Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Radiation Oncology, University Medical Center Groningen, University of Groningen, Groningen, NL.
Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Int J Radiat Oncol Biol Phys. 2021 Oct 1;111(2):549-558. doi: 10.1016/j.ijrobp.2021.04.042. Epub 2021 Jun 10.
Osteoradionecrosis (ORN) of the mandible represents a severe, debilitating complication of radiation therapy (RT) for head and neck cancer (HNC). At present, no normal tissue complication probability (NTCP) models for risk of ORN exist. The aim of this study was to develop a multivariable clinical/dose-based NTCP model for the prediction of ORN any grade (ORN) and grade IV (ORN) after RT (±chemotherapy) in patients with HNC.
Included patients with HNC were treated with (chemo-)RT between 2005 and 2015. Mandible bone radiation dose-volume parameters and clinical variables (ie, age, sex, tumor site, pre-RT dental extractions, chemotherapy history, postoperative RT, and smoking status) were considered as potential predictors. The patient cohort was randomly divided into a training (70%) and independent test (30%) cohort. Bootstrapped forward variable selection was performed in the training cohort to select the predictors for the NTCP models. Final NTCP model(s) were validated on the holdback test subset.
Of 1259 included patients with HNC, 13.7% (n = 173 patients) developed any grade ORN (ORN primary endpoint) and 5% (n = 65) ORN (secondary endpoint). All dose and volume parameters of the mandible bone were significantly associated with the development of ORN in univariable models. Multivariable analyses identified D and pre-RT dental extraction as independent predictors for both ORN and ORN best-performing NTCP models with an area under the curve (AUC) of 0.78 (AUC = 0.75 [0.69-0.82]) and 0.81 (AUC = 0.82 [0.74-0.89]), respectively.
This study presented NTCP models based on mandible bone D and pre-RT dental extraction that predict ORN and ORN (ie, needing invasive surgical intervention) after HNC RT. Our results suggest that less than 30% of the mandible should receive a dose of 35 Gy or more for an ORN risk lower than 5%. These NTCP models can improve ORN prevention and management by identifying patients at risk of ORN.
下颌骨放射性骨坏死（ORN）是头颈部癌症（HNC）放射治疗（RT）的一种严重且使人虚弱的并发症。目前，ORN 风险的正常组织并发症概率（NTCP）模型并不存在。本研究旨在建立一个多变量临床/剂量 NTCP 模型，以预测 HNC 患者接受 RT（±化疗）后任何等级（ORN）和等级 IV（ORN）ORN 的风险。
纳入的 HNC 患者于 2005 年至 2015 年期间接受（化疗）RT 治疗。下颌骨骨辐射剂量-体积参数和临床变量（即年龄、性别、肿瘤部位、RT 前拔牙、化疗史、术后 RT 和吸烟状况）被认为是潜在的预测因子。患者队列被随机分为训练（70%）和独立测试（30%）队列。在训练队列中进行了引导向前变量选择，以选择 NTCP 模型的预测因子。最终的 NTCP 模型在保留测试子集上进行验证。
在 1259 名 HNC 患者中，13.7%（n=173 例）发生了任何等级 ORN（ORN 主要终点），5%（n=65 例）发生了 ORN（次要终点）。在单变量模型中，下颌骨的所有剂量和体积参数均与 ORN 的发生显著相关。多变量分析确定 D 剂量和 RT 前拔牙是 ORN 和 ORN 最佳性能 NTCP 模型的独立预测因子，其曲线下面积（AUC）分别为 0.78（AUC=0.75[0.69-0.82]）和 0.81（AUC=0.82[0.74-0.89]）。
本研究提出了基于下颌骨 D 剂量和 RT 前拔牙的 NTCP 模型，可预测 HNC RT 后 ORN 和 ORN（即需要侵入性手术干预）的发生。我们的结果表明，下颌骨的 30%以下应接受 35Gy 或更高剂量的照射，以降低 5%以下的 ORN 风险。这些 NTCP 模型可以通过识别有 ORN 风险的患者来改善 ORN 的预防和管理。
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