P22 Response to tofacitinib in British Asians with ulcerative colitis; a real world tertiary centre experience
Bibliographic record
Abstract
<h3>Introduction</h3> We have previously shown UK South Asians (SA) with IBD are prescribed TNF antagonists earlier in disease course in comparison with white British (WB) patients, but are more likely to stop due to treatment failure (Gadhok 2020). However, it is currently unknown whether there is a similar variation in response to Tofacitinib, a non-selective JAK inhibitor. We aim to determine whether persistence to tofacitinib varies with ethnicity and evaluate real world efficacy in an inner-city tertiary referral centre. <h3>Methods</h3> Patients prescribed Tofacitinib since 2019 were identified from electronic prescribing records. The following data was collected: ethnicity (as per UK standard coding), disease history including Montreal classification of disease extent, prior advanced therapies, persistence on therapy, indication for cessation, side effects, and endoscopic and biochemical markers of disease activity. <h3>Results</h3> 30 adults with UC were prescribed tofacitinib, with a median duration of follow up of 833 days (n=31). 11 patients were female, and ethnicity was as follows: SA:11:Black:1:WB:12:Other/unstated:7. The median failure free survival was 447 days, with no significant variation associated with number of prior advanced therapies (1 prior biologic, 303.5 days (n=12) vs >1 prior biologic, 715 days (n=19) p=0.28). Comparison between characteristics and response to treatment of South Asian and White British patients, presented in table 1: There was no difference between median failure free survival of SA and WB patients (304 days vs 447 days, p=0.28). There was a trend towards lower primary non-response in SA patients, with fewer stopping treatment by 12 weeks, although this was not statistically significant (9.09% vs 33.33% p=0.17). No difference in disease duration at first prescription of tofacitinib between SA and WB patients was found (78.75 months vs 86.80 months p=0.78). 2 patients stopped treatment due to side effects, with 1 patient (SA) stopping due to MACE. <h3>Conclusion</h3> In contrast to our previous work on TNF antagonists, British SA patients prescribed tofacitinib for UC had failure free survival comparable with WB patients, with a trend towards fewer primary non responders. Although limited by sample size, these findings are reassuring given that SA patients are underrepresented in trials of novel therapies in IBD and warrants a larger study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".