Department of Clinical Oncology, Royal Marsden Hospital, Sutton and London, UK.
Department of Clinical Oncology, Royal Marsden Hospital, Sutton and London, UK; The Institute of Cancer Research, London, UK.
Int J Radiat Oncol Biol Phys. 2015 Nov 1;93(3):507-15. doi: 10.1016/j.ijrobp.2015.07.2263. Epub 2015 Jul 17.
The study aimed to apply the atlas of complication incidence (ACI) method to patients receiving radical treatment for head and neck squamous cell carcinomas (HNSCC), to generate constraints based on dose-volume histograms (DVHs), and to identify clinical and dosimetric parameters that predict the risk of grade 3 oral mucositis (g3OM) and pharyngeal dysphagia (g3PD).
Oral and pharyngeal mucosal DVHs were generated for 253 patients who received radiation (RT) or chemoradiation (CRT). They were used to produce ACI for g3OM and g3PD. Multivariate analysis (MVA) of the effect of dosimetry, clinical, and patient-related variables was performed using logistic regression and bootstrapping. Receiver operating curve (ROC) analysis was also performed, and the Youden index was used to find volume constraints that discriminated between volumes that predicted for toxicity.
We derived statistically significant dose-volume constraints for g3OM over the range v28 to v70. Only 3 statistically significant constraints were derived for g3PD v67, v68, and v69. On MVA, mean dose to the oral mucosa predicted for g3OM and concomitant chemotherapy and mean dose to the inferior constrictor (IC) predicted for g3PD.
We have used the ACI method to evaluate incidences of g3OM and g3PD and ROC analysis to generate constraints to predict g3OM and g3PD derived from entire individual patient DVHs. On MVA, the strongest predictors were radiation dose (for g3OM) and concomitant chemotherapy (for g3PD).
本研究旨在将并发症发生率图谱（ACI）方法应用于接受头颈部鳞状细胞癌（HNSCC）根治性治疗的患者，基于剂量-体积直方图（DVH）生成约束条件，并识别预测 3 级口腔黏膜炎（g3OM）和咽功能障碍（g3PD）风险的临床和剂量学参数。
为 253 例接受放疗（RT）或放化疗（CRT）的患者生成口腔和咽黏膜 DVH，用于生成 g3OM 和 g3PD 的 ACI。使用逻辑回归和自举法对剂量学、临床和患者相关变量的影响进行多变量分析（MVA）。还进行了受试者工作特征曲线（ROC）分析，并使用约登指数寻找区分毒性预测体积的体积约束。
我们得出了在 v28 到 v70 范围内预测 g3OM 的统计学显著剂量-体积约束。仅为 g3PD v67、v68 和 v69 得出了 3 个统计学显著的约束。在 MVA 中，口腔黏膜的平均剂量预测 g3OM，同期化疗预测 g3PD，下食管括约肌（IC）的平均剂量预测 g3PD。
我们使用 ACI 方法评估 g3OM 和 g3PD 的发生率，并使用 ROC 分析从整个个体患者 DVH 生成预测 g3OM 和 g3PD 的约束条件。在 MVA 中，最强的预测因子是放射剂量（用于 g3OM）和同期化疗（用于 g3PD）。
