Cited by 50Systemic Lupus Erythematosus ResearchSystemic Sclerosis and Related DiseasesVasculitis and related conditions

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

Anti-nucleosome antibodies outperform traditional biomarkers as longitudinal indicators of disease activity in systemic lupus erythematosus

Open access

Abstract

OBJECTIVE: The aim of this study was to determine whether anti-nucleosome antibodies function as activity-specific biomarkers in SLE. METHODS: Fifty-one patients were recruited and followed prospectively with periodic clinical and biochemical assessments over a 14-month period. Disease activity was determined by the SLEDAI-2K. Anti-nucleosome antibody levels were measured by an ELISA and its utility as an activity-specific biomarker as compared with that of anti-dsDNA antibodies and C3 was assessed both at baseline and in longitudinal analysis. RESULTS: Anti-nucleosome antibodies were significantly elevated in SLE patients vs controls and showed a moderate positive correlation with disease activity. The utility of anti-nucleosome antibodies in identifying patients with active disease in a cross-sectional analysis was comparable to that of anti-dsDNA antibodies and C3. Analysis of variance demonstrated that the level of anti-nucleosome antibodies and C3 varied significantly with changes in disease activity over time. Changes in clinical state were not mirrored by changes in anti-dsDNA antibodies. In time-dependent analysis, anti-nucleosome antibodies showed a better fit over time than anti-dsDNA antibodies and C3. In pairwise comparisons, C3 and anti-nucleosome antibodies outperformed other models, including the conventional pairing of C3 and anti-dsDNA antibodies, however, no biomarker alone or as a group accurately predicted impending remissions or exacerbations. CONCLUSION: Anti-nucleosome antibodies demonstrate greater fidelity as a biomarker for changes in SLE disease activity than traditional biomarkers, supporting the routine monitoring of this antibody in clinical practice.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/rheumatology/keu326

Cites

24 of 24 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • dsDNA antibodies are among the most commonly detected ANAs in SLE and correlate with disease activity and especially renal involvement.

    “As double-stranded DNA (dsDNA) antibodies are among the most commonly detected ANAs in SLE, reported to correlate also with disease activity and especially renal involvement (6-9)”

    From Anti-dsDNA Testing Specificity for Systemic Lupus Erythematosus: A Systematic Review. (2022) · cites this paper as [8]

    The cross-sectional analysis reports anti-dsDNA positivity in 39 of 50 SLE patients (78%) and a correlation with global disease activity. The Discussion links proliferative renal lesions to simultaneous positivity for anti-dsDNA and anti-nucleosome antibodies, but does not establish the claimed association between anti-dsDNA antibodies alone and especially renal involvement. No page numbers are available in our copy. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. Gladman, 2002, The Journal of Rheumatology, 29, 288
  2. Neogi, 2006, The Journal of Rheumatology, 33, 1785

Cited by

Sorted by citations

Metadata

Authors
Li, T., Prokopec, S. D., Morrison, S., Lou, W., Reich, H., Gladman, D., Urowitz, M., Scholey, J., Fortin, P. R., Boutros, P. C., Wither, J., & Landolt-Marticorena, C.
Affiliations
Ontario Institute for Cancer Research (CA)
Venue
Rheumatology
Published
2014-09-05
Volume
54
Issue
3
Pages
449-457
ISSN
  • 1462-0324 (ISSN-L)
  • 1462-0332
OpenAlex
W2141500677
Cited by
49
References
24
Citations by year
2026: 3 · 2025: 3 · 2024: 1 · 2023: 3 · 2022: 6 · 2021: 5 · 2020: 6 · 2019: 3 · 2018: 4 · 2017: 6 · 2016: 4 · 2015: 4 · 2014: 1
FWCI
4.15
Type
journal article
Language
en
Open access
Locations
  • Lara D. Veeken (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • University Health Network
  • Ontario Institute for Cancer Research
  • Government of Ontario
  • Arthritis Society
  • University of Toronto
  • Canadian Institutes of Health Research (QNT #78341)
Topics
  • Health Sciences › Medicine › Rheumatology › Systemic Lupus Erythematosus Research
  • Health Sciences › Medicine › Rheumatology › Systemic Sclerosis and Related Diseases
  • Health Sciences › Medicine › Rheumatology › Vasculitis and related conditions
Keywords
anti-nucleosome antibodies, systemic lupus erythematosus, disease activity markers, anti-dsDNA antibodies, complement C3, SLEDAI-2K, longitudinal disease monitoring
MeSH terms
Adolescent, Adult, Aged, Antibodies, Anti-Idiotypic, Complement C3, Cross-Sectional Studies, DNA, Female, Humans, Longitudinal Studies, Lupus Erythematosus, Systemic, Male, Middle Aged, Nucleosomes, Prospective Studies, Sensitivity and Specificity, Severity of Illness Index, Time Factors, Biomarkers, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review