Agreement between Rheumatologist and Patient-reported Adherence to Methotrexate in a US Rheumatoid Arthritis Registry
Bibliographic record
Abstract
OBJECTIVE: Rheumatologists have limited tools to assess medication adherence. The extent to which methotrexate (MTX) adherence is overestimated by rheumatologists is unknown. METHODS: We deployed an Internet survey to patients with rheumatoid arthritis (RA) participating in a US registry. Patient self-report was the gold standard compared to MTX recorded in the registry. RESULTS: Response rate to the survey was 44%. Of 228 patients whose rheumatologist reported current MTX at the time of the most recent registry visit, 45 (19.7%) had discontinued (n = 19, 8.3%) or missed ≥ 1 dose in the last month (n = 26, 11.4%). For the subgroup whose rheumatologist also confirmed at the next visit that they were still taking MTX (n = 149), only 2.6% reported not taking it, and 10.7% had missed at least 1 dose. CONCLUSION: MTX use was misclassified for 13%-20% of patients, mainly because of 1 or more missed doses rather than overt discontinuation. Clinicians should be aware of suboptimal adherence when assessing MTX response.
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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 | 0.032 | 0.088 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".