Evidence map›Paper›PMID 39962844›Full record

ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2024

[Analysis of the Correlation between Immune Cell Subsets in Bronchoalveolar Lavage Fluid and the Efficacy of First-line Use of Immunotherapy in Advanced Non-small Cell Lung Cancer: A Case-control Study].

Kai Zhang, Liang Shi, Tongmei Zhang, Li Tong, Song Wei, Hongxia Li

Abstract readEnglish Abstract
In one paragraph

Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2024. 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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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

6 authors.

Kai ZhangDepartment of Medical Oncology, Beijing Tuberculosis & Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
Liang ShiDepartment of Medical Oncology, Beijing Tuberculosis & Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
Tongmei ZhangDepartment of Medical Oncology, Beijing Tuberculosis & Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
Li TongDepartment of Medical Oncology, Beijing Tuberculosis & Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
Song WeiDepartment of Medical Oncology, Beijing Tuberculosis & Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.
Hongxia LiDepartment of Medical Oncology, Beijing Tuberculosis & Thoracic Tumor Research Institute/Beijing Chest Hospital, Capital Medical University, Beijing 101149, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundImmunotherapy has been a standard treatment for the patients with advanced non-small cell lung cancer (NSCLC), however, reliable biomarkers for predicting the response remain unclear. This study explores the subpopulations of lymphocytes in bronchoalveolar lavage fluid (BALF) and combines clinical and laboratory examination indicators of NSCLC patients to identify potential biomarkers related to immunotherapy.

methodsA retrospective analysis was conducted on 82 patients with locally advanced or metastatic NSCLC who underwent electronic bronchoscopy and received first-line immunotherapy at Beijing Chest Hospital, Capital Medical University between March 2020 and November 2022. Logistic regression and random forest models were employed to determine the correlation between immune cell subsets in BALF and response of immunotherapy. The predictive value was validated by the model.

resultsAll patients enrolled received first-line immunotherapy, and the efficacy was evaluated according to clinical guidelines: among the 82 patients included, 48 patients got objective response and the other 34 did not achieve. The relationship between collected indicators and the best clinical treatment response was analyzed. The result shows that a higher percentage of total lymphocytes in BALF was associated with good response of first-line immunotherapy (P<0.05), while a higher percentage of T helper cells in BALF was associated with poor prognosis (P<0.05).

conclusionsThe proportions of total lymphocytes and T helper cells in BALF could be used as predictive biomarkers for first-line immunotherapy in late stage NSCLC. A multivariable model improves predictive accuracy.

Indexed as

Bronchoalveolar Lavage FluidCarcinoma, Non-Small-Cell LungImmunotherapyLung NeoplasmsAdultAgedCase-Control StudiesFemaleHumansMaleMiddle AgedRetrospective StudiesTreatment OutcomeBronchoalveolar lavage fluidEfficacy predictionImmunotherapyLung neoplasms

Identifiers

PMID39962844
PMCPMC11839498

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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.