The Effect of Biologic and Targeted Synthetic Drugs on Work- and Productivity-related Outcomes for Patients with Psoriatic Arthritis: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To systematically review the effects of biologic therapies for psoriatic arthritis [secukinumab, ustekinumab, adalimumab, etanercept, certolizumab pegol (CZP), apremilast, golimumab (GOL), or infliximab (IFX)] on work productivity. METHODS: A systematic review of Medline, EMBASE, CENTRAL, and ClinicalTrials.gov was conducted to identify randomized controlled trials reporting on work productivity outcomes at the end of the placebo-controlled double-blind period. RESULTS: There were 7959 records identified. Full text of 377 records was further assessed for eligibility, of which 5 trials were included. All included trials were assessed with the Cochrane Risk of Bias Tool, and 4 out of 5 were judged to be of low risk of bias in most domains. Improvements in self-assessed work productivity were observed in 5 trials (IFX, GOL, CZP, ustekinumab, and apremilast), ranging from a mean difference of -0.9 to -1.8 on a 1-10 scale of self-assessed work productivity (negative change represents improvement), although statistical significance of the results was not reported for CZP and apremilast. Treatment with CZP resulted in a statistically significant reduction in absenteeism (200 mg) and presenteeism (200 and 400 mg). IFX and GOL reported a nonsignificant reduction of absenteeism. The Work Productivity Survey, the Work Limitations Questionnaire, and visual analog scales were used to measure work productivity. CONCLUSION: Treatment with IFX, GOL, CZP, ustekinumab, and apremilast resulted in improvements in self-reported work productivity. A pooled analysis was not possible because of the clinical heterogeneity of the trials and variability in outcome reporting.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".