Biologicals for rheumatoid arthritis
Bibliographic record
Abstract
#### Case scenario A 45 year old woman had seropositive erosive rheumatoid arthritis diagnosed three years ago with involvement of the hands, wrists, shoulders, and feet. She found it difficult to dress, cook, do the housework, and control her dog on her morning walk. She improved initially on triple disease modifying antirheumatic drug (DMARD) therapy (methotrexate 25 mg intramuscularly weekly with oral folic acid 1 mg daily, hydroxychloroquine 400 mg daily, sulfasalazine 1 g twice daily) and naproxen 500 mg twice daily. Her symptoms have now flared up despite continuation of triple DMARD therapy, with multiple swollen and tender joints. Radiographs show that since last year she has developed three new erosions in her metacarpophalangeal joints. She wants to discuss the new biological drugs that you mentioned would be an option if she did not respond to the above therapy The term biological describes treatments developed and produced in live cell systems. The drugs may also be referred to as biological therapies or cytokine modulators.1 By targeting molecules involved in the inflammatory response, such as tumour necrosis factor-α, some biologicals help to reduce or suppress inflammation, potentially reducing joint damage in rheumatoid arthritis. They are used for an increasing number of indications and are approved in some countries for conditions such as rheumatoid arthritis, ankylosing spondylitis, psoriasis, psoriatic arthritis, Crohn’s disease, and ulcerative colitis. Most of these conditions are autoimmune diseases characterised by upregulation of cytokines such as interleukins; tumour necrosis factor and T and B lymphocytes contribute to the inflammation, a central pathophysiological feature of these conditions. The following are approved for treatment of rheumatoid arthritis in the United Kingdom or the United States, or both:
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.038 | 0.024 |
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".