Evidence map›Paper›PMID 35197508›Full record

ArticleScientific reports2022

Diagnosing pleural effusions using mass spectrometry-based multiplexed targeted proteomics quantitating mid- to high-abundance markers of cancer, infection/inflammation and tuberculosis.

Aleksandra Robak, Michał Kistowski, Grzegorz Wojtas, Anna Perzanowska, Tomasz Targowski, Agata Michalak, Grzegorz Krasowski, Michał Dadlez, Dominik Domański

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
4.1field-weighted citation impact, top 5% 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

7 citing papers in PubMed, 28 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

9 authors at 2 institutions in 1 country.

Aleksandra RobakMass Spectrometry Laboratory, Institute of Biochemistry and Biophysics - Polish Academy of Sciences, Warsaw, Poland.
Michał KistowskiMass Spectrometry Laboratory, Institute of Biochemistry and Biophysics - Polish Academy of Sciences, Warsaw, Poland.
Grzegorz WojtasMazovian Center of Pulmonary Disease and Tuberculosis Treatment, Otwock, Poland.
Anna PerzanowskaMass Spectrometry Laboratory, Institute of Biochemistry and Biophysics - Polish Academy of Sciences, Warsaw, Poland.
Tomasz TargowskiDepartment of Geriatrics, National Institute of Geriatrics, Rheumatology and Rehabilitation, Warsaw, Poland.
Agata MichalakMazovian Center of Pulmonary Disease and Tuberculosis Treatment, Otwock, Poland.
Grzegorz KrasowskiMazovian Center of Pulmonary Disease and Tuberculosis Treatment, Otwock, Poland.
Michał DadlezMass Spectrometry Laboratory, Institute of Biochemistry and Biophysics - Polish Academy of Sciences, Warsaw, Poland.
Dominik DomańskiMass Spectrometry Laboratory, Institute of Biochemistry and Biophysics - Polish Academy of Sciences, Warsaw, Poland. dom.domanski@ibb.waw.pl.
Institute of Biochemistry and Biophysics, Polish Academy of Sciences · PLNational Institute of Geriatrics, Rheumatology and Rehabilitation · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pleural effusion (PE) is excess fluid in the pleural cavity that stems from lung cancer, other diseases like extra-pulmonary tuberculosis (TB) and pneumonia, or from a variety of benign conditions. Diagnosing its cause is often a clinical challenge and we have applied targeted proteomic methods with the aim of aiding the determination of PE etiology. We developed a mass spectrometry (MS)-based multiple reaction monitoring (MRM)-protein-panel assay to precisely quantitate 53 established cancer-markers, TB-markers, and infection/inflammation-markers currently assessed individually in the clinic, as well as potential biomarkers suggested in the literature for PE classification. Since MS-based proteomic assays are on the cusp of entering clinical use, we assessed the merits of such an approach and this marker panel based on a single-center 209 patient cohort with established etiology. We observed groups of infection/inflammation markers (ADA2, WARS, CXCL10, S100A9, VIM, APCS, LGALS1, CRP, MMP9, and LDHA) that specifically discriminate TB-PEs and other-infectious-PEs, and a number of cancer markers (CDH1, MUC1/CA-15-3, THBS4, MSLN, HPX, SVEP1, SPINT1, CK-18, and CK-8) that discriminate cancerous-PEs. Some previously suggested potential biomarkers did not show any significant difference. Using a Decision Tree/Multiclass classification method, we show a very good discrimination ability for classifying PEs into one of four types: cancerous-PEs (AUC: 0.863), tuberculous-PEs (AUC of 0.859), other-infectious-PEs (AUC of 0.863), and benign-PEs (AUC: 0.842). This type of approach and the indicated markers have the potential to assist in clinical diagnosis in the future, and help with the difficult decision on therapy guidance.

Indexed as

BiomarkersHumansInfectionsLung NeoplasmsMass SpectrometryPleural CavityPleural EffusionPneumoniaProteomicsROC CurveTuberculosisBiomarkers

Identifiers

PMID35197508
PMCPMC8866415
OpenAlexW4214631416

What OpenQuestion holds

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Registered trials

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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.