Evidence map›Paper›PMID 38116469›Full record

ArticleOsteoarthritis and cartilage open2024

Serum proteomic panel validated for prediction of knee osteoarthritis progression.

Virginia Byers Kraus, Alexander Reed, Erik J Soderblom, M Arthur Moseley, Ming-Feng Hsueh, Mukundun G Attur, Jonathan Samuels, Steven B Abramson, Yi-Ju Li

Abstract read
In one paragraph

Article in Osteoarthritis and cartilage open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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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.

Virginia Byers KrausDuke Molecular Physiology Institute, Duke University, Durham, NC, USA.
Alexander ReedDuke Molecular Physiology Institute, Duke University, Durham, NC, USA.
Erik J SoderblomDuke Proteomics and Metabolomics Core Facility, Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.
M Arthur MoseleyDuke Proteomics and Metabolomics Core Facility, Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.
Ming-Feng HsuehDuke Molecular Physiology Institute, Duke University, Durham, NC, USA.
Mukundun G AtturDivision of Rheumatology, Department of Medicine, NYU School of Medicine, New York, NY, USA.
Jonathan SamuelsDivision of Rheumatology, Department of Medicine, NYU School of Medicine, New York, NY, USA.
Steven B AbramsonDivision of Rheumatology, Department of Medicine, NYU School of Medicine, New York, NY, USA.
Yi-Ju LiDuke Molecular Physiology Institute, Duke University, Durham, NC, USA.

Funding

Leukocyte Gene Expression in OsteoarthritisR01AR052873 · NIAMS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ABRAMSON, STEVEN B · 2005 to 2016
$4.8M
6 · The paper itself

Abstract

Objective: To further validate a serum proteomics panel for predicting radiographic (structural) knee OA progression. Design: Serum peptides were targeted by multiple-reaction-monitoring mass spectrometry in the New York University cohort (n ​= ​104). Knee OA progression was defined as joint space narrowing ≥1 in the tibiofemoral compartment of one knee per study participant over a 24-month follow-up. The discriminative ability of an 11-peptide panel was evaluated by multivariable logistic regression and area under the receiver operating characteristic curve (AUC), without and with demographic characteristics of age, sex, and body mass index. The association of each peptide with OA progression was assessed by odds ratios (OR) in multivariable logistic regression models adjusted for demographics. Results: The cohort included 46 (44%) knee OA progressors. The panel of 11 peptides alone yielded AUC ​= ​0.66 (95% CI [0.55, 0.77]) for discriminating progressors from non-progressors; demographic traits alone yielded AUC ​= ​0.66 (95% CI [0.55, 0.77]). Together the 11 peptides and demographics yielded AUC ​= ​0.72 (95% CI [0.62, 0.83]). CRAC1 had the highest odds for predicting OA progression (OR 2.014, 95% CI [0.996, 4.296], p ​= ​0.058). Conclusions: We evaluated a parsimonious serum proteomic panel and found it to be a good discriminator of knee radiographic OA progression from non-progression. Since these biomarkers are quantifiable in serum, they could be deployed relatively easily to provide a simple, cost-effective strategy for identifying and monitoring individuals at high risk of knee OA progression.

Indexed as

CartilageOsteoarthritisProgressionProteomicsSerum

Identifiers

PMID38116469
PMCPMC10726242

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.