Effectiveness of Dose De-escalation of Biologic Therapy in Inflammatory Bowel Disease: A Systematic Review
Bibliographic record
Abstract
INTRODUCTION: De-escalation of biologic therapy is a commonly encountered clinical scenario. Although biologic discontinuation has been associated with high rates of relapse, the effectiveness of dose de-escalation is unclear. This review was performed to determine the effectiveness of dose de-escalation of biologic therapy in inflammatory bowel disease. METHODS: We searched EMBASE, MEDLINE, and the Cochrane Central Register of Controlled Trials from inception to October 2019. Randomized controlled trials and observational studies involving dose de-escalation of biologic therapy in adults with inflammatory bowel disease in remission were included. Studies involving biologic discontinuation only and those lacking outcomes after dose de-escalation were excluded. Risk of bias was assessed using the Newcastle-Ottawa Scale. RESULTS: We identified 1,537 unique citations with 20 eligible studies after full-text review. A total of 995 patients were included from 18 observational studies (4 prospective and 14 retrospective), 1 nonrandomized controlled trial, and 1 subgroup analysis of a randomized controlled trial. Seven studies included patients with Crohn's disease, 1 included patients with ulcerative colitis, and 12 included both. Overall, clinical relapse occurred in 0%-54% of patients who dose de-escalated biologic therapy (17 studies). The 1-year rate of clinical relapse ranged from 7% to 50% (6 studies). Eighteen studies were considered at high risk of bias, mostly because of the lack of a control group. DISCUSSION: Dose de-escalation seems to be associated with high rates of clinical relapse; however, the quality of the evidence was very low. Additional controlled prospective studies are needed to clarify the effectiveness of biologic de-escalation and identify predictors of success.
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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 | 0.017 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".