Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2025
A predictive model based on the dosimetric parameters of the parotid stem cell region to assess the recovery of radiation-induced xerostomia in long-term survivors of nasopharyngeal carcinoma after radical radiotherapy.
СтатьяМногоцентровое исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Zhang Mai, Gong Jie, Zhu Yong, Yang Zhi-Hua, Zhou Yong-Chun, Hu Jing, Guo Hui, Li Hai-Liang, Shi Quan, Wang Zhong-Fei, Liu Chang-Hao, Su Ning, Zhao Li-Na, Shi Mei, Zang Jian
Аннотация
BACKGROUND: For nasopharyngeal carcinoma (NPC) patients with bilateral parotids near high - dose areas, more research is needed on how radiation to the parotid stem cell region (SCR) impacts xerostomia. This multicenter study aims to explore SCR radiation dosimetric parameters and clinical factors that influence recovery from radiation-induced xerostomia in long-term survivors.
METHODS: We analyzed 648 NPC patients from four Chinese centers who underwent radical radiotherapy. Recovery was assessed via patient-reported (PRO) and physician-assessed (PAO) outcomes. The Cox proportional hazards model identified key clinical and dosimetric factors for recovery, aiming to develop an integrated prediction model. Prognostic performance was evaluated with time-dependent area under the receiver operating characteristic curve (AUC), and Cumulative incidence curve estimated recovery across different risk groups.
RESULTS: Patients were randomly allocated to training and validation sets at 7:3. Multivariate COX analysis identified age (p=0.000), induction chemotherapy (p=0.003), SCR Dmean (p=0.047), and SCR V20 (p=0.000) as key predictors for xerostomia recovery. A nomogram model using these factors outperformed individual ones in predicting xerostomia recovery for PRO recovery, 3-year/5-year AUC was 0.77/0.806 (training) and 0.773/0.81 (validation); for PAO recovery, it was 0.756/0.786 (training) and 0.748/0.786 (validation). Based on the median score derived from the model, the entire cohort was stratified into high-risk and low-risk groups. Notably, the low-risk group demonstrated a significantly higher recovery rate in both the training set and validation set (p < 0.001).
CONCLUSION: A model combining SCR dosimetry and clinical factors effectively predicts xerostomia recovery.
METHODS: We analyzed 648 NPC patients from four Chinese centers who underwent radical radiotherapy. Recovery was assessed via patient-reported (PRO) and physician-assessed (PAO) outcomes. The Cox proportional hazards model identified key clinical and dosimetric factors for recovery, aiming to develop an integrated prediction model. Prognostic performance was evaluated with time-dependent area under the receiver operating characteristic curve (AUC), and Cumulative incidence curve estimated recovery across different risk groups.
RESULTS: Patients were randomly allocated to training and validation sets at 7:3. Multivariate COX analysis identified age (p=0.000), induction chemotherapy (p=0.003), SCR Dmean (p=0.047), and SCR V20 (p=0.000) as key predictors for xerostomia recovery. A nomogram model using these factors outperformed individual ones in predicting xerostomia recovery for PRO recovery, 3-year/5-year AUC was 0.77/0.806 (training) and 0.773/0.81 (validation); for PAO recovery, it was 0.756/0.786 (training) and 0.748/0.786 (validation). Based on the median score derived from the model, the entire cohort was stratified into high-risk and low-risk groups. Notably, the low-risk group demonstrated a significantly higher recovery rate in both the training set and validation set (p < 0.001).
CONCLUSION: A model combining SCR dosimetry and clinical factors effectively predicts xerostomia recovery.