Leukocyte Cell Population Data (CPD) as a Discriminating Tool between Active Tuberculosis and Lung Cancer.

BACKGROUND: Cell population data (CPD) are parameters of cell size, shape, and content that can be used in the differential diagnosis of diseases such as leukemia, bacterial or viral infection, and dengue fever. The aim of this study was to screen for CPD parameters that can be used to differentiate active pulmonary tuberculosis (APTB) from lung cancer (LC) and to assess their efficacy. METHODS: Whole blood samples from 84 APTB patients, 109 LC patients, and 95 healthy volunteers were collected from January 2019 to November 2019. All samples were tested by DxH800 blood cell analyzer using VCS (volume, conductivity, and scatter) technology to obtain CPD parameters, total leukocyte count, and leukocyte classification count. The results were tested for normal distribution, followed by one-way analysis of variance (ANOVA) and area under the ROC curve (AUC) analysis to evaluate the diagnostic efficacy of CPD parameters. RESULTS: Twenty-three CPD parameters were significantly higher in the APTB group than in the LC group, 13 CPD parameters were significantly lower than in the LC group, and 6 CPD parameters were not statistically different between the two groups. The AUCs of CPD parameters between the APTB and LC groups were analyzed, and the results showed that the AUCs of nine CPD parameters were higher than 0.91, with the AUCs of neutronphil mean conductance (NMC), lymphocyte mean conductance (LMC), and monocyte mean conductance (MMC) even reaching 0.983, 0.930, and 0.996, respectively. Meanwhile, compared with the CPD parameters, white blood cells and their conventional differential counts (WBC, NE%, LY%, MO%) did not result in higher AUCs for the two groups (0.641, 0.757, 0.659, 0.733, respectively). CONCLUSIONS: Three CPD parameters (NMC, LMC, and MMC) obtained higher AUC than other indicators, and their combined diagnosis efficacy obtained 100% sensitivity and 99.1% specificity, which may be helpful for clinical differential diagnosis of APTB and LC.

Cell population data in identifying active tuberculosis and community-acquired pneumonia.

OBJECTIVE: Leukocyte morphological parameters known as CPD (cell population data) is detected by hematology analyzer UniCel DxH800 with VCS technology. This study aimed to investigate the diagnostic efficacy of morphological changes in CPD parameters in distinguishing active tuberculosis from community-acquired pneumonia. METHODS: From October 2018 to February 2019, 88 patients with active tuberculosis, 78 patients with community-acquired pneumonia, and 89 healthy controls were enrolled in this study. CPD was obtained using Unicel DxH800 analyzer for all whole blood samples, one-way ANOVA (non-parametric) and area analysis under ROC curve were performed. RESULTS: The neutrophil mean conductivity (NMC), monocyte mean volume (MMV), monocyte mean conductivity (MMC), lymphocyte percentage (LY%), and monocyte percentage (MO%) were significantly higher in the active tuberculosis group than in the community-acquired pneumonia group. The white blood cell (WBC) count and neutrophil percentage (NE%) were significantly lower in the active tuberculosis group than in the community-acquired pneumonia group. The analysis of the area under the ROC curve proved that WBC count, neutrophil percentage (NE%), lymphocyte percentage (LY%), and monocyte percentage (MO%) did not achieve a higher area under the curve (AUC: 0.63, 0.71, 0.62, and 0.7, respectively). However, the AUC of NMC, MMV, and MMC in the CPD parameters was 0.951, 0.877, 0.98, respectively, and the simultaneous measurement of the three parameters was 0.99. The sensitivity and specificity were 98.5% and 91.1%, respectively. CONCLUSION: The combined diagnosis of NMC, MMV, and MMC could assist the clinical diagnosis of active tuberculosis and community-acquired pneumonia.