Effectiveness and Safety of Abatacept in Moderate to Severe Rheumatoid Arthritis
Bibliographic record
Abstract
PURPOSE: Abatacept was approved in our hospital by the Pharmacy and Therapeutics Committee for treatment of moderate to severe rheumatoid arthritis (RA) in adult patients with inadequate response or intolerance to disease modifying antirheumatic drugs (DMARDs), including at least one anti-tumour necrosis factor (anti-TNF). The objectives of this study were to analyze compliance with our protocol and to evaluate effectiveness and safety of abatacept in our patients. METHODS: We performed a descriptive longitudinal study of patients with RA treated with abatacept between August 2008 and May 2010 in our day care unit. We reviewed clinical records and recorded the following data: sex, age, weight, year of diagnosis, previous antirheumatic treatments and reasons for withdrawal of anti-TNFs, indication for abatacept, dose and date of administration, Disease Activity Score (DAS28) and adverse events. Effectiveness was evaluated using the European League Against Rheumatism (EULAR) criteria. RESULTS: We recruited 16 patients. Mean follow-up time was 10.4 (SD: 6.1) months. All patients had been previously treated with DMARDs, including at least one anti-TNF, and the mean dose of abatacept was 9.4 (SD: 1.4) mg/kg. During the first 6 months of treatment, 11/16 of patients experienced a decrease in their DAS28 value, but only 5/16 achieved a satisfactory response. Dyspnea was the most frequent adverse event (7/16), followed by fatigue and asthenia (6/16) and dry skin (5/16). CONCLUSIONS: The indication for abatacept in our hospital complied with the protocol approved by the Pharmacy and Therapeutics Committee. Only 5/16 of patients achieved a satisfactory response; however, it should be noted that these patients had moderate to severe RA that was refractory to other treatments. Adverse reactions were consistent with those described in the summary of product characteristics. Further studies with larger cohorts are needed to analyze the long-term safety and effectiveness profile in clinical practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".