Michel Ticchioni1, Chantal Brouzes2, Françoise Durrieu3, Claude Lambert4. 1. Université Nice Côte d'Azur, Centre Hospitalier Universitaire Nice, Nice, France. 2. Hematology Laboratory, Hôpital Necker, Paris, France. 3. Medical laboratory, Bergonié Cancer Institute, Bordeaux, France. 4. Immunology Laboratory FRE-CNRS 3312, University Hospital, Cedex, France.
Abstract
BACKGROUND: As part of quality assurance in laboratories (labs) offering clinical cell analysis by flow cytometry (FCM), cell counting precision and robustness are evaluated but international desirable ranges are still missing. The aim of this study was to provide desirable interlaboratory variability reference values. METHODS: A prospective survey on monthly quality assessment was proposed to all French laboratories routinely performing lymphocyte subpopulation quantification, over one arbitrarily selected month (June 2017), regardless of instrument, counting system and quality controls used. Relative variabilities of the commercially available internal quality control (IQC) used locally were collected. Robust mean, standard deviation and CV were calculated on relative and absolute counts. RESULTS: Sixty-two labs participated, providing 91 sets of data on 82 instruments. All but three were enrolled in external quality assessment (EQA) and 46 in externalized IQA. The mean CV of five repeats ranged from 1.00 ± 0.33 for T cells to 4.78 ± 1.92 for NK cells and from 2.88 ± 1.46 to 5.87 ± 1.83 for relative and absolute counts, respectively. The precision correlated directly to the concentration of cells rather than the phenotype. Negligible differences were observed between IQC material: Multicheck™ (3.36 ± 1.30, n = 11); Immunotrol™ (3.62 ± 3.24, n = 21) and Statusflow™ (3.63 ± 1.87, n = 24) on CD4+ T cell, for example. Little difference was observed between counting systems such as Flowcount™ (4.55 ± 3.45, n = 19), Trucount™ (3.17 ± 1.40, n = 30) and the fully automated Aquios™ system (1.87 ± 0.75, n = 5) on single platforms, while dual platform CV was at 2.00 ± 0.58 (n = 2) on CD4+ T cell, as example. Robustness was measured on 21 ± 11 consecutive analyses of the same IQC material, providing CVs ranging from 4.45 ± 1.74 for T cells to 7.57 ± 2.19 for NK absolute counts. Average residuals calculated from the different low count IQC samples for CD4 T cells (median value below 200 cells/μl) were below 10 cells/μl, demonstrating their robustness for medical decisions. CONCLUSIONS: Real life variabilities in cell counting are directly related to the cell concentration and not to their phenotype. Desirable ranges within three SD are proposed according to different cell levels, based on 62 labs, different IQC material and systems.
BACKGROUND: As part of quality assurance in laboratories (labs) offering clinical cell analysis by flow cytometry (FCM), cell counting precision and robustness are evaluated but international desirable ranges are still missing. The aim of this study was to provide desirable interlaboratory variability reference values. METHODS: A prospective survey on monthly quality assessment was proposed to all French laboratories routinely performing lymphocyte subpopulation quantification, over one arbitrarily selected month (June 2017), regardless of instrument, counting system and quality controls used. Relative variabilities of the commercially available internal quality control (IQC) used locally were collected. Robust mean, standard deviation and CV were calculated on relative and absolute counts. RESULTS: Sixty-two labs participated, providing 91 sets of data on 82 instruments. All but three were enrolled in external quality assessment (EQA) and 46 in externalized IQA. The mean CV of five repeats ranged from 1.00 ± 0.33 for T cells to 4.78 ± 1.92 for NK cells and from 2.88 ± 1.46 to 5.87 ± 1.83 for relative and absolute counts, respectively. The precision correlated directly to the concentration of cells rather than the phenotype. Negligible differences were observed between IQC material: Multicheck™ (3.36 ± 1.30, n = 11); Immunotrol™ (3.62 ± 3.24, n = 21) and Statusflow™ (3.63 ± 1.87, n = 24) on CD4+ T cell, for example. Little difference was observed between counting systems such as Flowcount™ (4.55 ± 3.45, n = 19), Trucount™ (3.17 ± 1.40, n = 30) and the fully automated Aquios™ system (1.87 ± 0.75, n = 5) on single platforms, while dual platform CV was at 2.00 ± 0.58 (n = 2) on CD4+ T cell, as example. Robustness was measured on 21 ± 11 consecutive analyses of the same IQC material, providing CVs ranging from 4.45 ± 1.74 for T cells to 7.57 ± 2.19 for NK absolute counts. Average residuals calculated from the different low count IQC samples for CD4 T cells (median value below 200 cells/μl) were below 10 cells/μl, demonstrating their robustness for medical decisions. CONCLUSIONS: Real life variabilities in cell counting are directly related to the cell concentration and not to their phenotype. Desirable ranges within three SD are proposed according to different cell levels, based on 62 labs, different IQC material and systems.
Authors: Tatiana Raskovalova; Marc G Berger; Marie-Christine Jacob; Sophie Park; Lydia Campos; Carmen Mariana Aanei; Julie Kasprzak; Bruno Pereira; José Labarère; Jean-Yves Cesbron; Richard Veyrat-Masson Journal: Haematologica Date: 2019-04-19 Impact factor: 9.941