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Park YI, Cho MS, Chang JS, Kim JS, Kim YB, Lee IJ, Hong CS, Choi SH. Normal tissue complication probability models of hypothyroidism after radiotherapy for breast cancer. Clin Transl Radiat Oncol 2024; 45:100734. [PMID: 38317677 PMCID: PMC10839258 DOI: 10.1016/j.ctro.2024.100734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 01/19/2024] [Accepted: 01/21/2024] [Indexed: 02/07/2024] Open
Abstract
Purpose We aimed to develop Lyman-Kutcher-Burman (LKB) and multivariable normal tissue complication probability (NTCP) models to predict the risk of radiation-induced hypothyroidism (RIHT) in breast cancer patients. Materials and methods A total of 1,063 breast cancer patients who underwent whole breast irradiation between 2009 and 2016 were analyzed. Individual dose-volume histograms were used to generate LKB and multivariable logistic regression models. LKB model was fit using the thyroid radiation dose-volume parameters. A multivariable model was constructed to identify potential dosimetric and clinical parameters associated with RIHT. Internal validation was conducted using bootstrapping techniques, and model performance was evaluated using the area under the curve (AUC) and Hosmer-Lemeshow (HL) goodness-of-fit test. Results RIHT developed in 4 % of patients with a median follow-up of 77.7 months. LKB and multivariable NTCP models exhibited significant agreement between the predicted and observed results (HL P values > 0.05). The multivariable NTCP model outperformed the LKB model in predicting RIHT (AUC 0.62 vs. 0.54). In the multivariable model, systemic therapy, age, and percentage of thyroid volume receiving ≥ 10 Gy (V10) were significant prognostic factors for RIHT. The cumulative incidence of RIHT was significantly higher in patients who exceeded the cut-off values for all three risk predictors (systemic therapy, age ≥ 40 years, and thyroid V10 ≥ 26 %, P < 0.005). Conclusions Systemic therapy, age, and V10 of the thyroid were identified as strong risk factors for the development of RIHT. Our NTCP models provide valuable insights to clinicians for predicting and preventing hypothyroidism by identifying high-risk patients.
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Affiliation(s)
- Ye-In Park
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Min-Seok Cho
- Department of Radiation Oncology, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Gyeonggi do, South Korea
| | - Jee Suk Chang
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea
- BC Cancer - Vancouver Centre, Vancouver, British Columbia, Canada
| | - Jin Sung Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Yong Bae Kim
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Ik Jae Lee
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Chae-Seon Hong
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea
| | - Seo Hee Choi
- Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Seoul, Korea
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Wongwattananard S, Prayongrat A, Srimaneekarn N, Hayter A, Sophonphan J, Kiatsupaibul S, Veerabulyarith P, Rakvongthai Y, Ritlumlert N, Kitpanit S, Kannarunimit D, Lertbutsayanukul C, Chakkabat C. A multivariable normal tissue complication probability model for predicting radiation-induced hypothyroidism in nasopharyngeal carcinoma patients in the modern radiotherapy era. JOURNAL OF RADIATION RESEARCH 2024; 65:119-126. [PMID: 37996086 PMCID: PMC10803165 DOI: 10.1093/jrr/rrad091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/10/2023] [Indexed: 11/25/2023]
Abstract
Radiation-induced hypothyroidism (RHT) is a common long-term complication for nasopharyngeal carcinoma (NPC) survivors. A model using clinical and dosimetric factors for predicting risk of RHT could suggest a proper dose-volume parameters for the treatment planning in an individual level. We aim to develop a multivariable normal tissue complication probability (NTCP) model for RHT in NPC patients after intensity-modulated radiotherapy or volumetric modulated arc therapy. The model was developed using retrospective clinical data and dose-volume data of the thyroid and pituitary gland based on a standard backward stepwise multivariable logistic regression analysis and was then internally validated using 10-fold cross-validation. The final NTCP model consisted of age, pretreatment thyroid-stimulating hormone and mean thyroid dose. The model performance was good with an area under the receiver operating characteristic curve of 0.749 on an internal (200 patients) and 0.812 on an external (25 patients) validation. The mean thyroid dose at ≤45 Gy was suggested for treatment plan, owing to an RHT incidence of 2% versus 61% in the >45 Gy group.
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Affiliation(s)
- Siriporn Wongwattananard
- Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
| | - Anussara Prayongrat
- Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
| | - Natchalee Srimaneekarn
- Department of Anatomy, Faculty of Dentistry, Mahidol University, No. 6, Yothi Road, Ratchathewi District, Bangkok 10400, Thailand
| | - Anthony Hayter
- Department of Business Information and Analytics, University of Denver, 2101 S. University Blvd., Denver, CO 80208-8921, USA
| | - Jiratchaya Sophonphan
- HIV-NAT, Thai Red Cross AIDS Research Centre, 104, Ratchadamri Road, Pathumwan District, Bangkok 10330, Thailand
| | - Seksan Kiatsupaibul
- Department of Statistics and Social Innovation Research Unit, Faculty of Commerce and Accountancy, Chulalongkorn University, 254, Phayathai Road, Pathumwan District, Bangkok 10330, Thailand
| | - Puvarith Veerabulyarith
- Department of Statistics and Social Innovation Research Unit, Faculty of Commerce and Accountancy, Chulalongkorn University, 254, Phayathai Road, Pathumwan District, Bangkok 10330, Thailand
| | - Yothin Rakvongthai
- Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
- Department of Radiology, Faculty of Medicine, Chulalongkorn University Biomedical Imaging Group, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
| | - Napat Ritlumlert
- Department of Radiology, Faculty of Medicine, Chulalongkorn University Biomedical Imaging Group, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
- Biomedical Engineering Program, Faculty of Engineering, Chulalongkorn University, 254, Phayathai Road, Pathumwan District, Bangkok 10330, Thailand
| | - Sarin Kitpanit
- Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
| | - Danita Kannarunimit
- Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
| | - Chawalit Lertbutsayanukul
- Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
| | - Chakkapong Chakkabat
- Division of Radiation Oncology, Department of Radiology, Faculty of Medicine, Chulalongkorn University, 1873 Rama IV Road, Pathumwan District, Bangkok 10330, Thailand
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Wang C, Hou Y, Wang L, Yang Y, Li X. Analysis of correlative risk factors for radiation-induced hypothyroidism in head and neck tumors. BMC Cancer 2024; 24:5. [PMID: 38166748 PMCID: PMC10762937 DOI: 10.1186/s12885-023-11749-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024] Open
Abstract
OBJECTIVE The aim of the study is to identify clinical and dosimetric factors that could predict the risk of radiation-induced hypothyroidism(RIHT) in head and neck cancer(HNC) patients following intensity-modulated radiotherapy(IMRT). METHODS A total of 103 HNC patients were included in our study. General clinical characteristic and dosimetric data of all recruited patients were analyzed, respectively. The univariate and multivariate logistic regression anlalysis were successively conducted to identify optimal predictors, which aim to construct the nomogram. And the joint prediction was performed. RESULTS The incidence of patients with HNC was 36.9% (38/103). Among the clinical factors, gender, N stage, chemotherapy, frequency of chemotherapy and surgery involving the thyroid were related to RIHT. Logistic regression analysis showed that thyroid volume, Dmean, VS45, VS50, VS60 and V30,60 were independent predictors of RIHT, which were also incorporated in the nomogram. An AUC of 0.937 (95%CI, 0.888-0.958) also was showed outstanding resolving ability of the nomogram. When the volume of the thyroid was greater than 10.6 cm3, the incidence of RIHT was 14.8%, and when the volume of the thyroid was equal to or smaller than 10.6 cm3, the incidence was 72.5%. The incidence rates of RIHT in the group with VS60≦8.4cm3 and VS60 > 8.4cm3 were 61.4% and 19.3%, respectively. CONCLUSIONS Thyroid volume and thyroid VS60 are independent predictors of RIHT in patients with HNC. Moreover, more attention should be paid to patients with thyroid volume ≤ 10.6cm3. Thyroid VS60 > 8.4cm3 may be a useful threshold for predicting the development of RIHT. The nomogram conducted by the research may become a potential and valuable tool that could individually predict the risk of RIHT for HNC patients.
