Prognostic and Treatment Guiding Significance of MRI-Based Tumor Burden Features and Nodal Necrosis in Nasopharyngeal Carcinoma - Chen, Xi; Cao, Xun; Jing, Bingzhong; Xia, Weixiong; Ke, Liangru; Xiang, Yanqun; Liu, Kuiyuan; Qiang, Mengyun; Liang, Chixiong; Li, Jianpeng; Gao, Mingyong; Li, Wangzhong; et al. (Frontiers in Oncology, 2020)
We aimed to develop a nomogram integrating MRI-based tumor burden features (MTBF), nodal necrosis and some clinical factors to forecast the distant metastasis-free survival (DMFS) of patients suffering from nonmetastatic nasopharyngeal carcinoma (NPC). A total of 1640 patients treated at Sun Yat-sen University Cancer Center (Guangzhou, China) from 2011 to 2016 were enrolled, among which 1148 and 492 patients were randomized to a training cohort and an internal validation cohort, respectively. Additionally, 200 and 257 patients were enrolled in the Foshan and Dongguan validation cohorts, respectively, which served as independent external validation cohorts. The MTBF were developed from the stepwise regression of six multidimensional tumor burden variables, based on which we developed a nomogram also integrating nodal necrosis and clinical features. This model divided the patients into high- and low-risk groups by an optimal cutoff. Compared with those of patients in the low-risk group, the DMFS (hazard ratio [HR]: 4.76, 95% CI: 3.39-6.69; p<0.0001) and progression-free survival (PFS) (HR: 4.11, 95% CI: 3.13-5.39; p<0.0001) of patients in the high-risk group were relatively poor. Furthermore, in the training cohort, the 3-year DMFS of high-risk patients who received induction chemotherapy (ICT) combined with concurrent chemoradiotherapy (CCRT) was better than that of those who were treated with CCRT alone (p=0.0340), whereas low-risk patients who received ICT+CCRT had a similar DMFS to those who only received CCRT. The outcomes we obtained were all verified in the three validation cohorts. The survival model can be used as a reliable prognostic tool for NPC patients and is helpful to determine patients who will benefit from ICT.