Correlation Between the Gut Microbiome and Immunotherapy Response in Inflammatory Bowel Disease: A Systematic Review of the Literature
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is an autoimmune disease associated with dysbiosis within the gastrointestinal tract. Characteristic taxonomic shifts of microbial populations are observed in disease progression and remission; however, despite similarities, there are many differences among individuals presenting with IBD including IBD subset, clinical course, and response to therapy. Much is still unknown about how these taxonomic shifts interact with immunotherapy and how genetic variants contribute. In this systematic review, we aimed to compile information on the interactions of the gut microbiome with immunotherapy in the course of disease and treatment of IBD patients. This systematic review was conducted as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the PubMed database was methodically screened for literature search including keywords and Medical Subject Headings (MeSH) terms for relevant articles. The quality appraisal was completed using the Cochrane Tool, Newcastle-Ottawa checklist, and the Scale for the Assessment of Narrative Review Articles (SANRA) checklist, as appropriate, and 11 relevant articles were included in this systematic review. Our review concludes that although there are characteristic taxonomic shifts between diseased and healthy patients, genetic variants are an important consideration in the predictive quality of disease and treatment decisions. The comparison between interactions of microbial populations and treatment in addition to the role of genetic variants may provide insight into treatment non-responders. Due to our limitations in current knowledge including the complexity of the microcosm, ethnic genetic variations among human populations, and our focus on relevant articles published in English over the past six years, we may have missed relevant studies. Future studies should focus on the comparison between Western and other cultural populations as well as further implementation of Genome-Wide Association Studies (GWAS) in clinical predictability.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".