Should We Redefine Treatment Targets in Rheumatoid Arthritis? Low Disease Activity Is Sufficiently Strict for Patients Who Are Anticitrullinated Protein Antibody-negative
Bibliographic record
Abstract
OBJECTIVE: Clinical remission currently is the treatment target for all patients with rheumatoid arthritis (RA). At the same level of inflammation, the prognosis regarding joint damage is believed to be different for anticitrullinated protein antibody (ACPA)-negative and ACPA-positive patients. Our objective was to show the difference in prognosis at similar disease activity levels, and to illustrate how this could be translated to differentiation of treatment targets. METHODS: Data were used from the Nijmegen Early RA Cohort. The relation between the time-averaged disease activity level (by Disease Activity Score; DAS) and joint damage progression over 3 years was analyzed, separately for ACPA-negative and ACPA-positive patients. Joint damage was assessed as change in Ratingen score, and dichotomized as occurrence of erosions in joints that were unaffected at baseline. Linear and logistic multivariable regression models were used. RESULTS: The regression coefficient of DAS on change in Ratingen score was 3.9 (p < 0.001) for ACPA-negative and 4.7 (p < 0.001) for ACPA-positive patients, showing less joint damage progression at the same disease activity level in ACPA-negative patients. This difference became greater with increasing disease activity. The probability for erosions in joints unaffected at baseline was 0.35 in ACPA-negative patients when time-averaged DAS was < 2.4 versus 0.80 in ACPA-positive patients. CONCLUSION: At the same level of inflammation, ACPA-negative patients have less joint damage and lower probability for damage in newly affected joints than ACPA-positive patients. Low disease activity might be a sufficiently strict treatment target for ACPA-negative patients to prevent progression of joint damage.
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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 | 0.009 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| 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".