Corrected Lymphocyte Percentages Reduce the Differences in Absolute CD4+ T Lymphocyte Counts between Dual-Platform and Single-Platform Flow Cytometric Approaches

Corrected Lymphocyte Percentages Reduce the Differences in Absolute CD4+ T Lymphocyte Counts... Abstract Objective To determine whether a corrected lymphocyte percentage could reduce bias in the absolute cluster of differentiation (CD)4+ T lymphocyte counts obtained via dual-platform (DP) vs standard single-platform (SP) flow cytometry. Methods The correction factor (CF) for the lymphocyte percentages was calculated at 6 laboratories. The absolute CD4+ T lymphocyte counts in 300 blood specimens infected with human immunodeficiency virus (HIV) were determined using the DP and SP methods. Results Applying the CFs revealed that 4 sites showed a decrease in the mean bias of absolute CD4+ T lymphocyte counts determined via DP vs standard SP (−109 vs −84 cells/μL, −80 vs −58 cells/μL, −52 vs −45 cells/μL, and −32 vs 1 cells/μL). However, 2 participating laboratories revealed an increase in the difference of the mean bias (−42 vs −49 cells/μL and −20 vs −69 cells/μL). Conclusions Use of the corrected lymphocyte percentage shows potential for decreasing the difference in CD4 counts between DP and the standard SP method. flow cytometry, CD4 count, variability acquired immunodeficiency syndrome, single platform, dual platform The measurement of cluster of differentiation (CD)4+ T lymphocyte counts is particularly relevant in dealing with human immunodeficiency virus (HIV) infections. Recent guidelines recommend the initiation of antiretroviral therapy (ART) immediately after diagnosis of infection, irrespective of CD4 counts. However, the absolute CD4 T lymphocyte count is still necessary for the assessment of immunocompetence in individuals infected with and treated for HIV infection, and for monitoring the effectiveness of ART.1–3 Currently, flow cytometry is the most accepted standard technique for CD4+ T lymphocyte counting due to its accuracy, precision, and reproducibility. Further, flow cytometry remains the first choice if a large throughput of specimens is required.4–6 Absolute CD4+ T lymphocyte counts can be performed using single-platform (SP) or dual-platform (DP) flow cytometric testing. The SP method provides absolute CD4+ T lymphocyte counts directly, without the need for a hematology cell counter. This end can be achieved by counting the CD4+ T lymphocytes in a precisely determined blood-specimen volume or by adding a known number of reference microbeads in the lyophilized or liquid form admixed to a known volume of CD4 immunostained blood specimens. Considered more reliable and reproducible than the DP method, the SP method is known to be the preferred approach in an increasing number of laboratories.7–9 However, the SP method is expensive, compared with the DP method. An additional cost of US$5 to US$6 (local price) for the reference microbeads prevents the SP bead-based approach from being used in many resource-limited countries, including Thailand and India.7 For the DP method, the total white blood cell (WBC) counts and lymphocyte percentages are determined using an automated hematology cell counter. An absolute CD4+ T lymphocyte count is then derived by multiplying the absolute lymphocyte count by the percentage of CD4+ T lymphocytes obtained via flow cytometric testing. The DP method is affordable for absolute CD4+ T lymphocyte counting; however, it shows higher variability in absolute CD4+ T lymphocyte counts than does the SP method.10–13 In an individual patient follow-up study, the absolute CD4+ T lymphocyte counts obtained with the DP method contributed to more variability than the CD4+ T lymphocyte percentage values (20% to 33% within the Pearson coefficient of variation [CV] vs a CV of 10% to 16% when using the SP method). Previous investigations12–14 have indicated that the major source of this variability is the unmatched lymphocyte count due to the use of different automated hematology cell counters. To reduce this variability, a study4 suggests using CD45/side scatter (SSC) gating to determine the percentage of lymphocytes. However, another study that evaluated methods for absolute CD4+ T lymphocyte counting suggested that the reason for the bias between the SP and the DP methods is not improper lymphocyte gating or measuring of lymphocytes using a hematology cell counter.15 Although the sources of this variation remain inconclusive, these investigations suggest that the bias between SP and DP is consistent. Therefore, it is necessary to develop an alternative technique to correct all data to account for the biases. The correction factor (CF) is the mathematical calculation of the true value. It is determined by dividing the expected value by the measured value. Once a CF has been determined, it can then be used for subsequent measurements using the equation T = M × C, where T is the true value, M is the measurement value, and C is the CF. The CF concept has been used in medical laboratories to calibrate variation.16–18 To our knowledge, the CF concept has not yet been applied to correct the biases between the SP and the DP methods for CD4+ T lymphocyte enumeration. Therefore, the current investigation aimed to address whether the CF for the percentage of lymphocytes could remove the differences in CD4 counts obtained via DP and SP flow cytometry. Materials and Methods Evaluation Laboratories and Cell-Counter Instrumentation We chose 6 laboratories to participate in this study, all of which were certified by the Thai National Health Security Office Program for Quality Assessment and Standardization for CD4 Testing. Two of these laboratories are affiliated with the Siriraj Hospital, Mahidol University, Bangkok, Department of Immunology and the Office for Research and Development. A third laboratory is located at the Ramathibodi Hospital, Mahidol University. The other 3 laboratories are affiliated with Taksin Hospital and Lerdsin Hospital under the Bangkok Metropolitan Administration and the Department of Medical Science from the Ministry of Public Health. The automated hematology cell counters used in each laboratory are the Sysmex XT-2000i (Sysmex Corporation), Beckman Coulter LH750 and Beckman Coulter AcT (Beckman Coulter, Inc.), and CELL-DYN 1800 and CELL-DYN 3500 (Abbott Laboratories Inc.). Two participating laboratories used the same automated cell-counter model. Each instrument was installed, run, and calibrated according to the manufacturer-provided protocol. The instrument accuracy was regularly checked using an internal standard. Patients and Blood Specimens A total of 300 patients infected with HIV were enrolled in this study. Each participating laboratory consecutively collected 50 HIV-positive blood specimens after obtaining written informed consent for the enumeration of