Evidence map›Paper›PMID 38366632›Full record

ArticleRheumatology (Oxford, England)2024

Multiple serum biomarkers associate with mortality and interstitial lung disease progression in systemic sclerosis.

Matthew James Sinclair Parker, Adelle S Jee, Dylan Hansen, Susanna Proudman, Peter Youssef, Tony J Kenna, Wendy Stevens, Mandana Nikpour, Joanne Sahhar, Tamera J Corte

Open access · hybridAbstract read
In one paragraph

Article in Rheumatology (Oxford, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

13 citing papers in PubMed, 14 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

10 authors at 6 institutions in 2 countries.

Matthew James Sinclair ParkerFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0002-6550-1995
Adelle S JeeFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Dylan HansenDepartment of Rheumatology, St Vincent's Hospital, Melbourne, Australia.
Susanna ProudmanRheumatology Unit, Royal Adelaide Hospital, Adelaide, Australia.
Peter YoussefFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.
Tony J KennaCentre for Immunology and Infection Control, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia.
Wendy StevensDepartment of Rheumatology, St Vincent's Hospital, Melbourne, Australia.
Mandana NikpourDepartment of Rheumatology, St Vincent's Hospital, Melbourne, Australia.
Joanne SahharDepartment of Rheumatology, Monash Health, Melbourne, Australia.
Tamera J CorteFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.
The University of Sydney · AUSt Vincent's Hospital Melbourne · AUMonash Health · AUQueensland University of Technology · AURoyal Adelaide Hospital · AUThe University of Melbourne · AU

Funding

Australian Rheumatology AssociationAustralian Scleroderma Cohort StudyBrian Eaton MemorialCentre of Research Excellence in Pulmonary FibrosisDepartment of Allergy and Clinical Immunology and Department of RespiratoryLung Foundation AustraliaNHMRC GNT1162767Royal Prince Alfred HospitalScleroderma Clinical Trials Consortium, Boehringer-Ingelheim and BayerSt Vincent's Hospital Melbourne Information Technology DepartmentThe Australian Scleroderma Interest GroupThe Thoracic Society of Australia & New ZealandUniversity of Sydney
6 · The paper itself

Abstract

objectivesTo investigate the prognostic utility of 28 serum biomarkers in systemic sclerosis (SSc), SSc-associated interstitial lung disease (SSc-ILD) and clinically relevant disease subgroups.

methodsParticipants with sera, high-resolution CT and lung function within 12 months of baseline were identified from the Australian Scleroderma Cohort Study. Baseline was the time of serum collection. Twenty-seven of the prespecified 28 serum biomarkers were analysed and biomarker associations with mortality and ILD progression were investigated in univariable and multivariable analyses, including within disease subgroups and combined with established risk factors for poorer prognosis in SSc.

resultsA total of 407 participants were identified, 252 (61.9%) with SSc-ILD. The median (interquartile range) follow-up after biomarker measurement was 6.31 (3.11-9.22) years. Sixteen biomarkers were associated with increased mortality. High levels of VCAM-1 were most strongly associated with mortality [hazard ratio (HR) 3.55; 95% CI 2.37-5.33; P < 0.001]. Five additional biomarkers had an HR >2: SP-D (2.28, 1.57-3.31; P < 0.001), E-selectin (2.19, 1.53-3.14; P < 0.001), IL-6 (2.15, 1.50-3.09; P < 0.001), MMP-3 (2.05, 1.42-2.95; P < 0.001) and ET-1 (2.03, 1.40-2.92; P < 0.001). Eleven biomarkers were independently associated with mortality following adjustment for sex, age and baseline forced vital capacity (FVC%predicted). Three biomarkers were associated with ILD progression at 1-year follow-up: CXCL4 (odds ratio 2.67, 1.46-4.88; P = 0.001), MMP-1 (2.56, 1.43-4.59; P = 0.002) and ET-1 (2.18, 1.24-3.83; P = 0.007).

conclusionMultiple biomarkers, especially VCAM-1, E-selectin, SP-D and CXCL4, provide prognostic utility beyond that of established risk factors for patients with SSc.

Indexed as

BiomarkersDisease ProgressionLung Diseases, InterstitialScleroderma, SystemicAdultAgedAustraliaFemaleHumansInterleukin-6MaleMatrix Metalloproteinase 3Middle AgedPrognosisPulmonary Surfactant-Associated Protein DRisk FactorsBiomarkersInterleukin-6Matrix Metalloproteinase 3Pulmonary Surfactant-Associated Protein DVascular Cell Adhesion Molecule-1CXCL4E-selectinFVCprognosissclerodermaSP-DVCAM-1

Identifiers

PMID38366632
PMCPMC11534140
OpenAlexW4391897978

What OpenQuestion holds

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LicenceCC BY
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.