Evidence map›Paper›PMID 42170284›Full record

ArticleTranslational lung cancer research2026

Impact of effective dose to immune cells (EDIC) on survival in limited-stage small cell lung cancer treated with radiotherapy and immunotherapy.

Mengqian Jiang, Yuantao Qi, Zihong Zhu, Wenqing Cui, Ran Zhang, Jinming Yu, Dawei Chen

Abstract read
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Article in Translational lung cancer research, 2026. 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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1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Mengqian Jiang *School of Clinical Medicine, Shandong Second Medical University, Weifang, China.
Yuantao Qi *Department of Radiation Oncology and Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Zihong Zhu *Department of Radiation Oncology and Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Wenqing CuiSchool of Clinical Medicine, Shandong Second Medical University, Weifang, China.
Ran ZhangDepartment of Radiation Oncology and Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Jinming YuSchool of Clinical Medicine, Shandong Second Medical University, Weifang, China.
Dawei ChenDepartment of Radiation Oncology and Shandong Provincial Key Laboratory of Precision Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Concurrent chemoradiotherapy-immunotherapy is promising for limited-stage small cell lung cancer (LS-SCLC), but biomarkers integrating local and systemic immunity are needed. This study evaluates the prognostic value of combining effective dose to immune cells (EDIC) with hematological indicators in these patients. Methods: In this retrospective cohort study of 174 LS-SCLC patients receiving radiotherapy-immunotherapy, we collected clinical data, pre-radiotherapy hematological indices, and dosimetric parameters. EDIC was calculated using an established model. Prognostic cutoffs were determined by receiver operating characteristic (ROC) analysis, and survival outcomes were assessed via Kaplan-Meier and Cox regression methods. Results: ROC analysis established prognostic cutoffs for EDIC and hematological indices. EDIC demonstrated the highest predictive efficacy [progression-free survival (PFS)-area under the curve (AUC): 0.681; overall survival (OS)-AUC: 0.731], followed by platelet-to-lymphocyte ratio (PLR) among hematological markers (PFS-AUC: 0.659; OS-AUC: 0.630). The combination of EDIC and PLR significantly outperformed either marker alone. Survival analysis revealed that the low EDIC group had significantly better median PFS (not reached Conclusions: Our findings demonstrate that a risk stratification model integrating EDIC and PLR effectively discriminates prognostic outcomes in LS-SCLC patients receiving combined radiotherapy and immunotherapy, with low EDIC and low PLR correlating with superior survival.

Indexed as

effective dose to immune cells (EDIC)immunotherapyplatelet-to-lymphocyte ratio (PLR)radiotherapySmall cell lung cancer (SCLC)

Identifiers

PMID42170284
PMCPMC13186640

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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.