P711 A pilot study using point of care testing for infliximab and faecal calprotectin in IBD patients with a secondary loss of response
Bibliographic record
Abstract
Therapeutic drug monitoring (TDM) and faecal calprotectin (FCP) testing in IBD patients with secondary loss of response (LOR) to infliximab (IFX), help guide clinicians to the most appropriate intervention to recapture response. However, TDM and FCP result reporting can be delayed, hampering immediate treatment optimisation. We investigated the clinical utility of TDM, FCP and resultant early dose optimisation, using rapid point-of-care (POC) testing. Prospective inclusion of consecutive adults IBD patients accessed for secondary LOR to IFX. Results of testing for IFX through levels (TL) and FCP, measured by a POC device (BÜHLMANN device Quantum Blue®), were compared with standard IFX TL, anti-IFX antibodies (ELISA, Progenika) and FCP (ELISA, ALPCO), measured through a central laboratory. Based on POC results, an algorithmic approach to TDM/FCP results was implemented Algorithmic approach to POC testing Primary endpoint: proportion of patients in clinical remission at week 12, in those patients that underwent early treatment optimisation. Seventeen patients were included (65% female, mean age: 37.1 ± 17.4 years), CD n = 9 with mean HBI 6.33 ± 1.5; UC n = 8 with mean partial Mayo 4.5 ± 2.1. Mean duration of prior biological treatment was 28.1 months ± 36.1. Mean IFX TL with POC testing was 14.5 ± 6.6 and with standard testing was 16.8 ± 7.9 (R=0.8, p = 0.001). Mean FCP level with POC testing was 472 ± 332.7 and with standard testing was 489.9 ± 630.5 (R=0.53, p = 0.04). 7/17 (41%) patients had low TL and high FC, 4/17 (24%)had adequate TL and high FCP and 6/17 (35%) had adequate TL and low FCP. In the 7 patients with low IFX trough and elevated FCP, treatment was modified (dose escalation/change therapy) in 5 (71%) and 4 out of 6 (67%) with available follow-up data from this group were in clinical remission at week 4 and 12. Using an algorithmic approach with POC TDM and FCP suggests that immediate dose optimisation would have resulted in an inappropriate management in 10/17 (59%) patients. Clinical remission data at week 12 were available in 13 patients and 10 (77%) were in clinical remission. Clinical outcomes Using POC testing for IFX patients with a secondary LOR is clinically useful, correlates well with standardised testing, allows for immediate appropriate management of patients with low IFX trough and high FCP and results in a rapid clinical remission as early as 4 weeks.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".