Patterns and predictors of long-term retention of inflammatory bowel or rheumatoid disease patients on innovator infliximab: an analysis of a Canadian prescriptions claims database
Bibliographic record
Abstract
BACKGROUND: Long-term effectiveness is an important factor when considering treatment decisions. OBJECTIVE: To determine the long-term retention patterns of Canadian inflammatory bowel disease (IBD) and rheumatologic disease (RD) patients, including rheumatoid arthritis, psoriatic arthritis, and ankylosing spondylitis, treated with innovator infliximab (IFX) and to assess the impact of year-over-year cumulative IFX exposure on retention in both patient populations. PATIENTS AND METHODS: This analysis used a Canadian longitudinal prescription claims database to measure retention on IFX over a period of 5 years. Twelve-month unadjusted odds ratios of retention by time on IFX were calculated for the overall cohort, and within-group comparisons evaluated differences according to age, sex, region, insurance coverage, use of concomitant immunosuppressant therapy, indication (RD cohort only), and previous biologic experience. Between-group analyses compared unadjusted 5-year retention among the same variables. Variables that were independently associated with longer retention on IFX were identified using multivariable regression. RESULTS: Seven thousand eight hundred and six IBD patients and 2,935 RD patients on stable treatment with IFX were included in the analysis. Sixty-nine percent of IBD patients and 66% of RD patients were retained on IFX after 1 year and 33% and 29%, respectively, were retained after 5 years. Moreover, the probability of being retained on IFX significantly increased with cumulative time on IFX. Independent predictors of 5-year retention included sex, region, and type of insurance coverage among IBD patients and region, type of insurance, prior biologic therapy, and specific indication among RD patients. Patients with IBD were 17% more likely to be retained on IFX over 5 years compared to patients with RD. CONCLUSION: Real-world Canadian IBD and RD patients on IFX have good overall long-term treatment retention. Previous duration of IFX treatment predicts better future retention, and this knowledge could help inform treatment decisions when patients have been stable on IFX treatment for varying periods of time.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".