Evidence map›Paper›PMID 33089426›Full record

ArticleImmunologic research2020

Utility of serological biomarker' panels for diagnostic accuracy of interstitial lung diseases.

Laura Bergantini, Miriana d'Alessandro, Lucia Vietri, Giuseppe Domenico Rana, Paolo Cameli, Silvia Acerra, Piersante Sestini, Elena Bargagli

Open access · hybridAbstract read
In one paragraph

Article in Immunologic research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.4field-weighted citation impact, top 9% 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

18 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Phenotypes and Serum Biomarkers in Sarcoidosis.Diagnostics (Basel, Switzerland) · 2024
    Review
  5. Article
  6. Article
  7. Acute Exacerbations of Interstitial Lung Diseases: Focus on Biomarkers.International journal of molecular sciences · 2023
    Review
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Clinical phenotyping in sarcoidosis management.Sarcoidosis, vasculitis, and diffuse lung diseases : official journal of WASOG · 2021
    Article
  18. 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

8 authors at 2 institutions in 1 country.

Laura BergantiniDepartment of Medical Sciences, Surgery and Neuroscience, Respiratory Disease and Lung Transplant Unit, Siena University, Siena, Italy. laurabergantini@gmail.com.ORCID 0000-0002-1118-3223
Miriana d'AlessandroDepartment of Medical Sciences, Surgery and Neuroscience, Respiratory Disease and Lung Transplant Unit, Siena University, Siena, Italy.
Lucia VietriDepartment of Medical Sciences, Surgery and Neuroscience, Respiratory Disease and Lung Transplant Unit, Siena University, Siena, Italy.
Giuseppe Domenico RanaInternal Medicine Unit, Department of Internal Medicine, Geriatrics and Rare Diseases Unit, Bari University, Bari, Italy.
Paolo CameliDepartment of Medical Sciences, Surgery and Neuroscience, Respiratory Disease and Lung Transplant Unit, Siena University, Siena, Italy.
Silvia AcerraDepartment of Medical Sciences, Surgery and Neuroscience, Respiratory Disease and Lung Transplant Unit, Siena University, Siena, Italy.
Piersante SestiniDepartment of Medical Sciences, Surgery and Neuroscience, Respiratory Disease and Lung Transplant Unit, Siena University, Siena, Italy.
Elena BargagliDepartment of Medical Sciences, Surgery and Neuroscience, Respiratory Disease and Lung Transplant Unit, Siena University, Siena, Italy.
University of Siena · ITUniversity of Bari Aldo Moro · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interstitial lung diseases (ILD) are a heterogeneous group of illnesses of known and unknown aetiology. Differential diagnosis among the three disorders is often challenging. Specific biomarkers with good sensitivity and specificity are therefore needed to predict clinical outcome and guide clinical decisions. The aim of this study was to investigate inflammatory/fibrotic biomarkers, to determine whether single mediators or panels of mediators could be useful to stratify patients into three distinct domains: sarcoidosis, idiopathic pulmonary fibrosis (IPF) and chronic hypersensitivity pneumonitis (cHP). A total of 163 ILD patients monitored at Siena Referral Centre for Sarcoidosis and other Interstitial Lung Diseases were enrolled in the study. Clinical data, pulmonary function tests and biochemical analytes were retrospectively collected. SAA levels were detected by ELISA kit and Krebs von den Lungen 6 (KL-6) were measured by CLEIA method, for sarcoidosis, cHP and IPF patients. Multiple comparison analysis showed significant differences in C reactive protein (CRP), white blood cell count (WBC) and creatinine levels between the three groups. In the logistic regression model, KL-6, CRP and WBC showed areas under curves (AUC) 0.86, for sarcoidosis diagnosis. The logistic regression model KL-6 and SAA showed the best performance with an AUC 0.81 for discriminating IPF than cHP and sarcoidosis. For differential diagnosis of IPF and cHP, KL-6 and SAA were considered in the logistic regression model, showed an AUC 0.79. The combination of serum biomarkers proposed here offers insights into the pathobiology of ILDs. These panels of bioindicators will improve diagnostic accuracy and will be useful in the clinical management of ILDs.

Indexed as

AdultAgedBiomarkersDiagnosis, DifferentialDisease SusceptibilityFemaleHumansLung Diseases, InterstitialMaleMiddle AgedRadiography, ThoracicRespiratory Function TestsROC CurveSerologic TestsTomography, X-Ray ComputedBiomarkersBiomarkersDiagnosisILDKL-6SAA

Identifiers

PMID33089426
PMCPMC7674352
OpenAlexW3094108029

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.