Immunity Networks in Early Detection and Diagnosis of Lung Cancer Oleg Kshivets, MD, PhD Department of Surgery, Siauliai Cancer Center Lithuania The 4 th International Congress on Lung Cancer Halkidiki, Greece, 2001

Immune Testing

Table 1. Factors of T-, B- and K-cell Circuit between LCP (n=95) and NMP (n=282) in terms of Early Detection

Table 2. Factors of T-, B- and K-cell Circuit between LCP and NMP in terms of Diagnosis

Table 3. Results of Logistic Regression Modeling in Early Detection of Lung Cancer (n=95) from NMP (n=282)

Table 4. Results of Logistic Regression Modeling in Diagnosis of LC (n=533) from NMP (n=282)

Results of Multi-Factor Clustering in Early Detection of Lung Cancer

Results of Multi-Factor Clustering in Diagnosis of Lung Cancer

SEPATH-models in Early Detection of Lung Cancer

SEPATH-models in Diagnosis of Lung Cancer

Results of Monte Carlo Simulation in Early Detection and Diagnosis of Lung Cancer

T-, B-Cell Circuit in Early Detection of Lung Cancer

T-, B-Cell Circuit in Diagnosis of Lung Cancer

CD8, CD4 Cell Circuit in Diagnosis of Lung Cancer

Lymphocytes, Monocytes Circuit in Early Detection of Lung Cancer

Lymphocytes, Monocytes Circuit in Diagnosis of Lung Cancer

Neutrophils Circuit in Early Detection of Lung Cancer

Neutrophils Circuit in Diagnosis of Lung Cancer

Humoral Immunity in Early Detection of Lung Cancer

Humoral Immunity in Diagnosis of Lung Cancer

Lotka-Volterra Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics

Holling-Tenner Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics

Immunity Networks in Early Detection of Lung Cancer

Immunity Networks in Diagnosis of Lung Cancer

Lung Cancer Dynamics

Networks between Immune System and Recognition of Lung Cancer