5-YEAR SURVIVAL OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER RADICAL SURGERY SIGNIFICANTLY DEPENDED ON PHASE TRANSITION “EARLY-INVASIVE

CANCER”, LYMPH NODE METASTASES AND CELL RATIO FACTORS

Oleg Kshivets, MD, PhDSiauliai Public Hospital, Siauliai, Lithuania

Abstract• 5-YEAR SURVIVAL OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER

RADICAL SURGERY SIGNIFICANTLY DEPENDED ON PHASE TRANSITION “EARLY-INVASIVE CANCER”, LYMPH NODE METASTASES AND CELL RATIO FACTORS

• Oleg Kshivets• Surgery Department, Siauliai Public Hospital, Lithuania•  • OBJECTIVE: We examined factors associated with low/high-risk of generalization of lung cancer (LC) (T1-4N0-2M0)

after complete (R0) lobectomies/pneumonectomies.    METHODS: We analyzed data of 602 consecutive LC patients (LCP) (age=57.5±8.1 years; tumor size=4.4±2.3 cm) radically operated and monitored in 1985-2010 (m=536, f=66;  pneumonectomies=222, lobectomies=380, combined procedures with resection of pericardium, atrium, aorta, VCS, carina, diaphragm, esophagus, liver, chest wall, ribs, etc.=155; squamous cell carcinoma=367, adenocarcinoma=192, large cell carcinoma=43; T1=215, T2=232, T3=114, T4=41; N0=377, N1=118, N2=107; G1=150, G2=180, G3=272; early LC: LC till 2 cm in diameter with N0=110, invasive LC=492) was reviewed. Variables selected for 5-year survival (5YS) study were input levels of blood cell subpopulations, TNMG, tumor size. Survival curves were estimated by Kaplan-Meier method. Differences in curves between groups were evaluated using a log-rank test. Neural networks computing, multivariate Cox regression, clustering, discriminant analysis, structural equation modeling, Monte Carlo and bootstrap simulation were used to determine any significant regularity.

•   RESULTS: Overall life span (LS) was 1973.4±1466.8 days and cumulative 5YS reached 67.9%, 10 years – 59.2%, 20 years – 29.9%. 371LCP lived more than 5 years without LC. 186LCP died because of LC. Cox modeling displayed (Chi2=171.3, df=6, P=0.000) that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0--N1-2, cell ratio factors (CRF) (ratio between cancer cells – CC and blood cells subpopulations) (P=0.000-0.011). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0--N1-2 (rank=2), erythrocytes/CC, healthy cells/CC, thrombocytes/CC, segmented neutrophils/CC,monocytes/CC,leucocytes/CC, stab neutrophils/CC, lymphocytes/CC,eosinophils/CC. Correct prediction of 5YS was 100% by neural networks computing.

•     CONCLUSIONS:5YS of LCP after radical procedures significantly depended on: 1) PT “early-invasive LC”; 2) PT N0--N1-2; 3) CRF.

 

Data

• Males……………………………………………536• Females………….………………………………66• Age=57.5±8.1 years• Tumor Size=4.4±2.3 cm• Pneumonectomies.………………………......222• Bi/lobectomies……………………………..….380• Combined procedures with resection of

pericardium, atrium, aorta, VCS, carina, diaphragm, esophagus, liver, chest wall,

• ribs, etc………..……………………….………155

Staging

• T1……215 N0..…..377 G1..………150• T2……232 N1……118 G2…..……180• T3……114 N2……107 G3.….……272• T4……..41• Early Lung Cancer….………………………...110• Invasive Lung Cancer...................................492• Right..…………………………………………...327• Left………………………………………………275• Adenocarcinoma……………………………...192• Squamous Cell Carcinoma……..…………...367• Large Cell Carcinoma..……………………......43

Survival Rate

• 5-Year Survivors…………..…….371 (61.6%)

• Losses………………………….…186 (30.9%)

• General Life Span=1973.4±1466.8 days

• For 5-Year Survivors=2844.0±1195.7 days

• For Losses=562.5±378.0 days

• Cumulative 5-Year Survival………….67.9%

• Cumulative 10-Year Survival…..........59.2%

General Lung Cancer Patients Survival after Complete Procedures (Kaplan-Meier) (n=602)

Early and Invasive Lung Cancer Patients Survival after Complete Procedures (Kaplan-Meier) (n=602)

Survival of Lung Cancer Patients with N0 and N1-2 after Complete Procedures (Kaplan-Meier) (n=602)

Results of Cox Regression Modeling in Prediction of Lung Cancer

Patients Survival after Complete Procedures (n=602)

Overall Chi2=171.3; df=6; P=0.000;

• Factors Wald df P•• Phase Transition Early-Invasive LC 9.987 1 0.001578 • Phase Transition N0—N1-2 53.682 1 0.000000• Leucocytes/Cancer Cells 16.914 1 0.000039

Stab Neutrophils/Cancer Cells 6.346 1 0.011768• Segmented Neutrophils/Cancer Cells 17.891 1 0.000023• Lymphocytes/Cancer Cells 8.918 1 0.002826

