Immunologic Predictors of the Risc of Generalization in Non-Small Cell Lung

Cancer Patients after Comlete Resections

Oleg Kshivets, M.D., Ph.D.Department of Surgery, Siauliai Public Hospital, Lithuania

The 15th World Congress of World Society of Cardio-Thoracic Surgeons, Vilnius, Lithuania, 2005

Abstract:Abstract:IMMUNOLOGIC PREDICTORS OF THE RISK OF GENERALIZATION IN NON-SMALL CELL LUNG CANCER PATIENTS IMMUNOLOGIC PREDICTORS OF THE RISK OF GENERALIZATION IN NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE RESECTIONSAFTER COMPLETE RESECTIONS  Oleg Kshivets Oleg Kshivets   Department of Surgery, Siauliai Public Hospital, Siauliai, 5400, LithuaniaDepartment of Surgery, Siauliai Public Hospital, Siauliai, 5400, Lithuania   BackgroundBackground:: some non-small cell lung cancer (LC) patients (LCP) after complete resections are known to be rapidly progressive and some non-small cell lung cancer (LC) patients (LCP) after complete resections are known to be rapidly progressive and fatal requiring adjuvant treatment while others are not. We examined the immunologic factors associated with the low- and high-risk of fatal requiring adjuvant treatment while others are not. We examined the immunologic factors associated with the low- and high-risk of generalization of LC after surgery.generalization of LC after surgery. MethodsMethods: : WeWe analyzed data of 108 consecutive LCP radically operated and monitored in 1987-2004 (males – 94, females – 14; analyzed data of 108 consecutive LCP radically operated and monitored in 1987-2004 (males – 94, females – 14; pneumonectomy=45, upper/lobectomy=44, lower/lobectomy=11, upper/lower bilobectomy=7, middle lobectomy=1; stage II=34, stage pneumonectomy=45, upper/lobectomy=44, lower/lobectomy=11, upper/lower bilobectomy=7, middle lobectomy=1; stage II=34, stage III=74; squamos cell LC=56, adenocarcinoma=46, large cell=6; T1=38, T2=43, T3=23, T4=4; N0=63, N1=20, N2=25; G1=30, G2=34, III=74; squamos cell LC=56, adenocarcinoma=46, large cell=6; T1=38, T2=43, T3=23, T4=4; N0=63, N1=20, N2=25; G1=30, G2=34, G3=44). 59 LCP (age=56.7G3=44). 59 LCP (age=56.70.9 years; tumor size: D=4.30.9 years; tumor size: D=4.30.3 cm; life span: LS=1903.80.3 cm; life span: LS=1903.821.0 days) lived more than 5 years without any 21.0 days) lived more than 5 years without any features of LC progressing. 49 LCP (age=56.6features of LC progressing. 49 LCP (age=56.61.2 years; D=4.61.2 years; D=4.60.3 cm; LS=542.70.3 cm; LS=542.755.2 days) died because of generalization of LC 55.2 days) died because of generalization of LC during the first 5 years after radical procedures. Variables selected for 5YS study were input levels of 64 immunity blood parameters, sex, during the first 5 years after radical procedures. Variables selected for 5YS study were input levels of 64 immunity blood parameters, sex, age, TNMG, cell type, D. Survival curves were estimated by the Kaplan-Meier method. Differences in curves between groups of LCP were age, TNMG, cell type, D. Survival curves were estimated by the Kaplan-Meier method. Differences in curves between groups of LCP were evaluated