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 classifica-tion 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 dif-ferent 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 neutron-phil 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 clini-cal differential diagnosis of APTB and LC.(Clin. Lab. 2023;69:2299-2304. DOI: 10.7754/Clin.Lab.2023.230511)