放射诱发的淋巴细胞减少症 (RIL) 在接受放射治疗 (RT) 的患者中很常见，严重的 RIL 与不良后果有关。 RIL 的严重程度和风险可以根据基线临床特征和剂量测定参数进行预测。然而，剂量体积 (DV) 指数彼此高度相关，且与 RIL 相关性较弱。在这里，我们引入了“复合剂量计评分”（CDS）的新概念，作为浓缩感兴趣的免疫组织中的剂量分布的指标，以研究 RIL 的剂量依赖性。基于这一新的 RT 剂量测定特征，我们针对接受化疗的食管癌患者得出了一种改进的 4 级 (G4) RIL 风险多变量分类方案。提取了 734 名因活检证实的食管癌而接受化疗的患者的 DV 指数。使用非负矩阵分解将肺、心脏和脾脏的 DV 指数投影到单个 CDS 中； XGBoost 用于探索预测变量之间的显着交互作用；应用逻辑回归将所得 CDS 与基线临床因素和相互作用项结合起来，以促进免疫毒性的个体化预测。应用五倍交叉验证来评估模型性能。选定处于危险中的免疫器官（OAR，即心脏、肺和脾）的 CDS (1.791, 95 CI [1.350,2.377]) 是统计学上显着的风险G4RIL 的决定因素。个体免疫 OAR 的 CDS 与 G4RIL 风险的 Pearson 相关系数大于任何单一 DV 指数。基于 CDS 和 4 个临床危险因素的 G4RIL 个性化预测得出的曲线下面积值为 0.78。年龄和 CDS 之间的相互作用表明，对于≥65 岁的患者，G4RIL 风险随着 CDS 的增加而急剧增加。通过 CDS 可以预测接受食管癌化疗放疗的患者的免疫毒性风险。 CDS 概念可以扩展到其他癌症类型和目前基于 DV 指数的剂量反应模型中的免疫毒性。个性化治疗计划应利用 CDS 方法，而不是使用 DV 指数的单个或子集。版权所有 © 2024。由 Elsevier Inc. 出版。

Radiation-induced lymphopenia (RIL) is common among patients undergoing radiotherapy (RT), and severe RIL has been linked with adverse outcomes. The severity and risk of RIL can be predicted from baseline clinical characteristics and dosimetric parameters. However, dose-volume (DV) indices are highly correlated with one another and are only weakly associated with RIL. Here we introduce the novel concept of "composite dosimetric score" (CDS) as the index that condenses the dose distribution in immune tissues of interest to study the dosimetric dependence of RIL. We derived an improved multivariate classification scheme for risk of grade 4 (G4) RIL, based on this novel RT dosimetric feature, for patients receiving chemoRT for esophageal cancer.DV indices were extracted for 734 patients who received chemoRT for biopsy-proven esophageal cancer. Non-negative matrix factorization was used to project the DV indices of lung, heart, and spleen into a single CDS; XGBoost was employed to explore significant interactions among predictors; and logistic regression was applied to combine the resultant CDS along with baseline clinical factors and interaction terms to facilitate individualized prediction of immunotoxicity. Five-fold cross-validation was applied to evaluate the model performance.The CDS for selected immune organs at risk (OARs, i.e., heart, lung, and spleen) (1.791, 95 CI [1.350,2.377]) was a statistically significant risk determinant for G4RIL. Pearson correlation coefficients for CDS vs. G4RIL risk for individual immune OARs were greater than any single DV indices. Personalized prediction of G4RIL based on CDS and 4 clinical risk factors yielded an area under the curve value of 0.78. Interaction between age and CDS revealed that G4RIL risk increased more sharply with increasing CDS for patients ≥65.Risk of immunotoxicity for patients undergoing chemoRT for esophageal cancer can be predicted by CDS. The CDS concept can be extended to immunotoxicity in other cancer types and in dose-response models currently based on DV indices. Personalized treatment planning should leverage CDS methods rather than using individual or subsets of DV indices.Copyright © 2024. Published by Elsevier Inc.