Evidence map›Paper›PMID 41505423›Full record

ArticlePloS one2026

Prediction of differentiation levels in lung adenocarcinoma using peripheral blood inflammatory cytokines and tumor markers.

Yang Li, Jiahuan Wu, Meiling Long, Tingting Zeng, Depeng Jiang

Abstract read
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Article in PloS one, 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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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

5 authors.

Yang LiDepartment of Respiratory Medicine, The Second affiliated Hospital of Chongqing Medical University, Chongqing, China.
Jiahuan WuDepartment of Respiratory Medicine, The Second affiliated Hospital of Chongqing Medical University, Chongqing, China.
Meiling LongDepartment of Respiratory Medicine, The Second affiliated Hospital of Chongqing Medical University, Chongqing, China.
Tingting ZengDepartment of Endocrinology, The Second affiliated Hospital of Chongqing Medical University, Chongqing, China.
Depeng JiangDepartment of Respiratory Medicine, The Second affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0000-0003-2694-7449

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveLung Adenocarcinoma (LUAD) has highly aggressive and lethal, and its degree of differentiation significantly influences prognosis and treatment strategies, yet accurate prediction remains challenging. To assess the predictive value of combining peripheral blood inflammatory markers, such as the aggregate index of systemic inflammation (AISI), with tumor markers, including Carcinoembryonic Antigen (CEA) and Cytokeratin 19 fragment antigen 21-1(CYFRA21-1), etc, for determining LUAD differentiation levels.

methodsThis retrospective study included 203 LUAD patients treated at Chongqing Medical University's Second Affiliated Hospital, categorized by low and high differentiation. Demographic, clinical, and laboratory data including peripheral blood inflammatory and tumor markers were analyzed. A multivariate logistic regression model evaluated these markers' predictive accuracy.

resultsAISI (OR = 1.64, 95% CI = 1.08-2.58, p = 0.024), CEA (OR = 1.02, 95% CI = 1.00-1.04, p = 0.0497), ferritin (OR = 1.01, 95% CI = 1.00-1.01, p = 0.010), and Progastrin Releasing Peptide (ProGRP) (OR = 1.03, 95% CI = 1.00-1.07, p = 0.047) were risk factors of low differentiation LUAD. The model achieved an Area Under Curve(AUC) of 0.795 (95%CI: 0.726-0.864) for distinguishing low from high differentiation, with decision curve analysis confirming clinical utility.

conclusionThis model, combining inflammatory and tumor markers, effectively predicts LUAD differentiation, aiding personalized treatment planning, enhancing therapeutic outcomes, and supporting early LUAD detection.

Indexed as

AdenocarcinomaAdenocarcinoma of LungBiomarkers, TumorCytokinesLung NeoplasmsAgedCarcinoembryonic AntigenCell DifferentiationFemaleHumansInflammationKeratin-19MaleMiddle AgedPrognosisRetrospective StudiesBiomarkers, TumorCarcinoembryonic AntigenCytokinesKeratin-19

Identifiers

PMID41505423
PMCPMC12782445

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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.