P1263 Real-World Evidence Needs for Treatment Sequence Disease Modelling in Refractory Inflammatory Bowel Disease
Bibliographic record
Abstract
Abstract Background Sequential use of biologics in Inflammatory Bowel Disease (IBD) is often required in clinical practice to restore or maintain long-term remission. Health technology agencies are requiring treatment sequencing models which are more reflective of clinical practice. The accurate modelling of treatment sequences would help better understand expected patient benefit and make more informed decisions. The aim of our targeted literature review (TLR) was to identify real-world evidence (RWE) on the effectiveness of second-line or later treatments for Crohn’s disease (CD) or ulcerative colitis (UC) refractory to initial therapy and assess its suitability for treatment sequence modelling. Methods We identified observational studies from Europe, the United States (US), and Canada via EMBASE, MEDLINE, and MEDLINE-In-Process (searched from 01/01/2018 to 11/12/2023). Study selection was conducted by a senior researcher and quality was checked by a second one. Evidence was analysed to assess the availability of clinical remission and response, and steroid-free remission data by line of therapy and across various time points. We then conducted a gap analysis against the evidence needs of a treatment sequence model Results After screening a total of 145 publications were included for data extraction in the review: 61 in ulcerative colitis (UC), 50 in Crohn’s disease (CD), and 34 in combined IBD. Studies were predominantly conducted in Europe (n=95), followed by the US (n=26), and Canada (n=3). A total of 12 studies reported clinical remission for first line, four for second line, and two each for third and fourth lines of treatments of refractory patients with UC. Additionally, eight studies reported data for first line, seven for second line, eight for third line, three for fourth line, and two for fifth line treatments of refractory patients with CD. The remaining studies combined results for multiple lines of treatment. Clinical remission during maintenance for patients with CD ranged between 47% - 79%, 38% - 87%, 28% - 68%, and 16% - 63%, for first, second, third, and fourth line, respectively and 40%-67%, 35% - 77%, 41% - 47%, and 16% - 21% for patients with UC. Studies lacked granularity in the assessment of clinical remission and response specific to individual treatments, stratified by specific treatment failure history Conclusion Studies identified in our evidence review did not report sufficiently granular data on clinical response or remission to reliably inform a treatment sequence model. Addressing these data gaps is essential for enabling more reliable decision-making in clinical practice, supporting better resource allocation, and ultimately improving long-term outcomes for refractory patients with IBD.
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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 | 0.101 | 0.396 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.011 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 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".