A158 COMPARING CORTIMENT® AND PREDNISONE IN ULCERTATIVE COLITIS: A POPULATION-BASED STUDY OF OUTCOMES
Bibliographic record
Abstract
Abstract Background In August 2016 Cortiment® was approved for use in ulcerative colitis (UC) patients in Canada, but not approved for reimbursement; the Canadian Agency for Drugs and Technology in Health cited no comparable benefit for its use over other approved UC medications. Real-world data comparing Cortiment® to other UC medications is limited, especially during the COVID-19 pandemic where the use of steroids is counter-indicated for COVID-19-related outcomes. Aims To examine the comparative risk of hospitalization, surgery, and infection after initiation of Cortiment® or oral corticosteroids among UC patients using real-world data Methods Using population-based data from Alberta Canada, two cohorts were compared: 1. Patients dispensed Cortiment® and an ICD diagnostic code for UC [9: 556.X; 10: K51.X] (August 1, 2016 to October 31, 2019); and, 2. Validated (algorithm) UC patients dispensed a >30 day supply or >500mg in 24 hours of prednisone/prednisolone (April 1, 2016 to October 31, 2019). All hospitalizations, IBD-surgery, or infections (i.e., pneumonia, c.diff, sepsis, tuberculosis) that occurred 6 or 12 months from initial medication dispensing were identified. Cox-proportional hazard models, with Hazard Ratios (HR), assessed comparative outcomes. Kaplan-Meier survival curves were created, and Poisson regression (or negative binomial) used to assess the Average Monthly Percentage Change (AMPC) with associated 95% confidence intervals (CI). Results We identified 917 Cortiment® and 2,404 Prednisone patients. Over the study period, prednisone dispensing significantly decreased (AMPC:-2.53% [CI:-2.85,-2.21]) while Cortiment® remained stable. Dispensing of Cortiment® significantly decreased the hazard of hospitalization (all types, except surgery) at 12 months as compared to prednisone, and significantly decreased the hazard of an infection at both 6 and 12 months (Table 1, Fig 1). Conclusions The use of Cortiment® in a real-world setting is associated with fewer deleterious outcomes, and its use during a pandemic should be preferred, especially when it’s counterpart can exacerbate negative COVID-19-related outcomes. Table 1 Kaplan-Meier Survival Curves of 1-year Outcomes: A) All Hospitalizations; B) IBD-Related Hospitalizations; C) IBD-Specific Hospitalizations; and, D) Any Infection. Dashed Line Cortiment Cohort Solid Line Prednisone/Prednisolone Cohort Funding Agencies Ferring Pharmaceuticals
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".