Health-Related Quality of Life in Disease-Modifying Antirheumatic Drug–Treated Adults With Juvenile Idiopathic Arthritis Compared to Rheumatoid Arthritis and the General Population
Bibliographic record
Abstract
OBJECTIVE: To explore health-related quality of life (HRQOL) measured by the 36-item Short Form Health Survey (SF-36), SF-36 physical component summary (PCS), SF-36 mental component summary (MCS), and Short Form 6D (SF-6D) in adults with juvenile idiopathic arthritis (JIA) compared to patients with rheumatoid arthritis (RA) and the general population. METHODS: We used 6-month follow-up data from the Norwegian Disease-Modifying Antirheumatic Drug Register (NOR-DMARD), including adult patients with JIA and RA starting or switching disease-modifying antirheumatic drug (DMARD) treatment. Age- and gender-adjusted regression analyses were used to compare outcomes among JIA, RA, and the general Norwegian population. RESULTS: Register data were available for 232 patients with JIA and 2764 with RA at 6 months follow-up. Patients with JIA had poorer physical health compared to those with RA (adjusted difference [95% CI]: PCS -3.58 [-6.09 to -1.08]). Compared to the general population, PCS scores were lower in both JIA and RA (adjusted differences [95% CI]: JIA-general population -15.70 [-18.21 to -13.19], RA-general population -12.12 [-12.76 to -11.47]). Mental health measured by MCS was similar across the 3 groups. Average SF-6D utility levels were comparable in JIA and RA, but lower than in the general population. Similar proportions of patients with JIA and RA experienced improvements exceeding minimum clinically important difference (MCID) in SF-36 scale scores, PCS, MCS, and SF-6D after 6 months. CONCLUSION: Compared to patients with RA and the general population, patients with JIA had lower physical HRQOL 6 months after DMARD initiation. Mental health composite scores were similar among patients with JIA, those with RA, and the general population. Both disease groups showed similar levels of improvement with treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".