P397 Advanced therapy persistence and need for dose optimisation in a cohort of Inflammatory Bowel Disease patients in Argentina: a real-world evidence multicenter study (REMAR study)
Bibliographic record
Abstract
Abstract Background Treatment persistence, as well as time to dose optimisation, can be a proxy for a drug’s real-world therapeutic benefit. We sought to describe treatment persistence of biologics or small molecules in inflammatory bowel disease (IBD) patients and need for optimisation in patients with IBD in Argentina and their potential predictors. Methods A retrospective cohort study involving 13 hospitals from Argentina was undertaken. Adult patients with a diagnosis of Crohn’s disease (CD) or ulcerative colitis (UC) who received therapy with a biologic or a small molecule were included. Initiation date was registered for every therapy each patient received; in addition, treatment finalization as well as need for optimisation were registered. Treatment persistence was defined as the time between treatment initiation and treatment finalization, or as time between treatment initiation and last follow-up if patient continued with the treatment. Time to optimisation was defined as the time between treatment initiation and treatment dose optimisation. In patients that received more than one type of advanced therapy, treatment persistence and need for optimisation was analyzed separately for each treatment received. Kaplan-Meier analysis as well as Cox regression model were used to determine predictors of treatment persistence and need for optimisation. Results A total of 403 patients were included; 55.28% had a diagnosis of UC, mean age was 44.57±16 and 47.71% were male. Median time of follow-up was 80 months [IQR 41-152]. Adalimumab was the most frequently used biologic as a first-line treatment for CD and UC (59.78% and 51.39%, respectively), whereas ustekinumab and vedolizumab were the most frequently used agents for CD and UC patients previously exposed to biologics, respectively (41.42% and 36.73%). Median treatment persistence duration was 68 months [IQR 22-146]. History of steroid-dependency [HR 2.87 (1.02-8.12)], CD [0.42 (0.22-0.78]), prior biologic exposure [HR 2.25 (1-5.06)], dose optimisation [HR 2.93 (1.36-6.33)] and need for systemic steroids 6 months from treatment initiation [HR 4.98 (1.57-15.75)] were significant predictors of shorter treatment persistence. Median time to optimisation was 34 months [IQR 9-132]. CD [0.81 (0.55-0.94)], moderate-to-severe endoscopic activity [HR 1.91 (1-3.95)], prior biologic exposure [HR 2.29 (1.27-4.14)] and biologic initiation after 2017 [2.06 (1.09-3.55)] were significant predictors of need for dose optimisation. Conclusion A considerable proportion of IBD patients required dose optimisation or treatment finalization. Lower treatment persistence and time for dose optimisation were observed in UC patients and other factors were identified.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".