using a log-rank test. Multivariate Cox modeling, multi-factor clustering, discriminant analysis, structural equation modeling, evaluated using a log-rank test. Multivariate Cox modeling, multi-factor clustering, discriminant analysis, structural equation modeling, Monte Carlo, bootstrap simulation and neural networks computing were used to determine any significant dependence.Monte Carlo, bootstrap simulation and neural networks computing were used to determine any significant dependence. ResultsResults:: Cox modeling displayed that 5-year survival of LCP (n=108) after complete resections significantly depended on: N0-2 Cox modeling displayed that 5-year survival of LCP (n=108) after complete resections significantly depended on: N0-2 (P=0.000), T1-4 (P=0.005), lymphocytes (P=0.000), monocytes (P=0.018), CD19 (P=0.000), CD16 (P=0.001), CD4+2H (P=0.000), (P=0.000), T1-4 (P=0.005), lymphocytes (P=0.000), monocytes (P=0.018), CD19 (P=0.000), CD16 (P=0.001), CD4+2H (P=0.000), CD8VV (P=0.000), CD1 (P=0.001), CD8 (P=0.018), CD4 (P=0.001), stick nuclear neutrophils (P=0.000), NST (P=0.000), circular immune CD8VV (P=0.000), CD1 (P=0.001), CD8 (P=0.018), CD4 (P=0.001), stick nuclear neutrophils (P=0.000), NST (P=0.000), circular immune complexes (P=0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships between 5-complexes (P=0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships between 5-year survival of LCP and CD8VV (rank=1), N0-2 (2), CD19 (3), CD4+2H (4), natural antibodies (5), LC cell population (6), index thymus year survival of LCP and CD8VV (rank=1), N0-2 (2), CD19 (3), CD4+2H (4), natural antibodies (5), LC cell population (6), index thymus function index (7), protein (8), ratio of monocytes to LC cell population (9), CDw26 (10), heparin tolerance (11), gender (12), LC growth function index (7), protein (8), ratio of monocytes to LC cell population (9), CDw26 (10), heparin tolerance (11), gender (12), LC growth (13), ratio of CDw26 to LC cell population (14), monocytes (15), hemoglobin (16), prothrombin index (17), circular immune complexes (13), ratio of CDw26 to LC cell population (14), monocytes (15), hemoglobin (16), prothrombin index (17), circular immune complexes (18), G1-3 (19), D (20), weight (21), T1-4 (22), lymphocytes (23), recalcification time (24), eosinophils (25), erythrocytes (26), fibrinogen-(18), G1-3 (19), D (20), weight (21), T1-4 (22), lymphocytes (23), recalcification time (24), eosinophils (25), erythrocytes (26), fibrinogen-B (27), coagulation time (28), IgM (29), ratio of eosinophils to LC cell population (30). Correct prediction of LCP survival after radical B (27), coagulation time (28), IgM (29), ratio of eosinophils to LC cell population (30). Correct prediction of LCP survival after radical procedures was 88.9% by logistic regression (odds ratio=64.8), 95.4% by discriminant analysis and 100% by neural networks computing procedures was 88.9% by logistic regression (odds ratio=64.8), 95.4% by discriminant analysis and 100% by neural networks computing (area under ROC curve=1.0; error=0.001).(area under ROC curve=1.0; error=0.001).

