A machine learning model for grade 4 lymphopenia prediction during pelvic radiotherapy in patients with cervical cancer

Background/purposeSevere lymphopenia during pelvic radiotherapy (RT) predicts poor survival in patients with cervical cancer. However, the risk of severe lymphopenia has not been well predicted. We developed a machine learning model using clinical and dosimetric information to predict grade 4 (G4) l...

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Bibliographic Details
Published in:Frontiers in oncology 2022-09, Vol.12, p.905222-905222
Main Authors: Xu, Zhiyuan, Yang, Li, Yu, Hao, Guo, Linlang
Format: Article
Language:English
Subjects:
cervical cancer
lymphopenia
machine learning model
Oncology
pelvic radiotherapy
prediction
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Summary:Background/purposeSevere lymphopenia during pelvic radiotherapy (RT) predicts poor survival in patients with cervical cancer. However, the risk of severe lymphopenia has not been well predicted. We developed a machine learning model using clinical and dosimetric information to predict grade 4 (G4) lymphopenia during pelvic RT in patients with cervical cancer. MethodsThis retrospective study included cervical cancer patients treated with definitive pelvic RT ± induction/concurrent chemotherapy. Clinical information and a set of dosimetric parameters of external beam radiotherapy plan were collected. G4 lymphopenia during RT, which was also referred to as G4 absolute lymphocyte count (ALC) nadir, was defined as ALC nadir
ISSN:2234-943X
2234-943X
DOI:10.3389/fonc.2022.905222