S83 Real-World Treatment Persistence Among Advanced Therapy-Experienced Patients With Ulcerative Colitis Initiated on Ustekinumab or Adalimumab
Bibliographic record
Abstract
Background: Among patients with ulcerative colitis (UC), prior exposure to biologics or advanced therapies is associated with reduced response to future therapies, which may lead to treatment discontinuation. Therapy persistence is a proxy of real-world treatment performance and is important to achieve optimal clinical outcomes. This study compared persistence among advanced therapy-experienced patients with UC initiated on ustekinumab, an anti-interleukin 12/23 antibody, or adalimumab, an anti-tumor necrosis factor biologic. Methods: Adults with UC initiated on ustekinumab or adalimumab (index date) between 10/21/2019 and 03/02/2022 were selected from the IQVIA PharMetrics® Plus database. Patients were advanced therapy-experienced (i.e., had ≥1 claim for a non-index UC-indicated biologic or advanced therapy agent) in the 12-month baseline period before the index date. Patients with other auto-immune diseases during the baseline period were excluded. Cohorts were balanced on baseline characteristics using inverse probability of treatment weights. Persistence was defined as the absence of gaps between days of therapy supply of >120 days for ustekinumab (i.e., twice the 8-week on-label maintenance dosing interval) or >60 days for adalimumab (i.e., twice the mode of days of supply corresponding to 2 doses per the 2-week on-label maintenance dosing interval). Composite endpoints of being persistent while on monotherapy (no immunomodulators, non-index biologics, or advanced therapies) and persistent while corticosteroid-free (< 14 consecutive days of corticosteroid supply after day 90 post-index) were also assessed. All endpoints were evaluated from maintenance phase start until the earlier of 12 months follow-up, end of insurance eligibility or end of data using weighted Kaplan-Meier analyses and weighted Cox proportional hazards models adjusted for the use of ≥2 biologics and class of biologics used during the baseline period. Results: There were 693 patients in the weighted ustekinumab cohort (mean age: 42.6; 45.8% female) and 254 patients in the weighted adalimumab cohort (mean age: 41.6; 46.1% female). At 12 months after the maintenance phase start, 78.1% of the ustekinumab cohort and 59.2% of the adalimumab cohort were persistent on the index biologic; persistence was 2.44 times higher in the ustekinumab cohort relative to the adalimumab cohort (hazard ratio [HR]: 2.44; 95% confidence interval [CI]: 1.82-3.26; p-value: < 0.001). Moreover, 66.7% of the ustekinumab cohort and 40.5% of the adalimumab cohort persisted on the index biologic while on monotherapy; persistence while on monotherapy was 2.53 times higher in the ustekinumab cohort relative to the adalimumab cohort (HR: 2.53; 95% CI: 2.00-3.21; p-value: < 0.001). Finally, 48.0% of the ustekinumab cohort and 42.8% of the adalimumab cohort were persistent while corticosteroid-free; persistence while corticosteroid-free was 1.24 times higher in the ustekinumab cohort relative to the adalimumab cohort (HR: 1.24; 95% CI: 1.01-1.54; p-value 0.0447). Conclusions: Advanced therapy-experienced patients with UC treated with ustekinumab were more persistent, including persistent while on monotherapy and while corticosteroid-free, than patients treated with adalimumab. These findings may aid healthcare providers in choosing a biologic for advanced therapy-experienced patients with UC.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".