Some flow cytometric (FCM) immunophenotypic analyses of blood cells, like the enumeration of CD4+ T lymphocytes and CD34+ hematopoietic progenitor cells (HPC) can be now fully included in the category of quantitative assays, since a calibration curve can be set and standard reference material is available to determine a result [1]. Comprehensive guidelines for the correct analysis of such measurands are published 2], [3], [4, due to their important clinical impact, and national or international EQA/PT schemes have long been made available to assist the involved laboratorians in the routine practice.
The knowledge of the measurement uncertainty (MU) is commonplace in Clinical Chemistry, with open access tables reporting MU, Biological Variability (BV) and Total Error (TE) parameters for the majority of measurands [5, 6]. The prerequisite for the definition of these crucial performance parameters is that their expected BV is rather stable and predictable in most cases, and the acceptable, desirable and optimal levels of the total allowable imprecision can be therefore calculated using the seminal Fraser’s formulae 7], [8], [9], [10.
The BV of basic peripheral blood lymphocyte subset enumeration by FCM has been also recently estimated, thanks to the large experience on reference range studies and the overall limited quantitative percent and absolute level variations of the different subpopulations also in pathological conditions 11], [12], [13], [14.
The absolute or percent level of CD34+ HPC in peripheral blood, bone marrow and leukapheresis concentrates, on the contrary, is indeed a very peculiar measurand, posing unique methodological problems to laboratorians.
CD34+ cells have long been assumed as ‘blast equivalents’, namely normal or neoplastic cells able to generate a progeny both in vivo and in vitro. Although this assumption proved useful in the laboratory practice, it is however imprecise, since not all blasts express the CD34 antigen and not all CD34+ cells are genuine blasts, like B cell precursors (hematogones) and circulating endothelial cells.
The measurement of CD34+ cell levels by FCM has progressively assumed a great clinical and diagnostic importance, both in laboratory hematology and especially in the setting of autologous and allogeneic HPC transplantation [15].
Healthy subjects in steady-state show typically baseline levels between 0 and 10 CD34+ cells/μL, or less than 0.1 % of leukocytes in peripheral blood [16], and such levels remain remarkably stable in the absence of external stimuli, tissue repair phenomena, bone marrow regeneration or chemotherapy treatments. This measurement has put the basis for high-sensitivity FCM procedures and CD34+ cell count can be considered as the prototype of rare event analyses of clinical relevance [16]. Any evidence of CD34+ cells above 10/μL in peripheral blood may indicate that something wrong is occurring in the bone marrow hemopoietic machinery [17, 18], like myelodysplastic syndrome, myelofibrosis, myeloproliferative disorders or evolution to acute leukemias 19], [20], [21], [22], [23. In this regard, the FCM semi-quantitative assessment of CD34+ blasts in the peripheral blood or bone marrow of patients with acute leukemias remains outside the scope of true quantitative measurements.
The autologous or allogeneic HPC transplantation requires the rapid mobilization of large amounts of CD34+ cells into the peripheral blood of patients or healthy donors, and this can be accomplished thanks to the use of the clinically most relevant mobilizing agents, G-CSF (Filgrastim) and Plerixafor [24]. In good mobilizers, the absolute levels of CD34+ HPCs can raise from baseline levels up to 300 or more/μL in few days, with a great individual variability. The decision to trigger a leukapheresis procedure is made to collect as many CD34+ HPCs as possible, to provide at least 2 million HPCs per kg b.w. of the recipient [15], and this may be typically accomplished as soon as 10–20 to 50 CD34+/μL cells appear in the peripheral blood of mobilized subjects, according to local clinical policies [25].
The resulting leukapheresis bag contains a very concentrated and heterogenous mixture of peripheral blood cells, in which the final collection of CD34+ HPCs is measurable at quite variable but very high concentrations, ranging from some 500 to about 2000 or more/μL.
Not to mention the analysis of HPC in cord blood and in the thawed apheresis bags, presenting further complications, it is evident that with such diverse biological matrices and absolute level dynamics, the attempts to estimate the BV of CD34+ HPCs is a particularly challenging task. Due to the mentioned issues, it is not surprise that the CD34+ HPC level – as a measurand – lacks to date tables reporting MU, BV and TE.
