Flow cytometry is a globally accepted diagnostic tool used for the rapid identification of cells based on their surface and intracellular
antigens, especially for the diagnosis of haematological malignancies. The aim of this study was to evaluate the requests
received for flow cytometric immunophenotyping and to create a profile of diagnoses. In 2014 data regarding indications and
diagnoses were captured from request forms received and final diagnosis reports issued by the Tshwane Academic Division (TAD)
of the National Health Laboratory Service (NHLS). A total of 1234 requests were received over the one year period, of which 80.4%
were performed and 16.8 % were rejected. The most common indications were leukaemia, lymphoma and cytopenia. Nineteen
percent of requests received contained no correct indication or clinical history. In total, 103 and 153 diagnoses were established
based on peripheral blood and bone marrow aspirate specimens respectively. Samples were mostly rejected due to sample clotting,
electronic gate keeping rules and receiving the specimen more than 24 hours after collection.http://www.smltsa.org.za/publications.htmlam2018Haematolog

Nel, Jan Gert

Pool, Roger

Prinsloo, Andrea

UPSpace at the University of Pretoria

ISSN 1011 5528  |  www.smltsa.org.za    1Medical Technology SA  |  Volume 31 No. 1  |  June 2017OPEN ACCESSPeer reviewed ORIGINAL ARTICLERetRospective data analysis of all Requests foR flow cytometRic immunophenotyping in a teRtiaRy hospital settingA Prinsloo  MSc | J Nel  MMed (Haem) | R Pool  MMed (Haem)Tshwane Academic Division of the National Health Laboratory Service and the Department of Haematology, Faculty of Health Sciences, University of Pretoria, Pretoria, Gauteng, South AfricaCorresponding author: Mrs Andrea A Prinsloo | tel: +27 12 319 2279 | email: andrea.prinsloo@up.ac.zaAbsTRACTFlow cytometry is a globally accepted diagnostic tool used for the rapid identification of cells based on their surface and intracel-lular antigens, especially for the diagnosis of haematological malignancies. The aim of this study was to evaluate the requests received for flow cytometric immunophenotyping and to create a profile of diagnoses. In 2014 data regarding indications and diagnoses were captured from request forms received and final diagnosis reports issued by the Tshwane Academic Division (TAD) of the National Health Laboratory Service (NHLS). A total of 1234 requests were received over the one year period, of which 80.4% were performed and 16.8 % were rejected. The most common indications were leukaemia, lymphoma and cytopenia.  Nineteen percent of requests received contained no correct indication or clinical history. In total, 103 and 153 diagnoses were established based on peripheral blood and bone marrow aspirate specimens respectively. Samples were mostly rejected due to sample clotting, electronic gate keeping rules and receiving the specimen more than 24 hours after collection. KEYWORDsFlow cytometry, immunophenotyping, diagnostic profilesINTRODuCTIONImmunophenotyping is a diagnostic tool used for the identifica-tion of cells on the basis of the antigen specific location on the surface of the cell.[1] Flow cytometry has been described by Craig and Foon[2] as an “indispensable tool”. Advances in computational technology and the availability of fluorochromes in the past fifty years have led to the large scale adoption of this technique in clinical diagnoses.[2-4] Flow cytometry is one of the most popular techniques for the diagnosis of haematologi-cal malignancies.[5] Possessing the ability to analyse 100 000 cells per second, flow cytometry is a high throughput tech-nique from which results can be rapidly obtained.[6] In 2008, the World Health Organisation stipulated that flow cytometric results should be used in the classification of acute leukaemia.[7] Not only is flow cytometric immunophenotyping vital in the classification of haematologic malignancies, but it is imperative in determining prognosis, monitoring disease progression and therapy evaluation. Due to its high sensitivity, flow cytometry plays an important role in the detection of minimal residual disease (MRD), where residual cells can be identified and moni-tored to detect relapse of disease.[5,7]Flow cytometric immunophenotyping has had an impact in clinical diagnosis of haematological malignancies and disor-ders. Examples include foetal blood quantification, HIV patient monitoring, disease staging and patient response to drugs/therapies. It has also had an impact in the immunophenotyping of leukaemia and lymphoma, assessment of platelet function, structure and defects, as well as assisting in monitoring apop-tosis, chemotherapy management and pre-transplant reactions to name a few.