Evidence map›Paper›PMID 32643535›Full record

SynthesisTherapeutic advances in respiratory disease

The clinical value of suPAR in diagnosis and prediction for patients with chronic obstructive pulmonary disease: a systematic review and meta-analysis.

Qiangru Huang, Huaiyu Xiong, Tiankui Shuai, Yalei Wang, Chuchu Zhang, Meng Zhang, Lei Zhu, Jiaju Lu, Jian Liu

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Therapeutic advances in respiratory disease. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.1field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Review
  6. A CT-Based Lung Radiomics Nomogram for Classifying the Severity of Chronic Obstructive Pulmonary Disease.International journal of chronic obstructive pulmonary disease · 2024
    Article
  7. Article
  8. Article
  9. Early detection and prediction of acute exacerbation of chronic obstructive pulmonary disease.Chinese medical journal pulmonary and critical care medicine · 2023
    Review
  10. Article
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

9 authors at 1 institution in 1 country.

Qiangru HuangDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, China.
Huaiyu XiongDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, China.
Tiankui ShuaiDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, China.
Yalei WangDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, China.
Chuchu ZhangDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, China.
Meng ZhangDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, China.
Lei ZhuDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, China.
Jiaju LuDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, China.
Jian LiuDepartment of Intensive Care Unit, The First Hospital of Lanzhou University, Lanzhou, 730000, China.ORCID 0000-0002-1825-571X
First Hospital of Lanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSoluble urokinase-type plasminogen activator receptor (suPAR) is positively correlated with immune system activity. Inflammation can promote the development of chronic obstructive pulmonary disease (COPD). Therefore, this study conducted a systematic review and meta-analysis to assess the association between suPAR levels and the pathogenesis of COPD, and further assess the exact clinical value of suPAR in COPD.

methodsPubMed, Excerpt Medica Database (Embase), Web of Science (WOS), and Cochrane Library databases were searched for studies that reported the value of suPAR diagnosis for adult COPD patients.

resultsA total of 11 studies were included, involving 4520 participants. Both COPD patients with predicted forced expiratory volume in 1 s (FEV1)⩾80% [weighted mean difference (WMD) = 320.25; 95% confidence interval (CI): 99.79-540.71] and FEV1 < 80% (WMD = 2950.74; 95% CI: 2647.06-3254.43) showed higher suPAR level. The sensitivity and specificity of suPAR for diagnosis of COPD were 87% and 79%, respectively, and AUC was 84%. This can not only effectively identify acute exacerbation of COPD (AECOPD) in a healthy population (WMD = 3114.77; 95% CI: 2814.66-3414.88), but also has the potential to distinguish AECOPD from stable COPD (WMD = 351.40; 95% CI: 215.88-486.93). There was a significant decrease of suPAR level after treatment [WMD = -1226.97; 95% CI: -1380.91- (-1073.03)].

conclusionsuPAR as a novel biomarker has potential for early diagnosis of COPD and prediction of AECOPD. There is a potential correlation between the level of suPAR and the state of COPD, which may also indicate the early state and severity of COPD. When the suPAR level of COPD patients is further increased, the risk of acute exacerbation increases and should be highly valued. This also shows potential as a measure of treatment response, and as a guide to the clinical management in COPD.

Indexed as

AgedBiomarkersEarly DiagnosisFemaleForced Expiratory VolumeHumansLungMaleMiddle AgedPredictive Value of TestsPrognosisPulmonary Disease, Chronic ObstructiveReceptors, Urokinase Plasminogen ActivatorVital CapacityBiomarkersPLAUR protein, humanReceptors, Urokinase Plasminogen Activatorbiomarkerchronic obstructive pulmonary disease (COPD)meta-analysissoluble urokinase-type plasminogen activator receptor (suPAR)systematic review

Identifiers

PMID32643535
PMCPMC7350130
OpenAlexW3040962988

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.