Short-term influence of adalimumab on work productivity outcomes in patients with rheumatoid arthritis.
Bibliographic record
Abstract
OBJECTIVE: To evaluate the shortterm effect of adalimumab on work productivity in patients with moderate to severe active rheumatoid arthritis (RA). METHODS: In a substudy of the Canadian Adalimumab Clinical Trial (CanAct), clinical, health status, and productivity outcomes were measured at baseline and 12 weeks. Patients were classified as responders and nonresponders by the 20% American College of Rheumatology (ACR20) improvement criterion and the minimum clinically important difference (MCID) of the Health Assessment Questionnaire (HAQ) score (0.22), respectively. The Health and Labour Questionnaire (HLQ) was used to measure productivity outcomes and costs. RESULTS: Included in the analysis were 389 patients completing both baseline and 12-week HLQ questionnaire. Absenteeism (a decrease of 0.5 workdays per 2 weeks) and unpaid work productivity (3.5 fewer hours unpaid help per 2 weeks) were improved significantly after 12 weeks. Improvements in productivity outcomes were associated with clinical response. Bootstrapping results suggest that responders achieved statistically significant improvement in presenteeism (ACR20) and unpaid work productivity (ACR20 and HAQ) versus nonresponders. The costs saved by responders were up to $155.04 per 2 weeks more than those by nonresponders. CONCLUSION: The costs of adalimumab were partially offset, even in the short term, by cost savings induced by clinical response among Canadian patients with moderate to severe RA. These findings complement results of other study analyses that demonstrate early and sustained benefits of adalimumab.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".