[8,9]Annually, the NHLS Department of Immunology at the TAD, Pretoria, receives a large number of requests for immunophe-notyping. Although flow cytometry is a popular diagnostic tool in haematology, it remains a costly especially in terms of the high number of requests received at the TAD. Therefore, it is important to establish whether the test is being utilized effi-ciently at this laboratory. Fluorochrome conjugated antibodies in immunophenotyping accounts for the high cost factor of flow cytometry. It is recommended that multiple antibodies be used in a panel as aberrant markers may occur from time to time. Multiple antibody panels provide more information than a sin-gle antibody.[10] Each fluorochrome conjugate in a panel could cost approximately R200. Up to twenty conjugates might be required per panel for some flow cytometric tests, depending on the specific examination. Different test panels such as screening panels, lineage specific panels and diagnostic panels are used. The costs of tests could range between R3655.88 and R4974.07 per patient. It is important that flow cytometry is requested for the correct indications to prevent wastage of resources. The indications for flow cytometric immunophenotyping as rec-ommended by the 2006 Bethesda International Consensus[11]included possible signs and symptoms of: cytopenias, elevated leukocyte counts, observation of atypical cells or blasts in bodily fluids, plasmacytosis or monoclonal gammopathy, orga-nomegaly or tissue masses and patient monitoring.ISSN 1011 5528  |  www.smltsa.org.za    2Medical Technology SA  |  Volume 31 No. 1  |  June 2017OPEN ACCESSIn cases where patients present with non-specific signs and symptoms, causes other than haemato-lymphoid neoplasms must first be excluded. Once these have been ruled out, flow cytometry may then be indicated for the work-up of these pa-tients. Flow cytometric immunophenotyping is indicated in the instances of anaemia, leukopenia or thrombocytopenia. Pancy-topenia is regarded to be more likely associated with neoplasia, thereofore flow cytometric immunophenotyping is indicated. However, all lineages should be evaluated to determine the ori-gin, as any haematolymphoid neoplasm might cause cytopenia. For example, elevated leukocyte counts may be an indication for flow cytometric immunophenotyping because they are associat-ed with chronic myeloid leukaemia (CML) and chronic lympho-proliferative disorders. Flow cytometric immunophenotyping is unlikely to yield useful information in the cases of neutrophilia with the absence of blasts, isolated polycythaemia, thrombosis and basophilia. The presence of blasts in the peripheral blood or bone marrow is a definite indication for flow cytometry. Plasma-cytosis and monoclonal gammopathy have also been mentioned as indications for flow cytometric immunophenotyping, as it might assist in the detection of abnormal plasma cells and in the classification of multiple myelomas. Organomegaly, lymphad-enopathy and tissue infiltrates are considered to be indications for flow cytometric immunophenotyping as it is effective in the diagnosis of tissue-based lymphoid neoplasms. Indications for flow cytometry in patients, who have already been diagnosed with haematological neoplasms include: disease staging, detec-tion of potential therapeutic targets, therapy response assess-ment, disease acceleration and prognostication.[11]The aim of this study was to describe the number and type of diagnoses made, as well as indications for flow cytometric im-munophenotyping, requested at the Tshwane Academic Divi-sion (TAD) of the National Health Laboratory Service (NHLS) over a period of one year.Figure 1. Percentage distribution of the total requests Figure 2. Grouping of requests for flow cytometric immunophenotyping according to indication ISSN 1011 5528  |  www.smltsa.org.za    3Medical Technology SA  |  Volume 31 No. 1  |  June 2017OPEN ACCESSMATERIALs AND METhODsData was gathered from different sources, including all request forms received by the Department of Immunology, TAD of the NHLS, for flow cytometry during the period of 1st January 2014 to 31st December 2014, a list of rejected requests from the NHLS Laboratory Information System (LIS), as well as a da-tabase provided by the Department of Haematology. The final diagnosis of all performed flow cytometric immunophenotyping was obtained from the reports that were available for review. Details about the date of performed flow cytometry, requesting hospital, requesting ward, reason for request, age, specimen type received and diagnosis made, were also collected. Approval to access the flow cytometry data had been granted by the NHLS. Ethics approval was received from the Research Ethics Committee of the University of Pretoria (142/2015). DIsCussIONCurrently there is no published data on the number and indica-tions for flow cytometry requests received in a tertiary academ-ic setting. This data should be made available to monitor the appropriate cost-effectiveness of this test method in diagnostic laboratories.Most (80.4%) of the requests received for flow cytometric immu-nophenotyping were actually performed (Figure 1). This exem-plifies the large financial implications the Department of Health faced in 