A137 THERAPEUTIC DRUG MONITORING WITH INFLIXIMAB TROUGH LEVELS LEAD TO INCREASED INTERVENTION
Bibliographic record
Abstract
Therapeutic drug monitoring (TDM) of infliximab (IFX) as indicated in patients with loss of response (LOR) (known as reactive strategy) is a widely accepted strategy in the management of patients with inflammatory bowel disease (IBD). Proactive drug monitoring of IFX trough levels has been proposed as a way to pre-empt LOR and hopefully preserve IFX as a therapeutic options. The impact of proactive TDM at week 14, following induction therapy is not well studied. To compare week 30 remission rates in IFX IBD patients with week 14 TDM to those without TDM, as well as determine the proportion of patients with week 14 TDM that were dose escalated. This retrospective chart review in which ulcerative colitis (UC) and Crohn’s disease (CD) patients 17 years of age or older that were on IFX for at least 30 weeks. Charts were reviewed for objective and subjective assessments of clinical remission, concomitant immunosuppressants and dose changes. Parameters of ± 1 week were allowed for trough level inclusion and ± 1 month for all other markers. Categorical and quantitative data were presented as proportions through a Chi-squared test and the t-test, respectively. All significance is assessed at p < 0.05. In total, 240 patients initiated on IFX between January 2015 - June 2017 were identified and 156 patients were included in the final analysis. Eighty-four patients were excluded due to: clinical LOR at week 14 (n=1) and patients not on IFX at week 30 (n = 83). Clinical remission with TDM was not greater than those without TDM (69.4% - 84.8%; p = 0.049). Furthermore, dose escalation in patients was more common in patients with TDM than without TDM (77.3% - 30.4%; p < 0.001). In conclusion, proactive TDM was associated with more frequent dose escalation. † Chi-square; ‡ T-Test None
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".