Department of Radiation Oncology (Maastro Clinic), School for Oncology and Reproduction (GROW), Maastricht University Medical Center, Maastricht, The Netherlands.
Department of Medical Psychology, School for Mental Health and Neurosciences (MHeNS), Maastricht University Medical Center, Maastricht, The Netherlands.
Neuro Oncol. 2024 Aug 5;26(8):1467-1478. doi: 10.1093/neuonc/noae035.
Deterioration of neurocognitive function in adult patients with a primary brain tumor is the most concerning side effect of radiotherapy. This study aimed to develop and evaluate normal-tissue complication probability (NTCP) models using clinical and dose-volume measures for 6-month, 1-year, and 2-year Neurocognitive Decline (ND) postradiotherapy.
A total of 219 patients with a primary brain tumor treated with radical photon and/or proton radiotherapy (RT) between 2019 and 2022 were included. Controlled oral word association test, Hopkins verbal learning test-revised, and trail making test were used to objectively measure ND. A comprehensive set of potential clinical and dose-volume measures on several brain structures were considered for statistical modeling. Clinical, dose-volume and combined models were constructed and internally tested in terms of discrimination (area under the curve, AUC), calibration (mean absolute error, MAE), and net benefit.
Fifty percent, 44.5%, and 42.7% of the patients developed ND at 6-month, 1-year, and 2-year time points, respectively. The following predictors were included in the combined model for 6-month ND: age at radiotherapy > 56 years (OR = 5.71), overweight (OR = 0.49), obesity (OR = 0.35), chemotherapy (OR = 2.23), brain V20 Gy ≥ 20% (OR = 3.53), brainstem volume ≥ 26 cc (OR = 0.39), and hypothalamus volume ≥ 0.5 cc (OR = 0.4). Decision curve analysis showed that the combined models had the highest net benefits at 6-month (AUC = 0.79, MAE = 0.021), 1-year (AUC = 0.72, MAE = 0.027), and 2-year (AUC = 0.69, MAE = 0.038) time points.
The proposed NTCP models use easy-to-obtain predictors to identify patients at high risk of ND after brain RT. These models can potentially provide a base for RT-related decisions and post-therapy neurocognitive rehabilitation interventions.
原发性脑肿瘤患者接受放射治疗后神经认知功能恶化是最令人担忧的副作用。本研究旨在开发和评估使用临床和剂量-体积测量值的正常组织并发症概率(NTCP)模型,以预测放疗后 6 个月、1 年和 2 年的神经认知下降(ND)。
共纳入 219 例 2019 年至 2022 年期间接受根治性光子和/或质子放疗(RT)治疗的原发性脑肿瘤患者。采用受控口头词语联想测验、霍普金斯言语学习测验修订版和连线测验 A 和 B 客观测量 ND。考虑了一系列与脑结构相关的潜在临床和剂量-体积测量值,用于统计建模。构建了临床、剂量-体积和综合模型,并在区分度(曲线下面积,AUC)、校准(平均绝对误差,MAE)和净效益方面进行了内部测试。
分别有 50%、44.5%和 42.7%的患者在 6 个月、1 年和 2 年时出现 ND。以下预测因素被纳入 6 个月 ND 的综合模型:放疗时年龄>56 岁(OR=5.71)、超重(OR=0.49)、肥胖(OR=0.35)、化疗(OR=2.23)、脑 V20 Gy≥20%(OR=3.53)、脑干体积≥26 cc(OR=0.39)和下丘脑体积≥0.5 cc(OR=0.4)。决策曲线分析表明,综合模型在 6 个月(AUC=0.79,MAE=0.021)、1 年(AUC=0.72,MAE=0.027)和 2 年(AUC=0.69,MAE=0.038)时间点的净效益最高。
所提出的 NTCP 模型使用易于获得的预测因素来识别脑 RT 后发生 ND 的高危患者。这些模型可能为 RT 相关决策和治疗后神经认知康复干预提供依据。