2014. If the lowest priced general panel was used for all tests, the costs would have been a minimum of approximately, R3.6 million. In a country where there is great economic pres-sure, it is important that the healthcare system aims to maintain a balance between service delivery and cost efficiency. Indications designated on the request forms were categorized into eight groups namely: leukaemia, lymphoma, cytopenia, cytosis, anaemia, none, other and unknown (Figure 2). All re-quests which indicated suspected leukaemia i.e., acute myeloid leukaemia (AML), CML, acute lymphoblastic leukaemia (ALL), chronic lymphocytic leukaemia (CLL), Hairy Cell Leukaemia, Mantle Cell Lymphoma, relapse of leukaemia, MRD monitoring, etc. were included in the Leukaemia category (n=272; 22%). Any indication which included various types of lymphomas were all included in the Lymphoma category (n=114; 9%). The Cytope-nia category (n=176; 14%) included bicytopenia, pancytopenia and any single cell line cytopenia, such as thrombocytopenia. The category labelled other (n=271; 22%) consisted of all those indications which did not fall into the seven categories already mentioned, and included organomegaly, fever, bleeding, Parox-ysmal nocturnal haemoglobinuria (PNH) and multiple myeloma. The Unknown group category (n=89; 7%) included those speci-mens rejected for incorrect collection i.e., tube used, insufficient volume and those that were received after 24 hours of collection. Where a suspected leukaemia or a known leukaemia was indi-cated on the request form, it assisted in selecting specific panels, thus ensuring the best possible diagnostic results for the patient.No clinical history or reason for the requests was found in 234 (19%) of the requests received. This could possibly be explained by one of two things: namely the failure to complete the forms with all the necessary information required for performing the laboratory tests or the time constraint during clinical consulta-tions. Additionally, forms lacked clearly designated boxes for clinicians to complete. On 36 forms, the requested tests were written in the space allocated for clinical history. Therefore, no clinical history was provided on these forms.Focussing on the frequency of diagnosis reported per category, the highest rate was observed in the leukaemia category (n=148; 54%). The lowest rate of diagnosis reported was observed in the category other (n=48; 18%) shown in figure three below.Surprisingly, in 27 out of the 229 (12%) requests which con-tained no clinical history or reason for request, a final diagnosis was in fact established. This is important, as even when there was no clinical history, a possible diagnosis could still exist. However, if all requests received are performed, regardless of the indication it may cause a large financial burden. In total 256 peripheral blood specimens and 730 bone marrow aspirate specimens were received during the year. Diagnosis was established on 103 peripheral blood samples and 153 Figure 3. Quantity of diagnoses, rejection and unavailable final report per indication groupISSN 1011 5528  |  www.smltsa.org.za    4Medical Technology SA  |  Volume 31 No. 1  |  June 2017OPEN ACCESSbone marrow aspirates. Bone marrow samples are not always necessary in the diagnosis of acute leukaemias and chronic lymphoproliferative disorders, such as CLL.[12] Peripheral blood may also be used in the diagnosis of non-Hodgkin’s lymphoma (NHL) if there are circulating lymphoma cells.Regarding final diagnoses established (Figure 4), the greatest number was AML (n=54), followed by CML (n=35), CLL (n=35), Acute Leukaemia (n=34), ALL (n=26), B-cell lymphoprolif-erative disorder (n=25), other (n=19), plasma cells (n=17) and blasts (n=12). The Acute Leukaemia diagnosis category included final reports that indicated a relapse of an acute leukaemia. The B-cell Lymphoproliferative disorder diagnosis category included final reports which established the presence of a B-cell lymphopro-Figure 5. Number of requests rejected and reasons for rejectionFigure 4. Quantity of diagnoses established per type of diagnosis categoryISSN 1011 5528  |  www.smltsa.org.za    5Medical Technology SA  |  Volume 31 No. 1  |  June 2017OPEN ACCESSliferative disorder. However, the particular subtype could not be established with flow cytometry alone. Within the lymphoma category, there were a number of requests that suspected Hodg-kin’s lymphoma. Diagnosis of Hodgkin’s lymphoma relies on the detection of Reed-Sternberg cells, which are primarily found in the lymph nodes.[13] Due to the fact that these cells are rarely lo-cated extranodally, flow cytometric immunophenotyping is of limited use.