Health-Related Quality of Life During Natalizumab Maintenance Therapy for Crohn's Disease
Bibliographic record
Abstract
OBJECTIVES: We evaluated the effects of treatment on health-related quality of life (HRQoL) during a randomized controlled trial of natalizumab maintenance therapy (ENACT-2) using both disease-specific and generic measures. METHODS: Crohn's disease patients who received natalizumab as induction therapy in ENACT-1 (N=724) and responded (N=339) were re-randomized to ENACT-2 in which they received natalizumab 300 mg (N=168) or placebo (N=171) every 4 wk for 48 additional wk. Outcome measures were the change from baseline on the inflammatory bowel disease questionnaire (IBDQ), the short form-36 (SF-36), the EuroQol-5D (EQ-5D), and a subject global assessment. RESULTS: At entry into ENACT-1, scores indicated substantially impaired HRQoL for both the disease-specific and general measures. Natalizumab responders showed clinically meaningful improvement in HRQoL over the course of the ENACT-1 study. During maintenance therapy, IBDQ and SF-36 scale scores of patients who responded to natalizumab induction and were re-randomized to receive the drug in ENACT-2 (N=168) remained stable, while those re-randomized to placebo (N=171) worsened. At week 60, 48 wk after the initiation of maintenance therapy, the mean change from ENACT-1 baseline of all scales of the IBDQ and the SF-36 was significantly higher for those who continued to receive natalizumab (P<0.001 for all scales). The scores of patients who received maintenance natalizumab treatment were not statistically different from those of a cross-section of the U.S. population for 6 of 8 scales of the SF-36. CONCLUSIONS: The substantial improvement in HRQoL experienced by patients who responded to natalizumab induction therapy was maintained during an additional 48 wk of maintenance therapy.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".