The study by S. Fernández-Luis and Colleagues [26] is at present the first attempt to define the percent allowable total error (%aTE) of FCM absolute CD34+ cell counting, using data from a nationwide Spanish EQA scheme collected over the last twelve years. About 3,700 valid results were obtained from 40 laboratories that received fresh peripheral blood, cord blood or buffy-coat samples, that were analyzed by the ISHAGE method or in-house procedures, mostly by a single-platform technique.
The %aTE was calculated as the state-of-the-art (SOTA) performance of the 80th percentile of the results stratified by three increasing absolute levels of CD34+ cells/μL. As predictable, %aTE tapered from 34.4 % for the lowest level range (<15 cells/μL) to 21.1 % for the highest level (>25 cells/μL). Particular attention was paid to the risk of misclassifying patients due to measurement imprecision: this risk proved quite variable, from 0 to 40 % of cases (average about 13 %), was very dependent on the absolute CD34+ cell level, being most frequent for the lowest cell levels, and did not improve with the passing of time.
Imprecision in the absolute CD34+ cell count may mean misclassification of patients with hematological disorders, may give way to an apparent safe trigger for apheresis procedures, but doomed to the collection of insufficient amounts of CD34+ HPCs, or may give the false impression of having collected enough HPCs for transplantation. The most dangerous error in this field is indeed the overestimation of an actually inadequate HPC collection procedure, that may put patients’ life at risk for the lack of a timely and effective engraftment.
Fernández-Luis and colleagues have also highlighted that the best performing laboratories, in the upper quartile of %aTE data distribution, can show much tighter MU data than the rest of the group, indicating that a path to the continuous improvement of analytical performance up to excellence is possible with procedure standardization, education and practice also in the tricky field of CD34+ HPC enumeration.
The evaluation of %aTE is highly influenced by sample type, logistics, technology, geography and time. The strict adherence to the ISHAGE guidelines and the universal usage of single-platform FCM technique can greatly contribute to performance improvement [27]. It seems therefore likely that the pioneer findings by Fernández-Luis and colleagues may be further improved using highly standardized procedures and stabilized instead of fresh samples, as shown by very preliminary data from UKNEQAS LI exercises included in the forthcoming CLSI H63 guideline on CD34+ cell enumeration [4]. The use of stabilized samples may help to minimize the unavoidable preanalytical decay of fresh samples, surely causing some spread of %aTE calculations, and to focus the studies on MU on the purely analytical variability.
A big missing issue, however, still continues to negatively influence this field, namely the lack of EQA/PT studies using stabilized concentrated apheresis samples. As mentioned, the enumeration of the collected HPCs in leukapheresis suspensions deals with CD34+ cell levels from 50- to 200-fold higher than baseline, and HPCs are admixed to a concentrated mixture of troublesome accompanying cells, like nucleated red cells, large immature myeloid cells, apoptotic or dead cells and a lot of platelets. This final part of CD34+ HPC analysis is crucial to patients’ outcome, but is particularly prone to counting errors due to a number of preanalytical and analytical issues [28]. Unfortunately, concentrated leukapheresis preparations are hardly available for large-scale EQA/PT programs.
To conclude, the absolute enumeration of CD34+ HPC in the peripheral blood of both steady-state and mobilized subjects is a fully mature laboratory technique, for which the SOTA-based %aTE parameters can be evaluated. Ample margins for performance improvement have been demonstrated by studies on EQA/PT programs, indicating that time and practice are still needed in clinical laboratories to implement optimized quality specifications to make CD34+ cell enumeration fully compliant to ISO15189 requirements.
-
Research ethics: Not applicable.
-
Informed consent: Not applicable.
-
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
-
Use of Large Language Models, AI and Machine Learning Tools: None declared.
-
Conflict of interest: The authors state no conflict of interest.
-
Research funding: None declared.
-
Data availability: Not applicable.
