Journal of clinical laboratory analysis · 2026
The Application Value of Flow Cytometry-Based Peripheral Blood Leukocyte Classification in Screening for Acute Leukemia and Posttreatment Monitoring.
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Yan Penghua, Wu Lianfeng, Lin Xiangyang, Lu Hong, Qian Jingjing
Аннотация
OBJECTIVE: Assess the application value of flow cytometry (FCM) for peripheral blood leukocyte (PBL) classification in acute leukemia (AL) screening and monitoring.
METHODS: Analyzed EDTA-K2-anticoagulated blood from 100 nonhematological patients, 42 newly diagnosed AL patients, and 50 posttreatment leukemia patients using FCM, blood cell analyzers (BCA), and manual microscopy.
RESULTS: FCM and BCA showed significant positive correlations in classifying and counting neutrophils, eosinophils, basophils, lymphocytes, and monocytes (r = 0.994, 0.671, 0.946, 0.987, and 0.849, respectively; p < 0.01). A significant positive correlation was observed between FCM and manual methods in counting blast cells (r = 0.882, p < 0.01). Using microscopy as the reference standard and a cutoff value of ≥ 1% blast cells, FCM demonstrated 100% sensitivity, 85.7% specificity, and 97.8% accuracy in detecting blast cells. The type of peripheral blood blast cells provided by FCM showed good consistency with the clinical diagnosis of leukemia (Kappa value = 0.834). Additionally, a positive correlation was found between the detection rates of bone marrow and peripheral blood blast cells using FCM in posttreatment patients with leukemia (rs = 0.860, p < 0.01).
CONCLUSION: FCM-based PBL classification is precise and efficient for detecting blasts, providing rapid subtype identification. Its strong correlation with marrow findings underscores its clinical utility in AL screening and monitoring.
METHODS: Analyzed EDTA-K2-anticoagulated blood from 100 nonhematological patients, 42 newly diagnosed AL patients, and 50 posttreatment leukemia patients using FCM, blood cell analyzers (BCA), and manual microscopy.
RESULTS: FCM and BCA showed significant positive correlations in classifying and counting neutrophils, eosinophils, basophils, lymphocytes, and monocytes (r = 0.994, 0.671, 0.946, 0.987, and 0.849, respectively; p < 0.01). A significant positive correlation was observed between FCM and manual methods in counting blast cells (r = 0.882, p < 0.01). Using microscopy as the reference standard and a cutoff value of ≥ 1% blast cells, FCM demonstrated 100% sensitivity, 85.7% specificity, and 97.8% accuracy in detecting blast cells. The type of peripheral blood blast cells provided by FCM showed good consistency with the clinical diagnosis of leukemia (Kappa value = 0.834). Additionally, a positive correlation was found between the detection rates of bone marrow and peripheral blood blast cells using FCM in posttreatment patients with leukemia (rs = 0.860, p < 0.01).
CONCLUSION: FCM-based PBL classification is precise and efficient for detecting blasts, providing rapid subtype identification. Its strong correlation with marrow findings underscores its clinical utility in AL screening and monitoring.