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Affiliation(s)
- Chan Wang
- Department of Radiation Oncology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yanjie Hou
- Department of Radiation Oncology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Lili Wang
- Department of Radiation Oncology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Ye Yang
- Department of Radiation Oncology, The First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xianfeng Li
- Department of Radiation Oncology, The First Hospital of Shanxi Medical University, Taiyuan, China.
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Yang SS, Peng QH, Wu AQ, Zhang BY, Liu ZQ, Chen EN, Xie FY, OuYang PY, Chen CY. Radiomics and dosiomics for predicting radiation-induced hypothyroidism and guiding intensity-modulated radiotherapy. iScience 2023; 26:108394. [PMID: 38047064 PMCID: PMC10690639 DOI: 10.1016/j.isci.2023.108394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 06/28/2023] [Accepted: 11/01/2023] [Indexed: 12/05/2023] Open
Abstract
To guide individualized intensity-modulated radiotherapy (IMRT), we developed and prospectively validated a multiview radiomics risk model for predicting radiation-induced hypothyroidism in patients with nasopharyngeal carcinoma. And simulated radiotherapy plans with same dose-volume-histogram (DVH) but different dose distributions were redesigned to explore the clinical application of the multiview radiomics risk model. The radiomics and dosiomics were built based on selected radiomics and dosiomics features from planning computed tomography and dose distribution, respectively. The multiview radiomics risk model that integrated radiomics, dosiomics, DVH parameters, and clinical factors had better performance than traditional normal tissue complication probability models. And multiview radiomics risk model could identify differences of patient hypothyroidism-free survival that cannot be stratified by traditional models. Besides, two redesigned simulated plans further verified the clinical application and advantage of the multiview radiomics risk model. The multiview radiomics risk model was a promising method to predict radiation-induced hypothyroidism and guide individualized IMRT.
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Affiliation(s)
- Shan-Shan Yang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China
- Department of Radiation Oncology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250021, China
| | - Qing-He Peng
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China
| | - Ai-Qian Wu
- Department of Radiation Oncology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510405, China
| | - Bao-Yu Zhang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China
| | - Zhi-Qiao Liu
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China
| | - En-Ni Chen
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China
| | - Fang-Yun Xie
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China
| | - Pu-Yun OuYang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China
| | - Chun-Yan Chen
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Guangzhou, Guangdong 510060, China
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Tsai MH, Chang JTC, Lu HH, Wu YH, Pao TH, Cheng YJ, Zheng WY, Chou CY, Lin JH, Yu T, Chiang JH. Development and validation of a machine learning model of radiation-induced hypothyroidism with clinical and dose-volume features. Radiother Oncol 2023; 189:109911. [PMID: 37709053 DOI: 10.1016/j.radonc.2023.109911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/02/2023] [Accepted: 09/08/2023] [Indexed: 09/16/2023]
Abstract
BACKGROUND AND PURPOSE Radiation-induced hypothyroidism (RIHT) is a common but underestimated late effect in head and neck cancers. However, no consensus exists regarding risk prediction or dose constraints in RIHT. We aimed to develop a machine learning model for the accurate risk prediction of RIHT based on clinical and dose-volume features and to evaluate its performance internally and externally. MATERIALS AND METHODS We retrospectively searched two institutions for patients aged >20 years treated with definitive radiotherapy for nasopharyngeal or oropharyngeal cancer, and extracted their clinical information and dose-volume features. One was designated the developmental cohort, the other as the external validation cohort. We compared the performances of machine learning models with those of published normal tissue complication probability (NTCP) models. RESULTS The developmental and external validation cohorts consisted of 378 and 49 patients, respectively. The estimated cumulative incidence rates of grade ≥1 hypothyroidism were 53.5% and 61.3% in the developmental and external validation cohorts, respectively. Machine learning models outperformed traditional NTCP models by having lower Brier scores at every time point and a lower integrated Brier score, while demonstrating a comparable calibration index and mean area under the curve. Even simplified machine learning models using only thyroid features performed better than did traditional NTCP algorithms. The machine learning models showed consistent performance between folds. The performance in a previously unseen external validation cohort was comparable to that of the cross-validation. CONCLUSIONS Our model outperformed traditional NTCP models, with additional capabilities of predicting the RIHT risk at individual time points. A simplified model using only thyroid dose-volume features still outperforms traditional NTCP models and can be incorporated into future treatment planning systems for biological optimization.
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Affiliation(s)
- Mu-Hung Tsai
- Institute of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan; Department of Radiation Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Joseph T C Chang
- Department of Radiation Oncology, Chang Gung Memorial Hospital, Chang Gung University, Linkou, Taiwan
| | - Hsi-Huei Lu
- Division of Nuclear Medicine, Department of Medical Imaging, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan
| | - Yuan-Hua Wu
- Department of Radiation Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Tzu-Hui Pao
- Department of Radiation Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Yung-Jen Cheng
- Department of Radiation Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Wen-Yen Zheng
- Department of Radiation Oncology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Chen-Yu Chou
- Department of Radiation Oncology, Chang Gung Memorial Hospital, Chang Gung University, Linkou, Taiwan
| | - Jing-Han Lin
- Division of Endocrinology, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Tsung Yu
- Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jung-Hsien Chiang
- Institute of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan; Institute of Medical Informatics, National Cheng Kung University, Tainan, Taiwan.