CD4+ T lymphocyte counts. The Institutional Ethics Committees of each of the laboratories approved this study (approval number 604/2551 [EC04]). Peripheral blood specimens at various stages of HIV-1 infection were evaluated in this investigation. HIV status was validated using 2 rapid HIV-1/-2 diagnostic tests (Determine [Abbott Laboratories Inc.] and ImmunoComb II, HIV-1&2 BiSpot [Orgenics, Ltd.]). We collected 2 mL of venous blood from each patient by venipuncture into tripotassium ethylenediaminetetraacetic acid (K3EDTA)–containing tubes and processed the contents for immunophenotyping within 8 hours at each participating laboratory. All HIV-infected blood specimens were remainders from routine clinical specimens that were unlinked from identifiers. Reagents Anti–human monoclonal antibody to CD3 conjugated with fluorescein isothiocyanate (FITC), anti–human monoclonal antibody to CD4 conjugated with phycoerythrin (PE), anti–human monoclonal antibody to CD45 conjugated with peridinin-chlorophyll protein (PerCP), 10× FACS lysing solution, and TruCount were each purchased from Becton, Dickinson and Company). Phosphate-buffered saline was commercially obtained from Sigma-Aldrich Corporation. Immunophenotyping Staining of Blood Specimens The CD4+ T lymphocyte counts were enumerated using standard SP flow cytometry. Briefly, 50-μL blood specimens were incubated with 20 μL of CD3-FITC/CD4-PE/CD45-PerCP in TruCount tubes containing reference microbeads in the dark at room temperature. After 15 minutes, 450 μL of 10× FACS lysing solution was added into the tubes, which were then incubated for another 10 minutes. The stained specimens were then acquired and analyzed on a FACSCalibur flow cytometer using Multiset software (Becton, Dickinson and Company). The Multiset software automatically calculated percentage and the absolute number of CD3+/CD4+ T lymphocytes. For DP analysis, specimens were acquired and analyzed using CellQuest software (Becton, Dickinson and Company). Forward scatter and SSC were measured using a linear scale. Fluorescence (FL) signals, including FL-1, FL-2, and FL-3, were measured using a logarithmic scale. A minimum of 100,000 events was acquired. A CD45 vs SSC-H dot plot was used to identify the total WBC count. The gated lymphocytes were displayed on a CD3 vs CD4 dot plot to determine the CD4+ T lymphocyte percentage. The absolute numbers of CD4+ T lymphocytes were calculated using the following formula: CD4+ T lymphocytes (cells/μL) = total WBC count (cells/μL) × lymphocyte percentage (%) × CD4+ T lymphocyte percentage (%). Data detailing the total WBCs and lymphocyte percentages were obtained with an automated cell counter. All laboratories used a FACSCalibur flow cytometer (Becton, Dickinson and Company). Calculation of Correction Factors for Lymphocyte Percentage The flow cytometry determination of percentages of lymphocytes is illustrated in Figure 1. The lymphocyte percentage was calculated using the following formula: lymphocyte percentage = (events total WBCs [R1] in total lymphocytes [R2] / events of lymphocytes in R1) × 100. Afterward, the CF for each automated cell counter was calculated by dividing the average lymphocyte percentage obtained from flow cytometric testing with the average lymphocyte percentage obtained using the automated hematology cell counter. Figure 1 View largeDownload slide Flow cytometry determination of the percentage of lymphocytes. Total white blood cells (R1) and total lymphocytes (R2) in the nonrectangular region are identified on a cluster of differentiation (CD)45 vs side-scatter (SSC) dot plot. PerCP indicates peridinin-chlorophyll protein. Figure 1 View largeDownload slide Flow cytometry determination of the percentage of lymphocytes. Total white blood cells (R1) and total lymphocytes (R2) in the nonrectangular region are identified on a cluster of differentiation (CD)45 vs side-scatter (SSC) dot plot. PerCP indicates peridinin-chlorophyll protein. Statistical Analysis We analyzed and graphed the data using Graphpad Prism software (GraphPad Software). For reporting the assay variability, the mean, SD, and CV were calculated. Linear regression was used to calculate the correlation coefficients (r2) and to determine the relationship between the different methods. Bland-Altman analysis was used for assessing the agreement between the 2 methods; results were expressed as the mean bias (mean) and limit of agreement (LOA).19 Results Variability of Automated Hematologic Cell Counters We first examined the variation of 6 automated hematologic cell counters used in the current study. Five stabilized whole-blood preparations from CD-Chex Plus (Streck, Inc) were used. Aliquots of these commercially internal quality control (IQC)–stabilized blood specimens were sent to the participating laboratories. These specimens were analyzed using an automated hematology cell counter to determine the total WBC count, lymphocyte percentage, and absolute lymphocyte count for 10 consecutive days. An average CV of these parameters was calculated for each specimen across the 6 automated cell counters. For confidentiality of the performance results from each laboratory, participating laboratories were identified as Labs A, B, C, D, E, and F. The results demonstrated that the CV of lymphocyte percentage (18.73%–97.81%) and the calculated absolute numbers of lymphocytes (19.32%–97.92%) were higher than total WBC counts (2.4%–13.31%). Calculation of Correction Factor for Lymphocyte Percentage To calculate the CF for the lymphocyte percentage, 120 blood specimens from patients who tested HIV positive and who had CD4+ T lymphocyte counts of 1 to 1200 cells per μL were evaluated and analyzed for lymphocyte percentage using an automated hematology cell counter and flow cytometer, as previously described herein. The results showed that the CFs for the lymphocyte percentage of each hematology cell counter were 1.05, 1.05, 0.98, 1.01, 1.1, and 0.9, for Labs A, B, C, D, E, and F, respectively. Calculated Correction Factor for Determining the Absolute Numbers of CD4+ T Lymphocytes We conducted a further experiment to evaluate the use of the calculated CFs for determining the absolute CD4+ T lymphocyte count. A total of 300 blood specimens were collected from patients with HIV seropositivity patients at the 6 laboratories participating in the study. Our regression analysis of the absolute CD4+ T lymphocyte counts obtained from the 6 participating laboratories (Figure 2) showed excellent correlation, with r2 of 0.95 to 0.98 between DP and standard SP. Similarly, the absolute CD4+ T lymphocyte counts showed high correlation, with r2 of 0.95 to 0.98 between DP with CF and the standard SP. Among the 6 participating laboratories, 4 sites showed a decrease in the differences of mean bias (−109 vs −84 cells/μL, −80 vs −58 cells/μL, −52 vs −45 cells/μL, and −32 cells vs 1 cell/μL) However, data from 2 laboratories showed an increase in the difference of mean bias (−42 vs −49 cells/μL and −20 vs −69 cells/μL). Figure 2 View largeDownload slide Comparison of Bland-Altman plots of cluster of differentiation (CD)4+ T lymphocyte count between dual platform (DP) versus single platform (SP) and DP–correction factor (CF) versus SP in performance results from Labs A, B, C, D, E, and F. The numbers indicate the mean (SD) bias and the limit of agreement (LOA). The dotted lines correspond to a 0 difference. Figure 2 View largeDownload slide Comparison of Bland-Altman plots of cluster of differentiation (CD)4+ T lymphocyte count between dual platform (DP) versus single platform (SP) and DP–correction factor (CF) versus SP in performance results from Labs A, B, C, D, E, and F. The numbers indicate the mean (SD) bias and the limit of agreement (LOA). The dotted lines correspond to a 0 difference. To assess whether the CF improved the accuracy of CD4+ T lymphocyte counts with an absolute value below 350 cells per μL, all data from 6 laboratories were pooled. Specimens in which the absolute CD4+ T lymphocyte count was as high as 350 cells per μL were then selected for regression and Bland-Altman analysis (Figure 3). Our results showed good correlation between DP and standard SP, with r2 of 0.92 (y = 1x + 10; P <.001). Similarly, DP with CF and the standard SP also showed good correlation, with r2 of 0.92 (y = 1x + 11; P <.001). As we expected, the use of CF decreased the differences in the mean bias of CD4+ T lymphocyte counts between DP and the standard SP approach (−18 cells/μL vs −12 cells/μL). Our data suggest that the use of CF for calculating lymphocyte percentages can reduce the discrepancy in absolute CD4+ T lymphocyte counts between DP and the standard SP method at clinically relevant levels. Figure 3 View largeDownload slide Comparison of Bland-Altman plots between dual platform (DP) and single platform (SP) and DP–correction factor (CF) versus SP of cluster of differentiation (CD)4+ T lymphocytes less than 350 cells/μL. Figure 3 View largeDownload slide Comparison of Bland-Altman plots between dual platform (DP) and single platform (SP) and DP–correction factor (CF) versus SP of cluster of differentiation (CD)4+ T lymphocytes less than 350 cells/μL. Discussion DP flow cytometry is still widely used in Thailand and other countries with poor resources due to its cost effectiveness, compatibility with external quality assurance (EQA) programs, and the availability of QC reagents.20,21 However, DP shows high variability in absolute CD4+ T lymphocyte counts, compared with standard SP. To correct this bias, we have described the use of CFs of lymphocyte percentages to reduce the variability of absolute CD4+ T lymphocyte counts determined using DP. In the first study, we attempted to characterize the analytic variability of the hematologic measurements. The results showed the high variability of the percentage of lymphocytes. Our finding was consistent with those of a previous investigation.11 This finding may be explained by the difference in the technologies and cell classification algorithms used in automated hematology cell counter designs. These instrument algorithms can result in a bias for lymphocytes and granulocytes, despite that the 2 instruments were from the same manufacturer. We consider this finding to be important because the lack of matching between the lymphocyte percentages determined by the automated hematology cell counter and the flow cytometry technique results in a variability in absolute CD4+ T lymphocyte counts determined via DP, compared with standard SP. Considering the variability of DP, replacing DP with bead-based SP has been advised in several countries to reduce the variation. This approach has been supported by the development of alternative SP instruments, and several of these instruments have been evaluated in other studies.6,22 Despite the fact that this instrument is affordable, it is still difficult to replace an existing DP with any of these new SP technologies in resource-poor settings because additional funds are required to purchase the new equipment. Also, no compatible QC reagents are available for the new SP technologies. Considering the limitations of alternative SP methods, the development of techniques to reduce the variation of DP should be considered. Recent studies16–18 have applied the concept of CF to reduce the variability in medical laboratories. We have shown, for the first time in the literature to our knowledge, that the use of CF together with DP reduces the mean bias of absolute CD4+ T lymphocyte counts, compared with standard SP. By reducing the unmatched lymphocyte percentages, the precision of absolute CD4+ T lymphocyte counts was improved to reach the level of the standard SP. This suggestion was supported by our finding that among the 6 laboratories participating in this investigation, the mean bias of the absolute CD4 T lymphocyte counts had decreased at 4 sites. Our results also revealed that the use of CF in combination with DP reduces the mean bias of absolute CD4+ lymphocyte counts when analyzing the data for CD4 of 350 cells per μL or less. Considering the importance of CD4+ T lymphocyte counts, using CFs with the DP approach can improve the reliability of CD4 counts for management of patients infected with HIV and assessment of the effectiveness of ART. Further, the use of CFs has several advantages. CF is easy to determine and is affordable for all laboratories where DP is routinely performed for the determination of absolute CD4+ T lymphocyte counts. Users do not need to change standard protocols for staining specimens and gating strategies. Another advantage is that CF values indicate the difference in the lymphocyte percentages obtained from automated hematology cell counters and flow cytometry. Recent studies23,24 have shown a number of new cell-counter technologies available on the market. Considering these technologies, CF parameters can also be used to evaluate the new hematology cell counters before implementation in the laboratory. It is important to note that at 2 laboratories, the mean bias of the CD4+ T lymphocyte counts increased. The reasons for this unexpected result are unknown; this outcome could not be explained by random errors such as pipetting errors or operator errors. Further, the instruments and pipettes used in this study were carefully calibrated according to the manufacturer-provided recommendations. One limitation of the current study is that the use of CF would not show a dramatic reduction in the bias between SP and DP. This circumstance can be explained by the fact that the automated hematology cell counters used in our investigation are well calibrated by users. The results of previous studies25,26 suggest that regularly