TB Research

Th1/Th2 Imbalance and Elevated PD-L1 in Pleural Effusion Predict the Risk of Multi-Drug Resistant Tuberculous Pleuritis.

Hongyan Xu, Yueqing Yang, Qianhong Wu, Yan Zhang

PubMed · 2020-03

Abstract

BACKGROUND: Patient immune status might be indicative of the variance in bacterial genetics in drug-resistant tuberculous pleuritis and could be used for predicting the risk of multi-drug resistant tuberculous pleuritis (MDR-TB). OBJECTIVE: To determine the significance of Th2/Th1 ratio and concentration of PD-L1 in the pleural effusions for prediction of MDR-TB. METHODS: We measured the ratio of Th2 to Th1 T cells from pleural effusions in 373 tuberculous pleuritis patients. We also measured the concentration of programmed death ligand-1 (PD-L1) in the pleural effusions of these patients. Afterwards, we determined the optimal cut-off value for predicting the occurrence of multi-drug resistant tuberculous based on the Youden index, diagnostic evaluation test, and receiver operation curve. Multiple logistic analysis was employed to identify the independent risk factors for MDR-TB occurrence. RESULTS: The area under the curve (AUC) of the Th2 to Th1 ratio was 0.66 and the concentration of PD-L1 was 0.71. Based on the combined detection of PD-L1 concentration in pleural effusion and the Th2 to Th1 ratio, our AUC was 0.81 and had a specificity of 0.92. Only a combined detection was able to identify patients developing multidrug-resistant tuberculosis. Multiple logistic analysis showed that a high concentration of PD-L1 and a high Th2 to Th1 ratio in pleural effusions were indicative of an immunocompromised status. Therefore, these measurements might be independent risk factors for the occurrence of multidrug-resistant tuberculous. CONCLUSION: Evaluation of immune status based on PD-L1 pleural concentration and Th2 to Th1 ratio might predict the risk of MDR-TB occurrence.

MeSH terms

  • Medicine
  • Internal medicine
  • Tuberculosis
  • Pleural effusion
  • Youden's J statistic
  • Area under the curve
  • Gastroenterology
  • Receiver operating characteristic
  • Logistic regression