Hematopathology / EVALUATION OF THE PENTRA 80 HEMATOLOGY ANALYZER
Analytic Performance of the PENTRA 80 Automated
Blood Cell Analyzer for the Evaluation of Normal
and Pathologic WBCs
María E. Arroyo, PhD,1 María D. Tabernero, MD, PhD,2 María A. García-Marcos, MD, PhD,3
and Alberto Orfao, MD, PhD1
Key Words: PENTRA 80; Hematology analyzer; Flow cytometry; Five-part leukocyte differential; Atypical lymphocytes; Large immature
cells; Immunophenotyping
DOI: 10.1309/6U2T6UTWK10M3NCB
Abstract
We evaluated performance of the ABX PENTRA 80
(ABX Diagnostics, Montpellier, France) hematology
analyzer in enumerating the most frequent subsets of
WBCs in peripheral blood, atypical lymphocytes
(ALYs), and large immature cells (LICs) by comparing
results with those obtained by manual microscopic
counts, another hematology analyzer, and flow
cytometric immunophenotyping.
Identification and enumeration of neutrophils and
lymphocytes with the PENTRA 80 showed high
correlation with all 3 reference methods (R2 ≥ 0.92 and
R2 ≥ 0.88, respectively); quantification of eosinophils
showed good correlation with the other analyzer and
flow cytometric immunophenotyping (R2 ≥ 0.70); lower
correlation coefficients were found for comparisons with
conventional microscopy (R2 ≥ 0.50). For monocytes,
lower but acceptable correlation and agreement were
found; marginal correlation was found for basophils.
The PENTRA 80 also showed good performance in
detecting LICs but was less effective for the identification
of ALYs in relatively low frequencies in abnormal
peripheral blood samples. We found good performance
of the 5-part leukocyte differential analyses for the
PENTRA 80, especially for enumeration of neutrophils,
lymphocytes, eosinophils, and LICs.
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The PENTRA 80 automated cell counter is a new 80sample-per-hour hematology analyzer manufactured by ABX
Diagnostics (Montpellier, France) that, according to the specifications of the manufacturer, provides CBC counts, including a 5-part WBC differential count; at the same time, it provides enumeration of large immature cells (LICs) and atypical
lymphocytes (ALYs). Measurements are based on principles
of impedance, cytochemistry, and the measurement of light
absorbance through the use of the so-called double-hydrodynamic sequential system (or DHSS) technology1 associated
with staining of samples with a cytochemical reagent
(Eosinophix, ABX Diagnostics) before analysis of the cell
volume and light absorbance.
Owing to its recent availability, no studies have been
reported so far in which the PENTRA 80 automated cell
counter is evaluated in detail in a clinical diagnostic hematology laboratory for its performance in calculating the 5part WBC differential and the identification of the related
quantitative and/or morphologic abnormalities to be flagged.
Few studies have been reported on the PENTRA 120 (ABX
Diagnostics).1-3
According to the National Committee for Clinical and
Laboratory Standards (NCCLS),4 evaluation of the total and
differential counts of WBCs and WBC-related flags provided
by a new hematology analyzer should be based on conventional microscopic analysis. Although conventional microscopy is
extremely useful in clarifying complex hematologic samples
and verifying the nature of malignant vs reactive cells, it has
some disadvantages and limitations once applied to the control of WBC counts: (1) Few cells are available for counting.
(2) Experience is required to enumerate different cell types. (3)
It is time-consuming. In addition, some cells that normally
© American Society for Clinical Pathology
Hematopathology / ORIGINAL ARTICLE
circulate in the blood, such as dendritic cells, cannot be identified specifically by morphologic examination, and distinct
WBC populations can show a different distribution throughout
the slide, leading to variations in the differential counts.5
Flow cytometry is an innovative, rapid, sensitive, and less
operator-dependent technology6,7 that allows precise multiparameter enumeration of high numbers of cells from different
cell populations in a sample in a relatively short period.8 In
recent years, it has been suggested that combined flow cytometric analysis of the light scatter and phenotypic characteristics of WBCs might represent a reliable approach to accurately enumerating WBCs and their major subsets in normal and
pathologic samples.9
The aim of the present study was to evaluate the performance of the PENTRA 80 blood cell analyzer in the 5-part differential analysis of WBCs and its related quantitative and/or
morphologic flags. The results provided by this instrument were
compared with those obtained using conventional morphologic
examination, multiparameter flow cytometric immunophenotyping, and another independent hematologic cell analyzer.
