Department of Radiation Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China; Hubei Key Laboratory of Precision Radiation Oncology, Wuhan 430022, China.
Cancer Center, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
Radiother Oncol. 2024 Jan;190:110040. doi: 10.1016/j.radonc.2023.110040. Epub 2023 Nov 30.
Combining immune checkpoint inhibitors (ICIs) and thoracic radiotherapy (TRT) may magnify the radiation pneumonitis (RP) risk. Dosimetric parameters can predict RP, but dosimetric data in context of immunotherapy are very scarce. To address this knowledge gap, we performed a large multicenter investigation to identify dosimetric predictors of RP in this under-studied population.
All lung cancer patients from five institutions who underwent conventionally-fractionated thoracic intensity-modulated radiotherapy with prior ICI receipt were retrospectively compiled. RP was defined per CTCAE v5.0. Statistics utilized logistic regression modeling and receiver operating characteristic (ROC) analysis.
The vast majority of the 192 patients (median follow-up 14.7 months) had non-small cell lung cancer, received PD-1 inhibitors, and did not receive concurrent systemic therapy with TRT. Grades 1-5 RP occurred in 21.9%, 25.0%, 8.3%, 1.6%, and 1.0%, respectively. The mean MLD for patients with grades 1-5 RP was 10.7, 11.6, 12.6, 14.7, and 12.8 Gy, respectively. On multivariable analysis, tumor location and mean lung dose (MLD) significantly predicted for any-grade and grade ≥ 2 pneumonitis. Only MLD significantly predicted for grade ≥ 3 RP. ROC analysis was able to pictorially model RP risk probabilities for a variety of MLD thresholds, which can be an assistive tool during TRT treatment planning.
This study, by far the largest to date of dosimetric predictors of RP in the immunotherapy era, illustrates that MLD is the most critical dose-volume parameter influencing RP risk. These data may provide a basis for revising lung dose constraints in efforts to better prevent RP in this rapidly expanding ICI/TRT population.
联合免疫检查点抑制剂(ICI)和胸部放射治疗(TRT)可能会增加放射性肺炎(RP)的风险。剂量学参数可以预测 RP,但免疫治疗相关的剂量学数据非常有限。为了填补这一知识空白,我们进行了一项大型多中心研究,以确定该研究人群中 RP 的剂量学预测因素。
回顾性收集了来自五个机构的所有接受过常规分割胸部强度调制放射治疗且先前接受过 ICI 治疗的肺癌患者。RP 按照 CTCAE v5.0 标准定义。统计学方法采用逻辑回归模型和受试者工作特征(ROC)分析。
192 例患者(中位随访 14.7 个月)绝大多数为非小细胞肺癌患者,接受 PD-1 抑制剂治疗,且在 TRT 期间未同时接受全身治疗。RP 发生率分别为 1-5 级为 21.9%、25.0%、8.3%、1.6%和 1.0%。1-5 级 RP 患者的平均 MLD 分别为 10.7、11.6、12.6、14.7 和 12.8 Gy。多变量分析表明,肿瘤部位和平均肺剂量(MLD)显著预测了任何等级和≥2 级肺炎。只有 MLD 显著预测了≥3 级 RP。ROC 分析能够直观地为各种 MLD 阈值建模 RP 风险概率,这可以作为 TRT 治疗计划中的辅助工具。
这项迄今为止在免疫治疗时代对 RP 剂量学预测因素最大的研究表明,MLD 是影响 RP 风险的最关键剂量-体积参数。这些数据可能为修订肺剂量限制提供依据,以更好地预防这一快速发展的 ICI/TRT 人群中的 RP。