References
1. Devitt, KA, Oldaker, T, Shah, K, Illingworth, A. Summary of validation considerations with real-life examples using both qualitative and semiquantitative flow cytometry assays. Cytometry B Clin Cytom 2023;104:374–91. https://doi.org/10.1002/cyto.b.22123.Search in Google Scholar PubMed
2. Kelleher, P, Greathead, L, Whitby, L, Brando, B, UK NEQAS Leucocyte Immunophenotyping Steering Committee, Barnett, D, Bloxham, D, et al.. European flow cytometry quality assurance guidelines for the diagnosis of primary immune deficiencies and assessment of immune reconstitution following B cell depletion therapies and transplantation. Cytometry B Clin Cytom 2024. https://doi.org/10.1002/cyto.b.22195.Search in Google Scholar PubMed
3. Clinical and Laboratory Standards Institute (CLSI). Enumeration of immunologically defined cell populations by flow cytometry; Approved Guideline, 2nd ed.; 2007. CLSI document H42-A2.Search in Google Scholar
4. Clinical and Laboratory Standards Institute (CLSI). CD34+ hematopoietic stem cell enumeration; Approved Guideline. CLSI document H63, in press 2025.Search in Google Scholar
5. European Federation of Clinical Chemistry and Laboratoy Medicine (EFLM). Biological variation database. https://biologicalvariation.eu [Accessed Nov 2024].Search in Google Scholar
6. Westgard, QC. CLIA acceptance limits for proficiency testing; 2024. https://westgard.com/clia-a-quality/quality-requirements/2024-clia-requirements.html [Accessed Nov 2024].Search in Google Scholar
7. Fraser, CG, Hyltoft Petersen, P, Libeer, JC, Ricos, C. Proposals for setting generally applicable quality goals solely based on biology. Ann Clin Biochem 1997;34:8–12. https://doi.org/10.1177/000456329703400103.Search in Google Scholar PubMed
8. Fraser, CG. Reference change values. Clin Chem Lab Med 2012;50:807–12. https://doi.org/10.1515/cclm.2011.733.Search in Google Scholar PubMed
9. Johnson, PR, Shahangian, S, Astles, JR. Managing biological variation data: modern approaches for study design and clinical application. Crit Rev Clin Lab Sci 2021;58:493–512. https://doi.org/10.1080/10408363.2021.1932718.Search in Google Scholar PubMed
10. Sandberg, S, Coskun, A, Carobene, A, Fernandez-Calle, P, Diaz-Garzon, J, Bartlett, WA, et al.. Analytical performance specifications based on biological variation data - considerations, strengths and limitations. Clin Chem Lab Med 2024;62:1483–9. https://doi.org/10.1515/cclm-2024-0108.Search in Google Scholar PubMed
11. Tosato, F, Bernardi, D, Sanzari, MC, Pantano, G, Plebani, M. Biological variability of lymphocyte subsets of human adults’ blood. Clin Chim Acta 2013;424:159–63. https://doi.org/10.1016/j.cca.2013.06.001.Search in Google Scholar PubMed
12. Ticchioni, M, Brouzes, C, Durrieu, F, Lambert, C, Association Française de Cytométrie accreditation working group (AFC-AG). Acceptable “Real-Life” variability for lymphocyte counts by flow cytometry. Cytometry B Clin Cytom 2019;96:379–88. https://doi.org/10.1002/cyto.b.21751.Search in Google Scholar PubMed
13. Li, C, Wang, Y, Lu, H, Du, Z, Xu, C, Peng, M. Study of total error specifications of lymphocyte subsets enumeration using China National EQAS data and Biological Variation Data Critical Appraisal Checklist (BIVAC)-compliant publications. Clin Chem Lab Med 2020;59:179–86. https://doi.org/10.1515/cclm-2020-0741.Search in Google Scholar PubMed
14. Comins-Boo, A, Pérez-Pla, F, Irure-Ventura, J, López-Hoyos, M, Blanco-Peris, L, del Carmen Martín Alonso, M, et al.. Total error in lymphocyte subpopulations by flow cytometry-based in state of the art using Spanish EQAS data. Clin Chem Lab Med 2023;62:312–21. https://doi.org/10.1515/cclm-2023-0470.Search in Google Scholar PubMed
15. Lanza, F, Marchetti, M, Zannetti, BA. Overview on novel strategies and current guidelines for hematopoietic stem cell mobilisation and collection. Transfus Apher Sci 2023;62:103830. https://doi.org/10.1016/j.transci.2023.103830.Search in Google Scholar PubMed