Materials and Methods
Peripheral Blood Samples
In the present study, a total of 200 peripheral blood (PB)
samples were analyzed. Half of them were normal PB samples
defined by the absence of quantitative and qualitative morphologic and numeric flags on RBCs, WBCs, and platelets; the
other 100 samples were classified as abnormal based on the
presence of quantitative and/or qualitative morphologic and/or
numeric flags on a routine WBC differential analysis (CELLDYN 4000, Abbott Diagnostics, Santa Clara, CA). The abnormal samples were from patients with nonhematologic disorders
(n = 51) or diagnosed with hematologic disease (n = 49); the latter group included myelodysplastic syndromes (n = 4), acute
myeloid leukemia (n = 3), chronic myeloid leukemia (n = 2), Bcell chronic lymphocytic leukemia (n = 13), B-cell nonHodgkin lymphoma (n = 20), and multiple myeloma (n = 7).
All samples were obtained by venipuncture and placed
directly in VACUTAINER tubes containing tripotassium
EDTA as the anticoagulant (Becton Dickinson, Franklin
Lakes, NJ). In all cases, PB samples were analyzed within 6
hours after being obtained; whenever the sample was not analyzed immediately, it was kept at stable room temperature.
Analysis of samples was performed in parallel in the
PENTRA 80 and the 3 reference methods: (1) the CELL-DYN
4000 hematology analyzer (n = 200); (2) morphologic analysis of blood smears by optical microscopy (n = 200); and (3)
multiparameter flow cytometric immunophenotyping (n = 50;
25 normal and 25 abnormal randomly selected samples).
WBC Analysis With the PENTRA 80
All PB samples were analyzed in duplicate in the PENTRA 80 in the “differential and automatic” mode. The mean
value derived from duplicate measurements was calculated
and used in the evaluation. Information on the following
WBC-associated parameters was recorded specifically:
absolute WBC count and absolute and relative neutrophil,
lymphocyte, monocyte, eosinophil, and basophil counts.
Whenever present, information about abnormal WBC populations (eg, ALYs, which include large lymphocytes, activated
lymphocytes, lymphoid cells, and small lymphocytes, and/or
LICs, which include myelocytes, promyelocytes, metamyelocytes, and large blasts) also was recorded.
The mean coefficients of variation obtained between
sample replicates were 1.92% and 2.35% for neutrophils,
2.63% and 2.99% for lymphocytes, 4.28% and 4.47% for
monocytes, 9.84% and 10.49% for eosinophils, and 9.75%
and 9.83% for basophils in relative and absolute numbers,
respectively.
Morphologic Evaluation of PB WBC Differential Counts
For morphologic evaluation of the WBC differential
count, 4 smears were prepared and dried for each blood sample. Afterward, 3 of the 4 blood slides were stained with MayGrünwald-Giemsa according to well-established methods. Of
the 3 stained slides, 2 were assigned randomly for the evaluation of WBC differential counts. Blood smear examination
was performed by 2 independent expert physicians who randomly counted 200 WBCs each, following the NCCLS criteria.4 For each cell population identified in each sample, the
average value obtained by the 2 experts was used for comparison with the results obtained with the PENTRA 80. The mean
coefficients of variation (and correlation coefficients) obtained
for the measurements performed by the experts were 2.91%
(R2 = 0.84) for neutrophils, 3.54% (R2 = 0.92) for lymphocytes, 1.86% (R2 = 0.97) for monocytes, 4.7% (R2 = 0.99) for
eosinophils, and 14.1% (R2 = 0.93) for basophils.
Independent Automated Blood Cell Analysis
The CELL-DYN 4000 was used as an independent blood
cell counter. This instrument uses multiangle polarized side-scatter technology to calculate the distribution of the populations of
WBCs in PB samples.10 All 200 samples studied were processed
in the “differential and automatic” mode in the CELL-DYN
4000 by an independent operator as done with the PENTRA 80.
Multiparameter Flow Cytometric Immunophenotypic
Analysis of WBC Differential Counts
Fifty samples were randomly selected from the 100 normal (n = 25) and 100 abnormal (n = 25) sample groups and
analyzed by multiparameter flow cytometry. The Extended
Hematology Panel11 was used with permission for the staining
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of these samples. Briefly, an exact volume of 100 µL of premixed blood was placed by reverse pipetting using a calibrated
pipette in a 12 × 75-mm polystyrene tube containing TRUECOUNT beads (Becton Dickinson Biosciences [BDB], San
Jose, CA), to which the Extended Hematology Panel mixture of
monoclonal antibodies directly coupled with fluorescent dyes
was added.11 The mixture then was incubated for 15 minutes at
room temperature in the dark. Once this incubation period was
finished, 2 mL of FACS Lysing solution (BDB) diluted 1:10
(vol/vol) in distilled water was added to lyse the nonnucleated
RBCs, and another 10-minute incubation at room temperature
was performed in the dark. All samples were measured in a
FACSCalibur flow cytometer (BDB), and information on a total
of 50 × 103 cells plus the corresponding TRUECOUNT beads
was acquired and stored using CellQUEST software (BDB).