checking the performance of an automated hematology cell counter using EQA and IQC can improve the accuracy and reliability of test results. Doing so may reduce the variation in the lymphocyte percentages and WBC counts obtained from automated hematology cell counters because excellent correlation has been found between SP and DP without CF. Further investigations should address whether application of the CF concept yields a dramatic improvement in absolute CD4 T lymphocyte counts using DP in laboratories where the QC material for the automated cell counter is difficult to access. Also, the constancy of the CF for improvement of the CD4 count by DP should also be addressed over time. In conclusion, we have shown the potential of the use of CF to reduce the differences in absolute CD4+ T lymphocyte counts between DP and standard SP flow cytometry. Improvement in the accuracy and reliability of absolute CD4+ T lymphocyte counts with the DP approach is important in the therapeutic treatment, in resource-limited settings, of patients infected with HIV. Abbreviations CD cluster of differentiation ART antiretroviral therapy HIV human immunodeficiency virus SP single-platform DP dual-platform WBC white blood cell SSC side scatter CF correction factor K3EDTA tripotassium ethylenediaminetetraacetic acid FITC fluorescein isothiocyanate PE phycoerythrin PerCP peridinin-chlorophyll protein FL fluorescence LOA limit of agreement IQC internal quality control EQA external quality assurance R1 total white blood cells R2 total lymphocytes Acknowledgments We thank the Faculty of Medicine Siriraj Hospital, Mahidol University, and the National Health Security Office, Ministry of Public Health, Thailand, for supporting this research project. This project was also supported by Thailand Research Fund (TRF) to KP. References 1. When to Start Consortium . Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies . Lancet . 2009 ; 373 ( 9672 ): 1352 – 1363 . 2. Barnett D , Walker B , Landay A , Denny TN . CD4 immunophenotyping in HIV infection . Nat Rev Microbiol . 2008 ; 6 ( 11 Suppl ): S7 – 15 . 3. Asfaw A , Ali D , Eticha T , Alemayehu A , Alemayehu M , Kindeya F . CD4 cell count trends after commencement of antiretroviral therapy among HIV-infected patients in Tigray, Northern Ethiopia: a retrospective cross-sectional study . PLoS One . 2015 ; 10 ( 3 ): e0122583 . 4. Centers for Disease Control and Prevention . 1997 revised guidelines for performing CD4+ T-cell determinations in persons infected with human immunodeficiency virus (HIV) . MMWR Recomm Rep . 1997 ; 46 ( RR-2 ): 1 – 29 . 5. Clift IC . Diagnostic flow cytometry and the AIDS pandemic . Lab Med . 2015 ; 46 ( 3 ): e59 – e64 . 6. Pattanapanyasat K . Immune status monitoring of HIV/AIDS patients in resource-limited settings: a review with an emphasis on CD4+ T-lymphocyte determination . Asian Pac J Allergy Immunol . 2012 ; 30 ( 1 ): 11 – 25 . 7. Pattanapanyasat K , Noulsri E , Lerdwana S , Sukapirom K , Onlamoon N , Tassaneetrithep B . The use of glutaraldehyde-fixed chicken red blood cells as counting beads for performing affordable single-platform CD4(+) T-lymphocyte count in HIV-1-infected patients . J Acquir Immune Defic Syndr . 2010 ; 53 ( 1 ): 47 – 54 . 8. Nantakomol D , Chanprasert S , Soogarun S , Imwong M , Ohashi J , Nuchnoi P . Affordable technology for enumeration of the absolute CD4 T-lymphocyte count by cell bead assay . Lab Med . 2010 ; 41 ( 7 ): 423 – 428 . 9. Nantakomol D , Nuchnoi P , Noulsri E , et al. Enumeration of the absolute CD4 T-lymphocyte count by cell-bead assay . Cytometry B Clin Cytom . 2010 ; 78 ( 4 ): 260 – 266 . 10. Whitby L , Granger V , Storie I , et al. Quality control of CD4+ T-lymphocyte enumeration: results from the last 9 years of the United Kingdom National External Quality Assessment Scheme for Immune Monitoring (1993-2001) . Cytometry . 2002 ; 50 ( 2 ): 102 – 110 . 11. Simson E , Groner W . Variability in absolute lymphocyte counts obtained by automated cell counters . Cytometry . 1995 ; 22 ( 1 ): 26 – 34 . 12. Giorgi JV . Characterization of T lymphocyte subset alterations by flow cytometry in HIV disease . Ann N Y Acad Sci . 1993 ; 677 : 126 – 137 . 13. Glencross D , Scott LE , Jani IV , Barnett D , Janossy G . CD45-assisted PanLeucogating for accurate, cost-effective dual-platform CD4+ T-cell enumeration . Cytometry . 2002 ; 50 ( 2 ): 69 – 77 . 14. Irani MS , Banez EI . Hematology estimation of CD4 (T-Helper) cell count using an automated hematology analyzer . Lab Med . 1990 ; 21 ( 11 ): 746 – 748 . 15. Nicholson JK , Stein D , Mui T , Mack R , Hubbard M , Denny T . Evaluation of a method for counting absolute numbers of cells with a flow cytometer . Clin Diagn Lab Immunol . 1997 ; 4 ( 3 ): 309 – 313 . 16. Mansour MM , Azzazy HM , Kazmierczak SC . Correction factors for estimating potassium concentrations in samples with in vitro hemolysis: a detriment to patient safety . Arch Pathol Lab Med . 2009 ; 133 ( 6 ): 960 – 966 . 17. Burnett RW , Noonan DC . Calculations and correction factors used in determination of blood pH and blood gases . Clin Chem . 1974 ; 20 ( 12 ): 1499 – 1506 . 18. Pai SH , Cyr-Manthey M . Effects of hemolysis on chemistry tests . Lab Med . 1991 ; 22 ( 6 ): 408 – 410 . 19. Bland JM , Altman DG . Statistical methods for assessing agreement between two methods of clinical measurement . Lancet . 1986 ; 1 ( 8476 ): 307 – 310 . 20. Noulsri E , Lerdwana S , Pattanapanyasat K . Long-term external quality assessment program for CD4+ T-lymphocyte enumeration in Thailand . Accredit Qual Assur . 2016 ; 21 ( 5 ): 367 – 375 . 21. Noulsri E , Pattanapanyasat K . Guidelines for organizing national external quality assessment scheme for performing CD4+ T-lymphocyte determinations in persons infected with HIV in resource-limited settings . Accredit Qual Assur . 2015 ; 20 ( 6 ): 511 – 518 . 22. Glynn MT , Kinahan DJ , Ducrée J . CD4 counting technologies for HIV therapy monitoring in resource-poor settings–state-of-the-art and emerging microtechnologies . Lab Chip . 2013 ; 13 ( 14 ): 2731 – 2748 . 23. Green R , Wachsmann-Hogiu S . Development, history, and future of automated cell counters . Clin Lab Med . 2015 ; 35 ( 1 ): 1 – 10 . 24. Chabot-Richards DS , George TI . White blood cell counts: reference methodology . Clin Lab Med . 2015 ; 35 ( 1 ): 11 – 24 . 25. Buttarello M , Plebani M . Automated blood cell counts: state of the art . Am J Clin Pathol . 2008 ; 130 ( 1 ): 104 – 116 . 26. Buttarello M , Gadotti M , Lorenz C , et al. Evaluation of four automated hematology analyzers. A comparative study of differential counts (imprecision and inaccuracy) . Am J Clin Pathol . 1992 ; 97 ( 3 ): 345 – 352 . © American Society for Clinical Pathology 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Laboratory Medicine Oxford University Press