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Lian CL, Zhuo RG, Zhou R, Yu YF, Zhou P, Lin Q, Wu SG. Risk factors of early thyroid dysfunction after definitive radiotherapy in nasopharyngeal carcinoma patients. Head Neck 2023; 45:2344-2354. [PMID: 37415457 DOI: 10.1002/hed.27448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 06/22/2023] [Accepted: 06/25/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND To explore the patterns and risk factors of early thyroid dysfunction in nasopharyngeal carcinoma (NPC) patients within 1 year after intensity-modulated radiation therapy (IMRT). METHODS Patients with NPC who received definitive IMRT between April 2016 and April 2020 were included. All patients had normal thyroid function before definitive IMRT. The chi-square test, Student's T-test, Mann-Whitney U test, Kaplan-Meier method, receiver operating characteristics curve, and Cox proportional hazard analysis were used for statistical analysis. RESULTS A total of 132 NPC patients were identified. Of these patients, 56 (42.4%) had hypothyroidism and 17 (12.9%) had hyperthyroidism. The median time to hypothyroidism and hyperthyroidism was 9 months (range, 1-12 months) and 1 month (range, 1-6 months) after definitive IMRT, respectively. In patients with hypothyroidism, 41 (73.2%) had subclinical hypothyroidism and 15 (26.8%) had clinical hypothyroidism. In those with hyperthyroidism, 12 patients (70.6%) had subclinical hyperthyroidism, and five patients (29.4%) had clinical hyperthyroidism. Age, clinical stage, thyroid volume, and V45 were independent risk factors for early radiation-induced hypothyroidism within 1 year after IMRT. Patients aged <47 years, stage III/IV disease, or pre-irradiation thyroid volume < 14 cm3 had higher risks of developing hypothyroidism. CONCLUSION Primary subclinical hypothyroidism was the most common subtype of early thyroid dysfunction in NPC patients within 1 year after IMRT. Age, clinical stage, thyroid volume, and V45 were independent risk factors for early radiation-induced hypothyroidism in NPC patients.
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Affiliation(s)
- Chen-Lu Lian
- Department of Radiation Oncology, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People's Republic of China
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center (Xiamen branch), Xiamen, People's Republic of China
| | - Ren-Gong Zhuo
- Xiamen Key Laboratory of Chiral Drugs, School of Medicine, Xiamen University, Xiamen, People's Republic of China
| | - Rui Zhou
- Department of Radiation Oncology, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People's Republic of China
| | - Yi-Feng Yu
- Department of Radiation Oncology, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People's Republic of China
| | - Ping Zhou
- Department of Radiation Oncology, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People's Republic of China
| | - Qin Lin
- Department of Radiation Oncology, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People's Republic of China
| | - San-Gang Wu
- Department of Radiation Oncology, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, the First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People's Republic of China
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Rooney MK, Andring LM, Corrigan KL, Bernard V, Williamson TD, Fuller CD, Garden AS, Gunn B, Lee A, Moreno AC, Morrison WH, Phan J, Rosenthal DI, Spiotto M, Frank SJ. Hypothyroidism following Radiotherapy for Head and Neck Cancer: A Systematic Review of the Literature and Opportunities to Improve the Therapeutic Ratio. Cancers (Basel) 2023; 15:4321. [PMID: 37686597 PMCID: PMC10486996 DOI: 10.3390/cancers15174321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/23/2023] [Accepted: 08/25/2023] [Indexed: 09/10/2023] Open
Abstract
(1) Background: Radiotherapy (RT) is a central component for the treatment of many head and neck cancers. In this systematic review of the literature, we aimed to characterize and quantify the published evidence on RT-related hypothyroidism, including estimated incidence, clinical risk factors, and dosimetric parameters that may be used to guide clinical decision making. Furthermore, we aimed to identify potential areas of improvement in the prevention and clinical management of RT-induced hypothyroidism, including the role of modern advanced therapeutic techniques. (2) Methods: We conducted a systemic review of the literature in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. PubMed and Google Scholar were searched to identify original research articles describing the incidence, mechanism, dosimetry, treatment, or prevention of radiation-related hypothyroidism for adults receiving RT for the treatment of head and neck cancers. The snowball method was used to identify additional articles. For identified articles, we tabulated several datapoints, including publication date, patient sample size, estimated hypothyroidism incidence, cancer site/type, follow-up period, radiation modality and technique, use of multimodality therapy, method of thyroid function evaluation, and proposed dosimetric predictors of hypothyroidism. (3) Results: One hundred and eleven articles met inclusion criteria, reflecting a range of head and neck cancer subtypes. There was a large variation in the estimated incidence of RT-related hypothyroidism, with a median estimate of 36% (range 3% to 79%). Reported incidence increased in later publication dates, which was likely related to improved screening and longer follow up. There were a wide variety of predictive metrics used to identify patients at high risk of hypothyroidism, the most common of which were volumetric and mean dosimetrics related to the thyroid gland (Vxx%, Dmean). More recently, there has been increasing evidence to suggest that the thyroid gland volume itself and the volume of the thyroid gland spared from high-dose radiation (VSxx) may better predict thyroid function after RT. There were no identified studies investigating the role of advanced radiotherapeutic techniques such as MRI-guided RT or particle therapy to decrease RT-related hypothyroidism. Conclusions: Hypothyroidism is a common toxicity resulting from therapeutic radiation for head and neck cancer with recent estimates suggesting 40-50% of patients may experience hypothyroidism after treatment. Dosimetric predictive models are increasingly able to accurately identify patients at risk of hypothyroidism, especially those utilizing thyroid VS metrics. Further investigation regarding the potential for advanced radiotherapeutic therapies to decrease RT-induced thyroid dysfunction is needed.
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Affiliation(s)
- Michael K. Rooney
- Department of Radiation Oncology, MD Anderson Cancer Center, Houston, TX 77030, USA (V.B.); (T.D.W.); (S.J.F.)
