PTH-090 Laboratory experience of anti-tnf drug monitoring in routine practice – perspective from the first uk centre
Bibliographic record
Abstract
Introduction Therapeutic drug monitoring (TDM) of Infliximab (IFX) and Adalimumab (ADAL) has been in use in our centre since 2012. Here we present the TDM experience of our laboratory service at Viapath, St Thomas’ Hospital. Method Anti-TNF requests received between June 2012 and January 2015 were reviewed. All assays were performed using LISA-TRACKER Duo kits automated on eRobot (Theradiag, France). These assays measure free drug and anti-drug antibody (ADAb) and therefore inhibition studies were performed on samples with detectable drug levels (>1 ug/ml) and positive ADAb. Results were classified according to drug levels (DL) and ADAb status. Results The laboratory analysed 2424 (17% internal) samples for IFX (Median DL 3.8 ug/mL, IQR 1.2–6.3) and 1335 (21% internal) samples for ADAL (Median DL 5.2 ug/mL, IQR 3.4–7.3) from IBD patients. Prevalence of detectable antibodies was higher in IFX (10%) than ADAL (4.1%) samples. External requests originated from >90 different hospitals. Number of requests received for both assays doubled from 2013 to 2014 with batch frequency consequently decreasing from fortnightly to weekly. 40 patients had IFX >1 ug/ml and were antibody positive. 16 of these patients were confirmed to have switched to ADAL due to loss of response to IFX therapy. Detectable DL observed in these cases was due to cross reactivity of ADAL with the IFX assay. 11 patients had false positive drug levels and 4 patients had borderline antibodies due to non specific binding. 1 patient had sample collected around infusion. 4 patients had subtherapeutic ADAL (1.1–1.4 ug/ml) and were antibody positive. 1 of these patients was confirmed to have switched to IFX due to loss of response to ADAL therapy. Detectable DL observed in this case was due to cross reactivity of IFX with the ADAL assay. 3 patients had false positive results for ADAL. From the data, it was evident that some centres monitored patients with serial measurements and made subsequent changes to therapy. 63 patients (IFX) and 52 patients (ADAL) had an average of 7 and 3 repeat measurements taken respectively. Conclusion Anti-TNF testing has been embedded in several IBD centres as a way of optimising therapy however variation in TDM practices was observed highlighting the need for national guidance. Significant increase in test requesting suggests assay based treatment strategies combined with clinical assessment is now an accepted practice in IBD. Disclosure of interest Z. Arkir: None Declared, N. Unsworth: None Declared, G. Richards: None Declared, Z. Odho: None Declared, P. Irving Speaker Bureau of: MSD, Abbvie and Takeda.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".