Corrected Lymphocyte Percentages Reduce the Differences in Absolute CD4+ T Lymphocyte Counts between Dual-Platform and Single-Platform Flow Cytometric Approaches

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Abstract

Abstract Objective To determine whether a corrected lymphocyte percentage could reduce bias in the absolute cluster of differentiation (CD)4+ T lymphocyte counts obtained via dual-platform (DP) vs standard single-platform (SP) flow cytometry. Methods The correction factor (CF) for the lymphocyte percentages was calculated at 6 laboratories. The absolute CD4+ T lymphocyte counts in 300 blood specimens infected with human immunodeficiency virus (HIV) were determined using the DP and SP methods. Results Applying the CFs revealed that 4 sites showed a decrease in the mean bias of absolute CD4+ T lymphocyte counts determined via DP vs standard SP (−109 vs −84 cells/μL, −80 vs −58 cells/μL, −52 vs −45 cells/μL, and −32 vs 1 cells/μL). However, 2 participating laboratories revealed an increase in the difference of the mean bias (−42 vs −49 cells/μL and −20 vs −69 cells/μL). Conclusions Use of the corrected lymphocyte percentage shows potential for decreasing the difference in CD4 counts between DP and the standard SP method. flow cytometry, CD4 count, variability acquired immunodeficiency syndrome, single platform, dual platform The measurement of cluster of differentiation (CD)4+ T lymphocyte counts is particularly relevant in dealing with human immunodeficiency virus (HIV) infections. Recent guidelines recommend the initiation of antiretroviral therapy (ART) immediately after diagnosis of infection, irrespective of CD4 counts. However, the absolute CD4 T lymphocyte count is still necessary for the assessment of immunocompetence in individuals infected with and treated for HIV infection, and for monitoring the effectiveness of ART.1–3 Currently, flow cytometry is the most accepted standard technique for CD4+ T lymphocyte counting due to its accuracy, precision, and reproducibility. Further, flow cytometry remains the first choice if a large throughput of specimens is required.4–6 Absolute CD4+ T lymphocyte counts can be performed using single-platform (SP) or dual-platform (DP) flow cytometric testing. The SP method provides absolute CD4+ T lymphocyte counts directly, without the need for a hematology cell counter. This end can be achieved by counting the CD4+ T lymphocytes in a precisely determined blood-specimen volume or by adding a known number of reference microbeads in the lyophilized or liquid form admixed to a known volume of CD4 immunostained blood specimens. Considered more reliable and reproducible than the DP method, the SP method is known to be the preferred approach in an increasing number of laboratories.7–9 However, the SP method is expensive, compared with the DP method. An additional cost of US$5 to US$6 (local price) for the reference microbeads prevents the SP bead-based approach from being used in many resource-limited countries, including Thailand and India.7 For the DP method, the total white blood cell (WBC) counts and lymphocyte percentages are determined using an automated hematology cell counter. An absolute CD4+ T lymphocyte count is then derived by multiplying the absolute lymphocyte count by the percentage of CD4+ T lymphocytes obtained via flow cytometric testing. The DP method is affordable for absolute CD4+ T lymphocyte counting; however, it shows higher variability in absolute CD4+ T lymphocyte counts than does the SP method.10–13 In an individual patient follow-up study, the absolute CD4+ T lymphocyte counts obtained with the DP method contributed to more variability than the CD4+ T lymphocyte percentage values (20% to 33% within the Pearson coefficient of variation [CV] vs a CV of 10% to 16% when using the SP method). Previous investigations12–14 have indicated that the major source of this variability is the unmatched lymphocyte count due to the use of different automated hematology cell counters. To reduce this variability, a study4 suggests using CD45/side scatter (SSC) gating to determine the percentage of lymphocytes. However, another study that evaluated methods for absolute CD4+ T lymphocyte counting suggested that the reason for the bias between the SP and the DP methods is not improper lymphocyte gating or measuring of lymphocytes using a hematology cell counter.15 Although the sources of this variation remain inconclusive, these investigations suggest that the bias between SP and DP is consistent. Therefore, it is necessary to develop an alternative technique to correct all data to account for the biases. The correction factor (CF) is the mathematical calculation of the true value. It is determined by dividing the expected value by the measured value. Once a CF has been determined, it can then be used for subsequent measurements using the equation T = M × C, where T is the true value, M is the measurement value, and C is the CF. The CF concept has been used in medical laboratories to calibrate variation.16–18 To our knowledge, the CF concept has not yet been applied to correct the biases between the SP and the DP methods for CD4+ T lymphocyte enumeration. Therefore, the current investigation aimed to address whether the CF for the percentage of lymphocytes could remove the differences in CD4 counts obtained via DP and SP flow cytometry. Materials and Methods Evaluation Laboratories and Cell-Counter Instrumentation We chose 6 laboratories to participate in this study, all of which were certified by the Thai National Health Security Office Program for Quality Assessment and Standardization for CD4 Testing. Two of these laboratories are affiliated with the Siriraj Hospital, Mahidol University, Bangkok, Department of Immunology and the Office for Research and Development. A third laboratory is located at the Ramathibodi Hospital, Mahidol University. The other 3 laboratories are affiliated with Taksin Hospital and Lerdsin Hospital under the Bangkok Metropolitan Administration and the Department of Medical Science from the Ministry of Public Health. The automated hematology cell counters used in each laboratory are the Sysmex XT-2000i (Sysmex Corporation), Beckman Coulter LH750 and Beckman Coulter AcT (Beckman Coulter, Inc.), and CELL-DYN 1800 and CELL-DYN 3500 (Abbott Laboratories Inc.). Two participating laboratories used the same automated cell-counter model. Each instrument was installed, run, and calibrated according to the manufacturer-provided protocol. The instrument accuracy was regularly checked using an internal standard. Patients and Blood Specimens A total of 300 patients infected with HIV were enrolled in this study. Each participating laboratory consecutively collected 50 HIV-positive blood specimens after obtaining written informed consent for the enumeration of CD4+ T lymphocyte counts. The Institutional Ethics Committees of each of the laboratories