Predictors of Radiation-induced Hypothyroidism in Nasopharyngeal Carcinoma Survivors after Intensity-modulated Radiotherapy

Author(s):  
Ruiping Zhai ◽  
Yingchen Lyu ◽  
Mengshan Ni ◽  
Fangfang Kong ◽  
Chengrun Du ◽  
...  

Abstract BackgroundThe aim of the study is to identify clinical and dosimetric factors that could predict the risk of hypothyroidism in nasopharyngeal carcinoma (NPC) patients following intensity-modulated radiotherapy (IMRT). MethodsA total of 404 non-metastatic NPC patients were included in our study. All patients were treated with IMRT. The thyroid function were performed for all patients before and after radiation at regular intervals. The time onset for developing hypothyroidism was defined as the time interval between the completion of RT and the first recorded abnormal thyroid hormone test. The cumulative incidence rates of hypothyroidism were estimated using Kaplan-Meier method. Univariate and multivariate Cox regression analyses were performed to detect the most promising factors that were associated with hypothyroidism. ResultsMedian follow up was 60.6 months. The 3-, 5- and 7- year cumulative incidence rate of hypothyroidism was 39.4%, 49.1% and 54.7%, respectively. The median time to primary hypothyroidism and central hypothyroidism were 15.4 months (range: 2.9-83.8 months) and 29.9 months (range: 19.8-93.6 months), respectively. Univariate and multivariate analyses revealed that younger age, female gender and small thyroid volume were the most important factors in predicting the risk of hypothyroidism. Dtmean (mean dose of thyroid), V30-V50 (percentage of thyroid volume receiving a certain dose level) and VS45-VS60 (the absolute volumes of thyroid spared from various dose levels) remained statistically significant in multivariate analyses. Cutoff points of 45 Gy (Dtmean), 80% (Vt40) and 5 cm3 (VS45Gy) were identified to classify patients as high-risk or low-risk group. ConclusionThyroid Vt40 predicted the risk of hypothyroidism after IMRT for NPC patients. We recommended plan optimization objectives to reduce thyroid V40 to 80%.Trial registration: retrospectively registered.

2021 ◽  
Vol 11 ◽  
Author(s):  
Guanzhu Shen ◽  
Yinglin Peng ◽  
Jian Li ◽  
Haijun Wu ◽  
Guangshun Zhang ◽  
...  

ObjectiveTo evaluate the incidence of hypothyroidism in patients with nasopharyngeal carcinoma after intensity-modulated radiotherapy (IMRT), analyze its correlation with multiple influencing factors such as thyroid exposure dose, thyroid volume, and gender, and construct a multivariate-based normal tissue complication probability (NTCP) model for the occurrence of hypothyroidism after IMRT.Materials and MethodsThe thyroid hormone levels of patients at different points in time before and after radiotherapy were tested, and statistics on the incidence of hypothyroidism after treatment were obtained. The dose-volume data of patients’ thyroids were converted into EQD2 equivalent dose values. The correlation between hypothyroidism after radiotherapy and thyroid exposure dose, thyroid volume, gender, and other factors was analyzed, and an NTCP model was constructed.ResultsA total of 69 patients with nasopharyngeal carcinoma were enrolled in this study. Twelve months after radiotherapy, a total of 24 patients (34.8%) developed hypothyroidism. Univariate analysis and multivariate analysis revealed that the average thyroid dose and thyroid volume are the most important factors affecting hypothyroidism after radiotherapy. The NTCP model constructed based on the average dose and thyroid volume has a good degree of fit.ConclusionThe volume and average dose of the thyroid gland are the key factors affecting the occurrence of hypothyroidism in patients with nasopharyngeal carcinoma after radiotherapy. The NTCP model constructed based on multivariate construction suggests that reducing the average dose of the thyroid to the greatest extent is an effective way to protect thyroid functions.


2016 ◽  
Vol 7 (3) ◽  
pp. 276-282 ◽  
Author(s):  
Ji-Jin Yao ◽  
Guan-Qun Zhou ◽  
Ya-Nan Jin ◽  
Wang-Jian Zhang ◽  
Li Lin ◽  
...  

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