The value of integrating tumor volume and plasma Epstein-Barr virus DNA load during sequential chemoradiotherapy for prognostic prediction and therapeutic guidance in high-risk locoregionally advanced nasopharyngeal carcinoma.

Objectives: To investigate the value of integrating primary gross tumor volume (GTV) and gross tumor volume of nodes (GTV) after induction chemotherapy (IC) and dynamic changes in plasma cell-free Epstein-Barr virus DNA (cfEBV DNA) during sequential chemoradiotherapy (CRT) in high-risk locoregionally advanced nasopharyngeal carcinoma (LA-NPC).

Materials And Methods: We retrospectively reviewed 988 patients with LA-NPC undergoing IC plus concurrent chemoradiotherapy (CCRT) between 2014 and 2018. The entire cohort was divided into four subgroups according to tumor volume and the cfEBV DNA load. Using a supervised statistical clustering approach, we stratified the subgroups into three clusters. Overall survival (OS), disease-free survival (DFS), distant metastasis-free survival (DMFS) and locoregional relapse-free survival (LRRFS) were calculated using Kaplan-Meier analysis and inter-group differences were compared using the log-rank test.

Results: We observed that GTV & GTV and cfEBV DNA & cfEBV DNA were powerful prognostic factors for OS (p = 0.004, p < 0.001, p < 0.001, and p < 0.001, respectively). The survival curves of the three clusters were significantly different. The 5-year OS for the low-risk, intermediate-risk and high-risk clusters were 97.0%, 86.2% and 77.1% (all P values < 0.001), respectively. The risk stratification system showed better predictive performance than the current tumor-node-metastasis (TNM) classification for OS (area under curve [AUC]: 0.653 versus 0.560, p < 0.001), DFS (AUC: 0.639 versus 0.540, p < 0.001), DMFS (AUC: 0.628 versus 0.535, p < 0.001) and LRRFS (AUC: 0.616 versus 0.513, p < 0.001).

Conclusion: Both tumor volume and the cfEBV DNA level during sequential CRT are effective prognostic indicators for patients with high-risk LA-NPC. The developed risk stratification system incorporating above factors improved survival prediction and demonstrated potential value in decision-making.