Abstract
Objective This study aimed to establish a predictive model based on the clinical manifestations and laboratory findings in pleural fluid of patients with pleural effusion for the differential diagnosis of malignant pleural effusion (MPE) and tuberculous pleural effusion (TPE). Methods Clinical data and laboratory indices of pleural fluid were collected from patients with malignant pleural effusion and tuberculous pleural effusion in Zigong First People's Hospital between January 2019 and June 2020，and were compared between the two groups. Independent risk factors or Independent protective factors for malignant pleural effusion were investigated using multivariable logistic regression analysis. Receiver operating characteristic curve (ROC) analysis was performed to assess the diagnostic performance of factors with independent effects, and combined diagnostic models were established based on two or more factors with independence effect. ROC curve was used to evaluate the diagnostic ability of each model, and the fit of the eath model was measured using Hosmer-Lemeshow goodness-of-fit test. Results Patients with MPE were older than those with TPE, the rate of fever of patients with MPE was lower than that of patients with TPE, and these differences were statistically significant (p < 0.05). Carcinoembryonic antigen (CEA), neuron-specific enolase (NSE), cytokeratin-19 fragment antigen (CYFRA21-1), cancer antigen 125 (CA125), and glucose (GLU) levels in the pleural fluid were higher, but total protein (TP), albumin (ALB) and Adenosine deaminase (ADA) levels in the pleural fluid were lower in MPE patients than in TPE patients, and the differences were statistically significant (P<0.05). In multivariate logistic regression analysis, CEA and NSE levels in the pleural fluid were independent risk factors for MPE, whereas ADA levels in pleural fluid and fever were independent protective factors for MPE. The differential diagnostic value of pleural fluid CEA and pleural fluid ADA for MPE and TPE were higher than that of pleural fluid NSE（p<0.05） and the area under the ROC curve was 0.901, 0.892, and 0.601, respectively. Four different binary logistic diagnostic models were established based on pleural fluid CEA combined with pleural fluid NSE, pleural fluid ADA or ( and ) fever. Among them, the model established with the combination of pleural fluid CEA and pleural fluid ADA (logit (P) = 0.513 + 0.457*CEA-0.101*ADA) had the highest diagnostic value for malignant pleural effusion, and its predictive accuracy was high with an area under the ROC curve of 0.968 [95% confidence interval (0.947, 0.988)]. But the diagnostic efficacy of the diagnostic model could not be improved by adding pleural fluid NSE and fever. Conclusion The model established with the combination of CEA and ADA in the pleural fluid has a high differential diagnostic value for malignant pleural effusion and tuberculous pleural effusion, and NSE in the pleural fluid and fever cannot improve the diagnostic efficacy of the diagnostic model.
Different characteristics of tuberculous pleural effusion according to pleural fluid cellular predominance and loculation
