Patient-reported real-world experience of risankizumab on-body device (OBD) for the treatment of Crohn’s disease in the UK (COMMODUS)
Bibliographic record
Abstract
OBJECTIVE: To evaluate real-world patient-reported experience with subcutaneous (SC) risankizumab administered by on-body device (OBD) in patients with Crohn's disease (CD). METHODS: SC injection of four pre-filled syringes (PFS) self-administered in hospital were switched to OBD self-injection. Self-Injection Assessment Questionnaires (SIAQ) were completed pre- and post-first OBD use. The primary end-point was "Overall, how satisfied are you with your current way of taking your medication (self-injection)?" from post-injection SIAQ. Baseline patient data were collected retrospectively from medical records. RESULTS: The study recruited 50 patients with moderate-to-severe CD, 48 completed the study. Most (81%) were satisfied/very satisfied with self-injection using OBD vs only 54% with PFS. Satisfaction with the OBD was highest with home use (90% vs 65%). Confidence was high with the OBD; numerically higher rates of patients were confident in giving themselves an injection in the right way (83% vs 64%), in a clean and sterile way (90% vs 74%) and safely (85% vs 72%) post-OBD than before using OBD. Self-injection using the OBD was reported as easy by 92% and convenient by 83% of participants. Most participants reported that they would continue to use the OBD (82%) and be confident to self-inject at home (81%). The OBD was well tolerated. CONCLUSION: The OBD provides a safe, easy to use and convenient way to self-administer risankizumab at home using one injection with improved satisfaction and confidence vs self-administration of four PFS in hospital.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".