Results of Discriminant Analysis in Prediction of Lung Cancer Patients Survival after Complete Procedures (n=557)

• Discriminant Function Analysis Summary

• Wilks' Lambda: 0.759 approx. F (3,553)=58.533 p< 0.0000;

• Correct Classification Rate=75%

• Wilks'-Lambda P

• Phase Transition Early-Invasive Lung Cancer 0.779 0.000140

• Phase Transition N0—N1-2 0.867 0.000000

• Eosinophils/Cancer Cells 0.775 0.000726

Results of Multi-Factor Clustering of Clinicopathological Data in Prediction of Lung Cancer Patients Survival after Complete

Procedures (n=557)

Results of Clustering in Prediction of Lung Cancer Patients Survival after Complete Procedures

(n=557)

• Logical Formulas based on Simple Mean

• 5-Year Survivors• Early Cancer (11.2%) &• 0.99 <= Erythrocytes/Cancer Cells (10.6%) <= 26.21 &• 4.17 <= Healthy Cells/Cancer Cells (10.7%) <= 78.00 &• N0 (8.8%) & also no N12 (14.7%)• LCP 371 Error1 = 0.71 (265) Error2 = 0.01 (1)• ───────────────────────────────────────────────────────

Losses• Invasive Cancer (11.2%) &• 0.93 <= Erythrocytes/Cancer Cells (10.6%) <= 10.98 &• 3.33 <= Healthy Cells/Cancer Cells (10.7%) <= 35.65 &• no N0 (8.8%) & or N12 (14.7%)• LCP 186 Error1 = 0.33 (61) Error = 0.22 (81)

Neural Networks in Prediction of Lung Cancer Patients Survival after Complete Procedures (n=557)

5-Year Survivors Losses

Baseline Errors=0.000 Total 371 186Area under ROC Curve=1.0 Correct 371 186Correct Classification Rate=100% Wrong 0 0

Results of Neural Networks Computing in Prediction of Lung Cancer Patients Survival after Complete Procedures (n=557)

Error=0.000; Area under ROC Curve=1.00; Correct Classification Rate=100%

Factor Rank Sensitivity

• Phase Transition Early-Invasive LC 1 149776.4

• Phase Transition N0---N12 2 83185.8

• Erythrocytes/Cancer Cells 3 27099.1

• Healthy Cells/Cancer Cells 4 9551.3

• Thrombocytes/Cancer Cells 5 3664.4

• Segmented Neutrophils/Cancer Cells 6 1419.9

• Monocytes/Cancer Cells 7 679.3

• Leucocytes/Cancer Cells 8 590.9

• Stab Neutrophils/Cancer Cells 9 354.0

• Lymphocytes/Cancer Cells 10 140.5

• Eosinophils/Cancer Cells 11 78.2

Results of Genetic Algorithm Selection in Prediction of Lung Cancer Patients Survival after Complete Procedures (n=557)

Factor Useful for 5-Year Survival

• Phase Transition Early-Invasive Lung Cancer YesPhase Transition N0---N12 Yes

• Eosinophils/Cancer Cells Yes• Lymphocytes/Cancer Cells Yes• Monocyte/Cancer Cells Yes• Healthy Cells/Cancer Cells Yes

Results of Kohonen Self-Organizing Neural Networks Computing in Prediction of Lung Cancer Patients Survival after Complete Procedures

(n=557)

Results of Bootstrap Simulation in Prediction of Lung Cancer Patients

Survival after Complete Procedures (n=557)

• Number of Samples=3333• Significant Factors Rank Kend.Tau-A P• Phase Transition N0—N12 1 -0.200 0.000• Healthy Cells/Cancer Cells 2 0.152 0.000• Erythrocytes/Cancer Cells 3 0.151 0.000• Thrombocytes/Cancer Cells 4 0.144 0.000• Lymphocytes/Cancer Cells 5 0.133 0.000• Leucocytes/Cancer Cells 6 0.132 0.000• Phase Transition Early-Invas. LC 7 0.125 0.000• Eosinophils/Cancer Cells 8 0.118 0.000• Monocytes/Cancer Cells 9 0.113 0.000• Segm. Neutrophils/Cancer Cells 10 0.084 0.003

Ratio of Lymphocytes and Erythrocytes to Cancer Cells & Glucose Level in Prediction of Lung Cancer Patients Survival after Complete

Procedures (n=557)

Prognostic SEPATH-Model of Lung Cancer Patients Survival after Complete Procedures (n=557)

Lung Cancer Dynamics

Conclusions:

• 5-year survival and life span of lung cancer patients after complete procedures significantly depended on:

• 1) phase transition early—invasive lung cancer;• 2) phase tranzition N0---N12;• 3) cell ratio factors: ratio of cancer cell population to

blood cell subpopulations in integral patient organism.

Address:Oleg Kshivets M.D., Ph.D.,

Consultant Thoracic, Abdominal, General Surgeon & Surgical Oncologist

• Skype: okshivets Tel. 37060878390• e-mail: kshivets@yahoo.com, kshivets@gmail.com• http://myprofile.cos.com/Kshivets• http://youtube.com/user/Kshivets002• http://www.slideshare.net/Kshivets