B-108 Performance evaluation of ANCA and anti-GBM antibody test on a BioPlex 2200 system
Notice bibliographique
Résumé
Abstract Background Anti-neutrophil cytoplasmic antibodies (ANCA) including anti-MPO and anti-PR3 are important serum markers for the diagnosis of ANCA-associated vasculitides. Goodpasture’s syndrome is a rare autoimmune disease affecting lung and kidney, and it is associated with anti-glomerular basement membrane (GBM) antibody. These 3 antibodies play a crucial role in the diagnosis of autoimmune vasculitis and can be screened by solid phase immunoassay followed by confirmatory immunofluorescence assay (IFA). The BioPlex 2200 multiplex bead system is a solid phase immunoassay; the Vasculitis kit allows simultaneously detection of ANCA and anti-GBM antibody in a single run. In this study, we evaluated the analytical performance of BioPlex 2200 vasculitis panel as a primary screening method for autoimmune vasculitis. Methods As an FDA-approved assay, the following manufacturer-claimed performance parameters were verified per relevant CLSI guidelines: precision, linearity, dilution, method comparison, and reference interval (cutoff). Complex precision was conducted using two levels of QC across the cutoff (1.0 antibody index, AI) in a 2x2x5 design. A calibrator set was used to verify assay linearity. Four dilution factors (2, 4, 10, 20) were verified by serial manual dilution of the pooled patient samples. A quantitative method comparison was performed with an external lab using the same assay. In addition, we also compared the qualitative result interpretation between BioPlex assay and ELISA (Euroimmun) or IFA. 30 serum samples from healthy donors were used to verify the cutoff value. According to the literature and CAP survey criteria, the total allowable error of all 3 analytes was set at ±30%. Results were analyzed by EP Evaluator (Data Innovations). Results The total CV% of ANCA was < 5%, and the between-day CV% of anti-GBM was slightly higher but < 10%. All 3 assays demonstrated linearity (slope: 0.966 to 1.02, intercept: -0.13 to 0.02, observed error: 7.90% to 8.80%) and accuracy across manufacturer-claimed AMR (0.2-8.0 AI). However, the linearity was not retained after dilution due to a significantly increased recovery (> 110%). The BioPlex method run in the local lab and reference lab were comparable quantitatively (slope: 0.989 to 1.010, intercept: -0.39 to 0.53, R: 0.984 to 0.999). In the qualitative result interpretation, ANCA was highly consistent between BioPlex assay and ELISA (Kappa: 0.789 to 0.943). Although BioPlex assay detected few anti-GBM positive samples than ELISA, it correlated well with the gold standard IFA (sensitivity: 100%, specificity: 80%). Finally, all 30 healthy donor samples were negative for the 3 autoantibodies (< 0.2 AI), verifying the manufacturer-claimed cutoff. Conclusion The BioPlex 2200 vasculitis panel meets the manufacturer-claimed precision and AMR. The accuracy has been verified by method comparison with a reference lab using the same methodology. As a semi-quantitative test, dilution compromises linearity and leads to increased recovery. The qualitative interpretation of BioPlex assay result is consistent with ELISA for ANCA tests, whereas the anti-GBM by BioPlex assay correlates well with IFA except for some false positive cases. In conjunction with reflexing IFA tests on the positive samples, BioPlex 2200 vasculitis panel can be utilized as a primary screening method for autoimmune vascuiltis.
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 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,002 |
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 ».