PAINT-A-GATE software (BDB) was used for data analysis,
according to the Extended Hematology Panel protocol.
TRUECOUNT beads were used to calculate the absolute
count per microliter for each cell population identified as previously described.11 Briefly, for the identification of each subset of
WBCs the following phenotypic characteristics were used: neutrophils, forward scatter (FSC)int/side scatter (SSC)high/HLADR–/CD33lo/CD14–/lo/CD45+; monocytes, FSCint/SSCint/ HLADR+/CD33hi/CD14hi/CD45int to hi; lymphocytes,FSClo/SSClo/
HLA-DR– to +/CD33–/CD14–/CD45hi; eosinophils, FSCint/
SSCvery high/HLA-DR–/CD33+/CD14–/CD45+; basophils,
FSClo/SSClo/HLA-DR–/CD33+/CD14–/CD45+; and dendritic
cells, FSCint/SSClo to int/HLA-DRhi/CD33– or +/CD14– or
+/CD45int to hi. In addition, in pathologic samples, blast cells were
identified as being SSClo/CD45lo events and immature granulocytes as events showing phenotypic characteristics similar to the
neutrophils but with higher FSC and/or CD33 expression. ALYs
were identified as events similar to lymphocytes with abnormally high FSC and/or HLA-DR expression.
Statistical Methods
All numeric and coded data were introduced in a database
using SPSS 10.0 statistical software (SPSS, Chicago, IL). The
Pearson correlation was used for the initial comparison between
methods. The Bland-Altman test was used to assess the degree
of agreement between methods.12 To establish the best cutoff
values for maximum sensitivity, specificity, and efficiency for
the PENTRA 80 to identify the presence of a given population
of abnormal WBCs, receiver operating characteristic curves
were used, according to NCCLS recommendations.4
Results
❚Table 1❚ summarizes the results of correlating the relative and absolute counts for each WBC population analyzed
with the PENTRA 80 with those of the 3 reference methods.
High correlation was observed for WBC counts between the
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PENTRA 80 and the CELL-DYN 4000 and between the PENTRA 80 and flow cytometric immunophenotyping in normal
and abnormal samples (R2 ≥ 0.85 and R2 ≥ 0.93, respectively).
As shown in Table 1, a high degree of correlation was
observed between results from the PENTRA 80 and those in
normal and abnormal samples with the other 3 methods for
neutrophils (R2 ≥ 0.92 and R2 ≥ 0.84, respectively) and lymphocytes (R2 ≥ 0.88 and R2 ≥ 0.86, respectively).
High correlation also was observed for the relative and
absolute number of eosinophils obtained with the PENTRA 80
and with the CELL-DYN 4000 and flow cytometric
immunophenotyping in normal (R2 ≥ 0.92 and R2 ≥ 0.95,
respectively) and, to a lesser extent, in abnormal samples (R2 ≥
0.72 and R2 ≥ 0.66, respectively). The correlation between the
percentage of eosinophils obtained with the PENTRA 80 and
manual microscopic counts was lower in normal (R2 = 0.57)
and abnormal (R2 = 0.50) samples.
A clearly lower degree of correlation was obtained for the
percentage and absolute monocyte counts obtained with the
PENTRA 80 and the CELL-DYN 4000 (R2 ≥ 0.42 and R2 ≥
0.12, respectively), manual microscopic counts (R2 ≥ 0.30),
and flow cytometric immunophenotyping (R2 ≥ 0.46 and R2 ≥
0.15, respectively).
Regarding the number of basophils, no statistically significant correlation was found between results from the PENTRA 80 and the other 3 methods, except for a marginal correlation found between the PENTRA 80 cell counts and flow
cytometric immunophenotyping in normal PB samples for the
relative and absolute basophil counts.
On exploring the degree of agreement between results
obtained with the PENTRA 80 and the other methods, it should
be noted that, in general, higher concordance was observed for
normal than for abnormal samples in percentage and absolute
cell counts. Accordingly, a high degree of agreement was
observed for the WBC count with the PENTRA 80 compared
with the CELL-DYN 4000 (n = 200) and flow cytometric
immunophenotyping (n = 50) (83% and 94%, respectively).
