Clinical and Dosimetric Predictors of Early Onset Postradiation Hypothyroidism in Patients with Head and Neck Malignancies: A Logistic Regression Analysis.
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引用次数: 0
Abstract
Introduction: Hypothyroidism commonly occurs as a side effect following radiotherapy for head and neck malignancies, yet limited information exists to predict the risk of postradiation hypothyroidism. This study aims to investigate the clinical and dosimetric factors that may predict early onset postradiation hypothyroidism (EO-PRH).
Methods: A retrospective study was conducted on patients with head and neck cancer treated between 2018 and 2021, with a minimum follow-up duration of 12 months. The thyroid gland was contoured on computed tomography (CT) scans, and dose-volume histograms were analyzed, incorporating thyroid volume and V5-60 into the analysis. Logistic regression and receiver operating characteristic (ROC) analysis were performed to identify predictors and assess the model's predictive value.
Results: Among the 84 eligible patients, 17 (20.2%) developed hypothyroidism within 1 year. The percentage of thyroid volume receiving 30 Gy (V30) emerged as the sole significant dosimetric predictor of EO-PRH (odds ratio [OR] 1.02, 95% confidence interval [95% CI] 1.005-1.05, p = 0.03). Univariable analysis revealed significant differences in cancer histopathology, primary tumor site, V15,30, and VS15,30 (the volume of the thyroid spared from radiation doses 15 Gy and 30 Gy) between the hypothyroid and euthyroid groups (p < 0.10). Multivariable analysis identified the primary cancer site (OR 9.09, 95% CI 1.59-100) and V30 (OR 1.26, 95% CI 1.007-1.76) as independent significant variables predicting EO-PRH. The predictive model incorporating cancer histopathology, primary tumor site, V15,30, and VS15,30 effectively predicted postradiation thyroid dysfunction (area under the receiver operating characteristic curve [AUC-ROC] 0.84, 95% CI 0.73-0.95, p < 0.001).
Conclusions: V30 could serve as a dosimetric predictor of hypothyroidism following neck radiotherapy. This study underscores that a predictive model encompassing cancer type and site, along with V15,30 and VS15,30, can effectively predict EO-PRH.
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Oncology and Therapy is an international, peer reviewed, rapid-publication (peer review in 2 weeks, published 3–4 weeks from acceptance) journal dedicated to the publication of high-quality pre-clinical, clinical (all phases), observational, real-world, and health outcomes research around the discovery, development, and use of therapeutics and interventions (including devices) across all therapeutic areas. Studies relating to diagnostics and diagnosis, pharmacoeconomics, public health, epidemiology, quality of life, and patient care, management, and education are also encouraged.
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