MétaCan
Menu
← Retour à la cohorte
Enregistrement W2979048214 · doi:10.14309/00000434-201410002-01735

Predictors of Maintenance of Long-term Remission in Crohn’s Disease Patients Treated With Certolizumab Pegol: Multivariate and Univariate Analyses From the PRECiSE 3 Study

2014· article· en· W2979048214 sur OpenAlexaboutno aff
William Sandborn, Stefan Schreiber, Corey A. Siegel, Gil Melmed, Dermot McGovern, Bosny Pierre‐Louis, Gordana Kosutic, Marshall Spearman

Notice bibliographique

RevueThe American Journal of Gastroenterology · 2014
Typearticle
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueInflammatory Bowel Disease
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCertolizumab pegolMedicineInternal medicineCalprotectinUnivariate analysisCrohn's diseaseProportional hazards modelInfliximabMultivariate analysisFaecal calprotectinGastroenterologyDiseaseInflammatory bowel disease

Résumé

récupéré en direct d'OpenAlex

Introduction: Maintenance of remission in Crohn’s disease (CD) may be optimized by identifying factors that influence long-term treatment outcomes. Demographic, genetic, and clinical factors have been identified as short-term predictors of treatment efficacy and disease progression 1-3 and of relapse prevention 4. The PRECiSE 3 (P3) 7-year trial is the first opportunity to study predictors of maintenance of long-term remission in patients with CD treated with certolizumab pegol (CZP). Methods: Patients who completed double-blind, placebo-controlled studies (P1/P2) enrolled in P3, were followed prospectively, and received open-label CZP 400 mg every 4 weeks up to 7 years. Baseline (BL) factors for testing for association with time to loss of remission (Harvey-Bradshaw index [HBI] score >4) were identified based on clinical relevance, variables in the literature, age, C-reactive protein (CRP), HBI, disease duration, disease location and behavior (Montreal classification), smoking status, prior IBD surgery, BMI, fecal calprotectin, albumin, hematocrit, prior infliximab use, immunomodulator, and corticosteroid (CS) use (BL of P1/P2). Predictors that were significant by univariate analysis were confirmed by multivariate Cox regression and reduced stepwise multivariate Cox regression and were compared with each other to determine independence. Results: Of 594 patients in P3, 453 had sufficient data for univariate and multivariate analyses. Nonsignificant BL predictors of the time to loss of remission by included age, CRP, disease duration, disease behavior, BMI, fecal calprotectin, immunosuppressant, and CS use. Significant BL predictors included serum albumin concentrations (<35 g/L vs. ≥35 g/L), smoking (current vs. other), hematocrit (low <40%/<38% for males/females vs. normal ≥40%/≥38%, respectively), prior IBD surgery (yes vs. no), and entry HBI (<8 vs. ≥8; p<0.05 for all). All of these significant predictors were confirmed with Cox regression models and their influence was determined by the reduced stepwise multivariate Cox regression model (Table). Correlations between predictors were low. Conclusion: These analyses identified several key factors as influential for long-term remission of CD with CZP treatment. The BL factors described are being used to build an algorithm for predicting the success of long-term response to CZP. ClinicalTrials.gov: NCT00160524. Disclosure - William Sandborn - Consulting fees: Abbott Laboratories, ActoGeniX NV, AGI Therapeutics, Inc., Alba Therapeutics Corporation, Albireo, Alfa Wasserman, Amgen, AM-Pharma BV, Anaphore, Astellas Pharma, Athersys, Inc., Atlantic Healthcare Limited, Axcan Pharma (now Aptalis), BioBalance Corporation, Boehringer -Ingelheim Inc, Bristol Meyers Squibb, Celgene, Celek Pharmaceuticals, Cellerix SL, Cerimon Pharmaceuticals, ChemoCentryx, CoMentis, Cosmo Technologies, Coronado Biosciences, Cytokine Pharmasciences, Eagle Pharmaceuticals, Eisai