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Frometa-Castillo T, Pyakuryal A, Narayanasamy G, Wals-Zurita A, Mesbahi A. The use of the normal tissue non-complication probability (NTCP0) in the safety evaluations as a new alternative of assessing the side-effects of the radiation oncology treatments. Int J Radiat Biol 2023; 99:656-662. [PMID: 35930494 DOI: 10.1080/09553002.2022.2110299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Abstract
PURPOSE To encourage the use of the NTCP0 for evaluating safety as a new alternative of assessing the S-Es of the radiation oncology treatments; and the use of the 'NTCP0cal' methodology that calculates/estimates NTCP0. METHOD Revisions of studies related to use of the NTCP in the evaluations of S-Es. Development of the first version of the Matlab application of our methodology, which provides three options, two of them employ the well-known aspects of a phenomenological model, or the relationship with the TNTCP; where NTCP0 = 100%-TNTCP; and the third option determines NTCP0 from an assumed NTCP discrete probabilistic distribution from the binomial distribution, where one of its parameters is automatically defined from a databased of the Disease locations Vs. Late complications. RESULT As result of revisions of some QUANTEC studies, we can say that: (1) The majority of current NTCP models are DVH-based; (2) The risk of toxicity is the way of evaluating the S-Es of the radiation oncology treatments; and (3) The NTCP are used mainly for evaluations of individual or principal complications or Endpoints of the radiation treatments. The 'NTCP0cal' Matlab application developed in this study has three calculation options. Two of the options provide additional graphical information about the distributions. CONCLUSIONS The NTCP0 is a new radiobiological concept, its introduction let to correct some current P + and UTCP formulations, and will allow evaluating S-Es in whatever activity involving ionizing radiation, like radiation treatments; and its phenomenological model function of dose prescribed (D = n*d) will allow calculating values of NTCP0 for a range of dose per fraction (d) in a treatment with a determined number of fractions (n), or for range of n for a constant d. The DVH is irrelevant for this model. For whatever radiation treatment given to a population of similar patients under similar circumstances, the NTCP0 is calculated as ratio of the number of patients without acute/late complications and total of them. When this number is unknown, then NTCP0 can be obtained using the 'NTCP0cal' application.
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Affiliation(s)
| | - Anil Pyakuryal
- Division of Science and Mathematics, University of District of Columbia, Washington, DC, USA
| | - Ganesh Narayanasamy
- Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, AR, USA
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Deligiorgi MV, Trafalis DT. The continuum of care of anticancer treatment-induced hypothyroidism in patients with solid non thyroid tumors: time for an intimate collaboration between oncologists and endocrinologists. Expert Rev Clin Pharmacol 2022; 15:531-549. [PMID: 35757870 DOI: 10.1080/17512433.2022.2093714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Hypothyroidism is a common adverse event of various anticancer treatment modalities, constituting a notable paradigm of the integration of the endocrine perspective into precision oncology. AREAS COVERED The present narrative review provides a comprehensive and updated overview of anticancer treatment-induced hypothyroidism in patients with solid non-thyroid tumors. A study search was conducted on the following electronic databases: PubMed, Google Scholar, Scopus.com, ClinicalTrials.gov, and European Union Clinical Trials Register from 2011 until August 2021. EXPERT OPINION In patients with solid non-thyroid tumors, hypothyroidism is a common adverse event of radiotherapy, high dose interleukin 2 (HD IL-2), interferon alpha (IFN-α), bexarotene, immune checkpoint inhibitors (ICPi), and tyrosine kinase inhibitors (TKIs), while chemotherapy may induce hypothyroidism more often than initially considered. The path forward for the management of anticancer treatment-induced hypothyroidism in patients with solid non-thyroid tumors is an integrated approach grounded on 5 pillars: prevention, vigilance, diagnosis, treatment and monitoring. Current challenges concerning anticancer treatment-induced hypothyroidism await counteraction, namely awareness of the growing list of related anticancer treatments, identification of predictive factors, counteraction of diagnostic pitfalls, tuning of thyroid hormone replacement, and elucidation of its prognostic significance. Close collaboration of oncologists with endocrinologists will provide optimal patient care.
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Affiliation(s)
- Maria V Deligiorgi
- Department of Pharmacology - Clinical Pharmacology Unit, National and Kapodistrian University of Athens, Faculty of Medicine, Athens, Greece
| | - Dimitrios T Trafalis
- Department of Pharmacology - Clinical Pharmacology Unit, National and Kapodistrian University of Athens, Faculty of Medicine, Athens, Greece
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10
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Zhai R, Lyu Y, Ni M, Kong F, Du C, Hu C, Ying H. Predictors of radiation-induced hypothyroidism in nasopharyngeal carcinoma survivors after intensity-modulated radiotherapy. Radiat Oncol 2022; 17:57. [PMID: 35313921 PMCID: PMC8935811 DOI: 10.1186/s13014-022-02028-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 03/09/2022] [Indexed: 11/13/2022] Open
Abstract
Background The 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). Methods A 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. Results Median 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. Conclusion Thyroid Vt40 highly predicted the risk of hypothyroidism after IMRT for NPC patients. We recommended plan optimization objectives to reduce thyroid Vt40 to 80%. Trial registration: Retrospectively registered.
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Affiliation(s)
- Ruiping Zhai
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Room 703, Building 1, Dong'an Road 270, Shanghai, 200032, China
| | - Yingchen Lyu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Room 703, Building 1, Dong'an Road 270, Shanghai, 200032, China
| | - Mengshan Ni
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Room 703, Building 1, Dong'an Road 270, Shanghai, 200032, China
| | - Fangfang Kong
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Room 703, Building 1, Dong'an Road 270, Shanghai, 200032, China
| | - Chengrun Du
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Room 703, Building 1, Dong'an Road 270, Shanghai, 200032, China
| | - Chaosu Hu
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Room 703, Building 1, Dong'an Road 270, Shanghai, 200032, China.,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Hongmei Ying
- Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Room 703, Building 1, Dong'an Road 270, Shanghai, 200032, China. .,Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
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Torshabi A. Investigation the efficacy of fuzzy logic implementation at image-guided radiotherapy. JOURNAL OF MEDICAL SIGNALS & SENSORS 2022; 12:163-170. [PMID: 35755973 PMCID: PMC9215832 DOI: 10.4103/jmss.jmss_76_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Revised: 04/05/2021] [Accepted: 10/24/2021] [Indexed: 11/04/2022]
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Chow JC, Cheung KM, Cheung GT, Tam AH, Lui JC, Lee FK, Au KH, Ng WT, Lee AW, Yiu HH. Dose-volume predictors of post-radiation primary hypothyroidism in head and neck cancer: a systematic review. Clin Transl Radiat Oncol 2022; 33:83-92. [PMID: 35128087 PMCID: PMC8807951 DOI: 10.1016/j.ctro.2022.01.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 01/20/2022] [Indexed: 12/09/2022] Open
Abstract
This systematic review included 29 studies (n = 4,530 patients) on dosimetric predictors of primary hypothyroidism in HNC. Average crude incidence of primary hypothyroidism after HNC radiotherapy was 41.4%. Thyroid Dmean and V50 were the most widely reported dosimetric predictors for hypothyroidism. Thyroid volume is a predictor of hypothyroidism (pooled aOR 0.89 per 1 cc increment) independent of radiation dosimetry. Thyroid gland constraints individualized for thyroid volume are crucial in HNC radiotherapy.
