Evidence map›Paper›PMID 40612945›Full record

ArticleFrontiers in immunology2025

Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait.

Nicol Bernardinello, Federica Pezzuto, Lauren D'Sa, Luca Vedovelli, Chiara Giraudo, Anamaria Chelu, Cecilia de Chellis, Francesca Lunardi, Francesco Fortarezza, Francesca Boscaro and 4 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

14 authors.

Nicol Bernardinello *Respiratory Disease Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Federica Pezzuto *Department of Cardiac, Thoracic, Vascular Science, and Public Health, University of Padova, Padova, Italy.
Lauren D'SaDepartment of Histopathology, Royal Brompton and Harefield Hospitals, Guy's and St Thomas' National Health Service (NHS) Foundation Trust, London, United Kingdom.
Luca VedovelliDepartment of Cardiac, Thoracic, Vascular Science, and Public Health, University of Padova, Padova, Italy.
Chiara GiraudoDepartment of Cardiac, Thoracic, Vascular Science, and Public Health, University of Padova, Padova, Italy.
Anamaria CheluRespiratory Disease Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Cecilia de ChellisDepartment of Cardiac, Thoracic, Vascular Science, and Public Health, University of Padova, Padova, Italy.
Francesca LunardiDepartment of Cardiac, Thoracic, Vascular Science, and Public Health, University of Padova, Padova, Italy.
Francesco FortarezzaDepartment of Cardiac, Thoracic, Vascular Science, and Public Health, University of Padova, Padova, Italy.
Francesca BoscaroRespiratory Disease Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Elisabetta CocconcelliRespiratory Disease Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Paolo SpagnoloRespiratory Disease Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Elisabetta BalestroRespiratory Disease Unit, Department of Cardiac, Thoracic, Vascular Sciences and Public Health, University of Padova, Padova, Italy.
Fiorella CalabreseDepartment of Cardiac, Thoracic, Vascular Science, and Public Health, University of Padova, Padova, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The term progressive pulmonary fibrosis (PPF) refers to a specific disorder that becomes worse despite optimal treatment. The pathogenic explanation of this progressive worsening is still to be found. In this study, we explored whether any histological, molecular, radiological, or clinical features could predict a progressive phenotype in patients with fibrotic interstitial lung diseases. Methods: Two hundred and fifteen patients with PPF other than idiopathic pulmonary fibrosis (IPF) and connective tissue disease-associated ILD (CTD-ILD) were followed in our ILD clinic between January 2016 and May 2023. Based on tissue block availability, 48 patients were definitively enrolled. Progression was defined according to the most recent guidelines. Clinical, radiological, and functional data were also collected retrospectively and correlated with tissue morphological and molecular cytokine profiles. Results: Fifteen patients were classified as progressors (PPF) and 33 as non-progressors (nPPF) with similar age at diagnosis and gender. PPF showed a higher prevalence of traction bronchiectasis (80% vs. 27%; p=<0.001) at CT scan and lower functional parameters [FVC: 2.42 L vs. 3.37 L; p=0.004; TLC: 3.83 L vs. 4.65 L; p=0.027] at diagnosis. Lung specimens revealed a significant overexpression of IL9 in the PPF compared to the nPPF group (p=0.049). Boruta algorithm analysis showed that lymphoid aggregates and traction bronchiectasis at diagnosis are the most important variables in determining the PPF status. Conclusions: The present results increase the understanding of the pathological mechanisms of PPF, offering potential avenues for improved prognostication and therapeutic intervention.

Indexed as

BiomarkersCytokinesLungPulmonary FibrosisAgedDisease ProgressionFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesTomography, X-Ray ComputedBiomarkersCytokinesIL-9interstitial lung diseaselung fibrosisprogressive pulmonary fibrosistraction bronchiectasis

Identifiers

PMID40612945
PMCPMC12221905

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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.