ⅱ (Ⅱ_laterality), the laterality of retropharyngeal lymph node (RPLN_laterality), nodal grouping (NG), extranodal neoplastic spread (ENS), contrast-enhancing rim (CER) and Nodal_number. The calibration curves showed good agreement between nomogram-predicted and actual survival. Our nomogram models for OS and PFS, provided better results than the nomogram models combining clinical features with TNM classification. Results were further confirmed in the validation set. CONCLUSION: Detailed MRI findings of primary tumor and regional lymph nodes can improve the performance of prognostic nomograms for patients with nasopharyngeal carcinoma.
PURPOSE: To establish effective prognostic nomograms using clinical features and detailed magnetic resonance imaging (MRI) findings for primary tumor and regional lymph nodes after intensity-modulated radiotherapy (IMRT) in patients with nasopharyngeal carcinoma. METHOD: The nomogram for overall survival (OS) was based on a retrospective study of 595 patients who underwent IMRT at Sun Yat-sen University Cancer Center from 2010 to 2012. The predictive accuracy and discriminative ability of our nomogram models were determined by concordance index and calibration curve, and were compared with the nomogram models combining clinical features with tumor-node-metastasis (TNM) classification. The results were validated using bootstrap resampling and a cohort study of 241 patients. The same data cohort was used to predict the progress-free survival (PFS) of nasopharyngeal carcinoma with 3:1 training cohort (N = 558) and validation cohort (N = 278). RESULTS: The following factors were assembled into our prognostic survival nomogram models: Age, Epstein-Barr virus DNA copy number before treatment (EBV_DNA_CN), tensor veli palatini (TVP) involvement, musculus pterygoideus lateralis (MPL) involvement, prestyloid space (PS) involvement, prevertebral space (PVS) involvement, base of sphenoid bone (BOSB) involvement, paranasal sinus (PNS) involvement, the laterality of Ⅱ (Ⅱ_laterality), the laterality of retropharyngeal lymph node (RPLN_laterality), nodal grouping (NG), extranodal neoplastic spread (ENS), contrast-enhancing rim (CER) and Nodal_number. The calibration curves showed good agreement between nomogram-predicted and actual survival. Our nomogram models for OS and PFS, provided better results than the nomogram models combining clinical features with TNM classification. Results were further confirmed in the validation set. CONCLUSION: Detailed MRI findings of primary tumor and regional lymph nodes can improve the performance of prognostic nomograms for patients with nasopharyngeal carcinoma.