Factors:Factors: 1) Antropometric Factors……………1) Antropometric Factors……………44 2) Immune Testing...………………..2) Immune Testing...………………..5454 3) Blood Analysis……………………3) Blood Analysis……………………2626 4) Hemostasis Factors………………..4) Hemostasis Factors………………..88 5) Cell Ratio Factors………………..5) Cell Ratio Factors………………..1818 6) Lung Cancer Characteristics…….6) Lung Cancer Characteristics…….99 7) Biochemic Factors………………...7) Biochemic Factors………………...55 8) Treatment Characteristics………..8) Treatment Characteristics………..55 9) Survival Data………………………9) Survival Data………………………44 In All……………………………….In All……………………………….133133

Main Problem of Analysis of Alive Supersystems Main Problem of Analysis of Alive Supersystems (e.g. Lung Cancer Patient Homeostasis):(e.g. Lung Cancer Patient Homeostasis):

Phenomenon of «Combinatorial Explosion» Phenomenon of «Combinatorial Explosion»

Number of Clinicomorphological Factors:……...…..Number of Clinicomorphological Factors:……...…..133133 Number of Possible Combination for Random Search:Number of Possible Combination for Random Search:

……………..……………………………..………………n!=133!=1.487e+226n!=133!=1.487e+226 Operation Time of IBM Blue Gene/L Supercomputer Operation Time of IBM Blue Gene/L Supercomputer

(135.5TFLOPS) …………………………(135.5TFLOPS) …………………………4.7e+218 Years4.7e+218 Years The Age of Our Universe……….....The Age of Our Universe……….....1.3e+10 Years1.3e+10 Years

Basis:Basis: NP NP RP RP P P n! n! n*n*2(e+n) or n log n n*n*2(e+n) or n log n n n

AI AI CSA+S+B CSA+S+B SM SM

Samplings:Samplings:

Lung Cancer Patients Lived More than 5 Lung Cancer Patients Lived More than 5 Years after Radical Procedures……….Years after Radical Procedures……….5959

Lung Cancer Patients Died Because Lung Cancer Patients Died Because Generalization During First 5 Years After Generalization During First 5 Years After Radical Procedures……………...Radical Procedures……………...4949

In All…………………………………...108In All…………………………………...108 5-Year Survival…………………….54.6%5-Year Survival…………………….54.6%

Complete Pulmonary Resections:Complete Pulmonary Resections:

Pneumonectomy…………………..Pneumonectomy…………………..4545 Upper/Lower Bilobectomy……...…Upper/Lower Bilobectomy……...…77 Upper Lobectomy………………....Upper Lobectomy………………....4444 Lower Lobectomy………………....Lower Lobectomy………………....1111 Middle Lobectomy………………….Middle Lobectomy………………….11 In All…………………………...…108In All…………………………...…108

Staging:Staging:

T1……38T1……38 N0……63N0……63 G1……30G1……30 T2……43T2……43 N1……20N1……20 G2……34G2……34 T3……23T3……23 N2……25N2……25 G3……44G3……44 T4……..4T4……..4 Stage II…34 Stage III...74Stage II…34 Stage III...74 SquamoSquamouus Cell Carcinoma………s Cell Carcinoma……….......…56...…56 Adenocarcinoma……………………….46Adenocarcinoma……………………….46 Large Cell Carcinoma…………………..6Large Cell Carcinoma…………………..6

Immune Testing:Immune Testing:

Cumulative Proportion Lung Cancer Patients Surviving Cumulative Proportion Lung Cancer Patients Surviving after Complete Resections (Kaplan-Meier) (n=108)after Complete Resections (Kaplan-Meier) (n=108)

Survival FunctionComplete Censored

Survival of Lung Cancer Patients after Comlete Resectionsn=108

Years after Complete Resections

Cum

ulat

ive

Prop

ortio

n Su

rviv

ing

0.500.550.600.650.700.750.800.850.900.951.001.051.10

0 1 2 3 4 5 6 7 8 9

Results of Multivariate Proportional Hazard Cox Regression Analysis:Results of Multivariate Proportional Hazard Cox Regression Analysis:Chi2=127.643; df=22; n=108; P=0.000000Chi2=127.643; df=22; n=108; P=0.000000

FactorsFactors WaldWald dfdf PP Exp(B)Exp(B) 95%CI for Exp(B)95%CI for Exp(B)LowerLower UpperUpper

CD8+VV+%CD8+VV+% 46.05046.050 11 0.0000.000 1.1241.124 1.0871.087 1.1621.162 CD8+VV+absCD8+VV+abs 32.92532.925 11 0.0000.000 0.0040.004 0.0010.001 0.0250.025 CD1+absCD1+abs 10.19910.199 11 0.0010.001 0.0000.000 0.0000.000 0.0000.000 CD8+%CD8+% 5.5525.552 11 0.0180.018 0.9660.966 0.9390.939 0.9940.994 CD8+absCD8+abs 11.10111.101 11 0.0010.001 11.52111.521 2.7362.736 48.51848.518 B+%B+% 20.46520.465 11 0.0000.000 0.9240.924 0.8920.892 0.9560.956 CD16+absCD16+abs 11.34811.348 11 0.0010.001 1.2e+51.2e+5 133.00133.00 1.1e+81.1e+8 NSTsNSTs 18.57418.574 11 0.0000.000 1.0941.094 1.0501.050 1.1391.139 St.Neutrophils absSt.Neutrophils abs 28.98128.981 11 0.0000.000 1.6e+41.6e+4 487.83487.83 5.8e+55.8e+5 Monocytes absMonocytes abs 4.3164.316 11 0.0380.038 3.6e+33.6e+3 1.5901.590 8.3e+68.3e+6 Lymphocytes%Lymphocytes% 22.63622.636 11 0.0000.000 1.0861.086 1.0501.050 1.1241.124 CICCIC 21.39621.396 11 0.0000.000 0.9630.963 0.9480.948 0.9790.979