The differential neutrophil counts obtained with the PENTRA 80 were in total agreement with those measured by the
CELL-DYN 4000 and optical microscopy for normal PB samples; the values decreased substantially for abnormal samples
❚Table 2❚. For lymphocyte counts, a high degree of agreement
also was observed in relative numbers for the PENTRA 80 and
the CELL-DYN 4000 and microscopic counts (≥98%) in normal
samples; however, the degree of agreement decreased notably in
absolute values for the CELL-DYN 4000 in normal and abnormal samples. As could be expected, the degree of agreement
between results with the PENTRA 80 and the CELL-DYN 4000
and manual counts was lower for monocytes and eosinophils in
normal and, especially, abnormal samples. The degree of agreement observed for basophil counts in normal and abnormal
samples was consistently 22% or lower when results obtained
© American Society for Clinical Pathology
Hematopathology / ORIGINAL ARTICLE
❚Table 1❚
Degree of Correlation Between Percentage and Absolute Values for the Five-Part WBC Differential With Two Analyzers, Optical
Microscopy, and Flow Cytometric Immunophenotyping*
Samples
Neutrophils
Methods
Normal
Monocytes
Eosinophils
Basophils
Abnormal
Normal
Abnormal
Normal
Abnormal
Normal
Abnormal
Normal
0.84
1.05
1.77
<.001
0.94
0.90
4.73
<.001
0.88
0.81
8.38
<.001
0.49
0.54
2.39
<.001
0.42
0.77
6.00
<.001
0.94
0.93
0.43
<.001
0.73
0.64
0.71
<.001
0.00
–0.01
0.65
.78
0.02
0.70
2.84
.18
0.92
0.93
0.36
<.001
0.88
0.90
4.06
<.001
0.86
–7.18
1.09
<.001
0.32
0.41
3.63
<.001
0.30
0.88
12.40
<.001
0.57
0.78
1.02
<.001
0.50
0.50
0.91
<.001
0.00
0.02
0.64
.58
0.05
0.72
2.74
.02
0.92
0.94
3.38
<.001
0.96
0.93
4.80
<.001
0.93
0.86
6.31
<.001
0.46
0.48
2.40
<.001
0.58
0.81
3.87
<.001
0.95
0.99
0.58
<.001
0.86
0.81
0.80
<.001
0.32
0.29
0.40
.003
0.00
0.04
2.10
.94
0.99
1.14
–0.791
<.001
0.85
0.91
0.42
<.001
0.97
0.99
1.17
<.001
0.49
0.54
2.39
<.001
0.12
0.77
1.37
<.003
0.92
1.03
0.03
<.001
0.72
1.07
0.08
<.001
0.98
1.05
–1.36
<.001
0.91
0.88
0.35
<.001
0.97
0.91
1.05
<.001
0.65
0.65
0.07
<.001
0.15
0.57
1.03
<.07
0.97
0.96
0.02
<.001
0.66
0.78
0.07
<.002
Percentage
CELL-DYN 4000
R2
0.92
Slope
0.93
y-Intercept
2.73
P
<.001
Optical microscopy
R2
0.92
Slope
0.93
y-Intercept
2.61
P
<.001
Flow cytometry
R2
0.97
Slope
0.97
y-Intercept
0.25
P
<.001
Cells/µL
CELL-DYN 4000
R2
0.85
Slope
1.01
y-Intercept
0.31
P
<.001
Flow cytometry
R2
0.93
Slope
0.98
y-Intercept
–0.19
P
<.001
*
Lymphocytes
0.01
–0.06
0.04
.43
0.26
0.33
0.03
.012
Abnormal
0.02
2.32
0.77
.87
0.01
–0.57
0.57
.87
Methods vs the ABX PENTRA 80 blood cell analyzer. Numbers of samples for the comparisons were as follows: CELL-DYN 4000 hematology analyzer and microscopic-based
manual counts, 100 normal and 100 abnormal samples; flow cytometric immunophenotyping, 25 normal and 25 abnormal samples. For proprietary information, see the text.
with the PENTRA 80 were compared with those from the
CELL-DYN 4000 and microscopy.
The overall degree of agreement between results from the
PENTRA 80 and flow cytometric immunophenotyping is
shown in ❚Figure 1❚ for the 50 samples analyzed. A high
degree of agreement between the methods was observed for the
relative and absolute counts of neutrophils and lymphocytes.
For monocytes, the degree of agreement was acceptable in relative and absolute numbers. By contrast, for eosinophils and
basophils, the degree of agreement observed between the
PENTRA 80 and flow cytometry was lower (≥24%).
