Change Over Time in the Pattern of Clinical Response to First-line Biologic Drugs in Patients with Rheumatoid Arthritis: Observational Data in a Real-life Setting
Bibliographic record
Abstract
To the Editor: In the last 2 decades, the management of rheumatoid arthritis (RA) was dramatically changed by the introduction of the treat-to-target (T2T) approach1,2,3 and biologic disease-modifying antirheumatic drugs (bDMARD). The effectiveness of those targeted therapies to achieve remission and low disease activity (LDA) has been demonstrated in randomized controlled trials4, progressively increasing the use of bDMARD as a real-life application of the T2T strategy. Nevertheless, in the main international registries, the baseline median disease duration of bDMARD starters has been reported to be significantly high, possibly affecting the overall clinical response to this drug class5,6. To evaluate the real effect of T2T recommendations on RA management with bDMARD, we retrospectively analyzed the baseline characteristics and the 1-year clinical response in a cohort of patients with RA who received a first-line bDMARD in our Rheumatology Unit from September 1999 … Address correspondence to Dr. E.G. Favalli, Gaetano Pini Institute, Department of Rheumatology, Via Gaetano Pini 9, Milan 20122, Italy. E-mail: ennio.favalli{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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".