Results of Multivariate Proportional Hazard Cox Regression Analysis:Results of Multivariate Proportional Hazard Cox Regression Analysis:Chi2=127.643; df=22; n=108; P=0.000000

FactorsFactors WaldWald dfdf PP Exp(B)Exp(B) 95%CI for Exp(B)95%CI for Exp(B) LowerLower UpperUpper CD16+totCD16+tot 10.52110.521 11 0.0010.001 0.1190.119 0.0330.033 0.4310.431 CD4+2H+totCD4+2H+tot 30.22830.228 11 0.0000.000 1.7451.745 1.4311.431 2.1282.128 CD1+totCD1+tot 7.7217.721 11 0.0050.005 76.66276.662 3.5923.592 1.6e+31.6e+3 Monocytes totMonocytes tot 5.6455.645 11 0.0180.018 0.1590.159 0.0350.035 0.7250.725 T1-4T1-4 13.01213.012 33 0.0050.005 T1-4(1)T1-4(1) 0.1510.151 11 0.6970.697 1.3341.334 0.3120.312 5.6995.699 T1-4(2)T1-4(2) 0.4840.484 11 0.4870.487 0.6160.616 0.1580.158 2.4092.409 T1-4(3)T1-4(3) 2.1582.158 11 0.1420.142 0.3290.329 0.0750.075 1.4501.450 N0-2N0-2 27.42527.425 22 0.0000.000 N0-2(1)N0-2(1) 7.9727.972 11 0.0050.005 0.3440.344 0.1640.164 0.7220.722 CD4+/Cancer CellsCD4+/Cancer Cells 14.54714.547 11 0.0000.000 0.1960.196 0.0850.085 0.4530.453

Results of Discriminant Analysis in Prediction of Lung Cancer Results of Discriminant Analysis in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=108)Patients Survival after Lobectomies and Pneumonectomies (n=108)

Discriminant Function Analysis SummaryDiscriminant Function Analysis Summary Wilks' Lambda: 0.230 Wilks' Lambda: 0.230 approx. F (60,47)=2.619 approx. F (60,47)=2.619 p< 0.0004p< 0.0004 Wilks' Wilks' Partial Partial F-removeF-remove P-level P-level Lambda Lambda (1,421) Lambda Lambda (1,421) N0-2N0-2 .288494.288494 .798046.798046 11.89384 11.89384 .001199.001199 CD8+VV+%CD8+VV+% .272237.272237 .845700.845700 8.575248.57524 .005240.005240 B+%B+% .254813.254813 .903530.903530 5.018195.01819 .029850.029850 CICCIC .249275.249275 .923603.923603 3.887693.88769 .054543.054543 CD4+2H+%CD4+2H+% .246179.246179 .935218.935218 3.255643.25564 .077588.077588 CD8+VV+totCD8+VV+tot .245170.245170 .939066.939066 3.049713.04971 .087285.087285 NST2NST2 .242024.242024 .951274.951274 2.407432.40743 .127469.127469 CDw26+absCDw26+abs .240159.240159 .958661.958661 2.026732.02673 .161158.161158 PHNPHN .240297.240297 .958112.958112 2.054782.05478 .158348.158348 Seg.Neutrophils%Seg.Neutrophils% .239719.239719 .960422.960422 1.936801.93680 .170568.170568 Lymphocytes%Lymphocytes% .239040.239040 .963149.963149 1.798291.79829 .186365.186365 NANA .238421.238421 .965648.965648 1.671981.67198 .202313.202313 CD8+%CD8+% .237814.237814 .968113.968113 1.548061.54806 .219592.219592 PFTPFT .238148.238148 .966758.966758 1.616081.61608 .209895.209895 ISFISF .237157.237157 .970797.970797 1.413851.41385 .240391.240391 CDw26+/CCCDw26+/CC .236674.236674 .972780.972780 1.315151.31515 .257268.257268 CD4+/CCCD4+/CC .237153.237153 .970813.970813 1.413051.41305 .240522.240522 B+/CCB+/CC .230458.230458 .999018.999018 0.046210.04621 .830731.830731

