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Record W4411884087 · doi:10.3899/jrheum.2025-0314.111

The Efficacy of Leflunomide in the Treatment of Giant Cell Arteritis: A Systematic Review and Meta-Analysis

2025· review· en· W4411884087 on OpenAlexaffvenue
Na Zhu, Arielle Mendel, Carolyn Ross, Jean‐Paul Makhzoum

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typereview
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsHôpital du Sacré-Cœur de MontréalMcGill University Health CentreUniversité de Montréal
Fundersnot available
KeywordsMedicineLeflunomideMeta-analysisInternal medicineGiant cell arteritisDiscontinuationRandomized controlled trialPrednisoneSurgeryDiseaseRheumatoid arthritisVasculitis

Abstract

fetched live from OpenAlex

Objectives The objective of this systematic review is to assess the effectiveness of leflunomide in the treatment of new-onset, refractory or relapsing giant cell arteritis (GCA) as a glucocorticoid (GC)-sparing agent. Methods A systematic review was conducted using MEDLINE, CENTRAL, EMBASE, and conference proceedings to identify studies on leflunomide in patients with GCA. We included randomized controlled trials, cohort studies, case-control studies, and case series. The primary efficacy outcome was the proportion of patients who attained GC-free remission with leflunomide assessed at any time between 6 to 12 months of therapy. GC-free remission was defined as the absence of signs or symptoms of GCA, and/or normalization of inflammatory markers, and/or radiologic response, and complete discontinuation of GC. Our secondary efficacy outcome was the proportion of patients who attained low-dose GC remission (< 5 mg of prednisone equivalent). All included studies were appraised for risk of bias. We performed a meta-analysis of proportions using a random-effects model and a restricted maximal likelihood approach. We evaluated heterogeneity with I2 and Cochran’s Q test. Publication bias was assessed by producing funnel plots for each outcome. Results 357 studies were screened with 10 observational studies included in the final analysis. Out of the 358 patients that we pooled for analysis, 231 (69%) were females. A total of 233 (65%) patients had new-onset GCA, 83 patients had relapsing GCA (23%), and 19 patients had refractory GCA (5%). The disease subtype was not specified for 23 patients. The proportion of patients achieving GC-free remission with leflunomide was 45%, (95% CI 0.25-0.64, p<0.001, 7 studies) (Figure). Substantial statistical heterogeneity was present (I2=90.3%, Q=70.7, p<0.001). Meanwhile, the pooled proportion of patients achieving low-dose GC remission was 48% (95% CI 0.27-0.69, p<0.001, 6 studies). Funnel plots were slightly asymmetrical, which suggested the presence of publication bias as well as possible poor methodological quality in the reporting of outcomes. All the included studies were deemed to be at serious risk of bias.[1] Conclusion The main challenge in treating GCA is achieving and maintaining remission with minimal glucocorticoids. Our study shows that leflunomide may offer potential benefits in achieving remission without GCs or with low-dose GCs; however, the results exhibited variability due to differences in sample sizes and inconsistent reporting. Leflunomide’s role as a glucocorticoid-sparing agent is promising but needs further investigation into higher-quality studies. PROSPERO registration CRD42023490373. [1.] Sterne JA. BMJ 2016;355:i4919.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.033
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0240.030
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.036
GPT teacher head0.330
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes2
Has abstractyes

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