approved this study (approval number 604/2551 [EC04]). Peripheral blood specimens at various stages of HIV-1 infection were evaluated in this investigation. HIV status was validated using 2 rapid HIV-1/-2 diagnostic tests (Determine [Abbott Laboratories Inc.] and ImmunoComb II, HIV-1&2 BiSpot [Orgenics, Ltd.]). We collected 2 mL of venous blood from each patient by venipuncture into tripotassium ethylenediaminetetraacetic acid (K3EDTA)–containing tubes and processed the contents for immunophenotyping within 8 hours at each participating laboratory. All HIV-infected blood specimens were remainders from routine clinical specimens that were unlinked from identifiers. Reagents Anti–human monoclonal antibody to CD3 conjugated with fluorescein isothiocyanate (FITC), anti–human monoclonal antibody to CD4 conjugated with phycoerythrin (PE), anti–human monoclonal antibody to CD45 conjugated with peridinin-chlorophyll protein (PerCP), 10× FACS lysing solution, and TruCount were each purchased from Becton, Dickinson and Company). Phosphate-buffered saline was commercially obtained from Sigma-Aldrich Corporation. Immunophenotyping Staining of Blood Specimens The CD4+ T lymphocyte counts were enumerated using standard SP flow cytometry. Briefly, 50-μL blood specimens were incubated with 20 μL of CD3-FITC/CD4-PE/CD45-PerCP in TruCount tubes containing reference microbeads in the dark at room temperature. After 15 minutes, 450 μL of 10× FACS lysing solution was added into the tubes, which were then incubated for another 10 minutes. The stained specimens were then acquired and analyzed on a FACSCalibur flow cytometer using Multiset software (Becton, Dickinson and Company). The Multiset software automatically calculated percentage and the absolute number of CD3+/CD4+ T lymphocytes. For DP analysis, specimens were acquired and analyzed using CellQuest software (Becton, Dickinson and Company). Forward scatter and SSC were measured using a linear scale. Fluorescence (FL) signals, including FL-1, FL-2, and FL-3, were measured using a logarithmic scale. A minimum of 100,000 events was acquired. A CD45 vs SSC-H dot plot was used to identify the total WBC count. The gated lymphocytes were displayed on a CD3 vs CD4 dot plot to determine the CD4+ T lymphocyte percentage. The absolute numbers of CD4+ T lymphocytes were calculated using the following formula: CD4+ T lymphocytes (cells/μL) = total WBC count (cells/μL) × lymphocyte percentage (%) × CD4+ T lymphocyte percentage (%). Data detailing the total WBCs and lymphocyte percentages were obtained with an automated cell counter. All laboratories used a FACSCalibur flow cytometer (Becton, Dickinson and Company). Calculation of Correction Factors for Lymphocyte Percentage The flow cytometry determination of percentages of lymphocytes is illustrated in Figure 1. The lymphocyte percentage was calculated using the following formula: lymphocyte percentage = (events total WBCs [R1] in total lymphocytes [R2] / events of lymphocytes in R1) × 100. Afterward, the CF for each automated cell counter was calculated by dividing the average lymphocyte percentage obtained from flow cytometric testing with the average lymphocyte percentage obtained using the automated hematology cell counter. Figure 1 View largeDownload slide Flow cytometry determination of the percentage of lymphocytes. Total white blood cells (R1) and total lymphocytes (R2) in the nonrectangular region are identified on a cluster of differentiation (CD)45 vs side-scatter (SSC) dot plot. PerCP indicates peridinin-chlorophyll protein. Figure 1 View largeDownload slide Flow cytometry determination of the percentage of lymphocytes. Total white blood cells (R1) and total lymphocytes (R2) in the nonrectangular region are identified on a cluster of differentiation (CD)45 vs side-scatter (SSC) dot plot. PerCP indicates peridinin-chlorophyll protein. Statistical Analysis We analyzed and graphed the data using Graphpad Prism software (GraphPad Software). For reporting the assay variability, the mean, SD, and CV were calculated. Linear regression was used to calculate the correlation coefficients (r2) and to determine the relationship between the different methods. Bland-Altman analysis was used for assessing the agreement between the 2 methods; results were expressed as the mean bias (mean) and limit of agreement (LOA).19 Results Variability of Automated Hematologic Cell Counters We first examined the variation of 6 automated hematologic cell counters used in the current study. Five stabilized whole-blood preparations from CD-Chex Plus (Streck, Inc) were used. Aliquots of these commercially internal quality control (IQC)–stabilized blood specimens were sent to the participating laboratories. These specimens were analyzed using an automated hematology cell counter to determine the total WBC count, lymphocyte percentage, and absolute lymphocyte count for 10 consecutive days. An average CV of these parameters was calculated for each specimen across the 6 automated cell counters. For confidentiality of the performance results from each laboratory, participating laboratories were identified as Labs A, B, C, D, E, and F. The results demonstrated that the CV of lymphocyte percentage (18.73%–97.81%) and the calculated absolute numbers of lymphocytes (19.32%–97.92%) were higher than total WBC counts (2.4%–13.31%). Calculation of Correction Factor for Lymphocyte Percentage To calculate the CF for the lymphocyte percentage, 120 blood specimens from patients who tested HIV positive and who had CD4+ T lymphocyte counts of 1 to 1200 cells per μL were evaluated and analyzed for lymphocyte percentage using an automated hematology cell counter and flow cytometer, as previously described herein. The results showed that the CFs for the lymphocyte percentage of each hematology cell counter were 1.05, 1.05, 0.98, 1.01, 1.1, and 0.9, for Labs A, B, C, D, E, and F, respectively. Calculated Correction Factor for Determining the Absolute Numbers of CD4+ T Lymphocytes We conducted a further experiment to evaluate the use of the calculated CFs for determining the absolute CD4+ T lymphocyte count. A total of 300 blood specimens were collected from patients with HIV seropositivity patients at the 6 laboratories participating in the study. Our regression analysis of the absolute CD4+ T lymphocyte counts obtained from the 6 participating laboratories (Figure 2) showed excellent correlation, with r2 of 0.95 to 0.98 between DP and standard SP. Similarly, the absolute CD4+ T lymphocyte counts showed high correlation, with r2 of 0.95 to 0.98 between DP with CF and the standard SP. Among the 6 participating laboratories, 4 sites showed a decrease in the differences of mean bias (−109 vs −84 cells/μL, −80 vs −58 cells/μL, −52 vs −45 cells/μL, and −32 cells vs 1 cell/μL) However, data from 2 laboratories showed an increase in the