Development of a normal tissue complication probability (NTCP) model for radiation-induced hypothyroidism in nasopharyngeal carcinoma patients

Normal tissue complication probability models of hypothyroidism after radiotherapy for breast cancer

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.

A multivariable normal tissue complication probability model for predicting radiation-induced hypothyroidism in nasopharyngeal carcinoma patients in the modern radiotherapy era

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.

Analysis of correlative risk factors for radiation-induced hypothyroidism in head and neck tumors

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.

Radiomics and dosiomics for predicting radiation-induced hypothyroidism and guiding intensity-modulated radiotherapy

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.

Development and validation of a machine learning model of radiation-induced hypothyroidism with clinical and dose-volume features

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.

Risk factors of early thyroid dysfunction after definitive radiotherapy in nasopharyngeal carcinoma patients

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.

Hypothyroidism following Radiotherapy for Head and Neck Cancer: A Systematic Review of the Literature and Opportunities to Improve the Therapeutic Ratio

(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.

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

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.

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

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.

Predictors of radiation-induced hypothyroidism in nasopharyngeal carcinoma survivors after intensity-modulated radiotherapy

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.

Dose-volume predictors of post-radiation primary hypothyroidism in head and neck cancer: a systematic review

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This systematic review included 29 studies (n = 4,530 patients) on dosimetric predictors of primary hypothyroidism in HNC.

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Average crude incidence of primary hypothyroidism after HNC radiotherapy was 41.4%.

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Thyroid Dmean and V50 were the most widely reported dosimetric predictors for hypothyroidism.

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Thyroid volume is a predictor of hypothyroidism (pooled aOR 0.89 per 1 cc increment) independent of radiation dosimetry.

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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.

The impact of nutritional counseling on thyroid disorders in head and neck cancer patients after (chemo)radiotherapy: results from a prospective interventional trial

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.

Multivariate NTCP Model of Hypothyroidism After Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma

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.

Dosiomics-based prediction of radiation-induced hypothyroidism in nasopharyngeal carcinoma patients

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.

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

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 V_35Gy(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.

Research progress of radiation-induced hypothyroidism in head and neck cancer

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.

A New Model for Predicting Hypothyroidism After Intensity-Modulated Radiotherapy for Nasopharyngeal Carcinoma

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 V_x (percentage of thyroid volume receiving more than x Gy of radiation) and V_a,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.

Thyroid V50 is a risk factor for hypothyroidism in patients with nasopharyngeal carcinoma treated with intensity-modulated radiation therapy: a retrospective study

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, V_50, 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.

Dose-volume derived nomogram as a reliable predictor of radiotherapy-induced hypothyroidism in head and neck cancer patients

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.

Incorporation of Dosimetric Gradients and Parotid Gland Migration Into Xerostomia Prediction

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.