16. Eidenschink, L, DiZerega, G, Rodgers, K, Bartlett, M, Wells, DA, Loken, MR. Basal levels of CD34 positive cells in peripheral blood differ between individuals and are stable for 18 months. Cytometry B Clin Cytom 2012;82:18–25. https://doi.org/10.1002/cyto.b.20611.Search in Google Scholar PubMed
17. Jentzsch, M, Geus, U, Grimm, J, Vucinic, V, Pönisch, W, Franke, GN, et al.. Pretreatment CD34+/CD38− cell burden as prognostic factor in myelodysplastic syndrome patients receiving allogeneic stem cell transplantation. Biol Blood Marrow Transplant 2019;25:1560–6. https://doi.org/10.1016/j.bbmt.2019.03.022.Search in Google Scholar PubMed
18. Jelic, TM, Estalilla, OC, Vos, JA, Harvey, G, Stricker, CJ, Adelanwa, AO, et al.. Flow cytometric enumeration of peripheral blood CD34+ cells predicts bone marrow pathology in patients with less than 1% blasts by manual count. J Blood Med 2023;14:519–35. https://doi.org/10.2147/jbm.s417432.Search in Google Scholar
19. Ogata, K, Della Porta, MG, Malcovati, L, Picone, C, Yokose, N, Matsuda, A, et al.. Diagnostic utility of flow cytometry in low-grade myelodysplastic syndromes: a prospective validation study. Haematologica 2009;94:1066–74. https://doi.org/10.3324/haematol.2009.008532.Search in Google Scholar PubMed PubMed Central
20. Cesana, C, Klersy, C, Brando, B, Nosari, A, Scarpati, B, Scampini, L, et al.. Prognostic value of circulating CD34+ cells in myelodysplastic syndromes. Leuk Res 2008;32:1715–23. https://doi.org/10.1016/j.leukres.2008.03.028.Search in Google Scholar PubMed
21. Barosi, G, Campanelli, R, Catarsi, P, Abbà, C, Carolei, A, Massa, M, et al.. Type 1 CALR mutation allele frequency correlates with CD34/CXCR4 expression in myelofibrosis-type megakaryocyte dysplasia: a mechanism of disease progression? Blood Cancer J 2024;14:18. https://doi.org/10.1038/s41408-024-00991-2.Search in Google Scholar PubMed PubMed Central
22. Passamonti, F, Vanelli, L, Malabarba, L, Rumi, E, Pungolino, E, Malcovati, L, et al.. Clinical utility of the absolute number of circulating CD34-positive cells in patients with chronic myeloproliferative disorders. Haematologica 2003;88:1123–9.Search in Google Scholar
23. Luque Paz, D, Cottin, L, Lippert, E, Robin, JB, Bescond, C, Genevieve, F, et al.. Different number of circulating CD34 + cells in essential thrombocythemia, prefibrotic/early primary myelofibrosis, and overt primary myelofibrosis. Ann Hematol 2022;101:893–6. https://doi.org/10.1007/s00277-021-04672-z.Search in Google Scholar PubMed
24. Bonig, H, Papayannopoulou, T. Mobilization of hematopoietic stem/progenitor cells: general principles and molecular mechanisms. Methods Mol Biol 2012;904:1–14. https://doi.org/10.1007/978-1-61779-943-3_1.Search in Google Scholar PubMed PubMed Central
25. Makar, RS, Padmanabhan, A, Kim, HC, Anderson, C, Sugrue, MW, Linenberger, M. Use of laboratory tests to guide initiation of autologous hematopoietic progenitor cell collection by apheresis: results from the multicenter hematopoietic progenitor cell collection by Apheresis Laboratory Trigger Survey. Transfus Med Rev 2014;28:198–204. https://doi.org/10.1016/j.tmrv.2014.08.002.Search in Google Scholar PubMed
26. Fernández-Luis, S, Comins-Boo, A, Pérez-Pla, F, Irure Ventura, J, Insunza Gaminde, A, López-Hoyos, M, et al.. Allowable total error in CD34 cell analysis by flow cytometry based on state of the art using Spanish EQAS data. Clin Chem Lab Med 2025;63:367–75. https://doi.org/10.1515/cclm-2024-0956Search in Google Scholar PubMed
27. Whitby, A, Whitby, L, Fletcher, M, Reilly, JT, Sutherland, DR, Keeney, M, et al.. ISHAGE protocol: are we doing it correctly? Cytometry B Clin Cytom 2012;82:9–17. https://doi.org/10.1002/cyto.b.20612.Search in Google Scholar PubMed
28. Brando, B, GöhdeJrW, Scarpati, B, D’Avanzo, G, European Working Group on Clinical Cell Analysis. The “vanishing counting bead” phenomenon: effect on absolute CD34+ cell counting in phosphate-buffered saline-diluted leukapheresis samples. Cytometry 2001;43:154–60. https://doi.org/10.1002/1097-0320(20010201)43:2<154::aid-cyto1031>3.3.co;2-u.10.1002/1097-0320(20010201)43:2<154::AID-CYTO1031>3.3.CO;2-USearch in Google Scholar
© 2024 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Editorial
