Evidence map›Paper›PMID 42698059›Full record

ReviewRheumatology and therapy2026

Updates on the Evaluation of Lupus Arthritis.

Wei Tang, Alberto Nordmann-Gomes, Leila Khalili, Giovanna Rosas, Ellen Montgomery, Laurel Zhang, Stephen Suh, Robert Clancy, Anca D Askanase

Abstract readReview
In one paragraph

Review in Rheumatology and therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Wei Tang *Department of Medicine, Westchester Medical Center, Valhalla, NY, USA.
Alberto Nordmann-Gomes *Department of Medicine, Division of Rheumatology, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, 10032, USA.
Leila KhaliliDepartment of Medicine, Division of Rheumatology, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, 10032, USA.
Giovanna RosasDepartment of Medicine, Division of Rheumatology, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, 10032, USA.
Ellen MontgomeryDepartment of Medicine, Division of Rheumatology, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, 10032, USA.
Laurel ZhangDepartment of Medicine, Division of Rheumatology, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, 10032, USA.
Stephen SuhDepartment of Medicine, Division of Rheumatology, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, 10032, USA.
Robert Clancy *Department of Medicine, Division of Rheumatology, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, 10032, USA.
Anca D Askanase *Department of Medicine, Division of Rheumatology, Columbia University Irving Medical Center, 630 West 168th Street, New York, NY, 10032, USA. ada20@cumc.columbia.edu.ORCID http://orcid.org/0000-0003-4597-5023

Funding

U.S. Department of Defense W81XWH-21-1-0468
6 · The paper itself

Abstract

Lupus arthritis is the most common manifestation of systemic lupus erythematosus (SLE), affecting up to 95% of patients. Clinical presentations range from inflammatory arthralgia and non-deforming non-erosive (NDNE) synovitis to Jaccoud arthropathy and erosive arthritis, reflecting substantial clinical heterogeneity. Despite its high prevalence, widely used outcome measures lack the granularity to distinguish between these phenotypes or accurately quantify disease severity. This narrative review integrates clinical phenotypes, serologic biomarkers, imaging advances, and emerging therapies to provide a framework for evaluating lupus arthritis. Besides distinct clinical phenotypes, we propose a conceptual hypothesis-generating model describing the evolution of lupus arthritis. In an early, preclinical stage, genetically predisposed individuals may develop pathogenic autoantibodies and alterations in the gut microbiome that can lead to increased inflammation within the synovium. The intermediate stage is characterized by progressive leukocyte accumulation within the joint space, leading to clinical symptoms and early abnormalities on imaging including joint effusions, synovitis, and tenosynovitis. In the late stage, persistent inflammation results in clinically evident joint damage, including synovial hypertrophy, joint capsular swelling, and bone erosions. Biomarkers such as anti-citrullinated protein antibodies (ACPAs), anti-carbamylated protein (anti-carP) antibodies, interleukin (IL)-6, IL-17, and metalloproteinases may help identify patients at risk for erosive or deforming disease and those prone to rapid progression. Advances in imaging technologies including musculoskeletal ultrasound (MSK-US), MRI, and optical tomography may enable earlier detection before clinical manifestations or physical exam findings, creating opportunities for earlier intervention. Therapeutically, hydroxychloroquine (HCQ) remains the foundation of treatment. Belimumab and anifrolumab are US Food and Drug Administration (FDA)-approved biologics now recommended as standard of care for persistent disease, alongside conventional immunosuppressants such as methotrexate, mycophenolate, or azathioprine when indicated. Additional targeted therapies including obinutuzumab and Janus kinase (JAK) inhibitors are closely following behind. Chimeric antigen receptor T cell (CAR-T) represents a promising approach that may transform the future management of SLE.

Indexed as

ArthritisBiologicsBiomarkersLupus arthritisSystemic lupus erythematosus

Identifiers

PMID42698059
PMCPMC13624230

What OpenQuestion holds

Textmetadata
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.