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Record W3171881417 · doi:10.1093/ecco-jcc/jjab076.627

P505 Early therapeutic drug monitoring after induction therapy with infliximab: correlation with intestinal ultrasound

2021· article· en· W3171881417 on OpenAlexaboutno aff
Catarina Nascimento, B Morão, C Frias Gomes, Tiago Cúrdia Gonçalves, Francisca Dias de Castro, Maria João Moreira, José Cotter, Fábio Pereira, Ana Teresa Caldeira, Rui Dinis Sousa, Rosa Coelho, Guilherme Macedo, C Macedo, Maria João Ferreira, Marília Cravo, L Glória, Joana Torres, Carolina Palmela

Bibliographic record

VenueJournal of Crohn s and Colitis · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInfliximabInternal medicineCalprotectinGastroenterologyTherapeutic drug monitoringCrohn's diseaseTrough levelInflammatory bowel diseaseInduction therapyCohortProspective cohort studyCombination therapyMaintenance therapyDrugDiseaseSurgeryPharmacokineticsChemotherapyPharmacology

Abstract

fetched live from OpenAlex

Abstract Background Therapeutic drug monitoring (TDM) in patients receiving infliximab (IFX) has a role in assessing treatment and managing outcomes. Infliximab trough levels (ITL) have been suggested as useful markers for treatment optimization in Crohn’s disease (CD).Our goals were: to assess the relationship between ITL and transmural inflammation as assessed by intestinal ultrasound(IUS), following induction therapy with IFX; to assess which clinical, laboratorial or IUS parameters better predicted adequate levels by the end of induction therapy. Methods Prospective multicentric cohort study including patients with active CD starting IFX therapy. Clinical disease activity assessed using the Harvey-Bradshaw index (HBI), C-reactive protein (CRP), fecal calprotectin (FC) were measured at week 0 and after induction therapy (week 14). IUS was performed at week 0 and 14, bowel wall thickness (BWT) from the worst segment was selected for analysis. Ileocolonoscopy was performed at W0 and SES-CD was registered. ITL were measured at W14. Results We included 36 patients with CD (61% male; median age 30 years (range 16–73)). According to Montreal classification, most patients were A2 (69%), had ileocolonic disease (L3 56%) and an inflammatory phenotype (B1 58%).Perianal disease was present in 42%. Combination therapy was used in 61%. After induction therapy, 81% were in clinical remission (HBI <5) and 43% had laboratorial remission (normal CRP and FC). IUS response (decrease >25% in BWT) was observed in 24% of patients and remission (BWT normalization) in 11%. Median ITL were 4.3 (IQR 2.3–8.1) and 64% had ITL >3 ug/ml. There was a good negative correlation between ITL and SES-CD (r=-0.492, p=0.003). Adequate ITL were associated with lower HBI (1.5 vs 4.5, p=0.052), laboratory remission (61% vs 15%, p=0.014), lower BWT (4 vs 5.5 mm, p=0.009) and sonographic response (39% vs 0%, p=0.014) at W14. At the end of induction, we found a fair to good correlation between ITL and HBI (r=-0.430, p=0.009),CRP (r=-0,510, p=0.001), FC (r=-0.590, p=0.001) and BWT (R=-0.506, p=0.002). Receiver operating characteristic (ROC) curve analysis showed that FC at W14 had the largest area under the curve (AUC) in predicting adequate ITL (0.813 vs 0.716 vs 0.739 vs 0.772, p<0.05). Conclusion Patients with higher disease burden measured by ileocolonoscopy at baseline had lower ITL after induction. Adequate ITL were associated with laboratorial remission and sonographic response at the end of induction, with a good correlation with clinical, laboratorial and sonographic parameters. These findings suggest that adequate IFX levels after induction are associated with a better control of inflammation in IBD, so early proactive TDM during induction may be helpful in treatment management.

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)0.002
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
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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
Published2021
Admission routes1
Has abstractyes

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