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Record W4231615365 · doi:10.1093/ecco-jcc/jju027.066

DOP038. Faecal calprotectin measurement and infliximab trough levels predict therapeutic evolution CD patients in clinical remission

2015· article· en· W4231615365 on OpenAlexaff
Xavier Roblin, G. Duru, Léa Clavel, Melanie Rinaudo, Muriel Cuilleron, Camille Jarlot, J Phelip, Laurent Peyrin‐Biroulet, Stéphane Paul, Konstantinos Papamichail, Niels Vande Casteele, Thomas Billiet, Ann Gils, Sophie Tops, Karolien Claes, Gert Van Assche, P. Rutgeerts, Séverine Vermeire, Marc Ferrante

Bibliographic record

VenueJournal of Crohn s and Colitis · 2015
Typearticle
Languageen
FieldMedicine
TopicDiverticular Disease and Complications
Canadian institutionsUniversity Hospital
Fundersnot available
KeywordsInfliximabCalprotectinMedicineTrough (economics)Internal medicineFaecal calprotectinGastroenterologyTumor necrosis factor alphaInflammatory bowel disease

Abstract

fetched live from OpenAlex

Background: The deep remission notion (clinical remission and mucosal healing) is an important objective for patients under treatment.The appearance of inflammation and pharmacological biomarkers could be a non-harmful way of predicting the evolution of Crohn's disease (CD).The aim of our study was to offer a predictive model for relapse in CD patients presenting clinical remission undergoing infliximab (IFX) treatment.Methods: It was a prospective monocentric study that included all CD patients on IFX maintenance treatment (5mg/kg) and in clinical remission (CDAI< 150) for at least 16 weeks, between 2011 and 2014.On the day of the IFX infusion, all of these patients underwent a faecal calprotectin assay (Buhlmann technique), a CRP assay and pharmacological assays of IFX (ELISA , Theradiag).TLI ( > 2µg/ ml) were considered therapeutic as well as CRP levels < 5mg/l and faecal calprotectin levels < 250 mg/g of stools.All of the patients included were followed up for a minimum of nine months.A CDAI score was calculated at each IFX infusion.A patient was defined in loss of response to IFX (LOR) when the CDAI was above 220, resulting in a change of treatment deemed necessary by the physician (IFX optimisation, change of medical treatment including the use of corticosteroids, surgery).Results: 119 patients (mean age: 34 years, M:F sex ratio 1.2, mean duration of the disease 7.8 years) were included.The mean followup period was 20.4 months.17% of the patients were on combotherapy (IFX and azathioprine).During follow-up, 37 patients (31.1%) out of the 119 relapsed, 78% within the first 6 months (mean period: 4.6 months).While the clinical characteristics of the relapsed and non-relapsed patients were similar, a univariate analysis isolated four significant factors predicting LOR: (CRP > 5mg/l (p=0.043),ATI > 20ng/ml (p< 0.001), LTI > 2 µg/ml (p< 0.001) and calprotectin > 250 µg/g stools (p<0.001)).After logistic regression, two independent factors were linked to a loss of clinical response: LTI < 2µg/ml (OR: 4,34 ; 95% CI: 1.28-10.7;p=0.001) and faecal calprotectin > 250µg/g stools (OR: 3.5; 95% CI: 1.5-8.7;p=0.001).In light of these results, a training cohort of 55 patients was isolated randomly in order to implement a predictive model for LOR in patients on IFX and in clinical remission.The combination of calprotectin > 250µg/g stools and TLI < 2µg/ml enabled to be predicted LOR in 95% of the cases within 6 months.This model was validated on the test cohort of 64 patients with a PPV of 95% and an NPV of 95%.Conclusions: In IFX-treated CD patients and in clinical remission, a combination of TLI (< 2µg/ml) and faecal calprotectin (>250µg/g of stools) enable the prediction of LOR within 6 months in 95% of cases.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.084
GPT teacher head0.328
Teacher spread0.244 · 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
Published2015
Admission routes1
Has abstractyes

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