Changes in Treatment Patterns in Patients with Psoriatic Arthritis Initiating Biologic and Nonbiologic Therapy in a Clinical Registry
Bibliographic record
Abstract
OBJECTIVE: Treatment options for psoriatic arthritis (PsA) have increased and improved in the past decade; treatment patterns in PsA remain poorly understood. Understanding current practices would aid in treatment management of patients with PsA. METHODS: This observational study was based on data from the Corrona registry of adult patients with PsA in North America collected between January 1, 2004, and December 31, 2012. Patients were divided among 3 therapy cohorts: tumor necrosis factor inhibitor (TNFi) monotherapy, methotrexate (MTX) monotherapy, and TNFi and MTX combination therapy. Patients were further divided among 3 study periods to understand changes over time: 2004-2006, 2007-2009, and 2010-2012. Data were collected on persistence, discontinuation, restarting, switching, adding/dropping therapy, and dose stretching. RESULTS: This study included 520 patients: 190 TNFi monotherapy, 217 MTX monotherapy, and 113 combination therapy; 110 from 2004 to 2006, 192 from 2007 to 2009, and 218 from 2010 to 2012. Over time, the proportion of patients initiating TNFi monotherapy decreased, while the proportion initiating combination therapy remained constant. The percentage of patients who were persistent decreased over time across all therapy cohorts, but remained higher in TNFi monotherapy than in other cohorts. Duration of persistence decreased over time. Patients initiating MTX monotherapy were more likely than their TNFi counterparts to add therapy. CONCLUSION: Treatment patterns in patients with PsA have changed from 2004 to 2012. Physicians are not more likely to initiate TNFi monotherapy, although clinical evidence supporting its effectiveness has increased over this study period, and patients remain more persistent with it.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".