kshivets o. lung cancer surgery: synergetics and prediction

SIGNIFICANT IMPACT OF PHASE TRANSITIONS SIGNIFICANT IMPACT OF PHASE TRANSITIONS AND CELL RATIO FACTORS FOR 5-YEAR SURVIVAL AND CELL RATIO FACTORS FOR 5-YEAR SURVIVAL

OF NON SMALLOF NON SMALLCELL LUNG CANCER PATIENTS AFTER SURGERYCELL LUNG CANCER PATIENTS AFTER SURGERY   

Oleg Kshivets, MD, PhDOleg Kshivets, MD, PhDSurgery Department, Siauliai Public Hospital, LithuaniaSurgery Department, Siauliai Public Hospital, Lithuania

Abstract: N181SIGNIFICANT IMPACT OF PHASE TRANSITIONS AND CELL RATIO FACTORS FOR 5-YEAR SURVIVAL OF NON SMALL CELL LUNG CANCER PATIENTS AFTER RADICAL LOBECTOMIES AND PNEUMONECTOMIESOleg KshivetsSurgery Department, Siauliai Public Hospital, Siauliai, LithuaniaOBJECTIVE: The role of phase transitions (PT) in system “non-small cell lung cancer (LC)—human homeostasis” and cell ratio factors (CRF) (ratio between LC cell population: CC and blood cell subpopulations) for 5-year survival (5YS) after lobectomies/pneumonectomies was analyzed.METHODS: In trial (1985-2009) the data of consecutive 490 LC patients (LCP) after complete resections R0 (age=56.7±8 years; male - 439, female - 51; tumor diameter: D=4.5±2.1 cm; pneumonectomies - 206, lobectomies - 284, combined procedures with resection of pericardium, atrium, aorta, VCS, carina, diaphragm, esophagus, liver, chest wall, ribs, etc. - 130; squamous cell carcinoma - 308, adenocarcinoma - 147, large cell carcinoma - 35; T1 - 143, T2 - 217, T3 - 107, T4 - 23; N0 - 282, N1 - 115, N2 - 93; G1 - 114, G2 - 140, G3 - 236; early LC: LC till 2 cm in D with N0 - 58, invasive LC - 432) was reviewed. Variables selected for 5YS study were input levels of blood cell subpopulations, TNMG, D. 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: For total of 490 LCP overall life span (LS) was 1824±1304 days and real 5YS reached 62%, 10 years – 50.3%, 20 years – 45.3%. 304 LCP (LS=2597.3±1037 days) lived more than 5 years without LC progressing. 186 LCP (LS=559.8±383.1 days) died because of LC during first 5 years after surgery. 5YS of early LCP was significantly superior (100%) compared with invasive LCP (56.9%) (P=0.000 by log-rank test). 5YS of LCP with N0 was significantly better (78.4%) compared with LCP with N1-2 (39.9%) (P=0.000). Cox modeling displayed that 5YS significantly depended on: PT in terms of synergetics “early-invasive LC”, PT N0-N12, CRF (P=0.000-0.004). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT “early-invasive LC”, (rank=1), PT N0-N12 (2), erythrocytes/CC (3), healthy cells/CC (4), eosinophils/CC (5), lymphocytes/CC (6), monocytes/CC (7), thrombocytes/CC (8), segmented neutrophils/CC (9), leucocytes/CC (10), stab neutrophils/CC (11). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; urea under ROC curve=1.0). CONCLUSION: 5YS of LCP after radical procedures significantly depended on: 1) PT “early-invasive LC”; 2) PT N0-N12; 3) CRF; 4) LC characteristics.

Data:

Male………….…………..439Female………..……………51Age……..………56.7±8 yearsTumor Size…...…..4.5±2.1cm

Radical Procedures:Radical Procedures:

Pneumonectomy…………….…..206Bi/Lobectomy…........................…284In All…………………………......490

Combined & Extensive Radical Procedures with Resection of Pericardium, Atrium, Aorta, Vena Cava Superior, Vena Azygos, Carina, Trachea, Diaphragm, Chest Wall, Ribs, etc.…………………….130

Sistematic MediastinalSistematic MediastinalLymph Node-N2 Lymph Node-N2 Dissection…………..Dissection…………..490490