Background and Purpose This systematic review aims to identify radiation dose-volume predictors of primary hypothyroidism after radiotherapy in patients with head and neck cancer (HNC). Materials and methods We performed a systematic literature search of Medline, EMBASE and Web of Science from database inception to July 1, 2021 for articles that discuss radiation dose-volume predictors of post-radiation primary hypothyroidism in patients with HNC. Data on the incidence, clinical risk factors and radiation dose-volume parameters were extracted. A meta-analysis was performed using the random-effects model to estimate the pooled odds ratio (OR) of thyroid volume as a predictor of the risk of post-radiation hypothyroidism, adjusted for thyroid radiation dosimetry. Results Our search identified 29 observational studies involving 4,530 patients. With median follow-up durations ranging from 1.0 to 5.3 years, the average crude incidence of post-radiation primary hypothyroidism was 41.4 % (range, 10 %–57 %). Multiple radiation dose-volume parameters were associated with post-radiation primary hypothyroidism, including the thyroid mean dose (Dmean), minimum dose, V25, V30, V35, V45, V50, V30–60, VS45 and VS60. Thyroid Dmean and V50 were the most frequently proposed dosimetric predictors. The pooled adjusted OR of thyroid volume on the risk of post-radiation primary hypothyroidism was 0.89 (95 % confidence interval, 0.85–0.93; p < 0.001) per 1 cc increment. Conclusion Post-radiation primary hypothyroidism is a common late complication after radiotherapy for HNC. Minimizing inadvertent exposure of the thyroid gland to radiation is crucial to prevent this late complication. Radiation dose-volume constraints individualized for thyroid volume should be considered in HNC radiotherapy planning.
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Löser A, Ramke K, Grohmann M, Krause L, Roser P, Greinert F, Finger A, Sommer M, Culmann E, Lorenz T, Becker S, Henze M, Schodrok D, von Grundherr J, Tribius S, Krüll A, Petersen C. The impact of nutritional counseling on thyroid disorders in head and neck cancer patients after (chemo)radiotherapy: results from a prospective interventional trial. Strahlenther Onkol 2021; 198:135-148. [PMID: 34724084 PMCID: PMC8789704 DOI: 10.1007/s00066-021-01865-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 10/03/2021] [Indexed: 11/27/2022]
Abstract
Objective To analyze the impact of nutritional counseling on the development of hypothyroidism after (chemo)radiotherapy in head and neck cancer patients to propose a new normal tissue complication probability (NTCP) model. Materials and methods At baseline, at the end of (chemo)radiotherapy, and during follow-up, thyroid-stimulating hormone (TSH) with free thyroxin (fT3 and fT4), nutritional status, and nutrient intake were prospectively analyzed in 46 out of 220 screened patients. Patients received (chemo)radiotherapy within an intervention (individual nutritional counseling every 2 weeks during therapy) and a control group (no nutritional counseling). Results Overall median follow-up was 16.5 [IQR: 12; 22] months. Fourteen patients (30.4%) presented with hypothyroidism after 13.5 [8.8; 17] months. During (chemo)radiotherapy, nutritional status worsened in the entire cohort: body mass index (p < 0.001) and fat-free mass index (p < 0.001) decreased, calorie deficit (p = 0.02) increased, and the baseline protein intake dropped (p = 0.028). The baseline selenium intake (p = 0.002) increased until the end of therapy. Application of the NTCP models by Rønjom, Cella, and Boomsma et al. resulted in good performance of all three models, with an AUC ranging from 0.76 to 0.78. Our newly developed NTCP model was based on baseline TSH and baseline ferritin. Model performance was good, receiving an AUC of 0.76 (95% CI: 0.61–0.87), with a sensitivity of 57.1% and specificity of 96.9% calculated for a Youden index of 0.73 (p = 0.004; area = 0.5). Conclusion Baseline TSH and ferritin act as independent predictors for radiotherapy-associated hypothyroidism. The exclusion of such laboratory chemistry parameters in future NTCP models may result in poor model performance.
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Affiliation(s)
- Anastassia Löser
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany.
| | - Kerstin Ramke
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Maximilian Grohmann
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Linda Krause
- Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Pia Roser
- Center for Internal Medicine, Department of Nephrology, Rheumatology and Endocrinology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Franziska Greinert
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Anna Finger
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Margaret Sommer
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Eva Culmann
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Tessa Lorenz
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Saskia Becker
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Marvin Henze
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Daniel Schodrok
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Julia von Grundherr
- University Medical Center Hamburg-Eppendorf, University Cancer Center Hamburg (UCCH), Martinistraße 52, 20246, Hamburg, Germany
| | - Silke Tribius
- Hermann Holthusen Institute for Radiation Oncology, Asklepios Hospital St. Georg, Lohmühlenstraße 5, 20099, Hamburg, Germany
| | - Andreas Krüll
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany.,Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
| | - Cordula Petersen
- Outpatient Center of the UKE GmbH, Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany.,Department of Radiotherapy and Radiation Oncology, University Medical Center Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg, Germany
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Shen G, Peng Y, Li J, Wu H, Zhang G, Zhao C, Deng X. Multivariate NTCP Model of Hypothyroidism After Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma. Front Oncol 2021; 11:714536. [PMID: 34504792 PMCID: PMC8421234 DOI: 10.3389/fonc.2021.714536] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 08/06/2021] [Indexed: 11/13/2022] Open
Abstract
Objective To 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 Methods The 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. Results A 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. Conclusion The 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.
