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Record W4412132269 · doi:10.1093/ibd/izaf149

Response to “The Association of Inflammatory Bowel Disease and Eosinophilic Esophagitis: True Link or Surveillance Artifact?

2025· letter· en· W4412132269 on OpenAlexaff
Russell Yanofsky, Parul Tandon

Bibliographic record

VenueInflammatory Bowel Diseases · 2025
Typeletter
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsEosinophilic esophagitisMedicineInflammatory bowel diseaseDiseaseArtifact (error)GastroenterologyAssociation (psychology)Internal medicineDermatologyArtificial intelligence

Abstract

fetched live from OpenAlex

To the Editors, We thank Drs. Dai and Huang for their interest in our recent systematic review and meta-analysis examining the association of inflammatory bowel disease (IBD) and eosinophilic esophagitis (EoE).1,2 We sincerely appreciate the opportunity to address their comments below. The authors highlight the high heterogeneity in our meta-analysis (I² = 99.5% for IBD vs. controls). We agree with this limitation, which was accordingly acknowledged in our paper. Recognizing this limitation, we performed several sensitivity analyses to account for the heterogeneity, including leaving-one-out analyses, exclusion of non-cohort studies, and removal of statistical outliers, to assess the robustness of our findings. Notably, the direction and magnitude of the association remained consistent across these analyses, providing additional confidence in the validity of the pooled odds ratios despite underlying study variability. The authors also note the possibility of surveillance bias and misclassification bias that may lead to overestimates of the association between IBD and EoE. Surveillance bias may occur as patients with IBD are more likely to undergo upper endoscopies to evaluate their symptoms, and this could theoretically increase the likelihood of detecting EoE in this population. Likewise, misclassification bias in what constitutes EoE is also possible, as esophageal eosinophilia can occur in other conditions, and the diagnosis of EoE requires rigorous exclusion of alternative causes. These are legitimate concerns, and we recognized both limitations in the original paper. However, the association we observed between IBD and EoE was not disproportionately stronger for Crohn’s disease compared to ulcerative colitis, despite the latter being historically limited to the colon and thus less likely to prompt upper endoscopic evaluation. This finding may argue against surveillance and misclassification bias as explanations for the observed association between IBD and EoE. Furthermore, we included atopic dermatitis as a comparator condition to better appreciate the association between IBD and EoE compared to other autoimmune conditions. As the association between atopic dermatitis and EoE is well-established, this in effect serves as a positive control. Therefore, the consistent positive association we observed between atopic dermatitis and EoE further reinforces the validity of our methods, which were used to address the study question of whether there is an association between IBD and EoE.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.076
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0760.046
Insufficient payload (model declined to judge)0.0080.005

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.

Opus teacher head0.009
GPT teacher head0.248
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractno

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