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Interlaboratory Validation of a 3-Tube 10-Color Antibody Flow Cytometry Panel for Diagnosis of Myelodysplastic Syndromes

2012· article· en· W2579125732 on OpenAlexaboutno aff
Wolfgang Kern, Marie C. Béné, Anna Porwit

Bibliographic record

VenueBlood · 2012
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
Fundersnot available
KeywordsCytometryCD34MedicineFlow cytometryCD33AntigenAntibodyImmunologyPathologyBiologyStem cell

Abstract

fetched live from OpenAlex

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.

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)0.015
metaresearch head score (Gemma)0.015
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.040
GPT teacher head0.329
Teacher spread0.290 · 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
Published2012
Admission routes1
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