Treatment of rheumatoid arthritis in the USA: premature use of tumor necrosis factor inhibition and underutilization of concomitant methotrexate
Bibliographic record
Abstract
James R O’Dell,1 Stanley B Cohen,2 J Carter Thorne,3 Joel Kremer4 1Department of Rheumatology, Division of Rheumatology and Immunology, University of Nebraska Medical Center and the Omaha VA, Omaha, NE, USA; 2Department of Internal Medicine, Metroplex Clinical Research Center, University of Texas Southwestern Medical School, Dallas, TX, USA; 3Division of Rheumatology, University of Toronto, Southlake Regional Health Centre, Toronto, ON, Canada; 4The Center for Rheumatology, Albany Medical College, Albany, NY, USA Purpose: The objective of this study was to assess the treatment for patients with rheumatoid arthritis (RA) in the USA. Patients and methods: This study entailed analysis of claims data for patients with RA who initiated treatment with oral methotrexate (MTX) or a biologic in 2009 (n=48,910) or 2012 (n=107,636) and had follow-up for 4 years (2009 cohort) or 2 years (2012 cohort). Results: A biologic was initiated before MTX for 27% of the 2009 cohort and 36% of the 2012 cohort. Concomitant use of MTX and a biologic declined from 74.1% (2009 cohort) to 45.4% (2012 cohort). Conclusion: MTX is underused in the treatment of RA in the USA. Keywords: biologic, claims, methotrexate, tumor necrosis factor
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".