North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition position paper on the therapeutic drug monitoring in pediatric inflammatory bowel disease
Bibliographic record
Abstract
Inflammatory bowel diseases (IBD) require effective therapies to prevent morbidity and maintain quality of life. The introduction of biologic agents, beginning with monoclonal antibodies targeting tumor necrosis factor (TNF) alpha, has launched a new era of advancements that have markedly improved short- and long-term outcomes of Crohn's disease and ulcerative colitis. Along with these improvements, there have been challenges to address in optimizing use of biologic therapies in children with IBD. Young children may have rapid drug clearance, and growing children have changing medication needs related to changes in body size, metabolism, and development. For these and other reasons, one size (one dose) does not fit all. Therapeutic drug monitoring (TDM), which involves measurement of drug concentration in serum usually, typically at the predose trough, has emerged as a valuable tool for optimizing dosing and preventing pharmacokinetic failure. This society paper reviews the use of TDM, including target ranges during induction and maintenance therapy for anti-TNF agents and for emerging biologics. This report has been compiled by pediatric gastroenterologists on behalf of the North American Society for Pediatric Gastroenterology, Hepatology, and Nutrition IBD committee after extensive review of the current literature. The purpose of this clinical position statement is to provide guidance to clinicians in the use of TDM to optimize the treatment of children with IBD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".