S819 Non-Biologic Medication Use Pre- and Post-Ustekinumab Initiation Among Patients With Ulcerative Colitis
Bibliographic record
Abstract
Introduction: Among patients with ulcerative colitis (UC), treatment with immunomodulators, 5-ASA (5-aminosalicylic acid), and corticosteroids while receiving biologic agents is common. However, real-world information on non-biologic medication use among UC patients initiated on ustekinumab is limited. This study compared non-biologic medication use pre- and post-ustekinumab initiation among UC patients. Methods: Adults with UC initiated on ustekinumab (index date) between 10/18/2019 (FDA approval of ustekinumab for UC) and 10/31/2020 were selected from the de-identified health insurance claims Symphony Health Solutions’ Patient Transactional Datasets. Patients were excluded if they had a claim for Crohn’s disease anytime or for other autoimmune diseases pre-index. Patients were required to have: ≥1 claim for UC in the 12 months pre-index period (baseline), ≥2 ustekinumab claims within 90 days of the index date, and ≥6 months of follow-up. Non-biologic agent use in the 6 months period before and after the initiation of ustekinumab was compared with a logistic model estimated by generalized estimating equation. Results were reported as odds ratio with 95% confidence interval and p-values. Results: A total of 760 patients with UC were initiated on ustekinumab and selected for the study (age 44.6 years old; 48.9% female; baseline biologic use 52.1% [potentially underestimated given the database open nature]; Quan-Charlson comorbidity index 0.62). The likelihood of immunomodulator and 5-ASA use decreased by 22% and 46%, after ustekinumab initiation (all P< 0.05). Similarly, patients were 52% less likely to use any corticosteroids and 34% less likely to use corticosteroids for ≥60 days (all P< 0.05). Further, there was no significant changes observed for the use of opioids (18.9% vs. 17.4%) or the use of anti-diarrheals (5.9% vs. 6.1%), and patients were 29% less likely to use GI antispasmodics after ustekinumab initiation (P< 0.05; Table). In a descriptive analysis, corticosteroids use numerically decreased at each month post-ustekinumab from 25.4% during the first 30 days following the index date compared to 17.4% within 150-180 days post-ustekinumab (Figure). Conclusion: In this real-world study of patients with UC, initiating ustekinumab was associated with a significant decrease in the use of immunomodulators, 5-ASA, and corticosteroids. Longer-term data are necessary to better understand non-biologic medication use after biologic initiation and inform treatment choice for patients with UC.Figure 1.: Corticosteroid use during the 6 months post-ustekinumab initiation (N=760). Table 1. - Non-biologic medication use in the 6-month period before vs after the initiation of ustekinumab Pre-ustekinumab Post-ustekinumab Odds ratio1 (95% CI), p-value N = 760 Use of immunomodulators 120 (15.8) 97 (12.8) 0.78 (0.64, 0.95), 0.014* Use of 5-ASA 312 (41.1) 208 (27.4) 0.54 (0.47, 0.62), < 0.001* Use of corticosteroids 481 (63.3) 346 (45.5) 0.48 (0.41, 0.57), < 0.001* Cumulative use2 ≥60 days 243 (32.0) 180 (23.7) 0.66 (0.55, 0.79), < 0.001* Cumulative use2 ≥90 days 151 (19.9) 114 (15.0) 0.71 (0.58, 0.87), 0.001* ≥1 episode3 ≥ 60 days 201 (26.4) 156 (20.5) 0.72 (0.59, 0.87), < 0.001* ≥1 episode3 ≥ 90 days 118 (15.5) 89 (11.7) 0.72 (0.56, 0.93), 0.013* Use of opioids 144 (18.9) 132 (17.4) 0.90 (0.74, 1.10), 0.296 Use of antidiarrheals 45 (5.9) 46 (6.1) 1.02 (0.76, 1.38), 0.879 Use of GI antispasmodics 86 (11.3) 63 (8.3) 0.71 (0.54, 0.93), 0.013* Abbreviations: CI: Confidence interval; GI: Gastrointestinal; 5-ASA: 5-aminosalicylic acid Notes: (1) Odds ratio obtained from a logistic model estimated with generalized estimating equation; (2) Non-overlapping days of supply included; (3) A therapy exposure gap of 14 days of supply was used to define continuous use
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".