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Record W4243867159 · doi:10.1093/ibd/izy393.072

02 NEW ONSET AUTOIMMUNE DISORDERS, PRIMARILY PSORIASIS, IN ANTI-TNF BIOLOGIC EXPOSED PEDIATRIC PATIENTS – THE DEVELOP EXPERIENCE

2019· article· en· W4243867159 on OpenAlexaboutno aff
Richard B. Colletti, Anne M. Griffiths, Gigi Veereman, Johanna C. Escher, James Izanec, Christopher Busse, Yanli Wang, Benjamin D. Gold

Bibliographic record

VenueInflammatory Bowel Diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical studies and practices
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIncidence (geometry)CohortPsoriasisInflammatory bowel diseaseUlcerative colitisInternal medicinePopulationCohort studyPediatricsDiseaseImmunologyEnvironmental health

Abstract

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DEVELOP is a multicenter, prospective, observational registry of the long-term safety and clinical outcomes of 6070 pediatric patients with inflammatory bowel disease (IBD; Crohn’s disease, ulcerative colitis, or indeterminate colitis) treated with anti-tumor necrosis factor biologics (aTNF) and/or other medical therapies for IBD as part of routine clinical care. DEVELOP has sites in the United States, Canada and the European Union (EU). Our aim was to characterize the incidence of new autoimmune disorders in a pediatric IBD population exposed to aTNF compared to a population exposed only to non-biologics. Physicians participating in the registry prescribe IBD treatments based on their usual clinical practice and standards of care. Patients are categorized into cohorts according to their prevalent or incident medication exposure, including patients receiving therapy prior to enrollment and/or during registry follow-up. The most recent available data cut (June 30 2018) includes 21083 patient-years (PY) of follow up in the aTNF cohort and 11277 PY in the non-biologics cohort. Investigators record all new autoimmune disorders in the study database during biannual visits. Among all IBD patients, the incidence of all new autoimmune disorders was statistically significantly greater in the aTNF cohort (0.99 events/100 PY) than the nonbiologics cohort (0.27 events/100 PY) (Table 1). These results were driven by new-onset psoriasis (0.58 events/100 PY), the most frequently reported new autoimmune disorder in the aTNF cohort compared to 0.02 new psoriasis events/100 PY in the non-biologics cohort. The incidence of serious new autoimmune disorders was low in both the aTNF cohort (0.20 events/100 PY) and the non-biologics cohort (0.07 events/100 PY). In the aTNF cohort, serious new autoimmune disorders by preferred term that occurred more than once included the following: Psoriasis (0.06 events per 100 PY, n=12 events), Sclerosing Cholangitis (0.02 events per 100 PY, n=4) Lupus-like syndrome (0.02 events per 100 PY, n=4) Optic neuritis (0.01 events per 100 PY, n=3), Autoimmune hepatitis (0.01 events per 100 PY, n=3) In the non-biologics cohort, there were no reports of serious adverse events of psoriasis, optic neuritis, or lupus-like syndrome, one report (0.01 events/100 PY) each of serious autoimmune hepatitis and juvenile idiopathic arthritis and two cases of sclerosing cholangitis (0.02 events/100 PY). New autoimmune disorders were noted approximately once every 100 patient years in the aTNF cohort and were significantly more common compared to the non-biologic cohort. New serious autoimmune disorders in the aTNF cohort were uncommon, with only 0.20 new events per 100 PY. New autoimmune disorders do arise in aTNF treated pediatric IBD patients but overall are uncommon and not serious.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.022
GPT teacher head0.292
Teacher spread0.270 · 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 designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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