Postradiation hypothyroidism in head and neck cancers: A Department of Veterans Affairs single-institution case-control dosimetry study

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.

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.

Post-radiation primary hypothyroidism in patients with head and neck cancer: External validation of thyroid gland dose-volume constraints with long-term endocrine outcomes

BACKGROUND

Post-radiation primary hypothyroidism is a common late complication in head and neck cancer (HNC) survivors. No radiation dose-volume constraint of the thyroid gland has been externally validated for predicting long-term thyroid function outcomes.

MATERIALS AND METHODS

This external validation study evaluated the diagnostic properties of 22 radiation dose-volume constraints of the thyroid gland proposed in the literature. Radiation dosimetric data from 488 HNC patients who underwent neck irradiation from January 2013 to December 2015 at two tertiary oncology centers were reviewed. The diagnostic metrics of candidate constraints were computed by inverse probability of censoring weighting and compared using time-dependent receiver operating characteristic (ROC) curves with death designated as a competing event. Multivariable regression analyses were performed using the Fine-Gray sub-distribution hazard model.

RESULTS

Over a median follow-up period of 6.8 years, 205 (42.0 %) patients developed post-radiation primary hypothyroidism. The thyroid volume spared from 60 Gy (VS60) had the largest area under ROC curve of 0.698 at 5 years after radiotherapy. Of all evaluated constraints, VS60 at a cutoff value of 10 cc had the highest F-score of 0.53. The 5-year hypothyroidism risks of patients with thyroid VS60 ≥ 10 cc and < 10 cc were 14.7 % and 38.2 %, respectively (p < 0.001). The adjusted sub-hazard ratio for post-radiation primary hypothyroidism for VS60 < 10 cc was 1.87 (95 % confidence interval, 1.22-2.87; p < 0.001).

CONCLUSION

Thyroid VS60 is the best radiation dose-volume parameter to predict the long-term risk of primary hypothyroidism in patients with HNC who underwent neck irradiation. VS60 ≥ 10 cc is a robust constraint that limits the 5-year primary hypothyroidism risk to less than 15 % and should be routinely employed during radiotherapy optimization.

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.

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.