Interlaboratory Validation of a 3-Tube 10-Color Antibody Flow Cytometry Panel for Diagnosis of Myelodysplastic Syndromes
Notice bibliographique
Résumé
Abstract Abstract 4941 Background: Multiparameter flow cytometry (MFC) is increasingly used in the diagnostic work-up of patients with suspected myelodysplastic syndromes (MDS). Modern MFC allows the simultaneous detection of 10 fluorochrome-conjugated antibodies recognizing different antigens and thus provides the basis for a refined detection of MDS-related aberrant antigen expression. While efforts are made to harmonize MFC approaches to diagnose MDS, especially on the markers useful to investigate (Westers et al., Leukemia 2012), there has been no interlaboratory evaluation yet of uniform procedures including a common antibody panel and thus reproducibility remains to be proven. Aims: Prove the interlaboratory comparability of diagnostic read-out using a uniform MFC approach to diagnose MDS. Methods: A 10-color/3-tube panel was designed using the fluorochromes FITC, PE, ECD, PC5. 5, PC7, APC, APCA700, APCA750, Pacific Blue, and Krome Orange conjugated to the following antibodies: tube 1) CD14, CD13, CD38, CD123, CD117, CD11b, CD34, CD33, CD16, CD45; tube 2) CD71, CD4, CD64, CD56, CD117, CD36, CD34, CD33, HLA-DR, CD45; tube 3) CD7, CD10, CD8, CD5, CD2, CD3, CD34, CD19, CD15, CD45. Tube 1 was designed for the assessment of myeloid progenitor cells and granulocytes, tube 2 for monocytes and erythroid cells, tube 3 for lymphoid cells and granulocytes. Data acquisition was performed using Navios flow cytometers (Beckman Coulter, Miami, FL) in each of three laboratories from Germany, France, and Canada. Instrument settings were adjusted at all sites to match pre-defined target channels using beads as controls. During the pilot phase, data of a total of 10 MDS cases acquired at the different sites were analyzed by all of the 3 sites following systematic procedures agreed upon. The parameters evaluated included the percentages of respective cell compartments, expression patterns of CD13/CD16/CD11b in granulocytes, aberrant expression of myeloid markers, coexpression of lymphoid markers in granulocytes, monocytes, myeloid progenitor cells and erythroid cells. Coefficients of variation (CV) were calculated for each analyzed parameter for each patient. Results: The quantification of cell compartments was homogeneously performed by the different sites with median CVs amounting to 5. 7% for granulocytes, 10. 5% for monocytes, 7. 1% for lymphocytes, and 5. 0% for CD34 positive progenitor cells. The mean side scatter signal for granulocytes was consistently determined with a median CV of only 3. 4%. Mean fluorescent intensities (MFIs) for distinct markers in general were homogeneously determined between the three sites with the following median CVs: CD33 1. 8% in granulocytes; CD33 2. 6%, CD14 15. 6%, CD13 4. 8%, CD11b 3. 6%, CD56 23. 8%, HLA-DR 5. 1%, CD2 16. 7% in monocytes; CD71 6. 9%, CD36 2. 9% in erythroid cells; CD34 4. 8% in progenitor cells. This provides an important basis for the harmonization of rating aberrantly expressed antigens in MDS which often are identified by only relatively small changes in the respective MFIs. Importantly, also the percentages of positivity for cross-lineage expression of lymphatic antigens in myeloid progenitor cells, which have previously been shown to carry prognostic significance, were determined homogeneously between the three sites with median CVs of 22. 0%, 13. 4% and 33. 9% for the very small subsets of CD2, CD7 and CD5 positive cells. Another aim of the present pilot study has been the objective read-out of parameters which in general have been judged on subjectively. In this regard, the expression patterns of CD11b and CD16 as well as of CD13 and CD16 in granulocytes were subjectively judged aberrant or not aberrant with complete agreement between the three sites. Importantly, the separation of the giraffe-like pattern of CD11b/CD16 expression in granulocytes into 4 subpopulations was performed homogeneously (median CVs 4. 8%, 22. 1%, 18. 0%, 13. 6%) and the resulting MFIs for CD11b (median CVs 7. 2%, 12. 8%, 10. 8%, 11. 5%) in these 4 subpopulations also were consistently quantified between the three sites. Conclusions: This data indicates that harmonization of procedures across different sites in the flow cytometric evaluation of patients with MDS is feasible. While agreement for judgement on antigen expression patterns is possible by experienced scientists it may be complemented or even substituted by standardized data analysis procedures following testing rounds. Disclosures: Kern: MLL Munich Leukemia Laboratory: Equity Ownership; Beckman Coulter, Miami, Florida: Research Funding. Béné:Beckman Coulter, Miami, Florida: Research Funding. Porwit:Beckman Coulter, Miami, Florida: Research Funding.
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 | 0,015 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».