- CD34+ progenitor cells meet metrology
- Reviews
- Venous blood collection systems using evacuated tubes: a systematic review focusing on safety, efficacy and economic implications of integrated vs. combined systems
- The correlation between serum angiopoietin-2 levels and acute kidney injury (AKI): a meta-analysis
- Opinion Papers
- Advancing value-based laboratory medicine
- Clostebol and sport: about controversies involving contamination vs. doping offence
- Direct-to-consumer testing as consumer initiated testing: compromises to the testing process and opportunities for quality improvement
- Perspectives
- An improved implementation of metrological traceability concepts is needed to benefit from standardization of laboratory results
- Genetics and Molecular Diagnostics
- Comparative analysis of BCR::ABL1 p210 mRNA transcript quantification and ratio to ABL1 control gene converted to the International Scale by chip digital PCR and droplet digital PCR for monitoring patients with chronic myeloid leukemia
- General Clinical Chemistry and Laboratory Medicine
- IVDCheckR – simplifying documentation for laboratory developed tests according to IVDR requirements by introducing a new digital tool
- Analytical performance specifications for trace elements in biological fluids derived from six countries federated external quality assessment schemes over 10 years
- The effects of drone transportation on routine laboratory, immunohematology, flow cytometry and molecular analyses
- Accurate non-ceruloplasmin bound copper: a new biomarker for the assessment and monitoring of Wilson disease patients using HPLC coupled to ICP-MS/MS
- Construction of platelet count-optical method reflex test rules using Micro-RBC#, Macro-RBC%, “PLT clumps?” flag, and “PLT abnormal histogram” flag on the Mindray BC-6800plus hematology analyzer in clinical practice
- Evaluation of serum NFL, T-tau, p-tau181, p-tau217, Aβ40 and Aβ42 for the diagnosis of neurodegenerative diseases
- An immuno-DOT diagnostic assay for autoimmune nodopathy
- Evaluation of biochemical algorithms to screen dysbetalipoproteinemia in ε2ε2 and rare APOE variants carriers
- Reference Values and Biological Variations
- Allowable total error in CD34 cell analysis by flow cytometry based on state of the art using Spanish EQAS data
- Clinical utility of personalized reference intervals for CEA in the early detection of oncologic disease
- Agreement of lymphocyte subsets detection permits reference intervals transference between flow cytometry systems: direct validation using established reference intervals
- Cancer Diagnostics
- Atypical cells in urine sediment: a novel biomarker for early detection of bladder cancer
- External quality assessment-based tumor marker harmonization simulation; insights in achievable harmonization for CA 15-3 and CEA
- Cardiovascular Diseases
- Evaluation of the analytical and clinical performance of a high-sensitivity troponin I point-of-care assay in the Mersey Acute Coronary Syndrome Rule Out Study (MACROS-2)
- Analytical verification of the Atellica VTLi point of care high sensitivity troponin I assay
- Infectious Diseases
- Synovial fluid D-lactate – a pathogen-specific biomarker for septic arthritis: a prospective multicenter study
- Targeted MRM-analysis of plasma proteins in frozen whole blood samples from patients with COVID-19: a retrospective study
- Letters to the Editor
- Generative artificial intelligence (AI) for reporting the performance of laboratory biomarkers: not ready for prime time
- Urgent need to adopt age-specific TSH upper reference limit for the elderly – a position statement of the Belgian thyroid club
- Sigma metric is more correlated with analytical imprecision than bias
- Utility and limitations of monitoring kidney transplants using capillary sampling
- Simple flow cytometry method using a myeloma panel that easily reveals clonal proliferation of mature B-cells
- Is sweat conductivity still a relevant screening test for cystic fibrosis? Participation over 10 years
- Hb D-Iran interference on HbA1c measurement
Articles in the same Issue
