Golimumab for Adherence in Rheumatoid Arthritis (GO FAR): A Multicenter, Prospective, Observational Study of Patients Treated with Golimumab for Rheumatoid Arthritis
Bibliographic record
Abstract
Objectives Adherence to prescribed drug therapies is crucial to prevent irreversible joint damage in rheumatoid arthritis (RA). However, reported adherence rates in RA patients have shown significant variability, ranging from 49.5% and 98.5%, depending on the definition and method used. Despite this, real word evidence on adherence to golimumab, a biologic DMARD used in RA, remains limited. This study aimed to investigate whether non-adherence to RA drugs in patients treated with biologic DMARDs is associated with a higher frequency of RA flares in real-world clinical practice. Methods This was a prospective, non-interventional study conducted in 27 Canadian centers, which assessed real-world golimumab use in treating RA. The study collected data from medical records and patient/physician questionnaires. The study utilized the Rheumatoid Arthritis Flare Questionnaire (RA-FQ), a tool designed to assess disease activity and identify flares in patients with RA. Patients were categorized into low (≤80%) and high (>80%) predicted compliance groups using the Compliance Questionnaire in Rheumatology (CQR). Assessments occurred at baseline and 6-month intervals, covering joint counts, global assessments, adherence, and flares. Statistical analysis aimed to estimate flare rate differences between adherent (>80%) and non-adherent groups (≤80%), considering a 95% confidence interval. Results A total of 215 patients were treated and analyzed in the study, with 78.6% (169/215) completing the study. At 6 months, the mean RA-FQ was 22.5 (SD 13.1) and 23.8 (SD 13.2) in low and high baseline predicted compliance groups, respectively (p=0.55). At 12 months, the mean RA-FQ scores were 20.8 (SD 12.9) and 19.9 (SD 13.5) for the low and high baseline predicted compliance groups, respectively (p=0.70). Disease flares were observed in 35.7% (25/70) and 28.2% (20/71) of patients at 6 months in the low and high baseline predicted compliance groups, respectively (p=0.34). At 12 months, disease flares were observed in 30% (21/7) and 24.7% (18/71) of patients in the low and high baseline predicted compliance groups, respectively (p=0.49). No significant differences were observed in the incidence of adverse events between the low and high adherence compliance groups. Conclusion This study did not identify major differences in the RA-FQ total score or the proportion of participants reporting a flare in RA patients in the real-world clinical setting. Sensitivity analyses will be conducted to further explore RA-FQ and disease flare frequency by varying the CQR compliance classification.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".