Personalized Composite Dosimetric Score-Based Machine Learning Model of Severe Radiation-Induced Lymphopenia Among Patients With Esophageal Cancer

被引：0
|
作者：
Chu, Yan [1 ,2 ]
Zhu, Cong [1 ,3 ]
Hobbs, Brian P. [4 ]
Chen, Yiqing [1 ,5 ]
van Rossum, Peter S. N. [6 ]
Grassberger, Clemens [7 ]
Zhi, Degui [2 ]
Lin, Steven H. [8 ]
Mohan, Radhe [1 ]
机构：
[1] Univ Texas MD Anderson Canc Ctr, Dept Radiat Phys, Houston, TX 77030 USA
[2] Univ Texas Hlth Sci Ctr, Sch Biomed Informat, Houston, TX USA
[3] Univ Texas Hlth Sci Ctr, Sch Publ Hlth, Dept Epidemiol Human Genet & Environm Sci, Houston, TX USA
[4] Univ Texas Austin, Dell Med Sch, Dept Populat Hlth, Austin, TX USA
[5] Univ Texas Hlth Sci Ctr, Sch Publ Hlth, Dept Biostat & Data Sci, Houston, TX USA
[6] Univ Amsterdam, Med Ctr, Dept Radiat Oncol, Amsterdam, Netherlands
[7] Univ Washington, Dept Radiat Oncol, Seattle, WA USA
[8] Univ Texas MD Anderson Canc Ctr, Dept Thorac Radiat Oncol, Houston, TX USA
来源：
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS | 2024年 / 120卷 / 04期
基金：
美国国家卫生研究院;
关键词：
RADIOTHERAPY; SURVIVAL;
D O I：
10.1016/j.ijrobp.2024.05.018
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
Purpose: Radiation-induced lymphopenia (RIL) is common among patients undergoing radiation therapy (RT)' ' Severe RIL has been linked to adverse outcomes. The severity and risk of RIL can be predicted from baseline clinical characteristics and dosimetric parameters. However, dosimetric parameters, e.g. 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 fi cation scheme for risk of grade 4 RIL (G4RIL), based on this novel RT dosimetric feature, for patients receiving chemo RT for esophageal cancer.
引用
收藏
页码：1172 / 1180
页数：9
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