A142 INFLAMMATORY BOWEL DISEASE PATIENTS REQUIRE AN INCREASED ADALIMUMAB DRUG LEVEL TO SIMULTANEOUSLY ACHIEVE CLINICAL AND BIOLOGICAL REMISSION
Bibliographic record
Abstract
Physicians use therapeutic drug monitoring of adalimumab (ADA) as an optimization tool to guide patient therapy with inflammatory bowel disease (IBD). IBD consists primarily of Crohn’s disease (CD) and ulcerative colitis (UC). Presently, the literature on ADA therapeutic boundaries recommend a broad 5–20μg/mL range. Due to limited treatment options for moderate-to-severe IBD and the high loss of response risk with biologics, optimization to sustain clinical and biological remission is imperative. Clinical indices, including the Harvey-Bradshaw index (HBI) for CD and partial Mayo (PM) for UC, are used to assess clinical disease activity. Fecal calprotectin (FCP) is a biomarker that is used to assess intestinal inflammation. An FCP<100μg/g is correlated with mucosal remission. Currently, there is no model describing a concise therapeutic range for both clinical and biological remission in ADA patients. To assess the optimal ADA drug level (DL) that can simultaneously predict both clinical and biological remission. This is a retrospective, cross-sectional chart review of CD and UC patients, ≥18 years old, at the University of Alberta IBD Clinic, with at least one DL measured between May 2015 and May 2017. Receiver-operating characteristic (ROC) curves were used to evaluate when FCP levels were able to predict clinical disease activity, using HBI and PM scores, and the ability of DLs to predict an FCP<100μg/g. Area under the curve (AUC) is presented with a 95% CI and p-value. Youden’s method was used to determine the best cut-off. Significance is evaluated at α=0.05. There were 506 DLs collected from 305 patients. Demographics included: a mean age of 44 (15.0), 48% males, 79% CD, 30% had previous biologic exposure, and 46% on concomitant IMM. Therapy was escalated in 41% of DLs between 5–10μg/mL compared to 15% between 10–15μg/mL. Using ROC analysis, AUC for FCP to predict clinical disease activity was 0.733 (CI: 0.578–0.888, p=0.019) with an optimal cut-off of >99.5μg/g. This is comparable to the currently accepted FCP level of 100μg/g as a cut-off for biological remission. The AUC for DLs to predict an FCP<100μg/g was 0.586 (CI: 0.525–0.647, p=0.007) with an optimal cut-off of >12μg/mL. Figure 1 illustrates the ROC curves for (A) FCP to predict clinical disease activity, and (B) DLs to predict an FCP<100μg/g. A drug level of 12–20μg/mL is strongly correlated with simultaneously attaining both clinical and biological remission in adalimumab patients. Figure 1. ROC for: A, FCP to predict clinical disease activity; B, DLs to predict biological remission. The y-axis illustrates the Sensitivity (or true positives) and the x-axis is 1 – Specificity (or 1 – true negatives). 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".