Normal tissue complication probability (NTCP) models for predicting temporal lobe injury after intensity-modulated radiotherapy in nasopharyngeal carcinoma: A large registry-based retrospective study from China. (April 2021)

• Record Type: Journal Article
• Authors: Wen, Dan-Wan; Lin, Li; Mao, Yan-Ping; Chen, Chun-Yan; Chen, Fo-Ping; Wu, Chen-Fei; Huang, Xiao-Dan; Li, Zhi-Xuan; Xu, Si-Si; Kou, Jia; Yang, Xing-Li; Ma, Jun; Sun, Ying; Zhou, Guan-Qun
• Is Part Of: Radiotherapy and oncology. Volume 157(2021)
• Page Start: 99
• Page End: 105
• Publication Date: 2021-04
• Subjects: Intensity-modulated radiotherapy -- Machine learning -- Nasopharyngeal carcinoma -- Nomogram -- Normal tissue complication probability -- Temporal lobe injury; Oncology -- Periodicals; Radiotherapy -- Periodicals; Tumors -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- radiotherapy -- Periodicals; Radiotherapy -- Periodicals; Radiothérapie -- Périodiques; Cancérologie -- Périodiques; Tumeurs -- Périodiques; Electronic journals; 616.9940642
• DOI: 10.1016/j.radonc.2021.01.008
• Languages: English
• ISSNs: 0167-8140

Abstract

Highlights: Inclusion of clinical factors improved the dose-based model in predicting temporal lobe injury. D 0.5cc of 65.06 Gy was the tolerance dose of the temporal lobe. Reducing D 0.5cc may decrease TLI risk, especially in older patients with advanced T stage. A nomogram with age, T stage, and D 0.5cc could predict temporal lobe injury precisely. Abstract: Purpose: To develop predictive models with dosimetric and clinical variables for temporal lobe injury (TLI) in nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT). Materials and methods: Data of 8194 NPC patients who received IMRT-based treatment were retrospectively reviewed. TLI was diagnosed by magnetic resonance imaging. Dosimetric factors were selected by penalized regression and machine learning, with area under the receiver operating curve (AUC) calculated. Cox proportional hazards models containing the most predictive dosimetric factor with/without clinical variables were performed. A nomogram was generated as a visualization of Cox regression for predicting TLI-free survival. Results: During median follow-up of 66.8 months (interquartile range [IQR] 54.2–82.2 months), 12.1% of patients (989/8194) developed TLI. Median latency from IMRT to TLI was 36 months (IQR 28–47 months). D 0.5cc (dose delivered to 0.5-cm 3 temporal-lobe volume) was the most predictive dosimetric factor (AUC: 0.799). Tolerance dose for 5% and 50% probabilities to develop TLI in 5 years were 65.06 Gy (95% confidence interval [CI]: 64.19–65.92) and 89.75 Gy (95% CI: 87.39–92.11), respectively. A nomogram comprising age, T stage, and D 0.5cc significantly outperformed the model with only D 0.5cc in predicting TLI (C-index: 0.78 vs. 0.737 in train set; 0.775 vs. 0.73 in test set; both P < 0.001). The nomogram-defined high-risk group had worse 5-year TLI-free survival. Conclusions: D 0.5cc of 65.06 Gy was the tolerance dose of the temporal lobe. Reducing D 0.5cc decreased risk of TLI, especially in older patients with advanced T stage. The nomogram could predict TLI precisely and allow individualized follow-up management.