For the LIC flag obtained with the PENTRA 80, a relatively acceptable degree of agreement was observed with morphologic counts ❚Table 3❚. Once the “blast,” “band,” and “immature
❚Table 2❚
Percentage of Agreement Between Results Obtained With Two Analyzers and Optical Microscopy*
Normal Samples
CELL-DYN 4000
Cell Population
WBCs
Neutrophils
Lymphocytes
Monocytes
Eosinophils
Basophils
% of Cells
—
100
99
54
38
8
Cells/µL
96
95
68
80
39
4
Abnormal Samples
Microscopy
% of Cells
—
100
98
52
29
3
CELL-DYN 4000
Microscopy
% of Cells
Cells/µL
% of Cells
—
66
39
53
28
0
79
71
57
46
29
22
—
72
28
44
17
4
* Agreement
is between the results with the ABX PENTRA 80 hematology cell analyzer and those with the CELL-DYN 4000 and optical microscopy for enumeration of WBCs,
neutrophils, lymphocytes, monocytes, eosinophils, and basophils in 100 normal and 100 abnormal peripheral blood samples. Cutoff values for disagreement were established as
the difference between the values obtained with the 2 methods higher or lower than 10% of their mean values. Results are expressed as percentage values. For proprietary
information, see the text.
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B
–10
–20
0
20 40 60 80
Mean % of Neutrophils
100
20
15
10
5
0
–5
–10
0
58% agreement
10
20
Mean % of Monocytes
30
–2
–4
–6
0
10
20
30
40
Mean No. of Neutrophils/µL
7
6
28% agreement
5
4
3
2
1
0
–1
–2
–3
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5
Mean % of Basophils
20
74% agreement
10
0
–10
–20
0
20 40 60 80 100
Mean % of Lymphocytes
G
6
5
4
3
2
1
0
–1
–2
–3
–4
–5
0
76% agreement
1
2
3
4
Mean No. of Monocytes/µL
J
% Difference of Basophils
I
% Difference of Basophils
0
F
% Difference of Monocytes
% Difference of Monocytes
E
2
30
% Difference of Lymphocytes
0
86% agreement
D
4
28% agreement
3
2
1
0
–1
–2
–3
–0.5 0.0 0.5 1.0 1.5 2.0
Mean No. of Basophils/µL
2.0
1.5
1.0
0.5
0.0
–0.5
–1.0
0
8
6
4
2
74% agreement
0
–2
–4
–10 0 10 20 30 40 50
Mean No. of Lymphocytes/µL
H
0.6
24% agreement
0.5
0.4
0.3
0.2
0.1
0.0
–0.1
–0.2
0.0 0.1 0.2 0.3 0.4 0.5 0.6
Mean No. of Eosinophils/µL
% Difference of Eosinophils
10
4
% Difference of Lymphocytes
94% agreement
C
% Difference of Eosinophils
20
% Difference of Neutrophils
% Difference of Neutrophils
A
24% agreement
2
4
6
Mean % of Eosinophils
8
❚Figure 1❚ Degree of agreement for the relative and absolute
numbers of different subpopulations of peripheral blood
WBCs between the ABX PENTRA 80 hematology cell
counter and flow cytometric immunophenotyping in 50
peripheral blood samples analyzed. Cutoff values for
disagreement were established as the difference between
values obtained with the 2 methods higher or lower than
10% of their mean value. Dotted line, zero value; solid line,
mean difference; dashed line, 10% cutoff; continuous
external lines, ±SD. For proprietary information, see the text.
❚Table 3❚
Degree of Correlation and Agreement Between Relative and Absolute Counts of LICs and ALYs With Two Analyzers, Microscopy,
and Flow Cytometric Immunophenotyping*
% of Cells
Methods
CELL-DYN 4000
R2
Slope
y-Intercept
P
Percentage of agreement
Optical microscopy
R2
Slope
y-Intercept
P
Percentage of agreement
Flow cytometry
R2
Slope
y-Intercept
P
Percentage of agreement
LICs
Cells/µL
ALYs
LICs
ALYs
0.46
0.35
1.67
.11
43
0.36
0.43
0.09
<.001
2
0.64
0.43
0.09
.01
35
0.22
4.75
0.54
<.001
11
0.64
0.62
2.62
.01
36
0.12
0.42
3.27
<.001
6
—
—
—
—
—
—
—
—
—
—
0.49
0.45
1.47
<.001
62
0.60
0.31
1.55
<.001
8
0.25
0.49
0.34
.02
58
0.95
0.47
0.16
<.001
40
ALYs, atypical lymphocytes; LICs, large immature cells.
