Evidence map›Paper›PMID 41594305›Full record

ReviewDiagnostics (Basel, Switzerland)2026

Biomarkers in Rheumatoid Arthritis: From Traditional Serology to Precision Medicine Integration.

Muhammad Soyfoo, Julie Sarrand

Abstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
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

2 authors.

Muhammad SoyfooDepartment of Rheumatology, Hôpital Universitaire de Bruxelles, Université libre de Bruxelles, 1070 Brussels, Belgium.ORCID 0000-0002-9051-1810
Julie SarrandDepartment of Rheumatology, Hôpital Universitaire de Bruxelles, Université libre de Bruxelles, 1070 Brussels, Belgium.ORCID 0000-0002-6833-0044

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The biomarker landscape in rheumatoid arthritis (RA) is evolving from reliance on traditional markers toward integrated, multimodal strategies enabling precision medicine approaches. To critically evaluate emerging biomarkers across serological, cellular, genetic, imaging, and multi-omic domains, distinguishing those approaching clinical readiness from those requiring further development. In this study, a narrative review of the literature published between 2000 and 2024 relevant to clinical decision-making in RA was conducted. Among novel serological markers, 14-3-3η protein and anti-carbamylated protein antibodies show the strongest validation for seronegative disease and prognostic stratification. Calprotectin demonstrates utility for disease activity monitoring and de-escalation decisions. Multi-biomarker disease activity scores provide an objective assessment but lack outcome trial validation. Musculoskeletal ultrasound offers accessible imaging biomarker capability, while MRI bone marrow edema remains the strongest structural progression predictor. Synovial tissue pathotyping has demonstrated proof-of-concept for treatment stratification. Genetic, epigenetic, and metabolomic approaches remain investigational. Key clinical implications include using 14-3-3η and calprotectin to inform seronegative diagnosis and de-escalation decisions, integrating ultrasound for remission verification, and recognizing that emerging biomarkers for extra-articular complications, including cardiovascular risk and venous thromboembolism, represent important unmet needs.

Indexed as

14-3-3ηanti-citrullinated protein antibodiesbiomarkerscalprotectinMRImulti-biomarker disease activityprecision medicinerheumatoid arthritistreat-to-targetultrasound

Identifiers

PMID41594305
PMCPMC12840372

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.