Natalizumab Improves the Health Related Quality of Life (HRQOL) in Crohnʼs Disease Patients
Bibliographic record
Abstract
Purpose: Crohn's disease is associated with impaired HRQOL. This analysis investigated HRQOL outcomes during maintenance therapy with natalizumab (a humanized monoclonal IgG4 antibody to α4 integrin) in the ENACT-2 trial where higher rates of sustained response and remission were observed compared with placebo. Methods: Patients who responded to natalizumab induction therapy (n = 339) were randomized to natalizumab 300 mg (n = 168) or placebo infusions (n = 171) given monthly for up to 12 months. HRQOL was measured by the Inflammatory Bowel Disease Questionnaire (IBDQ) and the Short Form-36 (SF-36) at months 0, 3, 6, 9, and 12. Higher scores indicate better HRQOL. A minimally important difference (MID) is defined as 16 pts for Total IBDQ and 5 pts for SF-36 summary scores. Results: The change for all IBDQ scales from ENACT-1 baseline was significantly greater (p < 0.05) in natalizumab-treated patients at all timepoints. Changes in 7 of 10 SF-36 scales were significant by month 3 and all were significant in months 9 and 12. A significantly greater proportion of natalizumab patients achieved MID on the Total IBDQ at months 6–12 and the SF-36 PCS at months 3–12. Mean scores for physical function, social function, role-emotional, and mental health approximated US norms at month 12. Conclusions: Maintenance therapy with natalizumab resulted in significantly improved HRQOL, as evidenced by both disease specific (IBDQ) and general (SF-36) measures.Table: Change From Baseline [Mean (SD)]
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 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".