Methods vs the ABX PENTRA 80 blood cell analyzer. Numbers of samples for comparisons were as follows: CELL-DYN 4000 hematology analyzer, 100 abnormal samples;
microscopic-based manual counts, 100 abnormal samples; flow cytometric immunophenotyping, 25 abnormal samples. For proprietary information, see the text.
*
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Hematopathology / ORIGINAL ARTICLE
granulocyte” flags provided by the CELL-DYN 4000 were
summed up and compared with the LIC values from the PENTRA 80, an acceptable degree of agreement was observed. In
contrast, the presence of ALYs as determined by the PENTRA
80 showed poor agreement when compared with morphologic
examination and the CELL-DYN 4000 “Varlym” flag (≤11%).
Despite this, it should be noted that when compared with flow
cytometry, the LIC and ALY counts obtained with the PENTRA
80 showed statistically significant correlations in relative and
absolute numbers, even though the percentage of agreement
between methods was acceptable for the LIC flag but much
lower for the ALY flag.
Because the usefulness of the LIC and ALY flags provided by a hematology cell analyzer depends on qualitative rather
than quantitative data, a final goal of our study was to establish
the best cutoff values for optimal sensitivity, specificity, and
efficiency for both flags. As shown in ❚Figure 2❚, the cutoff values for percentages of LIC and ALY flags showing higher efficiency were 1.0%, 1.5%, and 3.0% for LICs and 20.5%,
12.2%, and 5.0% for ALYs for comparisons done with the
CELL-DYN 4000, microscopy, and flow cytometry, respectively. At these cutoff values, the sensitivity and specificity
obtained for the LIC and ALY flags given by the PENTRA 80
were 100.0% and 89.3%, 100.0% and 85.7%, and 85.7% and
91.4% for the LIC flag and 16.7% and 100.0%, 33.3% and
98.9%, and 66.7% and 97.9% for the ALY flag compared with
the CELL-DYN 4000, conventional microscopy, and flow
cytometry, respectively.
For the absolute counts of LICs and ALYs, highest efficiency was obtained at cutoff values of 0.14/µL and 6.8/µL
B
50
Cutoff = 1.0
Sensitivity = 100.0%
Specificity = 89.3%
25
0
100
75
50
25
% Specificity
75
50
25
% Specificity
0
100
50
% Sensitivity
75
Cutoff = 3.0
Sensitivity = 85.7%
Specificity = 91.4%
25
0
100
75
50
25
% Specificity
0
75
50
Cutoff = 5.0
Sensitivity = 66.7%
Specificity = 97.9 %
25
0
100
100
75
50
25
% Specificity
75
50
Cutoff = 1.5
Sensitivity = 100.0%
Specificity = 85.7%
25
0
100
75
50
25
% Specificity
0
75
50
Cutoff = 12.2
Sensitivity = 33.3%
Specificity = 98.9%
25
0
100
75
50
25
% Specificity
0
❚Figure 2❚ Receiver operating characteristic curve plots to
evaluate the sensitivity and specificity of the relative values
of large immature cell (A, C, and E) and atypical lymphocyte
(B, D, and F) flags provided by the ABX PENTRA 80
hematology cell counter compared with the CELL-DYN 4000
automated hematology cell analyzer, manual microscopic
counts, and multiparameter flow cytometry. For proprietary
information, see the text.
F
100
% Sensitivity
Cutoff = 20.5
Sensitivity = 16.7%
Specificity = 100.0%
25
0
100
0
E
75
50
D
100
% Sensitivity
75
Until now, the performance of a new hematology cell
analyzer for determining the WBC 5-part differential counts
has been evaluated against manual optical microscopy counts
as recommended in the NCCLS H20-A document4,13,14; in
many studies, in addition to conventional cytology, side-byside evaluation with another already validated blood cell
counter is performed in parallel.10,15,16 More recently, the
development of single-platform flow cytometric immunophenotyping assays capable of specifically and simultaneously
identifying and enumerating different subpopulations of
WBCs has provided a new, accurate, external, independent
tool for evaluation of the performance of 5-part differential
analysis of a cell counter, which overcomes many limitations
of microscopy.7,17,18
The PENTRA 80 automated blood cell counter performs a
CBC count and a 5-part WBC differential analysis based on
principles of impedance, cytochemistry, and the measurement
of light absorbance (DHSS technology). Since its development,
no external studies have been reported in which this hematologic blood cell analyzer has been specifically evaluated. Such
studies have shown good performance of the PENTRA 80 in
comparison with other hematology cell analyzers for the measurement of RBC- and platelet-associated parameters, as also
C
100
% Sensitivity
% Sensitivity
100
Discussion
% Sensitivity
A
and 0.11/µL and 0.88/µL when compared with the CELLDYN 4000 and flow cytometric immunophenotyping, respectively ❚Figure 3❚.