Results of Logistic Regression Analysis in Prediction of Lung Cancer Patients Survival after Complete Results of Logistic Regression Analysis in Prediction of Lung Cancer Patients Survival after Complete Resections (n=108); Chi2=88.714; df=19; P=0.00000; Odds ratio=64.800Resections (n=108); Chi2=88.714; df=19; P=0.00000; Odds ratio=64.800

Est. S.E.Est. S.E. Wald Wald P P OddsOdds 95.0% .Od.Ratio 95.0% .Od.Ratio RatioRatio LowerLower UpperUpper

Const.B Const.B 5.619 3.193 5.619 3.193 3.095 3.095 .0785.0785 275.578275.578 0.4830.483 1.5e+51.5e+5 T1-4 T1-4 -0.321 0.623-0.321 0.623 0.2650.265 0.60670.6067 0.7250.725 0.2100.210 2.5042.504 CD8+VV+%CD8+VV+% -0.216 0.077-0.216 0.077 7.814 7.814 0.00520.0052 0.8060.806 0.6910.691 0.9400.940 CD8+VV+absCD8+VV+abs 8.332 8.332 3.9873.987 4.367 4.367 0.03670.0367 4152.4864152.486 1.5041.504 1.1e+71.1e+7 CD1+absCD1+abs 46.682 22.22446.682 22.224 4.412 4.412 0.03570.0357 CD8+%CD8+% 0.141 0.0560.141 0.056 6.345 6.345 0.01180.0118 1.1511.151 1.0301.030 1.2871.287 CD4+absCD4+abs -0.771 2.419-0.771 2.419 0.102 0.102 0.74990.7499 0.4620.462 0.0040.004 56.62456.624 B+%B+% 0.257 0.0860.257 0.086 8.983 8.983 0.00270.0027 1.2941.294 1.0911.091 1.5341.534 CD16+absCD16+abs -22.709 10.715 -22.709 10.715 4.491 4.491 0.03410.0341 0.0000.000 0.0000.000 0.2430.243 NSTsNSTs -0.053 0.072-0.053 0.072 0.529 0.529 0.46720.4672 0.9490.949 0.8220.822 1.0951.095 St.Neutroph absSt.Neutroph abs -12.805 6.249 -12.805 6.249 4.200 4.200 0.04040.0404 0.0000.000 0.0000.000 0.6790.679 Monocytes abs -8.340 14.650Monocytes abs -8.340 14.650 0.320 0.320 0.57000.5700 0.0000.000 0.0000.000 1.0e+91.0e+9 Lymphocytes abs-2.866 1.491 Lymphocytes abs-2.866 1.491 3.694 3.694 0.05460.0546 0.0570.057 0.0030.003 1.1021.102 CIC CIC 0.031 0.028 0.031 0.028 1.264 1.264 0.26100.2610 1.0321.032 0.1290.129 14.32714.327 CD4+/CC CD4+/CC 0.309 1.184 0.309 1.184 0.068 0.068 0.79420.7942 1.0361.036 0.1290.129 14.32714.327 CD16+totCD16+tot 4.908 2.1064.908 2.106 5.4295.429 0.01980.0198 135.315135.315 2.0592.059 8894.4038894.403 CD4+2H+totCD4+2H+tot -0.617 0.359 -0.617 0.359 2.9442.944 0.08620.0862 0.5400.540 0.2640.264 1.1021.102 CD1+totCD1+tot -9.299 4.555 -9.299 4.555 4.1674.167 0.04120.0412 0.0000.000 0.0000.000 0.7820.782 Monocytes totMonocytes tot 1.733 2.902 1.733 2.902 0.3570.357 0.55030.5503 5.6585.658 0.0180.018 1807.2551807.255 N0-2N0-2 -1.425 0.520 -1.425 0.520 7.5217.521 0.00610.0061 0.2410.241 0.0860.086 0.6750.675

