Session: 803. Emerging Tools, Techniques and Artificial Intelligence in Hematology: Poster II
Hematology Disease Topics & Pathways:
Research, Lymphoid Leukemias, ALL, Acute Myeloid Malignancies, CLL, Lymphomas, assays, Clinical Research, health outcomes research, Plasma Cell Disorders, Diseases, immunology, Lymphoid Malignancies, Myeloid Malignancies, Biological Processes, Technology and Procedures, Study Population, Human
Immunophenotyping of abnormal cells by flow cytometer enabled this technology in diagnosing, prognostication and guiding therapy for blood malignancies. International consensus exist for diagnosis of leukemia, lymphoma and plasma cell neoplasm (PCN)1–3 using flow cytometer, but it is seldom used for screening these diseases. In clinical setting, including our tertiary care center in India, we come across patients whose peripheral blood (PB) smear examination does not hint towards the type of blood-related disorder. We identified the need to screen these patients by flow cytometry before channelling them towards established diagnostic work-up for malignancies. The aim of this study is to evaluate a flow cytometry screening assay, designed in-house, to detect blood malignancies in a resource-limited (sample, time, cost, infrastructure) clinical setting.
MATERIALS AND METHODS
This prospective double-blinded study was conducted between November 2022 and June 2023 with institutional ethical approval. Remainder of samples sent for routine clinical tests that met our inclusion/exclusion criteria were selected (n=221). Symptomatic patients with blood-related disorder, whose PB did not show any abnormal cells were included. All patients who had blast, lymphocytosis with atypical lymphocytes, lymphadenopathy, B-symptoms, splenomegaly or found to have plasmacytoma/amyloidosis/CRAB features were excluded. Three tube 8 colour 19 antibody panel (Table1) was designed. Immaturity markers and lineage specific markers are combined in a single tube to detect leukemias. CD5, CD10, CD19, CD20, kappa and lambda were put together to identify B-CLPD. A lyse-wash-stain protocol was followed and the samples were analysed in BD FACSCantoII flowcytometer with autofluroscence and compensation correction done for each sample. The findings of our screening assay were validated with morphological and clinical correlation and GraphPad Prism version 8.0.2 was used for statistical analysis.
RESULTS
Our antibody panel targeted only cell surface antigens, which reduced the cost of the test and permitted the analysis of the sample within 1 hour. During the study period, out of the 396 discard samples obtained, 221 patients met our inclusion criteria (Figure1). We analysed these samples with our screening assay and detected 51 patients with blood malignancies that included 19 acute leukemias, 11 lymphomas and 21 PCN and 167 samples with no evidence of leukemia, lymphoma or PCN which were subsequently diagnosed with anemias, platelet disorders, drug- or disease-induced leukocytosis/leukopenias and organ dysfunction not involving blood or bone marrow. The number of samples studied and the computed statistical parameters are given in Table2. Representative bivariate dot plots are given in Figure2.
Out of the 221 test results, 214 had clinical, morphological and screening test concordance. One case of PCN could not be identified by morphological examination, where screening assay could identify clonal plasma cell population. Another one case was clinically diagnosed as PCN, but missed on screening panel because we did not see a definite cluster of CD38+ cells showing light chain kappa/lambda restriction. The remaining 5 samples were dilute in nature. In 3 out of 5 dilute samples, screening panel could identify the abnormality which was concordant with clinical diagnosis (based on clinical, biochemical, imaging, molecular and cytogenetics) where morphology failed. The other 2 cases were identified morphologically on bone marrow imprint.
This flow cytometry screening assay was found to have overall 94.4% sensitivity, 100% specificity, 100% positive predictive value and 98.2% negative predictive value, delineating the efficacy of this minimal antibody screening panel in detecting blood malignancies.
CONCLUSION
Compared to the existing screening panels, this novel screening test has comprehensive set of antibodies (19 only) to detect leukemia, lymphoma and PCN simultaneously within 1 hour and at a lower cost. In patients screened negative, further blood malignancy-related testing may be avoided, thereby reducing the total cost incurred to the patient. The usefulness of this screening test is limited with dilute sample. However, the present study shows that this screening panel can be used in small resource-constrained and remote settings with a trained flow cytometry technologist alone.
Disclosures: No relevant conflicts of interest to declare.