A119 THERAPUTIC DRUG MONITORING IN PATIENTS WITH ULCERATIVE COLITIS TREATED WITH GOLIMUMAB
Bibliographic record
Abstract
Anti-tumor necrosis factor (TNF) is a mainstay of treatment in patients with inflammatory bowel disease (IBD) who are refractory to traditional therapies. The most recent anti-TNF that obtained its marketing license for treatment of ulcerative colitis (UC) is Golimumab (GLM). Other anti-TNF drugs in this category include Infliximab and Adalimumab. These 2 drugs have validated algorithms with respect to Therapeutic Drug Monitoring (TDM) and dose optimization strategies however such algorithms are not yet available for GLM. The PURSUIT trial strongly suggested that high GLM trough levels correlated with patients’ improvement and resulted in higher rates of clinical response and remission. Although, there is no consensus on what constitutes an adequate trough level, a recent review article in Therapeutic Advances in Gastroenterology, has suggested a trough level of 2.5 μg/ml to optimize clinical response. To determine the proportion of patients with ulcerative colitis treated with GLM in the IBD clinic at Western University who have obtained adequate trough levels of GLM. This is a retrospective cross-sectional analysis of GLM trough levels and antibodies to GLM (ATG) in patients with ulcerative colitis on GLM maintenance therapy treated between December 2015 and October 2017. 40 patients were initiated on GLM in the study period and 11 patients remained on the drug at the end of the study period. TDM was available on 11 patients. The most common initial maintenance regimen was 100 mg every 4 weeks with one patient receiving a lower dose and two patients receiving the drug more frequently. The mean GLM trough level was 2.58 μg/ml with a median of 1.43 μg/ml. Only 3/11 (27%) of patients had a trough level above the level suggested for optimal clinical response. All patients did have measurable drug levels although one patient had a level of only 0.1 μg/ml on 50 mg every 4 weeks that increased to only 0.15 μg/ml when the dose was doubled. 3 patients with trough levels below 2.5 μg/ml had their dose doubled, resulting in a mean increase of 1.27 μg/ml or 142% but only 1/3 obtained a level above 2.5 μg/ml. None of the patients had measurable levels of ATG. Although ATG appear to be rare with GLM administration, the traditional dosing regiment appears to produce trough levels that may not be adequate for an optimal clinical response. Use of an initial maintenance dose higher than 100 mg every 4 weeks may prove to be a more effective strategy. 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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".