difference of mean bias (−42 vs −49 cells/μL and −20 vs −69 cells/μL). Figure 2 View largeDownload slide Comparison of Bland-Altman plots of cluster of differentiation (CD)4+ T lymphocyte count between dual platform (DP) versus single platform (SP) and DP–correction factor (CF) versus SP in performance results from Labs A, B, C, D, E, and F. The numbers indicate the mean (SD) bias and the limit of agreement (LOA). The dotted lines correspond to a 0 difference. Figure 2 View largeDownload slide Comparison of Bland-Altman plots of cluster of differentiation (CD)4+ T lymphocyte count between dual platform (DP) versus single platform (SP) and DP–correction factor (CF) versus SP in performance results from Labs A, B, C, D, E, and F. The numbers indicate the mean (SD) bias and the limit of agreement (LOA). The dotted lines correspond to a 0 difference. To assess whether the CF improved the accuracy of CD4+ T lymphocyte counts with an absolute value below 350 cells per μL, all data from 6 laboratories were pooled. Specimens in which the absolute CD4+ T lymphocyte count was as high as 350 cells per μL were then selected for regression and Bland-Altman analysis (Figure 3). Our results showed good correlation between DP and standard SP, with r2 of 0.92 (y = 1x + 10; P <.001). Similarly, DP with CF and the standard SP also showed good correlation, with r2 of 0.92 (y = 1x + 11; P <.001). As we expected, the use of CF decreased the differences in the mean bias of CD4+ T lymphocyte counts between DP and the standard SP approach (−18 cells/μL vs −12 cells/μL). Our data suggest that the use of CF for calculating lymphocyte percentages can reduce the discrepancy in absolute CD4+ T lymphocyte counts between DP and the standard SP method at clinically relevant levels. Figure 3 View largeDownload slide Comparison of Bland-Altman plots between dual platform (DP) and single platform (SP) and DP–correction factor (CF) versus SP of cluster of differentiation (CD)4+ T lymphocytes less than 350 cells/μL. Figure 3 View largeDownload slide Comparison of Bland-Altman plots between dual platform (DP) and single platform (SP) and DP–correction factor (CF) versus SP of cluster of differentiation (CD)4+ T lymphocytes less than 350 cells/μL. Discussion DP flow cytometry is still widely used in Thailand and other countries with poor resources due to its cost effectiveness, compatibility with external quality assurance (EQA) programs, and the availability of QC reagents.20,21 However, DP shows high variability in absolute CD4+ T lymphocyte counts, compared with standard SP. To correct this bias, we have described the use of CFs of lymphocyte percentages to reduce the variability of absolute CD4+ T lymphocyte counts determined using DP. In the first study, we attempted to characterize the analytic variability of the hematologic measurements. The results showed the high variability of the percentage of lymphocytes. Our finding was consistent with those of a previous investigation.11 This finding may be explained by the difference in the technologies and cell classification algorithms used in automated hematology cell counter designs. These instrument algorithms can result in a bias for lymphocytes and granulocytes, despite that the 2 instruments were from the same manufacturer. We consider this finding to be important because the lack of matching between the lymphocyte percentages determined by the automated hematology cell counter and the flow cytometry technique results in a variability in absolute CD4+ T lymphocyte counts determined via DP, compared with standard SP. Considering the variability of DP, replacing DP with bead-based SP has been advised in several countries to reduce the variation. This approach has been supported by the development of alternative SP instruments, and several of these instruments have been evaluated in other studies.6,22 Despite the fact that this instrument is affordable, it is still difficult to replace an existing DP with any of these new SP technologies in resource-poor settings because additional funds are required to purchase the new equipment. Also, no compatible QC reagents are available for the new SP technologies. Considering the limitations of alternative SP methods, the development of techniques to reduce the variation of DP should be considered. Recent studies16–18 have applied the concept of CF to reduce the variability in medical laboratories. We have shown, for the first time in the literature to our knowledge, that the use of CF together with DP reduces the mean bias of absolute CD4+ T lymphocyte counts, compared with standard SP. By reducing the unmatched lymphocyte percentages, the precision of absolute CD4+ T lymphocyte counts was improved to reach the level of the standard SP. This suggestion was supported by our finding that among the 6 laboratories participating in this investigation, the mean bias of the absolute CD4 T lymphocyte counts had decreased at 4 sites. Our results also revealed that the use of CF in combination with DP reduces the mean bias of absolute CD4+ lymphocyte counts when analyzing the data for CD4 of 350 cells per μL or less. Considering the importance of CD4+ T lymphocyte counts, using CFs with the DP approach can improve the reliability of CD4 counts for management of patients infected with HIV and assessment of the effectiveness of ART. Further, the use of CFs has several advantages. CF is easy to determine and is affordable for all laboratories where DP is routinely performed for the determination of absolute CD4+ T lymphocyte counts. Users do not need to change standard protocols for staining specimens and gating strategies. Another advantage is that CF values indicate the difference in the lymphocyte percentages obtained from automated hematology cell counters and flow cytometry. Recent studies23,24 have shown a number of new cell-counter technologies available on the market. Considering these technologies, CF parameters can also be used to evaluate the new hematology cell counters before implementation in the laboratory. It is important to note that at 2 laboratories, the mean bias of the CD4+ T lymphocyte counts increased. The reasons for this unexpected result are unknown; this outcome could not be explained by random errors such as pipetting errors or operator errors. Further, the instruments and pipettes used in this study were carefully calibrated according to the manufacturer-provided recommendations. One limitation of the current study is that the use of CF would not show a dramatic reduction in the bias between SP and DP. This circumstance can be explained by the fact that the automated hematology cell counters used in our investigation are well calibrated by users. The results of previous studies25,26 suggest that regularly checking the performance of an automated hematology cell counter using EQA and IQC can