Clinical trial: the effects of certolizumab pegol therapy on work productivity in patients with moderate‐to‐severe Crohn’s disease in the PRECiSE 2 study
Bibliographic record
Abstract
BACKGROUND: The effect of certolizumab pegol on employment status and work productivity has not been previously assessed. AIM: To assess the impact of treatment with certolizumab pegol, the only PEGylated, Fab' TNF antagonist, on work productivity in patients with active Crohn's disease (CD) from the PRECiSE 2 study. METHODS: Patients (n = 668) with active disease [CD activity index (CDAI) score of 220-450] were treated with open-label subcutaneous certolizumab pegol 400 mg (week 0, 2, 4). Responders (n = 425) (> or = 100-point decrease in CDAI from baseline) were randomized to receive certolizumab pegol 400 mg or placebo every 4 weeks until week 24, with final evaluation at week 26. Patients completed the Work Productivity and Activity Impairment for CD questionnaire (WPAI:CD) and the Inflammatory Bowel Disease Questionnaire (IBDQ) at weeks 0, 6, 16 and 26 and at the withdrawal visit. RESULTS: Work productivity improved following induction with certolizumab pegol. Between week 6 and 26, certolizumab pegol-treated patients experienced significant improvement in work productivity compared with placebo recipients (11% and 10% overall improvement in work and activity impairment, respectively). During the maintenance phase, impairments in productivity and activities due to CD were significantly less in the certolizumab pegol group than in the placebo group. CONCLUSION: Induction and maintenance therapy with certolizumab pegol significantly improved the work productivity of patients with active CD compared with those in the placebo group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".