Clinical Outcomes With Therapeutic Drug Monitoring in Inflammatory Bowel Disease: A Systematic Review With Meta-Analysis
Bibliographic record
Abstract
BACKGROUND AND AIMS: We undertook a systematic review and meta-analysis examining the effectiveness of therapeutic drug monitoring [TDM] to improve clinical outcomes in inflammatory bowel disease patients treated with anti-tumour necrosis factor alpha [anti-TNF] drugs. METHODS: We searched MEDLINE, Epub Ahead of Print, EMBASE and Cochrane up to October 2017 for randomized trials [RCTs] and cohort studies comparing proactive or reactive TDM to each other or empiric care. Outcomes included clinical remission [primary], clinical relapse, endoscopic remission, anti-TNF response durability, cost and adverse events [secondary]. Pooled odds ratios and mean differences were calculated. RESULTS: The search identified nine studies [three RCTs, six observational], focused on infliximab maintenance therapy in adults. Neither proactive nor reactive TDM was associated with superior clinical remission rates compared to empiric dose optimization. However, evidence of a cost benefit, particularly for reactive TDM vs empiric care, was identified. In several studies, TDM, particularly proactive TDM, was associated with favourable outcomes related to durability of anti-TNF response, such as lower drug discontinuation rates compared to empiric care and reactive TDM, and lower relapse rates compared to empiric care. No consistent benefit was found for endoscopic or surgical outcomes. CONCLUSIONS: The existing limited evidence does not support an association between any TDM strategy and superior clinical remission rates but does support a cost savings benefit [particularly for reactive TDM] and suggests a potential benefit for anti-TNF durability [particularly proactive TDM]. Additional, longer-term studies are needed, particularly to further investigate proactive TDM, and to generate data on other anti-TNF agents, the induction period and paediatric populations.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| 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".