improve the accuracy and reliability of test results. Doing so may reduce the variation in the lymphocyte percentages and WBC counts obtained from automated hematology cell counters because excellent correlation has been found between SP and DP without CF. Further investigations should address whether application of the CF concept yields a dramatic improvement in absolute CD4 T lymphocyte counts using DP in laboratories where the QC material for the automated cell counter is difficult to access. Also, the constancy of the CF for improvement of the CD4 count by DP should also be addressed over time. In conclusion, we have shown the potential of the use of CF to reduce the differences in absolute CD4+ T lymphocyte counts between DP and standard SP flow cytometry. Improvement in the accuracy and reliability of absolute CD4+ T lymphocyte counts with the DP approach is important in the therapeutic treatment, in resource-limited settings, of patients infected with HIV. Abbreviations CD cluster of differentiation ART antiretroviral therapy HIV human immunodeficiency virus SP single-platform DP dual-platform WBC white blood cell SSC side scatter CF correction factor K3EDTA tripotassium ethylenediaminetetraacetic acid FITC fluorescein isothiocyanate PE phycoerythrin PerCP peridinin-chlorophyll protein FL fluorescence LOA limit of agreement IQC internal quality control EQA external quality assurance R1 total white blood cells R2 total lymphocytes Acknowledgments We thank the Faculty of Medicine Siriraj Hospital, Mahidol University, and the National Health Security Office, Ministry of Public Health, Thailand, for supporting this research project. This project was also supported by Thailand Research Fund (TRF) to KP. References 1. When to Start Consortium . Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies . Lancet . 2009 ; 373 ( 9672 ): 1352 – 1363 . 2. Barnett D , Walker B , Landay A , Denny TN . CD4 immunophenotyping in HIV infection . Nat Rev Microbiol . 2008 ; 6 ( 11 Suppl ): S7 – 15 . 3. Asfaw A , Ali D , Eticha T , Alemayehu A , Alemayehu M , Kindeya F . CD4 cell count trends after commencement of antiretroviral therapy among HIV-infected patients in Tigray, Northern Ethiopia: a retrospective cross-sectional study . PLoS One . 2015 ; 10 ( 3 ): e0122583 . 4. Centers for Disease Control and Prevention . 1997 revised guidelines for performing CD4+ T-cell determinations in persons infected with human immunodeficiency virus (HIV) . MMWR Recomm Rep . 1997 ; 46 ( RR-2 ): 1 – 29 . 5. Clift IC . Diagnostic flow cytometry and the AIDS pandemic . Lab Med . 2015 ; 46 ( 3 ): e59 – e64 . 6. Pattanapanyasat K . Immune status monitoring of HIV/AIDS patients in resource-limited settings: a review with an emphasis on CD4+ T-lymphocyte determination . Asian Pac J Allergy Immunol . 2012 ; 30 ( 1 ): 11 – 25 . 7. Pattanapanyasat K , Noulsri E , Lerdwana S , Sukapirom K , Onlamoon N , Tassaneetrithep B . The use of glutaraldehyde-fixed chicken red blood cells as counting beads for performing affordable single-platform CD4(+) T-lymphocyte count in HIV-1-infected patients . J Acquir Immune Defic Syndr . 2010 ; 53 ( 1 ): 47 – 54 . 8. Nantakomol D , Chanprasert S , Soogarun S , Imwong M , Ohashi J , Nuchnoi P . Affordable technology for enumeration of the absolute CD4 T-lymphocyte count by cell bead assay . Lab Med . 2010 ; 41 ( 7 ): 423 – 428 . 9. Nantakomol D , Nuchnoi P , Noulsri E , et al. Enumeration of the absolute CD4 T-lymphocyte count by cell-bead assay . Cytometry B Clin Cytom . 2010 ; 78 ( 4 ): 260 – 266 . 10. Whitby L , Granger V , Storie I , et al. Quality control of CD4+ T-lymphocyte enumeration: results from the last 9 years of the United Kingdom National External Quality Assessment Scheme for Immune Monitoring (1993-2001) . Cytometry . 2002 ; 50 ( 2 ): 102 – 110 . 11. Simson E , Groner W . Variability in absolute lymphocyte counts obtained by automated cell counters . Cytometry . 1995 ; 22 ( 1 ): 26 – 34 . 12. Giorgi JV . Characterization of T lymphocyte subset alterations by flow cytometry in HIV disease . Ann N Y Acad Sci . 1993 ; 677 : 126 – 137 . 13. Glencross D , Scott LE , Jani IV , Barnett D , Janossy G . CD45-assisted PanLeucogating for accurate, cost-effective dual-platform CD4+ T-cell enumeration . Cytometry . 2002 ; 50 ( 2 ): 69 – 77 . 14. Irani MS , Banez EI . Hematology estimation of CD4 (T-Helper) cell count using an automated hematology analyzer . Lab Med . 1990 ; 21 ( 11 ): 746 – 748 . 15. Nicholson JK , Stein D , Mui T , Mack R , Hubbard M , Denny T . Evaluation of a method for counting absolute numbers of cells with a flow cytometer . Clin Diagn Lab Immunol . 1997 ; 4 ( 3 ): 309 – 313 . 16. Mansour MM , Azzazy HM , Kazmierczak SC . Correction factors for estimating potassium concentrations in samples with in vitro hemolysis: a detriment to patient safety . Arch Pathol Lab Med . 2009 ; 133 ( 6 ): 960 – 966 . 17. Burnett RW , Noonan DC . Calculations and correction factors used in determination of blood pH and blood gases . Clin Chem . 1974 ; 20 ( 12 ): 1499 – 1506 . 18. Pai SH , Cyr-Manthey M . Effects of hemolysis on chemistry tests . Lab Med . 1991 ; 22 ( 6 ): 408 – 410 . 19. Bland JM , Altman DG . Statistical methods for assessing agreement between two methods of clinical measurement . Lancet . 1986 ; 1 ( 8476 ): 307 – 310 . 20. Noulsri E , Lerdwana S , Pattanapanyasat K . Long-term external quality assessment program for CD4+ T-lymphocyte enumeration in Thailand . Accredit Qual Assur . 2016 ; 21 ( 5 ): 367 – 375 . 21. Noulsri E , Pattanapanyasat K . Guidelines for organizing national external quality assessment scheme for performing CD4+ T-lymphocyte determinations in persons infected with HIV in resource-limited settings . Accredit Qual Assur . 2015 ; 20 ( 6 ): 511 – 518 . 22. Glynn MT , Kinahan DJ , Ducrée J . CD4 counting technologies for HIV therapy monitoring in resource-poor settings–state-of-the-art and emerging microtechnologies . Lab Chip . 2013 ; 13 ( 14 ): 2731 – 2748 . 23. Green R , Wachsmann-Hogiu S . Development, history, and future of automated cell counters . Clin Lab Med . 2015 ; 35 ( 1 ): 1 – 10 . 24. Chabot-Richards DS , George TI . White blood cell counts: reference methodology . Clin Lab Med . 2015 ; 35 ( 1 ): 11 – 24 . 25. Buttarello M , Plebani M . Automated blood cell counts: state of the art . Am J Clin Pathol . 2008 ; 130 ( 1 ): 104 – 116 . 26. Buttarello M , Gadotti M , Lorenz C , et al. Evaluation of four automated hematology analyzers. A comparative study of differential counts (imprecision and inaccuracy) . Am J Clin Pathol . 1992 ; 97 ( 3 ): 345 – 352 . © American Society for Clinical Pathology 2018. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

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Laboratory MedicineOxford University Press

Published: Mar 13, 2018

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