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A Novel Serum Test to Describe the Mucosal Healing State by Disease Location in Crohnʼs Disease Patients

2017· article· en· W2913476107 on OpenAlexaboutno aff
Séverine Vermeire, Geert D’Haens, Michael Hale, Venkateswarlu Kondragunta, Kurt Bray, Anjali Jain, David Laharie

Bibliographic record

VenueThe American Journal of Gastroenterology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineCrohn's diseaseGastroenterologyColonoscopyDiseaseBiomarkerSerologyEndoscopyLogistic regressionInflammatory bowel diseasePathologyColorectal cancerImmunologyCancer

Abstract

fetched live from OpenAlex

Introduction: Non-invasive serological tests can be an attractive option as adjuncts or surrogates for endoscopy in the management of IBD patients. Their utility is particularly helpful in patients with Crohn's disease (CD) given its transmural nature and lack of optimal endoscopic accessibility to the small bowel. A newly developed serological test has been shown to be an effective tool for assessing the intestinal mucosal state in CD patients. The aim of the present study was to assess the diagnostic performance and clinical utility of this novel test in specific subtypes of CD patients classified by the location of their disease. Methods: A 13-biomarker (Ang1, Ang2, CEACAM1, CRP, EMMPRIN, IL7, mmp-1, -2, -3, -9, SAA1, TGF||, and VCAM1) mucosal healing monitoring test termed as the Mucosal Healing Index (MHI) has been developed and validated on a combined cohort of 748 serum specimens with matching colonoscopy scores. MHI is a scale of 0-100 where 0-40 identifies patients in remission (CDEIS<3) or mild (CDEIS 3-8) endoscopic disease and 50-100 identifies patients with endoscopically active (CDEIS ≥3) disease. Multiple logistic regression models were used in developing the MHI score. In the present study, validation of the MHI, according to disease location, has been evaluated in 412 longitudinal specimens from 118 CD patients collected during the TAILORIX clinical trial. Specimens were collected from patients at the time of or close to endoscopy. Endoscopic scoring was centrally read and MH was defined as the absence of visual endoscopic ulcers. MHI test assay performance was assessed for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) in the combined group and by each disease location. Results: Patient characteristics are shown in Table 1. Disease locations were classified according to the Montreal classification. Test accuracy was 95%, 90%, and 87% for ileal, ileocolonic, and colonic disease, respectively. The detailed performance across disease locations is shown in Table 2.Table: Table. Crohn's Disease Patient CharacteristicsTable: Table. MH Index Performance by Crohn's Disease LocationConclusion: A novel serum test for the non-invasive evaluation of mucosal health shows comparable performance across ileal, ileocolonic and colonic anatomic disease locations in patients with CD. These results further validate the clinical utility of the test as a beneficial aid in assessing the state of the intestinal mucosa in CD patients regardless of disease location.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.006
GPT teacher head0.240
Teacher spread0.234 · 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
Published2017
Admission routes1
Has abstractyes

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