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Record W4207037080 · doi:10.1093/ecco-jcc/jjab232.465

P338 Early proactive drug monitoring strategy of infliximab as monotherapy for inflammatory bowel disease in paediatric patients is associated with good sustained clinical remission

2022· article· en· W4207037080 on OpenAlexaff
C. Girard, S Achkar, Samuel Sassine, Laurence Chapuy, Prévost Jantchou, Colette Deslandres

Bibliographic record

VenueJournal of Crohn s and Colitis · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMcGill UniversityMontreal Children's HospitalUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineInfliximabInterquartile rangeInternal medicineInflammatory bowel diseaseCrohn's diseaseTherapeutic drug monitoringRetrospective cohort studyMaintenance therapyDiseaseSurgeryGastroenterologyPharmacokineticsChemotherapy

Abstract

fetched live from OpenAlex

Abstract Background Monotherapy with infliximab (IFX) could be as efficient as combotherapy with immunomodulators in the treatment and maintenance of remission for children with inflammatory bowel disease (IBD) if a proactive therapeutic drug monitoring strategy is adequately performed. This strategy may allow optimization of blood levels of IFX in order to obtain a sustained clinical response. Methods A retrospective study was conducted amongst children with IBD, aged from, 2 to, 18 years old and diagnosed between January, 2018 and June, 2020. All patients were treated with IFX less than, 30 days after diagnosis. Data concerning disease activity was collected at diagnosis, at one year after diagnosis. Close monitoring of IFX blood levels were collected before the third and fourth dose and regularly thereafter. Adjustments in IFX dose per infusion were made according to blood levels and clinical response. The primary outcome was clinical remission, defined by a PUCAI or shortPCDAI score <, 10 without the need of corticosteroid, at one year after diagnosis. The secondary outcomes measured were the median (interquartile range (IQR)) dose of IFX (in mg/kg) after a year of treatment, the median (IQR) number of changes of IFX dose, the time intervals between IFX infusions over a year, and the median (IQR) number of blood levels of IFX done in a year. Results A total of, 91 patients were included (81% Crohn’s disease; mean age at diagnosis was, 13.2 years (IQR = 11.3 to, 15.15)). After one year of treatment, 76 patients (83.5%) reached clinical remission. IFX was discontinued in, 13 patients:, 6 due to antibody occurrence, 5 because of treatment failure, 1 due to psoriasis and, 1 due to autoimmune hepatitis. In total, 61.5% of patients needed two or more IFX dose/interval optimization over the course of a year. At one year after diagnosis, the median IFX dose per infusion was, 8.78 mg/kg (IQR = 7.5 mg/kg to, 9.9 mg/kg) with infusions given, 6 weeks apart or less in, 82% of the patients. Patients who were diagnosed before the age of, 10 had a median IFX dose of, 9.43 mg/kg. The median number of IFX blood level dosage was, 4 per patient over a year (IQR=, 3.5 to 6). Conclusion Early treatment for IBD with IFX as monotherapy and a proactive optimization strategy is associated with a good sustained steroid free clinical remission. Most patients needed an increase of IFX dose during the first year of treatment. We therefore recommend to proactively monitor blood levels of IFX before the third and fourth dose of IFX and thereafter, in order to lower the risk of treatment failure and anti-infliximab antibodies occurrence.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.000

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 head0.008
GPT teacher head0.264
Teacher spread0.256 · 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
Published2022
Admission routes1
Has abstractyes

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