P707 Real-world Long-term efficacy of ustekinumab in the treatment of Perianal Fistulizing Crohn's disease: Results from a single-center retrospective study
Bibliographic record
Abstract
Abstract Background The efficacy of ustekinumab (UST) in treating perianal fistulizing Crohn's disease (PFCD) remains inconclusive. This study aimed to investigate the long-term efficacy and prognostic factors of UST in the treatment of PFCD patients. Methods This is a retrospective single-center analysis of PFCD patients who had at least one year of follow-up and began UST treatment between November 2020 and September 2022. The primary outcome was fistula clinical remission at any time point. Secondary outcomes included fistula clinical response, intestinal clinical remission, and response. Factors associated with long-term fistula clinica remission were screened using the univariate analysis, LASSO regression and extreme gradient boosting (XGBoost) model, and visualized using SHAP. Results A total of 131 patients were included in the study, the mean follow-up was 70.39 weeks. Among these patients, 51 (38.9%), 72 (55.0%), and 82 (62.6%) achieved clinical fistula remission at weeks 24, 52, and the last follow-up, respectively. 111 patients (84.7%) achieved intestinal clinical remission and 119 patients (90.8%) achieved intestinal clinical response. Ninety-one patients (69.5%) had prior exposure to other biologics. This study did not ascertain a significant difference in the outcome of UST for CD between biologics Naïve and biologics Exposure patients. The XGBoost model integrated eight independent variables: Montreal L3, Montreal A2, CDAI, PDAI, ESR, body mass index, simple fistula, and re-operation events. The model revealed a favourable discrimination ability with AUC was 0.798 in the internal cohorts. Conclusion This study defined the effectiveness and eight risk factors of UST in long-term clinical fistula remission in PFCD patients, which is helpful for early identification of UST beneficiaries.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".