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Affiliation(s)
- Guanzhu Shen
- Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.,Department of Radiation Oncology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yinglin Peng
- Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China.,School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Jian Li
- Department of Radiation Oncology, Central Hospital of Guangdong Nongken, Zhanjiang, China
| | - Haijun Wu
- Department of Radiation Oncology, Cancer Center, First People's Hospital of Foshan, Affiliated Foshan Hospital of Sun Yat-sen University, Foshan, China
| | - Guangshun Zhang
- Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Chong Zhao
- Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Xiaowu Deng
- Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
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Ren W, Liang B, Sun C, Wu R, Men K, Xu Y, Han F, Yi J, Qu Y, Dai J. Dosiomics-based prediction of radiation-induced hypothyroidism in nasopharyngeal carcinoma patients. Phys Med 2021; 89:219-225. [PMID: 34425512 DOI: 10.1016/j.ejmp.2021.08.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 07/23/2021] [Accepted: 08/11/2021] [Indexed: 11/19/2022] Open
Abstract
PURPOSE To predict the incidence of radiation-induced hypothyroidism (RHT) in nasopharyngeal carcinoma (NPC) patients, dosiomics features based prediction models were established. MATERIALS AND METHODS A total of 145 NPC patients treated with radiotherapy from January 2012 to January 2015 were included. Dosiomics features of the dose distribution within thyroid gland were extracted. The minimal-redundancy-maximal-relevance (mRMR) criterion was used to rank the extracted features and selected the most relevant features. Machine learning (ML) algorithms including logistic regression (LR), support vector machine (SVM), random forest (RF), and k-nearest neighbor (KNN) were utilized to establish prediction models, respectively. Nested sampling and hyper-tuning methods were adopted to train and validate the prediction models. The dosiomics-based (DO) prediction models were evaluated through comparing with the dose-volume factor-based (DV) models in terms of the area under the receiver operating characteristic (ROC) curve (AUC). The demographics factors (age and gender) were included in both DO model and DV model. RESULTS Age, V45 and 37 dosiomics features exhibited significant correlations with RHT in univariate analysis. For prediction performance, DO prediction models exhibited better results with the best AUC value 0.7 while DV prediction models 0.61. In DO prediction models, the AUC values displayed a trend from ascending to descending with the increasing of selected features. The highest AUC value was achieved when the number of selected features was 3. In DV prediction model, similar trend was not observed. CONCLUSION This study established a prediction model based on the dosiomics features with better performance than conventional dose-volume factors, leading to early predict the possible RHT among NPC patients who had received radiotherapy and take precaution measures for NPC patients.
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Affiliation(s)
- Wenting Ren
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Bin Liang
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Chao Sun
- Department of Ultrasound, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Runye Wu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Kuo Men
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yingjie Xu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Fei Han
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Junlin Yi
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Yuan Qu
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
| | - Jianrong Dai
- Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China.
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Zhu MY, Wu HJ, Miao JJ, Di MP, Chen BY, Huang HG, Mai HQ, Wang L, Zhao C. Radiation-induced hypothyroidism in patients with nasopharyngeal carcinoma treated with intensity-modulated radiation therapy with or without chemotherapy: Development of a nomogram based on the equivalent dose. Oral Oncol 2021; 120:105378. [PMID: 34174518 DOI: 10.1016/j.oraloncology.2021.105378] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 06/03/2021] [Accepted: 06/05/2021] [Indexed: 01/02/2023]
Abstract
OBJECTIVE The aim of this study was to establish a nomogram for predicting radiation-induced hypothyroidism (RHT) based on an equivalent dose at 2 Gy per fraction (EQD2) in patients with nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiation therapy (IMRT) with or without chemotherapy. METHODS Two hundred forty-four eligible patients with NPC were recruited for this study. Patients' clinical factors and dose-volume parameters of the thyroid gland were retrieved from medical records and the IMRT treatment planning system, respectively. The irradiation doses were converted into EQD2 for analysis. Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate logistic regression analysis were performed to identify optimal predictors of RHT for constructing the nomogram. RESULTS With a median follow-up of 63.0 months, the cumulative incidence rates of RHT at 3 months and 1-, 2-, 3-, 4- and 5- year after IMRT were 10.2%, 36.2%, 47.6%, 54.2%, 58.8% and 69.4%, respectively. Four independent factors for predicting RHT, including gender, age, pretreatment volume of the thyroid gland and V35Gy(3Gy) of the thyroid gland, were identified and incorporated into the nomogram. The area under the ROC curve of the nomogram was 0.747 (95% confidence interval 0.685 - 0.809). Calibration curves and DCA curves showed that the nomogram was in good agreement with the actual observations and clinical usefulness. CONCLUSIONS The nomogram proposed in this study provides a reliable estimate of RHT risk in patients with NPC after IMRT and appears to have the potential to be a useful tool for widespread clinical applications.
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Affiliation(s)
- Man-Yi Zhu
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province 510060, China.
| | - Hai-Jun Wu
- Department of Radiation Oncology, The First People's Hospital of Foshan, Foshan, Guangdong Province 510060, China
| | - Jing-Jing Miao
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province 510060, China.
| | - Mu-Ping Di
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province 510060, China.
| | - Bo-Yu Chen
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province 510060, China.
| | - Hua-Geng Huang
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province 510060, China.
| | - Hai-Qiang Mai
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province 510060, China.
| | - Lin Wang
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province 510060, China.
| | - Chong Zhao
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong Province 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen University Cancer Center, Guangzhou, Guangdong Province 510060, China.
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Takada T, Damen JAAG, Tambas M, Spijker R, Steenbakkers RJHM, Sharabiani M, Clementel E, Langendijk JA, Moons KGM, Schuit E. Prognostic models for radiation-induced complications after radiotherapy in head and neck cancer patients. Hippokratia 2021. [DOI: 10.1002/14651858.cd014745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Toshihiko Takada
- Julius Center for Health Sciences and Primary Care; University Medical Center Utrecht, Utrecht University; Utrecht Netherlands
| | - Johanna AAG Damen
- Julius Center for Health Sciences and Primary Care; University Medical Center Utrecht, Utrecht University; Utrecht Netherlands
- Cochrane Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University; Utrecht Netherlands
| | - Makbule Tambas
- Department of Radiation Oncology, University Medical Center Groningen; University of Groningen; Groningen Netherlands
| | - René Spijker
- Cochrane Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University; Utrecht Netherlands
| | - Roel JHM Steenbakkers
- Department of Radiation Oncology, University Medical Center Groningen; University of Groningen; Groningen Netherlands
| | - Marjan Sharabiani
- European Organisation for Research and Treatment of Cancer (EORTC) Headquarters; Brussels Belgium
| | - Enrico Clementel
- European Organisation for Research and Treatment of Cancer (EORTC) Headquarters; Brussels Belgium
| | - Johannes A Langendijk
- Department of Radiation Oncology, University Medical Center Groningen; University of Groningen; Groningen Netherlands
| | - Karel GM Moons
- Julius Center for Health Sciences and Primary Care; University Medical Center Utrecht, Utrecht University; Utrecht Netherlands
- Cochrane Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University; Utrecht Netherlands
| | - Ewoud Schuit
- Julius Center for Health Sciences and Primary Care; University Medical Center Utrecht, Utrecht University; Utrecht Netherlands
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18
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Zhou L, Chen J, Tao CJ, Chen M, Yu ZH, Chen YY. Research progress of radiation-induced hypothyroidism in head and neck cancer. J Cancer 2021; 12:451-459. [PMID: 33391441 PMCID: PMC7738994 DOI: 10.7150/jca.48587] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 10/30/2020] [Indexed: 12/24/2022] Open
Abstract
This paper reviews the factors related to hypothyroidism after radiotherapy in patients with head and neck cancer to facilitate the prevention of radiation-induced hypothyroidism and reduce its incidence. Hypothyroidism is a common complication after radiotherapy in patients with head and neck cancer, wherein the higher the radiation dose to the thyroid and pituitary gland, the higher the incidence of hypothyroidism. With prolonged follow-up time, the incidence of hypothyroidism gradually increases. Intensity modulated radiotherapy should limit the dose to the thyroid, which would reduce the incidence of hypothyroidism. In addition, the risk factors for hypothyroidism include small thyroid volume size, female sex, and previous neck surgery. The incidence of radiation-induced hypothyroidism in head and neck cancer is related to the radiation dose, radiotherapy technique, thyroid volume, sex, and age. A prospective, large sample and long-term follow-up study should be carried out to establish a model of normal tissue complications that are likely to be related to radiation-induced hypothyroidism.
