Evidence map›Paper›PMID 41590989›Full record

ArticleNEJM evidence2026

A Quantitative Lung Mucin Score to Identify Chronic Bronchitis.

Mehmet Kesimer, Giorgia Radicioni, Amina A Ford, Agathe Ceppe, Neil E Alexis, R Graham Barr, Eugene R Bleecker, Stephanie A Christenson, Christopher B Cooper, MeiLan K Han and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NEJM evidence, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

18 authors.

Mehmet KesimerMarsico Lung Institute/Cystic Fibrosis and Pulmonary Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Giorgia RadicioniMarsico Lung Institute/Cystic Fibrosis and Pulmonary Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Amina A FordMarsico Lung Institute/Cystic Fibrosis and Pulmonary Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Agathe CeppeMarsico Lung Institute/Cystic Fibrosis and Pulmonary Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Neil E AlexisCenter for Environmental Medicine, Asthma, and Lung Biology, Division of Allergy and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
R Graham BarrDepartment of Medicine, Columbia University Medical Center, New York, NY, USA.
Eugene R BleeckerCenter for Genetics and Genomic Medicine, University of Arizona Health Sciences, Tucson, AZ, USA.
Stephanie A ChristensonDivision of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of San Francisco Medical Center, University of California, San Francisco, CA, USA.
Christopher B CooperDepartment of Medicine and Physiology, David Geffen School of Medicine, University of California, Los Angeles, CA, USA.
MeiLan K HanDivision of Pulmonary and Critical Care Medicine, University of Michigan Health System, Ann Arbor, MI, USA.
Nadia N HanselDivision of Pulmonary and Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Annette T HastieSection on Pulmonary, Critical Care, Allergy and Immunology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Eric A HoffmanDepartment of Radiology, Division of Physiologic Imaging, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Richard E KannerDepartment of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Utah, Salt Lake City, UT, USA.
Fernando J MartinezDepartment of Medicine, UMass Chan Medical School, North Worcester, MA, USA.
Robert PaineDepartment of Internal Medicine, Division of Pulmonary and Critical Care Medicine, University of Utah, Salt Lake City, UT, USA.
Prescott G WoodruffDivision of Pulmonary, Critical Care, Allergy, and Sleep Medicine, Department of Medicine, University of San Francisco Medical Center, University of California, San Francisco, CA, USA.
Richard C BoucherMarsico Lung Institute/Cystic Fibrosis and Pulmonary Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Funding

SPIROMICS II: Biological underpinnings of COPD heterogeneity and progressionU01HL137880 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI WOODRUFF, PRESCOTT G · 2017 to 2021
$27.9M
Airway mucus/mucin composition and proteome in COPD: A SPIROMICS ancillary studyR01HL110906 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KESIMER, MEHMET · 2011 to 2014
$1.4M
NHLBI NIH HHS R01 HL110906NHLBI NIH HHS U01 HL137880
6 · The paper itself

Abstract

backgroundWe previously demonstrated that sputum total mucin concentration is an objective marker for chronic bronchitis (CB). This current study introduces a novel Mucin Quantitative Score (MUCQ) that combines total mucin concentration and mucin composition to improve the assessment of risk, onset of clinically diagnosed disease, and progression of muco-obstructive lung diseases.

methodsPatients from the SPIROMICS (SubPopulations and InteRmediate Outcome Measures in COPD Study) cohort were classified as having CB, or not, based on clinical questionnaires. Using the measured total mucin, MUC5AC, and MUC5B concentrations in sputum samples, we calculated MUCQ as [Total mucin]×([MUC5AC]÷[MUC5B])÷100 μg/ml, which is a unitless, weighted concentration score. Our primary outcome was the net reclassification of patients with a diagnosis of CB, or not, based on total mucin concentrations in their sputum compared with using the MUCQ score. Participants were first classified as CB- positive or -negative using a total mucin concentration threshold of 2306 μg/ml, then reclassified using the MUCQ threshold of 4.30. Associated z statistics and a P value for the primary outcome are reported.

resultsAmong 164 patients in the SPIROMICS cohort with clinically defined CB, using the MUCQ score up-classified 18 patients who were currently smoking to a diagnosis of CB and down-classified 5 patients who were currently smoking and 3 control participants who had never smoked, compared with the classification of CB was based on total mucin concentrations alone (P=0.001). In addition, MUCQ correlated with other clinical and pathological indices of chronic airway disease and airway obstruction.

conclusionsThe MUCQ metric was superior in distinguishing patients with CB compared to a total mucin concentration. Trials are needed to ascertain the prospective use of MUCQ metrics in research and clinical settings for assessment, management, and tracking therapeutic responses in CB and potentially other muco-obstructive conditions. (Funded by the National Institutes of Health and others.).

Indexed as

Bronchitis, ChronicMucin 5ACMucin-5BMucinsSputumAgedBiomarkersCohort StudiesFemaleHumansMaleMiddle AgedBiomarkersMUC5B protein, humanMucin 5ACMucin-5BMucins

Identifiers

PMID41590989
PMCPMC13055890

What Socratic holds

Textmetadata
LicenceTDM
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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 Socratic graph.