Dual Biologic Therapy in a Patient With Niemann‐Pick Type C and Crohn Disease
Bibliographic record
Abstract
Dual biologic therapy has become a new area of interest in inflammatory bowel disease (IBD). Monogenic/polygenic IBD and the role of genetics in IBD is an evolving field, with many of these patients having difficult treatment courses. We present a case of a teenage patient with Niemann-Pick disease type C and Crohn colitis, who sustained clinical remission only after escalating to dual biologic therapy (anti-tumor necrosis factor alpha [infliximab] and anti-interleukin-12/anti-interleukin-23 [ustekinumab]). A literature review of dual biologic therapy in pediatric IBD revealed 8 case series and 1 cohort study. In pediatric patients with genetic disorders and IBD who are not responding adequately to biologic therapy, adding a second biologic medication with a different mechanism of action may be efficacious. Targeting both anti-tumor necrosis factor alpha (which induces pro-inflammatory cytokines) and the pro-inflammatory cytokines themselves (interleukin-12/interleukin-23) may be important in impaired macrophage function and increased cytokine response. Our case adds to the sparse literature on the utility of combining ustekinumab and infliximab in pediatric IBD and is the first to describe its use for treating ongoing active luminal disease.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".