Hematological Indexes Can Be Used to Predict the Incidence of Hypothyroidism in Nasopharyngeal Carcinoma Patients after Radiotherapy
Zhou, Ling1,2,3,4; Chen, Jia5; Tao, Chang-Juan1,2,3; Huang, Shuang1,2,3; Zhang, Jiang1,2,3; Shen, Wei5; Zhu, Chao-Nan5; Chen, Ming1,2,3; Yu, Zhong-Hua6; Chen, Yuan-Yuan1,2,3
刊名BIOMED RESEARCH INTERNATIONAL
2020-05-13
卷号2020
ISSN号2314-6133
DOI10.1155/2020/3860936
通讯作者Chen, Yuan-Yuan(chenyy@zjcc.org.cn)
英文摘要Background. This study explored the relationship between thyroid-associated antibodies, immune cells, and hypothyroidism to establish a predictive model for the incidence of hypothyroidism in patients with nasopharyngeal carcinoma (NPC) after radiotherapy. Methods. A total of 170 patients with NPC treated at the Cancer Hospital of University of Chinese Academy of Sciences between January 2015 and August 2018 were included. The complete blood count, biochemical, coagulation function, immune cells, and thyroid-associated antibodies tested before radiotherapy were evaluated. A logistic regression model was performed to elucidate which hematological indexes were related to hypothyroidism development. A predictive model for the incidence of hypothyroidism was established. Internal verification of the multifactor model was performed using the tenfold cross-validation method. Results. The univariate analysis showed that immune cells had no statistically significant differences among the patients with and without hypothyroidism. Sex, N-stage, antithyroid peroxidase antibody (TPO-Ab), antithyroglobulin antibody (TG-Ab), thyroglobulin (TG), and fibrinogen (Fb) were associated with hypothyroidism. Males and early N-stage were protective factors of thyroid function, whereas increases in TPO-Ab, TG-Ab, TG, and Fb counts were associated with an increased rate of hypothyroidism incidence. The multivariate analysis showed that TPO-Ab, TG-Ab, TG, and Fb were independent predictors of hypothyroidism. The comprehensive effect of the significant model, including TPO-Ab, TG-Ab, TG, and Fb counts, represented the optimal method of predicting the incidence of radiation-induced hypothyroidism (AUC=0.796). Tenfold cross-validation methods were applied for internal validation. The AUCs of the training and testing sets were 0.792 and 0.798, respectively. Conclusion. A model combining TPO-Ab, TG-Ab, TG, and Fb can be used to screen populations at a high risk of developing hypothyroidism after radiotherapy.
资助项目National Natural Science Foundation of China[81672971] ; Key Technologies Research and Development Program[2017YFC0113201]
WOS关键词CORONARY-HEART-DISEASE ; TO-LYMPHOCYTE RATIO ; SUBCLINICAL HYPOTHYROIDISM ; RISK
WOS研究方向Biotechnology & Applied Microbiology ; Research & Experimental Medicine
语种英语
出版者HINDAWI LTD
WOS记录号WOS:000537144100004
资助机构National Natural Science Foundation of China ; Key Technologies Research and Development Program
内容类型期刊论文
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/103155]  
专题中国科学院合肥物质科学研究院
通讯作者Chen, Yuan-Yuan
作者单位1.Chinese Acad Sci, Inst Canc & Basic Med ICBM, Hangzhou, Peoples R China
2.Univ Chinese Acad Sci, Canc Hosp, Dept Radiat Oncol, Hangzhou, Peoples R China
3.Zhejiang Canc Hosp, Dept Radiat Oncol, Hangzhou, Peoples R China
4.Guangdong Med Univ, Postgrad Educ, Zhanjiang, Peoples R China
5.Hangzhou YITU Healthcare Technol Co Ltd, Hangzhou, Peoples R China
6.Guangdong Med Univ, Affiliated Hosp, Dept Oncol, Zhanjiang, Peoples R China
推荐引用方式
GB/T 7714
Zhou, Ling,Chen, Jia,Tao, Chang-Juan,et al. Hematological Indexes Can Be Used to Predict the Incidence of Hypothyroidism in Nasopharyngeal Carcinoma Patients after Radiotherapy[J]. BIOMED RESEARCH INTERNATIONAL,2020,2020.
APA Zhou, Ling.,Chen, Jia.,Tao, Chang-Juan.,Huang, Shuang.,Zhang, Jiang.,...&Chen, Yuan-Yuan.(2020).Hematological Indexes Can Be Used to Predict the Incidence of Hypothyroidism in Nasopharyngeal Carcinoma Patients after Radiotherapy.BIOMED RESEARCH INTERNATIONAL,2020.
MLA Zhou, Ling,et al."Hematological Indexes Can Be Used to Predict the Incidence of Hypothyroidism in Nasopharyngeal Carcinoma Patients after Radiotherapy".BIOMED RESEARCH INTERNATIONAL 2020(2020).
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