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Affiliation(s)
- Ling Zhou
- Institute of Cancer and Basic Medical (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, China.,The First Clinical Medical College, Guangdong Medical University, Zhanjiang, Guangdong 524000, China
| | - Jia Chen
- Medical Research Institute, Hangzhou YITU Healthcare Technology Co., Ltd, Hangzhou, Zhejiang 330106, China.,Shanghai Key Laboratory of Artificial Intelligence for Medical Image and Knowledge Graph, Shanghai 200050, China
| | - Chang-Juan Tao
- Institute of Cancer and Basic Medical (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, China
| | - Ming Chen
- Institute of Cancer and Basic Medical (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, China
| | - Zhong-Hua Yu
- Department of Oncology, the Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong 524001, China
| | - Yuan-Yuan Chen
- Institute of Cancer and Basic Medical (ICBM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, China.,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, China
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Peng L, Mao YP, Huang CL, Guo R, Ma J, Wen WP, Tang LL. A New Model for Predicting Hypothyroidism After Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma. Front Oncol 2020; 10:551255. [PMID: 33102218 PMCID: PMC7546200 DOI: 10.3389/fonc.2020.551255] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 09/02/2020] [Indexed: 12/12/2022] Open
Abstract
Objectives To develop a model that can predict the risk of hypothyroidism (HT) after intensity-modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC), and to accordingly recommend dose constraints. Materials and Methods NPC patients treated between 2011 and 2015 were retrospectively reviewed. HT was defined by an abnormally high level of thyrotropin. The dosimetry parameters Vx (percentage of thyroid volume receiving more than x Gy of radiation) and Va,b (percentage of thyroid volume receiving >a Gy, while ≤b Gy radiation) were calculated. The primary endpoint was the development of HT within the first 2 years after IMRT. The least absolute shrinkage and selection operator and multivariate logistic regression were used to identify predictors of HT. Results A total of 545 patients were included in the analyses, with a median follow-up of 36 months. Of the 545 patients, 138 developed HT within 2 years, and the 2-year incidence of HT was 25.3%. In patients with thyroid volume >20 cm3, the 2-year incidence of HT was 11.7% (16/137); in patients with thyroid volume ≤20 cm3 and V30,60 ≤ 80%, the 2-year HT incidence was 19.9% (33/166); in patients with thyroid volume ≤20 cm3 and V30,60 > 80%, the 2-year incidence of HT was 36.8% (89/242). Conclusion Thyroid volume and V30,60 could be reliable predictors of HT after IMRT for NPC. For patients with thyroid volume ≤20 cm3, thyroid V30,60 ≤ 80% might be a useful dose constraint to adopt during IMRT planning.
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Affiliation(s)
- Liang Peng
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China.,Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yan-Ping Mao
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China
| | - Cheng-Long Huang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China
| | - Rui Guo
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China
| | - Jun Ma
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China
| | - Wei-Ping Wen
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Ling-Long Tang
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.,Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China
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Generalizability assessment of head and neck cancer NTCP models based on the TRIPOD criteria. Radiother Oncol 2020; 146:143-150. [DOI: 10.1016/j.radonc.2020.02.013] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Revised: 02/06/2020] [Accepted: 02/17/2020] [Indexed: 12/23/2022]
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Zhou L, Chen J, Shen W, Chen ZL, Huang S, Tao CJ, Chen M, Yu ZH, Chen YY. Thyroid V 50 is a risk factor for hypothyroidism in patients with nasopharyngeal carcinoma treated with intensity-modulated radiation therapy: a retrospective study. Radiat Oncol 2020; 15:68. [PMID: 32293496 PMCID: PMC7087364 DOI: 10.1186/s13014-020-01490-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Accepted: 02/12/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND We investigated the risk factors of radiation-induced thyroid dysfunction, then combined the clinical factors and optimum thyroid dosimetric parameters to predict the incidence rate of hypothyroidism (HT) and to guide individualized treatment. METHODS A total of 206 patients with histologically proven nasopharyngeal carcinoma (NPC) treated at the Cancer Hospital of the University of Chinese Academy of Sciences between January 2015 and August 2018 were included. Dose-volume histogram (DVH) data, including mean dose, absolute volume, V20, V25, V30, V35, V40, V45, V50, V55, and V60 were extracted and used as dosimetric parameters. A logistic regression analysis model was built to identify predictors related to HT occurring within 2 years. RESULTS Sex, N stage, thyroid volume, mean thyroid dose, and thyroid V20 and V50 were significantly different between patients with and without HT. Logistic regression analysis showed that N stage, thyroid volume, and thyroid V50 were independent predictors of HT. The radiosensitivity of the thyroid decreased as the thyroid volume increased. Patients with N stage > 1 had significantly higher HT incidence (37.38%) than patients with N stage ≤1 (13.11%). The incidence of HT was 54.55% in patients with thyroid V50 > 24% and was 34.15% in patients with thyroid V50 ≤ 24%. CONCLUSIONS The incidence of HT is significantly associated with N stage, thyroid volume, and thyroid V50. More attention should be paid to patients with NPC with thyroid volume ≤ 12.82 cm3 and advanced N stage disease.
