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Automated database-guided expert-supervised orientation for immunophenotypic diagnosis and classification of acute leukemia

Authors :
Lhermitte, L
Mejstrikova, E
Van Der Sluijs-Gelling, A
Grigore, G
Sedek, L
Bras, A
Gaipa, G
Sobral Da Costa, E
Novakova, M
Sonneveld, E
Buracchi, C
De Sa Bacelar, T
Te Marvelde, J
Trinquand, A
Asnafi, V
Szczepanski, T
Matarraz, S
Lopez, A
Vidriales, B
Bulsa, J
Hrusak, O
Kalina, T
Lecrevisse, Q
Martin Ayuso, M
Bruggemann, M
Verde, J
Fernandez, P
Burgos, L
Paiva, B
Pedreira, C
Van Dongen, J
Orfao, A
Van Der Velden, V
Lhermitte, L
Mejstrikova, E
Van Der Sluijs-Gelling, A
Grigore, G
Sedek, L
Bras, A
Gaipa, G
Sobral Da Costa, E
Novakova, M
Sonneveld, E
Buracchi, C
De Sa Bacelar, T
Te Marvelde, J
Trinquand, A
Asnafi, V
Szczepanski, T
Matarraz, S
Lopez, A
Vidriales, B
Bulsa, J
Hrusak, O
Kalina, T
Lecrevisse, Q
Martin Ayuso, M
Bruggemann, M
Verde, J
Fernandez, P
Burgos, L
Paiva, B
Pedreira, C
Van Dongen, J
Orfao, A
Van Der Velden, V
Publication Year :
2018

Abstract

Precise classification of acute leukemia (AL) is crucial for adequate treatment. EuroFlow has previously designed an AL orientation tube (ALOT) to guide towards the relevant classification panel (T-cell acute lymphoblastic leukemia (T-ALL), B-cell precursor (BCP)-ALL and/or acute myeloid leukemia (AML)) and final diagnosis. Now we built a reference database with 656 typical AL samples (145 T-ALL, 377 BCP-ALL, 134 AML), processed and analyzed via standardized protocols. Using principal component analysis (PCA)-based plots and automated classification algorithms for direct comparison of single-cells from individual patients against the database, another 783 cases were subsequently evaluated. Depending on the database-guided results, patients were categorized as: (i) typical T, B or Myeloid without or; (ii) with a transitional component to another lineage; (iii) atypical; or (iv) mixed-lineage. Using this automated algorithm, in 781/783 cases (99.7%) the right panel was selected, and data comparable to the final WHO-diagnosis was already provided in >93% of cases (85% T-ALL, 97% BCP-ALL, 95% AML and 87% mixed-phenotype AL patients), even without data on the full-characterization panels. Our results show that database-guided analysis facilitates standardized interpretation of ALOT results and allows accurate selection of the relevant classification panels, hence providing a solid basis for designing future WHO AL classifications.

Details

Database :
OAIster
Notes :
STAMPA, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1376787839
Document Type :
Electronic Resource