Application of ImmunoScore Model for the Differentiation between Active Tuberculosis and Latent Tuberculosis Infection as Well as Monitoring Anti-tuberculosis Therapy

Abstract

Tuberculosis (TB) is a leading global public health problem. To achieve the end TB strategy, non-invasive markers for diagnosis and treatment monitoring of TB disease are urgently needed, especially in high-endemic countries such as China. Interferon-gamma release assays (IGRAs) and tuberculin skin test (TST), frequently used immunological methods for TB detection, are intrinsically unable to discriminate active tuberculosis (ATB) from latent tuberculosis infection (LTBI). Thus, the specificity of these methods in the diagnosis of ATB is dependent upon the local prevalence of LTBI. The pathogen-detecting methods such as acid-fast staining and culture, all have limitations in clinical application. ImmunoScore (IS) is a new promising prognostic tool which was commonly used in tumor. However, the importance of host immunity has also been demonstrated in TB pathogenesis, which implies the possibility of using IS model for ATB diagnosis and therapy monitoring. In the present study, we focused on the performance of IS model in the differentiation between ATB and LTBI and in treatment monitoring of TB disease. We have totally screened five immunological markers (four non-specific markers and one TB-specific marker) and successfully established IS model by using Lasso logistic regression analysis. As expected, the IS model can effectively distinguish ATB from LTBI (with a sensitivity of 95.7% and a specificity of 92.1%) and also has potential value in the treatment monitoring of TB disease.

Lymphocyte Non-Specific Function Detection Facilitating the Stratification of Mycobacterium tuberculosis Infection

“…Besides, TBAg/PHA ratio was helpless in identifying ATB with negative T-SPOT results due to its computational limitations. Several studies have demonstrated that the combination of multiple indicators could promote ATB diagnosis (31,32). Accordingly, we speculate that the use of the combination of lymphocyte non-specific function (non-specific marker) and T-SPOT (TB-specific marker) has the potential to improve rapid differential diagnosis between ATB and LTBI.…”

A Model Based on the Combination of IFN-γ, IP-10, Ferritin and 25-Hydroxyvitamin D for Discriminating Latent From Active Tuberculosis in Children

“…Regarding the possible use of biomarkers in the field, considering the TPPs recommended by FIND/WHO, the sensitivity and specificity achieved by the combination of IFN-γ, IP-10, ferritin and 25(OH)D were optimal (Denkinger et al, 2015). In recent years, two case-control studies presented two models for the diagnosis of TB in children with minimal TPPs higher than those reached in this study for the development of a new diagnostic test (Armand et al, 2014; Zhou et al, 2017). However, they were not able to discriminate between active TB and LTBI cases.…”

Predicting Grating Orientations With Cross-Frequency Coupling and Least Absolute Shrinkage and Selection Operator in V1 and V4 of Rhesus Monkeys

“…LASSO is a regression analysis method that performs both variable selection and regulation to enhance the prediction accuracy and interpretability of the statistical model it produces (Friedman et al, 2010 ; Ciuperca, 2012 ). It can effectively avoid the problems of over-fitting and high correlation in the least squares estimation, and solve the problem of multicolinearity in regression analysis (Zhou et al, 2017 ; Zhang et al, 2018 ). LASSO has been widely used in many fields, such as the prediction of disease outcomes (Tang et al, 2018 ) and genome-wide (Waldmann et al, 2019 ).…”