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Record W4213389062 · doi:10.1093/jcag/gwab049.128

A129 CYP2C19 PHARMACOGENETIC TESTING IN PAEDIATRIC PATIENTS WITH EOSINOPHILIC ESOPHAGITIS INFLUENCES DOSING OF PROTON-PUMP-INHIBITORS AND RESPONSE TO THERAPY

2022· article· en· W4213389062 on OpenAlexaff
Karin Bortolin, Iris Cohn, S Da Silva, Shinya Ito, P Marcon, N Afzal, S Scodellaro, Ruud H J Verstegen, Jessie M. Hulst

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2022
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsUniversity of TorontoHospital for Sick Children
Fundersnot available
KeywordsCYP2C19Eosinophilic esophagitisRabeprazoleMedicineProton-pump inhibitorPharmacogeneticsInternal medicineDosingLansoprazoleGastroenterologyOmeprazoleNerdGERDPharmacologyDiseaseGenotypeRefluxMetabolismGene

Abstract

fetched live from OpenAlex

Abstract Background Eosinophilic esophagitis (EoE) is a chronic inflammatory disorder that can be treated with a proton pump inhibitor (PPI). Pharmacogenetics (PGx) is the study of how variations in an individual’s genome influences drug response. Genetic variation in the metabolism gene CYP2C19 can produce differences in enzyme activity which is known to be a contributing factor for therapeutic failure with PPI treatment. Use of 2nd generation PPI (rabeprazole) can be beneficial in some as this PPI is less effected by CYP2C19 metabolism. PGx has been studied in PPI therapy for peptic ulcer disease but has not been demonstrated in patients with EoE. Aims To describe the CYP2C19 metabolism in patients with EoE on PPI and to estimate the clinical utility of PGx testing in directing subsequent changes in therapy with improvement in remission rates. Methods Interim analyses of a single centre, non-interventional, ongoing descriptive pilot study investigating CYP2C19 metabolism in patients with EoE, as part of a larger PGx pilot study and EoE- AHEAD Registry Study at SickKids. Patients with EoE that were newly diagnosed and started PPI or those not in remission on current non-PPI therapy or not in remission on dose PPI (2 mg/kg/day, max 30 mg lansoprazole BID) were included. Active disease was defined as a peak eosinophil count >15/hpf. Results 37 patients met the inclusion criteria with completed PGx test; mean age was 13 years, 29(78%) were male, and 13(35%) had concurrent atopic disease. PGx testing showed that 12(32%) and 4(11%) were rapid (RM) and ultrarapid metabolizers (URM) respectively (Fig.1), which is significantly higher than the population average. Of this subgroup, 9 started rabeprazole, 3 had a lansoprazole dose increase, and 4 had no changes. Overall, changes in therapy based on PGx testing were made in 29(78%) patients, 8 are awaiting follow-up (Fig 2). Currently, the patients with available repeat biopsy results after PGx test-guided therapy changes is limited due COVID-19 related delays in endoscopies. Conclusions The preliminary findings of our study using PGx to guide PPI dosing in pediatric patients with EoE demonstrate that PGx test results lead to a change in clinical management in most patients. In RM and URM, PGx results trigger an adjustment of PPI dose or type could lead to earlier disease remission in PPI-responsive patients, thereby optimizing PPI efficacy. PGx may support dose reduction in poor metabolizers aiming to avoid long-term adverse events. Further correlation with endoscopy and histology findings of patients after PGx-guided therapy changes will follow. Furthermore, it is important to examine if CYP2C19 variant information available before PPI therapy further streamlines an initial phase of the treatment. Funding Agencies Dr. Marcon: J Garfield Campbell Fund, Dr. Hulst: Start-up Funds from the Department of Pediatrics at SickKids

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)0.004
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 score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.009
GPT teacher head0.232
Teacher spread0.224 · 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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Citations1
Published2022
Admission routes1
Has abstractyes

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