Clastering in in Prediction of Lung Cancer Patients Clastering in in Prediction of Lung Cancer Patients Survival after Complete Resections (n=108)Survival after Complete Resections (n=108)

Clastering in in Prediction of Lung Cancer Patients Clastering in in Prediction of Lung Cancer Patients Survival after Complete Resections (n=108)Survival after Complete Resections (n=108)

Neural Networks in Prediction of Lung Cancer Patients Neural Networks in Prediction of Lung Cancer Patients Survival after Complete Resections (n=108)Survival after Complete Resections (n=108)

LossesLosses 5-year survivors 5-year survivors Baseline Errors=0.001074;Baseline Errors=0.001074; TotalTotal 49 49 59 59 Area under ROC curve=1Area under ROC curve=1.00; .00;

CorrectCorrect 49 49 59 59 Correct Classification Rate=Correct Classification Rate=100%100% Wrong 0Wrong 0 0 0

Genetic Algorithm SelectionGenetic Algorithm Selection Useful forUseful for Lymphocytes/CC B/CC CD16/CC CD4+2H+/CC CD8+VV+/CC CD8/CC Lymphocytes/CC B/CC CD16/CC CD4+2H+/CC CD8+VV+/CC CD8/CC SurvivalSurvival Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

YesYes

Results of Neural Networks Computing in Prediction of Lung Results of Neural Networks Computing in Prediction of Lung Cancer Patients SurvivalCancer Patients Survival after Complete Resections (n=108)after Complete Resections (n=108)

Error=0.001074; Area under ROC Curve=1.0; Correct Classification Rate=100%Error=0.001074; Area under ROC Curve=1.0; Correct Classification Rate=100% FactorFactor RankRank ErrorError RatioRatio CD8+VV+%CD8+VV+% 11 0.1830.183 169.33169.33 N0-2N0-2 22 0.1290.129 120.30120.30 B (CD19+)%B (CD19+)% 33 0.1280.128 118.93118.93 CD4+2H+absCD4+2H+abs 44 0.1220.122 113.60113.60 NANA 55 0.1040.104 97.26197.261 LC CellsLC Cells 66 0.0950.095 88.29988.299 Thymus FIThymus FI 77 0.0930.093 86.73886.738 Protein Protein 88 0.0840.084 78.48378.483 Monocytes/CCMonocytes/CC 99 0.0810.081 75.47175.471 CDw26+totCDw26+tot 1010 0.0790.079 73.74173.741 Heparin Tol.Heparin Tol. 1111 0.0630.063 58.66758.667 GenderGender 1212 0.0530.053 49.38849.388 LC GrowthLC Growth 1313 0.0510.051 47.18247.182 CDw26+/CCCDw26+/CC 1414 0.0360.036 33.92133.921 Monocytes absMonocytes abs 1515 0.0360.036 33.88333.883

FactorFactor RankRank ErrorError RatioRatio HbHb 1616 0.0310.031 29.62529.625 PIPI 1717 0.0310.031 29.09829.098 CICCIC 1818 0.0260.026 24.52024.520 G1-3G1-3 1919 0.0230.023 21.49521.495 DD 2020 0.0180.018 16.52016.520 WeightWeight 2121 0.0120.012 11.46711.467 T1-4T1-4 2222 0.0110.011 10.42710.427 Lymphocytes%23Lymphocytes%23 0.0080.008 7.3857.385 Recalcif.TimeRecalcif.Time 2424 0.0080.008 7.3487.348 Eosinophils %Eosinophils % 2525 0.0070.007 6.3126.312 ErythrocytesErythrocytes 2626 0.0060.006 5.5105.510 Fibrinogen-BFibrinogen-B 2727 0.0040.004 4.0404.040 Coagul.TimeCoagul.Time 2828 0.0040.004 3.9033.903 IgMIgM 2929 0.0040.004 3.3183.318 Eosinophils/CC30Eosinophils/CC30 0.0030.003 2.9912.991

