Diagnostic Accuracy of Serologic Screening Tests for Celiac Disease in Asymptomatic Adults and Children with Type 1 Diabetes
Notice bibliographique
Résumé
Background: As related autoimmune conditions, celiac disease (CD) is more common in individuals with type 1 diabetes (T1D) and is frequently asymptomatic. Despite this association, evidence as to the diagnostic accuracy of screening as well as the potential benefits or harms of screening for CD is limited in asymptomatic patients with T1D. Methods: T1D patients, aged 8-45 years, were serologically screened for CD at multiple centers across Ontario, Canada as part of the Celiac Disease and Diabetes Dietary Intervention and Evaluation Trial (CD-DIET). Patients were deemed asymptomatic on the basis of the absence of GI symptoms, weight changes, anemia and other CD-related clinical features. Screening was conducted in 2,386 patients using chemiluminescent (CL, BioFlash™) and/or ELISA (Celikey™) tissue transglutaminase (TTG) IgA assays, yielding 140 positives. Of these, 104 patients had a duodenal biopsy with CD confirmation (Marsh ≥2). Receiver operating characteristic (ROC) curve analysis was conducted and positive predictive values (PPV) of available screening tests for CD were evaluated. Results: CL and ELISA data were available for 100/104 and 36/104 patients, respectively. The area under the curve of the ROC for CL TTG was 0.918, while the PPV using the manufacturer referenced upper limit (RUL) of 30 CU was 85.9% (95% CI: 82.3-90.8%). According to our data, an optimal cut-off of 156.5 CU, or 5.2 times the RUL, showed an improved PPV of 95.8% (95% CI: 92.4-100.0%). With respect to ELISA TTG, the PPV was 94.4% at the RUL of 8 U/ml and reached to 100% at the optimal cut-off determined by our analysis of 58.7 U/ml, which translates to 7.3 times the RUL. Conclusion: Results from serologic CL and ELISA TTG assays that were greater than 5 times the reported upper limit showed a high PPV for biopsy-confirmed CD in asymptomatic adult and pediatric T1D patients, which may help guide diagnostic evaluation in this population. Disclosure M. Gould: None. F.H. Mahmud: None. A.B. Clarke: None. E. Assor: None. A. Parikh: None. A. Advani: Research Support; Self; AstraZeneca, Boehringer Ingelheim GmbH. Other Relationship; Self; Boehringer Ingelheim GmbH. B.A. Perkins: Advisory Panel; Self; Boehringer Ingelheim GmbH. Research Support; Self; Boehringer Ingelheim GmbH, Novo Nordisk Inc.. Advisory Panel; Self; Novo Nordisk Inc., Abbott. Speaker's Bureau; Self; Abbott, Janssen Pharmaceuticals, Inc.. Advisory Panel; Self; Insulet Corporation. Speaker's Bureau; Self; Insulet Corporation, Dexcom, Inc.. B.R. Shah: None. C.S. Zuijdwijk: None. C. McDonald: None. D. Mack: None. D. Koltin: None. E. Hsieh: None. E.M. Szentgyorgyi: None. F. Saibil: None. G. Mukerji: None. H.A. Lochnan: Research Support; Self; Amylin Pharmaceuticals, Boston Therapeutics, Inc., Sanofi. J. Gilbert: Other Relationship; Self; AstraZeneca, Boehringer Ingelheim GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk Inc., Janssen Pharmaceuticals, Inc., Sanofi. K. Bax: None. M.L. Lawson: None. M.D. Beaton: Advisory Panel; Self; Takeda Canada Inc., Janssen Pharmaceuticals, Inc., AbbVie Inc.. N.A. Saloojee: None. O. Lou: None. P.H. Gallego: None. R.L. Houlden: Research Support; Self; Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc., AstraZeneca, Eli Lilly and Company. R. Aronson: Other Relationship; Self; Novo Nordisk Inc., Janssen Pharmaceuticals, Inc., Sanofi, AstraZeneca. Research Support; Self; Eli Lilly and Company, Becton, Dickinson and Company, Merck & Co., Inc., Senseonics, Boehringer Ingelheim Pharmaceuticals, Inc.. S.E. Kirsch: None. W.G. Paterson: None. Z. Punthakee: Research Support; Self; Amgen, Astra Zeneca/Bristol Myers Squibb, Lexicon, Merck, NovoNordisk, Sanofi. Speaker's Bureau; Self; Abbott, Astra Zeneca/Bristol Myers Squibb, Boehringer Ingelheim/Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Sanofi. Advisory Panel; Self; Astra Zeneca/Bristol Myers Squibb, Boehringer Ingelheim/Eli Lilly, Dexcom, Janssen, Medtronic, NovoNordisk, Pfizer, Sanofi. M.A. Marcon: None.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».