Evidence map›Paper›PMID 41132998›Full record

ArticleTranslational lung cancer research2025

Prognostic impact of dose to circulating blood cells in non-small cell lung cancer patients after chemoradiotherapy.

Sangseok Ha, Byung-Hee Kang, Hak Jae Kim, Hong-Gyun Wu, Joo Ho Lee, Wonmo Sung

Abstract read
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Article in Translational lung cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sangseok Ha *Department of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0003-0810-1298
Byung-Hee Kang *Department of Radiation Oncology, Ewha Womans University Medical Center, Ewha Womans University School of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-5130-4579
Hak Jae KimDepartment of Radiation Oncology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0003-3602-2263
Hong-Gyun WuDepartment of Radiation Oncology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-0167-7991
Joo Ho LeeDepartment of Radiation Oncology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0001-7248-3214
Wonmo SungDepartment of Biomedical Engineering, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.ORCID https://orcid.org/0000-0002-0172-0646

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Severe radiation-induced lymphopenia (SRIL) is an adverse effect in which lymphocyte counts drop below a defined threshold after radiotherapy. This study aimed to identify key dosimetric factors associated with SRIL and survival in non-small cell lung cancer (NSCLC) patients undergoing chemoradiotherapy (CRT). Methods: A total of 241 NSCLC patients treated with definitive CRT were retrospectively analyzed. Baseline blood counts and dosimetric parameters of normal organs, including circulating blood, were assessed to identify predictors of SRIL and evaluate their impact on survival. SRIL was defined as an absolute lymphocyte count (ALC) nadir of <200/µL. Circulating blood dose was estimated using both stochastic and deterministic models: the hematological dose (HEDOS) model and the effective dose to immune cells (EDIC), respectively. Multivariate logistic regression identified predictors of SRIL, while multivariate Cox regression and Kaplan-Meier analyses evaluated prognostic effects on survival. Generalized additive models (GAM) assessed nonlinear associations. Results: SRIL occurred in 68 patients (28.2%) during treatment. The median overall survival (OS) and progression-free survival (PFS) for the entire cohort were 35.0 [95% confidence interval (CI): 29.0-41.0] and 10.0 months (95% CI: 8.0-12.0), respectively. Higher minimum blood dose [HEDOS D100, odds ratio (OR) 1.26, P=0.04], increased lung volume receiving ≥10 Gy (Lung V10, OR 1.03, P=0.02), lower baseline ALC (OR 1.00, P=0.02), and hemoglobin (OR 0.82, P=0.04) were significant predictors of SRIL. GAM identified a critical threshold of 8.29 Gy for HEDOS D100, above which survival outcomes were significantly worse, with shorter median OS (18.0 Conclusions: HEDOS D100 is a strong predictor of SRIL and survival, highlighting the importance of minimizing radiation exposure to circulating blood during CRT to improve clinical outcomes in NSCLC.

Indexed as

chemoradiotherapy (CRT)lymphopeniaNon-small cell lung cancer (NSCLC)radiation dose to circulating bloodsurvival

Identifiers

PMID41132998
PMCPMC12541861

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.