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

after Complete after Complete ResectionsResections (n=108) (n=108)

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

after Complete after Complete ResectionsResections (n=108) (n=108)

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

after Complete after Complete ResectionsResections (n=108) (n=108)

Results of Bootstrap Simulation in Prediction of Lung Cancer Patients SurvivalResults of Bootstrap Simulation in Prediction of Lung Cancer Patients Survival after after Complete Resections (n=108)Complete Resections (n=108)

Number of Samples=3333Number of Samples=3333 Significant FactorsSignificant Factors RankRank Kendall’s Tau-AKendall’s Tau-A P< P< CD8+VV+ %CD8+VV+ % 11 -0.239-0.239 0.0000.000 CCD8+VV+ absD8+VV+ abs 22 -0.239-0.239 0.0000.000 CD8+VV+totCD8+VV+tot 33 -0.219-0.219 0.0000.000 B %B % 44 0.2160.216 0.0010.001 CD8+ %CD8+ % 55 0.1990.199 0.010.01 CD1+ absCD1+ abs 66 -0.191-0.191 0.010.01 CD1+ %CD1+ % 77 -0.183-0.183 0.010.01 N0-2N0-2 88 -0.179-0.179 0.010.01 ErythrocytesErythrocytes 99 0.1740.174 0.010.01 CD1+ totCD1+ tot 1010 -0.172-0.172 0.010.01 CD8+VV+/CCCD8+VV+/CC 1111 -0.163-0.163 0.050.05 CD1+/CCCD1+/CC 1212 -0.153-0.153 0.050.05 CD8+ absCD8+ abs 1313 0.1520.152 0.050.05 CD4+ absCD4+ abs 1414 -0.148-0.148 0.050.05 CD4+ %CD4+ % 1515 -0.146-0.146 0.050.05 Heparin ToleranceHeparin Tolerance 1616 -0.145-0.145 0.050.05 CD8+/CCCD8+/CC 1717 0.1440.144 0.050.05 CD8+ totCD8+ tot 1818 0.1430.143 0.050.05 CD16+ absCD16+ abs 1919 -0.142-0.142 0.050.05 CD4+2H+ %CD4+2H+ % 2020 -0.140-0.140 0.050.05 CD4+2H+ absCD4+2H+ abs 2121 -0.140-0.140 0.050.05 CD4+2H+ totCD4+2H+ tot 2222 -0.135-0.135 0.050.05 HbHb 2323 0.1350.135 0.050.05

Ratio of B+, CD8+VV+ and CD16+Cell and Cancer Cell Populations Ratio of B+, CD8+VV+ and CD16+Cell and Cancer Cell Populations in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Survival after Complete Resections Patients Survival after Complete Resections (n= (n=108108))

Ratio of B+, CD8+VV+ and CD16+Cell and Cancer Cell Populations Ratio of B+, CD8+VV+ and CD16+Cell and Cancer Cell Populations in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Survival after Complete Resections Patients Survival after Complete Resections (n= (n=108108))

Ratio of B+, CD8+VV+ and CD16+Cell and Cancer Cell Populations Ratio of B+, CD8+VV+ and CD16+Cell and Cancer Cell Populations in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Survival after Complete Resections Patients Survival after Complete Resections (n= (n=108108))

Prediction of Prediction of LungLung Cancer Patients Survival after Cancer Patients Survival after Complete Resections (n=108)Complete Resections (n=108)

Classification of Cases by Logistic Regression, n=108Classification of Cases by Logistic Regression, n=108 (5-Year Survivors--Losses) (5-Year Survivors--Losses) Odds Ratio=68.8Odds Ratio=68.8