Medical Research Inc., Elan Pharmaceuticals, EnGene, Inc., Eli Lilly, Enteromedics, Exagen Diagnostics, Inc., Ferring Pharmaceuticals, Flexion Therapeutics, Inc., Funxional Therapeutics Limited, Genzyme Corporation, Genentech (now Roche), Gilead Sciences, Given Imaging, Glaxo Smith KlineGlaxoSmithKline, Human Genome Sciences, Ironwood Pharmaceuticals (previously Microbia Inc.), Janssen (previously Centocor), KaloBios Pharmaceuticals, Inc., Lexicon Pharmaceuticals, Lycera Corporation, Meda Pharmaceuticals (previously Alaven Pharmaceuticals), Merck Research Laboratories, MerckSeronoMerck Serono, Millennium Pharmaceuticals (subsequently merged with Takeda), Nisshin Kyorin Pharmaceuticals Co., Ltd., Novo Nordisk A/S, NPS Pharmaceuticals, Optimer Pharmaceuticals, Orexigen Therapeutics, Inc., PDL Biopharma, Pfizer, Procter and Gamble, Prometheus Laboratories, ProtAb Limited, Purgenesis Technologies, Inc., Receptos, Relypsa, Inc., Salient Pharmaceuticals, Salix Pharmaceuticals, Inc., Santarus, Schering Plough Corporation (acquired by Merck), Shire Pharmaceuticals, Sigmoid Pharma Limited, Sirtris Pharmaceuticals, Inc. (a GSK company), S.L.A. Pharma (UK) Limited, Targacept, Teva Pharmaceuticals, Therakos, Tillotts Pharma AG (acquired by Zeria Pharmaceutical Co., Ltd), TxCell SA, UCB Pharma, Viamet Pharmaceuticals, Vascular Biogenics LimitedLtd. (VBL), Warner Chilcott UK Limited, and Wyeth (now Pfizer). Speakers fees: Abbott Laboratories, Bristol Meyers Squibb, and Janssen (previously Centocor). Financial support for research: Abbott Laboratories, Bristol Meyers Squibb, Genentech, Glaxo Smith Kline (now Roche), GlaxoSmithKline, Janssen (previously Centocor), Millennium Pharmaceuticals (now Takeda), Novartis, Pfizer, Procter and Gamble Pharmaceuticals, Shire Pharmaceuticals, and UCB Pharma. CR: Ironwood Pharmaceuticals, Forest Labs, Santarus Pharmaceuticals, Salix Pharmaceuticals, Boston Scientific, Takeda, Prometheus, UCB, Janssen, and Santarus. Stefan Schreiber - Consulting Fee/Advisory Board: Abbvie, MSD, Jansen, Takeda, Hospira, UCB, Federal Funding: German Government, EU Funding, NIH. Corey Siegel - Consultant/Advisory Board: Abbvie, BiolineRX, Given Imaging, Lilly, Janssen, Salix, Millenium, Pfizer, Prometheus, Takeda, UCB, Speaker for CME activities: Abbvie, Janssen, Merck, Grant support: CCFA, AHRQ (1R01HS021747-01) Abbvie, Janssen, Salix, Warner-Chilcott, UCB, Intellectual property - Dartmouth-Hitchcock Medical Center and Cedars-Sinai Medical Center have a patent pending for a “System and Method of Communicating Predicted Medical Outcomes”, filed 3/34/10. Dr. Corey Siegel and Dr. Lori Siegel are inventors. Gil Melmed - Consultant for: abbvie, ucb, given imaging, luktpold pharma, Research grant: shire, Prometheus. Dermot McGovern - Salary from Foundation Source: The Leona M. and Harry B. Helmsley Charitable Trust, Crohns and Colitis Foundation of America, Consulting Fee/Advisory Board: UCB, Merck, Ferring, NovoNordisk, Genentech, Eli Lilly, Federal Funding: NIH, European Union. Bosny Pierre-Louis, Gordana Kosutic, and Marshall Spearman are employees of UCB Pharma and have stocks and stock options.Table 1: Predictors of Maintenance of Long-term Remission, the Influence of Covariates on the Time to Loss of Remission (Years) Starting From the BL of P1/P2 (Reduced Stepwise Multivariate Cox Regression Model)

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,005
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,004
Score d'incertitude au seuil0,022

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,005
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,008
Tête enseignante GPT0,251
Écart entre enseignants0,244 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2014
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueThe American Journal of Gastroenterology→Même sujetInflammatory Bowel Disease→Travaux en français237 207→