Evaluation of the meaningfulness of health‐related quality of life improvements as assessed by the SF‐36 and the EQ‐5D VAS in patients with active Crohn’s disease
Bibliographic record
Abstract
BACKGROUND: Crohn's disease (CD) is a chronic inflammatory illness characterized by episodic abdominal pain, diarrhoea, fever, bleeding and obstruction. While the Crohn's Disease Activity Index (CDAI) remains the most commonly accepted measure for assessing the disease status in clinical trials, patient-reported outcome (PRO) instruments are being utilized more frequently to provide information about health-related quality of life (HRQOL). To facilitate interpretation of results, it is common to identify a meaningful unit of PRO score change, such as a minimal clinically important difference (MCID). AIM: To define and apply MCID estimates for the SF-36 and EuroQol-5D visual analogue scale (EQ-5D VAS) for use in CD treatment evaluation. METHODS: Data from two phase III randomized controlled trials of certolizumab pegol were utilized. MCID estimates were computed from one trial using anchor-based and distribution-based methods. These estimates were applied to data from the other trial. RESULTS: SF-36 PCS and MCS MCID estimates ranged from 1.6 to 7.0 and 2.3 to 8.7 respectively, depending on approach. EQ-5D VAS MCID estimates ranged from 4.2 to 14.8. CONCLUSIONS: For the first time, the MCID values provided interpretation guidelines for PRO results in CD. This research demonstrates that patients treated with certolizumab pegol benefit from meaningful and sustained HRQOL improvements.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".