0
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Arroyo et al / EVALUATION OF THE PENTRA 80 HEMATOLOGY ANALYZER
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Am J Clin Pathol 2005;123:206-214
DOI: 10.1309/6U2T6UTWK10M3NCB
A
B
100
75
50
% Sensitivity
% Sensitivity
100
Cutoff = 0.14
Sensitivity = 98.7%
Specificity = 87.6%
25
0
100
75
50
25
% Specificity
75
50
Cutoff = 0.11
Sensitivity = 100.0%
Specificity = 84%
25
0
100
0
C
75
50
25
% Specificity
0
D
100
100
75
50
% Sensitivity
% Sensitivity
found in the present study (mean ± SD, 4.14 ± 0.88 × 106/µL
[4.14 ± 0.88 × 1012/L] and 204 ± 115 × 103/µL [204 ± 115 ×
109/L], respectively [data not shown]). However, none of these
studies compared the results of the WBC 5-part differential
obtained with the PENTRA 80 on a large series of samples
with 2 or more independent reference methods, including flow
cytometric immunophenotyping.
In the present study, we compared the WBC 5-part differential results obtained with the PENTRA 80 not only with
conventional morphologic results but also with 2 other reference methods in parallel using the same samples: another
blood cell counter and a 4-color, single-platform flow cytometric immunophenotyping assay. Overall, the PENTRA 80
showed good performance compared with the 3 reference
methods in the analysis of normal and abnormal samples.
However, it should be noted that the quality of the results
obtained varied significantly for different subpopulations of
WBCs. Accordingly, performance was extremely good for
neutrophils and lymphocytes, even in abnormal samples, but it
clearly was lower for monocytes and very poor for basophils.
Overall, these results would be in agreement with those
obtained in evaluation studies of other cell counters.13,19,20 It
is interesting, however, that slight variations also were
observed in the results obtained depending on the reference
method with which they were compared. Accordingly, the
highest and the lowest coefficients of correlation for the 5 cell
populations analyzed in normal and abnormal samples were
obtained when the PENTRA 80 results were compared with
flow cytometry and conventional microscopy, respectively;
comparisons with the CELL-DYN 4000 showed intermediate
correlation coefficients near those observed with flow cytometry. These observations might be related directly to the use
in the new instrument evaluated herein of flow
cytometry–based principles for the identification of different
populations of WBCs and to the higher precision the blood
cell analyzers have because of the greater numbers of cells
counted.1,21,22 Despite this, it should be highlighted that when
results obtained for individual samples were compared, the
degree of agreement between the 2 cell counters tended to be
higher than that found for flow cytometry and PENTRA 80
comparisons.
As for other cell counters, the identification and enumeration of neutrophils and lymphocytes did not represent a
major problem23 with any of the 4 methods used; extremely
high correlation coefficients and degrees of agreement were
observed consistently. Enumeration of eosinophils by the 2
cell counters and flow cytometric immunophenotyping,
despite showing high correlation, consistently displayed a
degree of agreement of 39% or less and even lower for comparisons with conventional morphologic examination. These
results are in contrast with previous reports that have shown
much better correlation for eosinophil counts between cell
Cutoff = 6.8
Sensitivity = 22.2%
Specificity = 99.5%
25
0
100
75
50
25
% Specificity
0
75
50
Cutoff = 0.88
Sensitivity = 40%
Specificity = 100.0%
25
0
100
75
50
25
% Specificity
0
❚Figure 3❚ Receiver operating characteristic curve plots to
evaluate the sensitivity and specificity of the absolute
numbers of large immature cell (A and B) and atypical
lymphocyte (C and D) flags provided by the ABX PENTRA 80
hematology cell counter compared with the CELL-DYN 4000
automated hematology cell analyzer and multiparameter flow
cytometry immunophenotyping. For proprietary information,
see the text.
counters and conventional cytology.1,14,24 Our findings could
directly reflect the relatively low frequency at which
eosinophils are present in blood samples because even when a
total of 400 cells per sample are counted, the mean coefficient
of variation of the microscopic measurement for a mean number of 2% eosinophils per sample is around 14%.