[14]A total of 207 requests received for flow cytometric immu-nophenotyping were rejected (Figure 5). Most of the rejected requests were observed in the category None (n=29), followed by Other (n=27), Leukaemia (n=22), Cytopenia (n=16) and Lymphoma (n=13) categories (Figure 3). The most common reason for request rejection was due to clotted samples. There were 73 (35%) samples which on arrival were clotted and there-fore unsuitable for flow cytometric immunophenotyping.The adverse clotting of samples during sample collection is mainly attributed to two reasons: i.e., challenging or prolonged venipuncture, or failing to adequately mix the tube after col-lection ensuring optimal interaction between the blood and anticoagulant.[15] The correct ratio of anticoagulant to blood is vital for the integrity of the sample.[16]The gate keeping system of the Steve Biko Academic Hospital rejected 49 (24%) requests. This system has prevented the flow cytometric immunophenotyping from being done, and possibly saved a minimum of R179.138.12 (if only a general screen had been performed).A cause for concern was the number of requests rejected be-cause they reached the laboratory after the optimal time period of 6-24 hours for processing, had passed. Other reasons for flow cytometry rejection included the following: cancellation by the requesting doctor, inadequate sample (poor cell viability, insuf-ficient sample), incorrect or duplicate registrations of tests and the test was not being indicated clinically, an incorrect sample tube, or that the sample leaked.CONCLusIONsThe results obtained from this study could be used to inform clinicians of the type of requests received for flow cytometric immunophenotyping compared to the proportion which were medically indicated. This would reduce the number of unneces-sary requests and preserve funds so that capital may be utilized in a more cost effective manner, thus improving the diagnostic platform. The lack of published flow cytometric data was a limi-tation to this study. We aim to expand the study to include data from other sites in order to compare our findings. We also hope to establish an overview of flow cytometry statistics in tertiary academic settings throughout South Africa.ACKNOWLEDGEMENTsWe are grateful to the National Health Laboratory Service which allowed access to data analysed. Special thanks to Miss S Naicker for gathering and analysing the data.REfERENCEs1. National Cancer Institute at the National Institute of Health [Internet]. NCI dictionary of cancer terms. NCI: [updated 2015; cited 2015 Feb16]. Available from: http://www.cancer.gov/dictionary?cdrid=341450.2. Craig FE, Foon KA. Flow cytometricimmunophenotyping for he-matologic neoplasms. Blood 2008; 111(8):3941-67.3. Jennings CD, Foon KA. Recent advances in flow cytometry: appli-cation to the diagnosis of hematologic malignancy. Blood 1997; 90(8):2869-92.4. Henel G, Schmitz JL. Basic theory and clinical applications of flow cytometry. LabMed 2007; 38(7):428-36.5. Orfao A, Schmitz G, Brando Bet al. Clinically useful informa-tion provided by the flow cytometricimmunophenotyping of hematological malignancies: current status and future directions. ClinChem 1999; 45(10):1708-17.6. Cibas ES, Ducatman SB. Cytology: diagnostic principles and clin-ical correlates. 2nd ed. Edinburgh: Saunders; 2003. p. 309-11.7. Vardiman JW, Thiele J, Arber DA, Brunning RD, Borowitz MJ, Porwit A. The 2008 revision of the World Health Organization (WHO) classification of myeloid neoplasms and acute leukemia: rationale and important changes. Blood 2009; 114(5):937-51.8. Brown M, Wittwer C. Flow cytometry: principles and clinical ap-plications in hematology. ClinChem 2000; 46(8):1221-9.9. Hoffbrand A, Moss PAH. Essential Haematology. 6th ed. Sussex: Wiley-Blackwell; 201110. Cibas ES, Ducatman BS. Cytology: diagnostic principles and clinical correlates. 2nd ed. Edinburgh: Saunders; 2003. p. 30911. Davis BH, Holden JT, BeneMCet al. 2006 Bethesda international consensus recommendations on the flow cytometricimmunophe-notypic analysis of hematolymphoid neoplasia: medical indica-tions. Clinical Cytometry. 2007; (72):S5-13.12. Bain BJ. Bone marrow aspiration. J ClinPathol 2001;(54):657-6313. University of Virginia School of Medicine [Internet]. Pathology Thread. Charlottesville: University of Virginia; [updated 2015; cited 2015 Oct 25]. Available from: https://www.med-ed.virginia.edu/courses/path/innes/wcd/hodgkin.cfm14. Fromm JR, Thomas A, Wood BL. Flow cytometry can diagnose classical Hodgkin lymphoma in lymph nodes with high sensitiv-ity and specificity. Am J Clin Path 2009;(131):322-3215. Giavarina D, Lippi G. Blood venous sample collection: Rec-ommendations overview and a checklist to improve qual-ity. ClinBiochem 2017, http://dx.doi.org/10.1016/j.clinbio-chem.2017.02.02116. Narayanan S. The pre-analytic phase an important component of laboratory medicine. Am J Clin Path 2000; (113):429-52.© The Society of Medical Laboratory Technologists of South Africa

Retrospective data analysis of all requests for flow cytometric immunophenotyping in a tertiary hospital setting

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Retrospective data analysis of all requests for flow cytometric immunophenotyping in a tertiary hospital setting

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