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Annals of the rheumatic diseases

October 5, 2026 · via Europe PMC

Preclinical and clinical outcomes in patients with high rheumatoid factor levels treated with TNF inhibitors:a systematic review.

Smolen J, Nikiphorou E, Pope J, +5 more, Fleischmann RM.

Journal ArticleAbstract only — full text under license

AI summary — for doctors, generated from the abstract only

Patients with high rheumatoid factor treated with Fc-free TNF inhibitors had similar or slightly better outcomes than those with low RF, suggesting a possible advantage over Fc-containing agents.

What was studied

A systematic review (MEDLINE, Embase, Cochrane CENTRAL to January 2025, updated July 2025) of how rheumatoid factor binds TNF inhibitors with and without an Fc portion, and its effect on drug levels and clinical outcomes in adults with RA.

Key findings

  • 21 studies were included: 3 preclinical, 1 with both preclinical and clinical data, and 18 reporting outcomes in 8910 patients
  • Disease activity and Boolean remission outcomes were similar or slightly better in high-RF patients on Fc-free TNF inhibitors than in low-RF patients
  • The authors conclude Fc-free TNF inhibitors may offer some advantages in high-RF patients

Clinical relevance

RF level may be one consideration when choosing among TNF inhibitors in RA, though the evidence here is indirect and not a head-to-head comparison.

Who should care

Clinical Immunology & Rheumatology

Limitations

The abstract does not report results for Fc-containing agents in numbers or assess study quality; the included studies are heterogeneous and mostly observational, and the conclusion is hedged.

High RF may blunt response to Fc-containing TNF inhibitors, and Fc-free agents may do relatively better, but direct comparative evidence is lacking.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

Objectives

Rheumatoid factor (RF) binds to the fragment crystallisable (Fc) portion of immunoglobulin G1 and can also bind to the Fc region of biologic agents, forming immune complexes that are subsequently cleared by macrophages, contributing to reduced drug availability and diminished therapeutic response. In this systematic review, we examined the binding mechanism and impact of RF on tumour necrosis factor inhibitors (TNFis) with and without an Fc portion, along with the impact of RF levels on drug concentration and clinical outcomes in patients with rheumatoid arthritis (RA).

Methods

Searches were carried out in MEDLINE, Embase, and Cochrane CENTRAL up to January 2025 and updated in July 2025. Abstracts and full texts were screened, and discrepancies were resolved by consensus. Studies that included at least 1 group of adult patients with high RF treated with TNFis (with or without an Fc region) with outcomes of interest were considered for inclusion.

Results

Of the 21 studies included, 1 study reported both clinical and preclinical data, 3 studies reported preclinical data, and 18 studies reported efficacy and effectiveness outcomes in 8910 patients treated with TNFis. Clinical endpoints, such as the Clinical Disease Activity Index, the Simple Disease Activity Index, the Disease Activity Score-28 with C-reactive protein (DAS28-CRP), or erythrocyte sedimentation rate (DAS28-ESR), and Boolean remission were similar or slightly better in patients with high RF who received Fc-free TNFis, relative to those with low RF levels.

Conclusions

Considering these observations, Fc-free TNFis may provide some advantages to RA patients with high RF levels.

DOI

10.1016/j.ard.2026.08.009

PMID

42833948

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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