Observed Pred.Losses Pred.Survivors CorrectObserved Pred.Losses Pred.Survivors Correct LossesLosses 42 7 85.7% 42 7 85.7% 5-Year Survivors 5-Year Survivors 5 55 544 91.5% 91.5% Total Total 96 12 96 12 8888.9%.9%

Classification of Cases by Discriminant Analysis, n=108Classification of Cases by Discriminant Analysis, n=108 (5-Year Survivors--Losses)(5-Year Survivors--Losses)

Observed Pred.Losses Pred.Survivors CorrectObserved Pred.Losses Pred.Survivors Correct LossesLosses 46 3 93.9% 46 3 93.9% 5-Year Survivors 5-Year Survivors 22 5757 96.6% 96.6% Total Total 103 5 103 5 9595.4%.4%

Classification of Cases by Neural Networks, n=108 (5-Year Survivors--Losses)

Observed Pred.Losses Pred.Survivors Correct Losses 49 0 100% 5-Year Survivors 0 59 100% Total 49 59 100%

Immunity Networks and 5-Year Survival of Lung Cancer Patients, Immunity Networks and 5-Year Survival of Lung Cancer Patients, n=108n=108

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

0 2 4 6 8 10 12

0.1

10

100

Early Cancer; 5-Year Survival=100%Invasive Cancer, Stage II; 5-Year Survival=76%Invasive Cancer, Stage III; 5-Year Survival=53%Generalization; 5-Year Survival=0%

Model "Lung Cancer---Cytotoxic Cells"

Lung Cancer Cell Population

Cyt

otox

ic C

ell P

opul

atio

n

11

0.473

X1 3

X2 3

X3 3

X4 3

110.082 X1 2 X2 2

X3 2 X4 2

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

0 100 200 300 400

0.1

10

100

Cytotoxic CellsLung Cancer Cells

Model "Lung Cancer---Cytotoxic Cells"

Time

Lung

Cel

l Pop

ulat

ion

Dyn

amic

s11

0.185

X1 2

X1 3

3000 X1 1

Lung Cancer DynamicsLung Cancer Dynamics

SUPERONCOPROGNOSIS-1.0

PROGNOSIS SURVIVAL-2

PROG-1 PROG-2 PROG-3 E

SURVIVAL LESS 5 YEARS SURVIVAL MORE 5 YEARS

SURVIVAL-1

A B

C

Conclusions:Conclusions: 5-year survival of lung cancer patients after complete 5-year survival of lung cancer patients after complete

resections significantly depended on: resections significantly depended on: 1) level of T-, B- and K-cell circuit;1) level of T-, B- and K-cell circuit; 2) value of monocyte- and macrophage-circuit; 2) value of monocyte- and macrophage-circuit; 3) level of humoral immunity;3) level of humoral immunity; 4) ratio of malignant cell population quantity to immunity cell 4) ratio of malignant cell population quantity to immunity cell

subpopulations in integral patient’s organism (immune cell subpopulations in integral patient’s organism (immune cell ratio factors);ratio factors);

5) cancer characteristics;5) cancer characteristics; 6) blood cell circuit;6) blood cell circuit; 7) hemostasis system;7) hemostasis system; 8) biochemic homeostasis;8) biochemic homeostasis; 9) anthropometric data.9) anthropometric data.

Oleg Kshivets, M.D., Ph.D. Oleg Kshivets, M.D., Ph.D. Thoracic Surgeon, Department of SurgeryThoracic Surgeon, Department of Surgery

Siauliai Cancer Center, Tilzes:42-16, LT5400 Siauliai, LithuaniaSiauliai Cancer Center, Tilzes:42-16, LT5400 Siauliai, Lithuania Tel. (37041)416614; Fax 1(270)9687098Tel. (37041)416614; Fax 1(270)9687098

kshivets@yahoo.comkshivets@yahoo.com http//:myprofile.cos.com/Kshivetshttp//:myprofile.cos.com/Kshivets