A comprehensive predictive model for radiation-induced brain injury in risk stratification and personalized radiotherapy of nasopharyngeal carcinoma

Background and purpose: Radiation-induced brain injury (RBI) is a severe radiotoxicity for nasopharyngeal carcinoma (NPC) patients, greatly affecting their long-term life quality and survival. We aim to establish a comprehensive predictive model including clinical factors and newly developed genetic variants to improve the precision of RBI risk stratification.Materials and methods: By performing a large registry-based retrospective study with magnetic resonance imaging follow-up on RBI development, we conducted a genome-wide association study and developed a polygenic risk score (PRS) for RBI in 1189 NPC patients who underwent intensity-modulated radiotherapy. We proposed a tolerance dose scheme for temporal lobe radiation based on the risk predicted by PRS. Additionally, we established a nomogram by combining PRS and clinical factors for RBI risk prediction.Results: The 38-SNP PRS could effectively identify high-risk individuals of RBI (P = 1.42 x 10(-34)). Based on genetic risk calculation, the recommended tolerance doses of temporal lobes should be 57.6 Gy for individuals in the top 10 % PRS subgroup and 68.1 Gy for individuals in the bottom 50 % PRS. Notably, individuals with high genetic risk (PRS > P50) and receiving high radiation dose in the temporal lobes (D0.5CC > 65 Gy) had an approximate 50-fold risk over individuals with low PRS and receiving low radiation dose (HR = 50.09, 95 %CI = 24.27-103.35), showing an additive joint effect (Pinteraction < 0.001). By combining PRS with clinical factors including age, tumor stage, and radiation dose of temporal lobes, the predictive accuracy was significantly improved with C-index increased from 0.78 to 0.85 (P = 1.63 x 10(-2)).Conclusions: The PRS, together with clinical factors, could improve RBI risk stratification and implies person-alized radiotherapy.

Automated summary

In this study, researchers aimed to establish a predictive model for radiation-induced brain injury (RBI) in nasopharyngeal carcinoma (NPC) patients by incorporating clinical factors and newly developed genetic variants. They conducted a large-scale retrospective study and a genome-wide association study to develop a polygenic risk score (PRS) for RBI risk prediction. The results showed that the PRS, combined with clinical factors, improved the accuracy of RBI risk stratification and suggested personalized radiotherapy.