Too Little Too Late: Effect of Poor Access to Biologics for Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
Biologic disease-modifying antirheumatic drugs (bDMARD), in particular anti-tumor necrosis factor (anti-TNF) medications, which were developed in the 1990s, have improved the radiographic and functional status of patients with rheumatoid arthritis (RA)1. It has been thought as a corollary that rates of joint replacement in patients with RA would decrease. Results in various national databases since the advent of biologic medications have been discrepant; for example, in a US cohort there was a decrease in arthroplasty in juvenile idiopathic arthritis, but not RA from 1991 to 20052, whereas in Ireland the arthroplasty rate was halved from 1995 to 20103. In Japan there was no change in the rate up to 2008, while in Sweden the hip arthroplasty rate decreased, but the knee rate did not4. Overall, however, the trend seems to be toward lower rates of arthroplasty in patients with RA. An article in this issue of The Journal , by Stamp, et al 5, provides an interesting analysis of the rates of joint replacement in New Zealand from 1999 to 2015 in both OA and RA since the advent of … Address correspondence to Dr. B.K. Johnson, Jacobi/NCB, Rheumatology, 1400 Pelham Parkway, South Building 1, Suite 306, New York, New York 10461, USA. E-mail: beverly.johnson06{at}gmail.com
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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 | 0.002 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".