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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
The Main Characteristics of The Study Populations Lung Cancer Patients  (males – 472, females – 61; age=57.4  0.4 years) ………………………..…….. 533 Stage I………………………………………………... 48 Stage II……………………………………………….. 47 Stage III……………………………………………… 321 Stage IV……………………………………………… 117 Lung Non-Malignant Pathology  (males – 188, females – 94; age=50.3  0.7 years)   …………….. 282 Non-Malignant Tumor..…………………………… 100 Abscess………………………..……………………. 112 Tuberculoma…………………..…………………….. 70
Procedures (n= 815 ) Lung Cancer Patients …………… 533 Pneumonectomy… 181 Upper Lobectomy.. 138 Lower Lobectomy.... 67 Upper/Lower Bilobectomy…….…. 24 Middle Lobectomy.… 6 Segmentectomy.…. 76 Exploratory Thoraco-tomy, biopsy………. 41   Lung Non-Malignant Pathology ………… 282 Pneumonectomy…... 5 Upper Lobectomy… 96 Lower Lobectomy.... 81 Middle Lobectomy.… 2 Segmentectomy, Wedge Resection…. 98
Lung Cancer Patients Characteristics (n= 533 ) Squamous Cell..… 294 Adenocarcinoma.. 171 Large Cell…………. 48 Small Cell…………. 20 T1.………………… 116 T2…………………. 168 T3…………………. 125 T4…………………. 124 N0…………………. 148 N1…………………. 144 N2…………………. 159 N3…………………… 82 G1…………………... 88 G2…………………. 166 G3…………………. 279 M0…………………. 438 M1…………………... 95
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
 
Conclusions: early detection and diagnosis of lung cancer significantly depended on: 1) the level of immune cell circuit; 2) the value of humoral immunity factors; 3) the level of monocyte and macrophage circuit; 4) the value of neutrophils circuit.
Address: Oleg Kshivets, M.D., Ph.D. Thoracic Surgeon Department of Surgery Siauliai Cancer Center Tilzes:42-16, 5400 Siauliai, Lithuania Tel. (37041)416614 Fax (37041)526430 [email_address]   [email_address] http//:myprofile.cos.com/Kshivets

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Kshivets O. Lung Cancer Surgery

  • 1. 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
  • 2. The Main Characteristics of The Study Populations Lung Cancer Patients (males – 472, females – 61; age=57.4  0.4 years) ………………………..…….. 533 Stage I………………………………………………... 48 Stage II……………………………………………….. 47 Stage III……………………………………………… 321 Stage IV……………………………………………… 117 Lung Non-Malignant Pathology (males – 188, females – 94; age=50.3  0.7 years) …………….. 282 Non-Malignant Tumor..…………………………… 100 Abscess………………………..……………………. 112 Tuberculoma…………………..…………………….. 70
  • 3. Procedures (n= 815 ) Lung Cancer Patients …………… 533 Pneumonectomy… 181 Upper Lobectomy.. 138 Lower Lobectomy.... 67 Upper/Lower Bilobectomy…….…. 24 Middle Lobectomy.… 6 Segmentectomy.…. 76 Exploratory Thoraco-tomy, biopsy………. 41 Lung Non-Malignant Pathology ………… 282 Pneumonectomy…... 5 Upper Lobectomy… 96 Lower Lobectomy.... 81 Middle Lobectomy.… 2 Segmentectomy, Wedge Resection…. 98
  • 4. Lung Cancer Patients Characteristics (n= 533 ) Squamous Cell..… 294 Adenocarcinoma.. 171 Large Cell…………. 48 Small Cell…………. 20 T1.………………… 116 T2…………………. 168 T3…………………. 125 T4…………………. 124 N0…………………. 148 N1…………………. 144 N2…………………. 159 N3…………………… 82 G1…………………... 88 G2…………………. 166 G3…………………. 279 M0…………………. 438 M1…………………... 95
  • 6. Table 1. Factors of T-, B- and K-cell Circuit between LCP (n=95) and NMP (n=282) in terms of Early Detection
  • 7. Table 2. Factors of T-, B- and K-cell Circuit between LCP and NMP in terms of Diagnosis
  • 8. Table 3. Results of Logistic Regression Modeling in Early Detection of Lung Cancer (n=95) from NMP (n=282)
  • 9. Table 4. Results of Logistic Regression Modeling in Diagnosis of LC (n=533) from NMP (n=282)
  • 10. Results of Multi-Factor Clustering in Early Detection of Lung Cancer
  • 11. Results of Multi-Factor Clustering in Diagnosis of Lung Cancer
  • 12. SEPATH-models in Early Detection of Lung Cancer
  • 13. SEPATH-models in Diagnosis of Lung Cancer
  • 14. Results of Monte Carlo Simulation in Early Detection and Diagnosis of Lung Cancer
  • 15. T-, B-Cell Circuit in Early Detection of Lung Cancer
  • 16. T-, B-Cell Circuit in Diagnosis of Lung Cancer
  • 17. CD8, CD4 Cell Circuit in Diagnosis of Lung Cancer
  • 18. Lymphocytes, Monocytes Circuit in Early Detection of Lung Cancer
  • 19. Lymphocytes, Monocytes Circuit in Diagnosis of Lung Cancer
  • 20. Neutrophils Circuit in Early Detection of Lung Cancer
  • 21. Neutrophils Circuit in Diagnosis of Lung Cancer
  • 22. Humoral Immunity in Early Detection of Lung Cancer
  • 23. Humoral Immunity in Diagnosis of Lung Cancer
  • 24. Lotka-Volterra Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics
  • 25. Holling-Tenner Models of Lung Cancer Cell Population and Cytotoxic Cell Population Dynamics
  • 26. Immunity Networks in Early Detection of Lung Cancer
  • 27. Immunity Networks in Diagnosis of Lung Cancer
  • 29. Networks between Immune System and Recognition of Lung Cancer
  • 30.  
  • 31. Conclusions: early detection and diagnosis of lung cancer significantly depended on: 1) the level of immune cell circuit; 2) the value of humoral immunity factors; 3) the level of monocyte and macrophage circuit; 4) the value of neutrophils circuit.
  • 32. Address: Oleg Kshivets, M.D., Ph.D. Thoracic Surgeon Department of Surgery Siauliai Cancer Center Tilzes:42-16, 5400 Siauliai, Lithuania Tel. (37041)416614 Fax (37041)526430 [email_address] [email_address] http//:myprofile.cos.com/Kshivets