By contrast, the decreased degree of correlation found for
monocytes is in agreement with previous observations for
most blood cell counters25-27 and could not be explained
entirely in terms of their relatively low frequency in the samples analyzed. In fact, monocytes are a difficult subpopulation
to identify by morphologic and light scatter characteristics; at
the same time, they might not be identified in pathologic samples including other abnormal cells such as immature granulocytes or large lymphocytes. Moreover, circulating dendritic
cell precursors, which represent up to 1% of all nucleated cells
in normal blood,5 also might interfere with the unequivocal
identification of monocytes and their accurate enumeration.
Despite the efforts made in recent years for improving the
identification of basophils in automated blood cell analyzers,
the results presented herein once again verify that they represent
© American Society for Clinical Pathology
Hematopathology / ORIGINAL ARTICLE
the individual subpopulation of normal blood WBCs showing
the worst results. This could be explained by the fact that
basophils not only usually are present at very low frequencies
in blood28 but also are difficult to identify with the currently
used strategies in blood cell analyzers,29,30 as supported by the
low correlation reported herein between the PENTRA 80 and
the CELL-DYN 4000 and between the PENTRA 80 and other
cell counters evaluated subsequently in our laboratory (R2 ≤
0.02; data not shown). An additional potential explanation for
these poor results could be related to the use of conventional
morphologic counts in the calibration of automated blood cell
analyzers for the enumeration of basophils in normal blood
samples.24
In addition to the aforementioned populations of WBCs
present in normal blood and according to the specifications of
the manufacturer, the PENTRA 80 also is capable of identifying 2 abnormal cell subpopulations in blood: ALYs and
LICs. In the present study, up to a total of 100 abnormal samples showing the presence of these quantitative and/or qualitative morphologic flags were analyzed in parallel by the
PENTRA 80 and the other 3 reference methods. For the ALY
counts, the correlation observed with the 3 reference methods, except flow cytometry, was low, with a relatively low
efficiency for the cutoff values used for flagging. This could
be explained because the limit of detection for this subpopulation is rather low (>3.5%), and probably some normal large
granular lymphocytes might be identified in the ALY flag.
Also by optical microscopy, the limit to identify atypical lymphocytes usually is higher (≥7%)31; thus, some samples
flagged by the PENTRA 80 are not considered abnormal by
optical microscopy. However, a detailed analysis of our
results shows that the PENTRA 80 overestimated the ALY
counts compared with the reference methods. This could be
related to the relatively arbitrary algorithms established in the
cell counters for the distinction between normal and atypical
lymphocytes.31-33 In fact, in several abnormal samples we
observed this morphologic flag, but no atypical lymphocytes
could be detected by optical microscopy or by flow cytometry (data not shown). In this sense, our results suggest that by
increasing the flagging cutoff values for ALYs, the efficiency
of the PENTRA 80 could be improved significantly but at the
expense of sensitivity.
It is interesting that relatively good correlation was
observed for the percentage of LICs found with the PENTRA
80 and all 3 reference methods. Despite this, the degree of
agreement observed for individual samples was acceptable
only for the comparisons of the number of LICs obtained
with the PENTRA 80 and flow cytometric immunophenotyping. The cutoff values selected in our study as showing the
highest efficiency displayed only slight improvement compared with those currently used by the PENTRA 80 instrument
(data not shown). However, it should noted that the inability to
distinguish LICs corresponding to blasts from immature granulocytes might be a limitation of this instrument.
Our results showed good performance of the 5-part
leukocyte differential blood cell analyses by the PENTRA 80,
especially for the enumeration of neutrophils, lymphocytes,
and eosinophils (performance was lower for monocytes and
poor for basophils). In addition, the PENTRA 80 also showed
good performance for the detection of LICs (promyelocytes,
myelocytes, metamyelocytes, and blasts) but was less effective for the identification of ALYs in relatively low frequencies
in abnormal PB samples.
From the 1General Cytometry Service, Cancer Research Center
and Department of Medicine, University of Salamanca; and
2Research Unit and 3Hematology Service, University Hospital of
Salamanca, Salamanca, Spain.
Supported by a grant from the Ministry of Science and
Technology (Ramón y Cajal Program), Madrid, Spain (Dr
Tabernero).
Address reprint requests to Dr Orfao: Servicio General de
Citometría. Laboratorio de Hematología, Hospital Universitario
Salamanca, Paseo San Vicente, 58-182, 37007 Salamanca, Spain.
Acknowledgments: We thank ABX Diagnostics Iberica Group,
Madrid, Spain, and ABX Diagnostics Group, Montpellier, France,
for their support with equipment (PENTRA 80) for this study.
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© American Society for Clinical Pathology