Evidence map›Paper›PMID 37606981›Full record

ArticleRheumatology (Oxford, England)2024

Characterizing the lavage and serum cytokine profiles of interstitial pneumonia with autoimmune features and their implications for progressive fibrosis.

Ziyi Zhang, Xiaoqian Ma, Junye Bai, Shu Xia, Qian Han, Qun Luo

Open access · hybridAbstract read
In one paragraph

Article in Rheumatology (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.8field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Ziyi ZhangState Key Laboratory of Respiratory Disease, National Clinical Research Centre for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Xiaoqian MaState Key Laboratory of Respiratory Disease, National Clinical Research Centre for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Junye BaiState Key Laboratory of Respiratory Disease, National Clinical Research Centre for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Shu XiaState Key Laboratory of Respiratory Disease, National Clinical Research Centre for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Qian HanState Key Laboratory of Respiratory Disease, National Clinical Research Centre for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
Qun LuoState Key Laboratory of Respiratory Disease, National Clinical Research Centre for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, Guangdong, China.
First Affiliated Hospital of Guangzhou Medical University · CNGuangzhou Medical University · CNState Key Laboratory of Respiratory Disease · CN

Funding

National Key Research and Development 2021YFC2500702
6 · The paper itself

Abstract

objectiveTo explore whether cytokines could be potential biomarkers to predict the occurrence of the progressive fibrosis (PF) phenotype among patients with interstitial pneumonia with autoimmune features (IPAF).

methodsThis study prospectively collected 51 IPAF and 15 idiopathic pulmonary fibrosis (IPF) patients who were diagnosed at the First Affiliated Hospital of Guangzhou Medical University from July 2020 to June 2021. All IPAF patients were followed up for 1 year to assess the development of PF phenotype. Paired bronchoalveolar lavage fluid (BALF) and serum samples were collected at enrolment and analysed for differences in 39 cytokines expression. Principal component analysis (PCA) and cluster analysis were conducted to identify a subgroup of IPAF patients at high risk for developing the PF phenotype. Finally, cytokine differences were compared between subgroups to identify potential biomarkers for PF-IPAF occurrence.

resultsAccording to the PCA analysis, 81.25% of PF-IPAF patients share overlapped BALF cytokine profiles with IPF. Cluster analysis indicated that IPAF patients in subtype 2 had a higher risk of developing the PF phenotype within 1 year (P = 0.048), characterized by higher levels of CCL2 and CXCL12, and lower lymphocyte proportion (LYM%) in BALF. Elevated levels of BALF CCL2 (>299.16 pg/ml) or CXCL12 (>660.115 pg/ml) were associated with a significantly higher risk of developing PF phenotype within the 1-year follow-up period (P = 0.009, 0.001, respectively).

conclusionPF-IPAF phenotype exhibits similar inflammatory cytokine profiles to IPF. Cytokine CCL2 and CXCL12, and LYM% in BALF serve as potential biomarkers for predicting the PF phenotype in IPAF patients. CLINICAL

trial registrationRegister: Qian Han, Website: http://www.chictr.org.cn/showproj.aspx?proj=61619, Registration number: ChiCTR2000040998.

Indexed as

BiomarkersBronchoalveolar Lavage FluidCytokinesIdiopathic Pulmonary FibrosisLung Diseases, InterstitialAdultAgedAutoimmune DiseasesDisease ProgressionFemaleHumansMaleMiddle AgedProspective StudiesBiomarkersCytokinesbronchoalveolar lavage fluidinflammatory cytokine profilesinterstitial pneumonia with autoimmune featuresprognosisprogressive fibrosis

Identifiers

PMID37606981
PMCPMC11065445
OpenAlexW4386046054

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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.