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Affiliation(s)
- Ling Zhou
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China.,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, China.,Postgraduate Education, Guangdong Medical University, Zhanjiang, China
| | - Jia Chen
- Hangzhou YITU Healthcare Technology Co, Ltd, Hangzhou, China
| | - Wei Shen
- Hangzhou YITU Healthcare Technology Co, Ltd, Hangzhou, China
| | - Zheng-Lu Chen
- Postgraduate Education, Guangdong Medical University, Zhanjiang, China
| | - Shuang Huang
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China.,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, China
| | - Chang-Juan Tao
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China.,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, China
| | - Ming Chen
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China.,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China.,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, China
| | - Zhong-Hua Yu
- Department of Oncology, the Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
| | - Yuan-Yuan Chen
- Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, China. .,Department of Radiation Oncology, Cancer Hospital of University of Chinese Academy of Sciences, Hangzhou, China. .,Department of Radiation Oncology, Zhejiang Cancer Hospital, Hangzhou, China.
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22
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Dose-volume derived nomogram as a reliable predictor of radiotherapy-induced hypothyroidism in head and neck cancer patients. Radiol Oncol 2019; 53:488-496. [PMID: 31747379 PMCID: PMC6884936 DOI: 10.2478/raon-2019-0055] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 10/04/2019] [Indexed: 12/12/2022] Open
Abstract
Background The aim of this study was to determine the possible predictive value of various dosimetric parameters on the development of hypothyroidism (HT) in patients with head and neck squamous cell carcinoma (HNSCC) treated with (chemo)radiotherapy. Patients and methods This study included 156 patients with HNSCC who were treated with (chemo)radiotherapy in a primary or postoperative setting between August 2012 and September 2017. Dose-volume parameters as well as V10 toV70, D02 to D98, and the VS10 to VS70 were evaluated. The patients’ hormone status was regularly assessed during follow-up. A nomogram (score) was constructed, and the Kaplan-Maier curves and Log-Rank test were used to demonstrate the difference in incidence of HT between cut-off values of specific variables. Results After a median follow-up of 23.0 (12.0–38.5) months, 70 (44.9%) patients developed HT. In univariate analysis, VS65, Dmin, V50, and total thyroid volume (TTV) had the highest accuracy in predicting HT. In a multivariate model, HT was associated with lower TTV (OR 0.31, 95% CI 0.11–0.87, P = 0.026) and Dmin (OR 9.83, 95% CI 1.89–108.08, P = 0.042). Hypothyroidism risk score (HRS) was constructed as a regression equation and comprised TTV and Dmin. HRS had an AUC of 0.709 (95% CI 0.627–0.791). HT occurred in 13 (20.0%) patients with a score < 7.1 and in 57 (62.6%) patients with a score > 7.1. Conclusions The dose volume parameters VS65, Dmin, V50, and TTV had the highest accuracy in predicting HT. The HRS may be a useful tool in detecting patients with high risk for radiation-induced hypothyroidism.
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Astaburuaga R, Gabryś HS, Sánchez-Nieto B, Floca RO, Klüter S, Schubert K, Hauswald H, Bangert M. Incorporation of Dosimetric Gradients and Parotid Gland Migration Into Xerostomia Prediction. Front Oncol 2019; 9:697. [PMID: 31417872 PMCID: PMC6684756 DOI: 10.3389/fonc.2019.00697] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 07/15/2019] [Indexed: 12/23/2022] Open
Abstract
Purpose: Due to the sharp gradients of intensity-modulated radiotherapy (IMRT) dose distributions, treatment uncertainties may induce substantial deviations from the planned dose during irradiation. Here, we investigate if the planned mean dose to parotid glands in combination with the dose gradient and information about anatomical changes during the treatment improves xerostomia prediction in head and neck cancer patients. Materials and methods: Eighty eight patients were retrospectively analyzed. Three features of the contralateral parotid gland were studied in terms of their association with the outcome, i.e., grade ≥ 2 (G2) xerostomia between 6 months and 2 years after radiotherapy (RT): planned mean dose (MD), average lateral dose gradient (GRADX), and parotid gland migration toward medial (PGM). PGM was estimated using daily megavoltage computed tomography (MVCT) images. Three logistic regression models where analyzed: based on (1) MD only, (2) MD and GRADX, and (3) MD, GRADX, and PGM. Additionally, the cohort was stratified based on the median value of GRADX, and a univariate analysis was performed to study the association of the MD with the outcome for patients in low- and high-GRADX domains. Results: The planned MD failed to recognize G2 xerostomia patients (AUC = 0.57). By adding the information of GRADX (second model), the model performance increased to AUC = 0.72. The addition of PGM (third model) led to further improvement in the recognition of the outcome (AUC = 0.79). Remarkably, xerostomia patients in the low-GRADX domain were successfully identified (AUC = 0.88) by the MD alone. Conclusions: Our results indicate that GRADX and PGM, which together serve as a proxy of dosimetric changes, provide valuable information for xerostomia prediction.
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Affiliation(s)
- Rosario Astaburuaga
- Department of Medical Physics in Radiation Oncology, Deutsches Krebsforschungszentrum, Heidelberg, Germany.,Medical Faculty of Heidelberg, Universität Heidelberg, Heidelberg, Germany.,Heidelberg Institute for Radiation Oncology, Heidelberg, Germany.,Institute of Physics, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Hubert S Gabryś
- Department of Medical Physics in Radiation Oncology, Deutsches Krebsforschungszentrum, Heidelberg, Germany.,Medical Faculty of Heidelberg, Universität Heidelberg, Heidelberg, Germany.,Heidelberg Institute for Radiation Oncology, Heidelberg, Germany
| | | | - Ralf O Floca
- Heidelberg Institute for Radiation Oncology, Heidelberg, Germany.,Medical Image Computing, Deutsches Krebsforschungszentrum, Heidelberg, Germany.,Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany
| | - Sebastian Klüter
- Heidelberg Institute for Radiation Oncology, Heidelberg, Germany.,Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany
| | - Kai Schubert
- Heidelberg Institute for Radiation Oncology, Heidelberg, Germany.,Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany
| | - Henrik Hauswald
- Heidelberg Institute for Radiation Oncology, Heidelberg, Germany.,Department of Radiation Oncology, University Hospital Heidelberg, Heidelberg, Germany.,Clinical Cooperation Unit Radiation Oncology, Deutsches Krebsforschungszentrum, Heidelberg, Germany
| | - Mark Bangert
- Department of Medical Physics in Radiation Oncology, Deutsches Krebsforschungszentrum, Heidelberg, Germany.,Heidelberg Institute for Radiation Oncology, Heidelberg, Germany
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