Staging:Staging:T1…..143 N0..…282 G1…..114T2…..217 N1…..115 G2…..140T3…..107 N2……93 G3…..236T4……23 Early LC...58 Invasive LC...432Squamous Cell Carcinoma…..……….308Adenocarcinoma………………………147Large Cell Carcinoma………………….35Central…………202 Peripherical…..288

Survival Rate of Lung Cancer Patients after Survival Rate of Lung Cancer Patients after Lobectomies and Pneumonectomies (R0) (n=490):Lobectomies and Pneumonectomies (R0) (n=490):

5-Year Survivors……………………...304 (62%) Losses from Lung Cancer…………….186 (38%)Life Span……………………..….1824±1304 days10-Year Survival………………………….50.3% 20-Year Survival………………………….45.3%5-Year Survival for Early LC……………100%5-Year Survival for Invasive LC…………56.9% 5-Year Survival for LC with N0…………78.4%5-Year Survival for LC with N1-2……….39.9%

Product-Limit (Kaplan-Maier) Analysis Results in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=490):

Survival Function5-Year Survival=62%

10-Year Survival=50.3%20-Year Survival=45.3%

Complete Censored

-5 0 5 10 15 20 25

Years after Surgery

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Survival of Early LCP was Significantly Better Compared to Invasive LCP:

Survival of LCP with N0 was Significantly Better Compared to LCP with N1-2:

Results of Multivariate Proportional Hazard Cox Regression Modeling in Prediction of LCP Survival after Lobectomies and

Pneumonectomies (n=490):

Global 2=131.51; Df=7; P=0.000

Results of Discriminant Function Analysis in Prediction of LCP survival after lobectomies and

pneumonectomies (n=490):

Wilks' Lambda=0.785; approx. F (4,485)=33.159 P=0.000Correct Classification Rate=72%

Wilks' - Lambda

Partial - Lambda

F-remove - (1,485) P Toler. 1-Toler. -

(R-Sqr.)

Phase Transition “Early LC---Invasive LC” 0.800861 0.980512 9.63957 0.002 0.905212 0.094787

Eosinophils/Cancer Cells 0.797277 0.984920 7.42555 0.007 0.837585 0.162415

Lymphocytes/Cancer Cells 0.792552 0.990791 4.50772 0.034 0.822803 0.177197

Phase Transition “N0---N12” 0.879453 0.892889 58.18034 0.000 0.947110 0.052890

Results of Multifactor Clustering of Cell RatioFactors in Prediction of Lung Results of Multifactor Clustering of Cell RatioFactors in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=490):Cancer Patients Survival after Lobectomies and Pneumonectomies (n=490):

Correct Classification Rate=81%Correct Classification Rate=81%

Neural Networks in Prediction of Lung Cancer Patients Survival after Neural Networks in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=490):Lobectomies and Pneumonectomies (n=490):

Losses 5-year survivors Baseline Errors=0.000;Total 186 304 Area under ROC curve=1.0;

Correct 186 304 Correct Classification Rate= 100%Wrong 0 0

Results of Neural Networks Computing in Prediction of 5-Year Survival of LCP after Lobectomies and Pneumonectomies (n=490):

Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies

and Pneumonectomies (n=490):

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

after Lobectomies and Pneumonectomies (n=490):

Holling-Tenner Models of Alive Supersystem Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell Population“Lung Cancer-Cytotoxic Cell Population”

Lung Cancer Dynamics:

SEPATH Networks in Prediction of Lung Cancer SEPATH Networks in Prediction of Lung Cancer Patients Survival after Lobectomies and Patients Survival after Lobectomies and

Pneumonectomies (n=490):Pneumonectomies (n=490):

Conclusions:Conclusions:5-year survival and life span of lung cancer patients after complete lobectomies and pneumonectomies significantly depended on: 1) phase transition “early---invasive lung cancer”; 2) phase transition “N0---N12”; 3) cell ratio factors (ratio between blood cell subpopulations and cancer cell population); 4) lung cancer characteristics.

Address: Oleg Kshivets, M.D., Ph.D.Thoracic Surgeon, Dep.of Surgery, Siauliai Public Hospital,Tilzes:42-16, Siauliai, LT78206, LithuaniaTel. (37041)416614 kshivets@yahoo.comhttp//:myprofile.cos.com/Kshivets