ArticleReumatologia2024
Early predictive factors in routine clinical practice for rituximab therapy response in patients with rheumatoid arthritis.
Article in Reumatologia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
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Who cites it
2 citing papers in PubMed.
- Global patterns and predictors of initial treatment in early rheumatoid arthritis: insights from a multinational machine learning study.Clinical rheumatology · 2026Article
- Efficacy and Safety of Biologic and Targeted Synthetic DMARDs in Young-Onset Rheumatoid Arthritis: A Systematic Review.Life (Basel, Switzerland) · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Identifying early predictive factors of how rheumatoid arthritis (RA) patients respond to rituximab (RTX) treatment is crucial for both individual treatment outcome and the improvement of clinical practice overall. This study aimed to identify early predictive factors available in standard clinical practice for predicting RTX treatment outcomes in RA patients. Material and methods: Data on seventy patients diagnosed with RA treated with RTX (two 1,000 mg doses 2 weeks apart or two 500 mg doses 2 weeks apart) were retrospectively collected. Baseline information collected at the initiation of RTX treatment included patient characteristics such as age, sex, disease duration, disease activity, Health Assessment Questionnaire score, erythrocyte sedimentation rate, C-reactive protein, and serological status regarding rheumatoid factor (RF) and anti-cyclic citrullinated protein antibodies (ACPA). Clinical responses were analyzed 6 months after RTX initiation using the European Alliance of Associations for Rheumatology criteria. Potential predictors associated with positive RTX response at 6 months were identified using a multivariate ordinal logistic regression model. Results: The analysis showed that persistently active RA disease, Disease Activity Score with 28-joint count (DAS28) values at the treatment onset and after 3 months, along with erythrocyte sedimentation rate at treatment initiation, were negatively correlated with the response to RTX therapy ( Conclusions: The optimal model for predicting RTX response at 6 months involves the interaction of all clinical factors examined in this study, as revealed by the analysis of multiple variables.
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