- Frontmatter
- Editorial
- CD34+ progenitor cells meet metrology
- Reviews
- Venous blood collection systems using evacuated tubes: a systematic review focusing on safety, efficacy and economic implications of integrated vs. combined systems
- The correlation between serum angiopoietin-2 levels and acute kidney injury (AKI): a meta-analysis
- Opinion Papers
- Advancing value-based laboratory medicine
- Clostebol and sport: about controversies involving contamination vs. doping offence
- Direct-to-consumer testing as consumer initiated testing: compromises to the testing process and opportunities for quality improvement
- Perspectives
- An improved implementation of metrological traceability concepts is needed to benefit from standardization of laboratory results
- Genetics and Molecular Diagnostics
- Comparative analysis of BCR::ABL1 p210 mRNA transcript quantification and ratio to ABL1 control gene converted to the International Scale by chip digital PCR and droplet digital PCR for monitoring patients with chronic myeloid leukemia
- General Clinical Chemistry and Laboratory Medicine
- IVDCheckR – simplifying documentation for laboratory developed tests according to IVDR requirements by introducing a new digital tool
- Analytical performance specifications for trace elements in biological fluids derived from six countries federated external quality assessment schemes over 10 years
- The effects of drone transportation on routine laboratory, immunohematology, flow cytometry and molecular analyses
- Accurate non-ceruloplasmin bound copper: a new biomarker for the assessment and monitoring of Wilson disease patients using HPLC coupled to ICP-MS/MS
- Construction of platelet count-optical method reflex test rules using Micro-RBC#, Macro-RBC%, “PLT clumps?” flag, and “PLT abnormal histogram” flag on the Mindray BC-6800plus hematology analyzer in clinical practice
- Evaluation of serum NFL, T-tau, p-tau181, p-tau217, Aβ40 and Aβ42 for the diagnosis of neurodegenerative diseases
- An immuno-DOT diagnostic assay for autoimmune nodopathy
- Evaluation of biochemical algorithms to screen dysbetalipoproteinemia in ε2ε2 and rare APOE variants carriers
- Reference Values and Biological Variations
- Allowable total error in CD34 cell analysis by flow cytometry based on state of the art using Spanish EQAS data
- Clinical utility of personalized reference intervals for CEA in the early detection of oncologic disease
- Agreement of lymphocyte subsets detection permits reference intervals transference between flow cytometry systems: direct validation using established reference intervals
- Cancer Diagnostics
- Atypical cells in urine sediment: a novel biomarker for early detection of bladder cancer
- External quality assessment-based tumor marker harmonization simulation; insights in achievable harmonization for CA 15-3 and CEA
- Cardiovascular Diseases
- Evaluation of the analytical and clinical performance of a high-sensitivity troponin I point-of-care assay in the Mersey Acute Coronary Syndrome Rule Out Study (MACROS-2)
- Analytical verification of the Atellica VTLi point of care high sensitivity troponin I assay
- Infectious Diseases
- Synovial fluid D-lactate – a pathogen-specific biomarker for septic arthritis: a prospective multicenter study
- Targeted MRM-analysis of plasma proteins in frozen whole blood samples from patients with COVID-19: a retrospective study
- Letters to the Editor
- Generative artificial intelligence (AI) for reporting the performance of laboratory biomarkers: not ready for prime time
- Urgent need to adopt age-specific TSH upper reference limit for the elderly – a position statement of the Belgian thyroid club
- Sigma metric is more correlated with analytical imprecision than bias
- Utility and limitations of monitoring kidney transplants using capillary sampling
- Simple flow cytometry method using a myeloma panel that easily reveals clonal proliferation of mature B-cells
- Is sweat conductivity still a relevant screening test for cystic fibrosis? Participation over 10 years
- Hb D-Iran interference on HbA1c measurement