Kshivets O. Lung Cancer Surgery

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NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES PNEUMONECTOMIES Oleg Kshivets, MD, PhD Oleg Kshivets, MD, PhD Surgery Department,Siauliai Cancer Center, Surgery Department,Siauliai Cancer Center, Lithuania Lithuania The Society of Cardiothoracic Surgeons of Great Britain The Society of Cardiothoracic Surgeons of Great Britain and Ireland Annual and Ireland Annual Scientific Scientific Meeting Meeting , , London London , the UK, , the UK, March March 5-8, 2005. 5-8, 2005.

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NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES

Transcript of Kshivets O. Lung Cancer Surgery

Page 1: Kshivets O. Lung Cancer Surgery

NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG

CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES PNEUMONECTOMIES

  

 Oleg Kshivets, MD, PhDOleg Kshivets, MD, PhD

Surgery Department,Siauliai Cancer Center, LithuaniaSurgery Department,Siauliai Cancer Center, LithuaniaThe Society of Cardiothoracic Surgeons of Great Britain and Ireland AnnualThe Society of Cardiothoracic Surgeons of Great Britain and Ireland Annual

ScientificScientific Meeting Meeting,, London London, the UK, March, the UK, March 5-8, 2005. 5-8, 2005.

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AbstractAbstractNEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OFNON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES Oleg Kshivets Surgery Department, Siauliai Cancer Center, LithuaniaOBJECTIVE: The potential prognostic clinicomorphological factors for outcome of non-small lung cancer (LC) patients (LCP) after surgery were investigated.METHODS: In trial (1985-2004) the data of consecutive 511 LCP after complete resections R0 (age=57.1±0.4 years; male=460, female=51; tumor diameter: D=4.6±0.1 cm; pneumonectomy=212, upper lobectomy=173, lower lobectomy=93, middle lobectomy=7, bilobectomy=26, combined procedures with resection of pericardium, left atrium, aorta, v. cava superior, carina, diaphragm, ribs=143; only surgery-S=310, adjuvant chemoimmunoradiotherapy-AT=99: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy, postoperative radiotherapy 45-50Gy-RT=102) with stage II-III (squamous cell=329, adenocarcinoma=144, large cell=38; stage II=171, stage III=340; T1=143, T2=225, T3=112, T4=31; N0=297, N1=116, N2=98; G1=122, G2=144, G3=245) was reviewed. Variables selected for 5YS study were input levels of blood, biochemic and hemostatic factors, sex, age, 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, Cox regression, clustering, discriminant analysis, structural equation modeling, Monte Carlo and bootstrap simulation were used to determine any significant regularity. RESULTS: For total of 511 LCP overall life span (LS) was 57.7±1.9 months and 5-year (5Y) survival (5YS) reached 57.9%. 296 LCP (age=56.1±0.5 years; LS=86.1±2.0 months; D=4.3±0.1 cm) lived more than 5Y without LC progressing. 185 LCP (age=57.2±0.6 years; LS=18.7±0.9 months; D=5.0±0.2 cm) died because of LC during first 5Y after surgery. . Cox modeling displayed that 5YS of LCP significantly depended on: N0-2 (P=0.000), AT (P=0.000), histology (P=0.001), T1-4 (P=0.024), age (P=0.006), weight (P=0.000), 16 blood factors (P=0.000-0.041). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS of LCP and N0-2 (rank=1), LC growth (2), S (3), T1-4 (4), procedure type (5), G1-3 (6), histology (7), RT (8), AT (9), ESS (10), blood protein (11), prothrombin index (12), gender (13), percent of segmented neutrophils (14), D (15), percent of lymphocytes (16), ratio of monocytes/LC cells (LCC) (17), thrombocytes/LCC (18), eosinophils/LCC (19), healthy cells/LCC (20), leucocytes/LCC (21), blood glucose (22), lymphocytes/LCC (23), blood bilirubin (24). Correct prediction of LCP survival after surgery was 76.6% by logistic regression, 81.3% by discriminant analysis and 99.8% by neural networks computing (error=0.0456; urea under ROC curve=0.996).

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Factors:1) Antropometric Factors…………...42) Blood Analysis…………………...263) Hemostasis Factors……………….84) Cell Ratio Factors………………...9 5) Lung Cancer Characteristics…….86) Biochemic Factors………………...57) Treatment Characteristics……….58) Survival Data……………………...3 In All……………………………….68

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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:……...….. 68Number of Possible Combination for Random Search:……………..………………….. n!=68!=2.48e+96 Operation Time of IBM Blue Gene/L Supercomputer (70.72TFLOPS) ………………………….1.11e+75 YearsThe Age of Our Universe……….....1.3e+10Years

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Basis:Basis:

NP RP P n! n*n*2(e+n) or n log n n AI CSA+S+B SM

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Antropometric Factors:

Male………….…………..460Female………..……………51Age……..…….57.1±0.4 yearsWeight………...……70±05 kgHeight…………168.5 ±0.3 cm

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Radical Procedures:Radical Procedures:Pneumonectomy………………..212Upper/Lower Bilobectomy…...…26Upper Lobectomy…………...…173Lower Lobectomy……………….93Middle Lobectomy………….…….7In All…………………………....511

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Combined & Extensive Radical Procedures with Resection of Pericardium, Left Atrium, Aorta, Vena Cava Superior, Vena Azygos, Carina, Trachea, Diaphragm, Chest Wall, Ribs, etc.…………………….143

Sistematic MediastinalSistematic MediastinalLymph Node-N2 Lymph Node-N2 Dissection…………..Dissection…………..386386

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Staging:Staging:

T1…..143 N0..…297 G1…..122T2…..225 N1…..116 G2…..144T3…..112 N2……98 G3…..245T4……31 Stage II...171 Stage III...340Squamous Cell Carcinoma…..……….329Adenocarcinoma………………………144Large Cell Carcinoma………………….38Central…………211 Peripherical…..300

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Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies by TNMG-system (n=481)

Discriminant Function Analysis Summary Wilks' Lambda: 0.812 approx. F (4,476)=27.472 p< 0.0000

Wilks' Partial F-remove P-level Lambda Lambda (1,476)

Histology .814560 .997400 1.24064 .265909G1-3 .816419 .995129 2.32995 .127570T1-4 .818500 .992559 3.54892 .060194N0-2 .954873 .850838 83.44819 .000000

Logistic Regression Analysis Summary Chi2=92.530; df=4; P=0.00000; Odds Ratio=5.696

Est. S.E. Wald P Odds 95.0% C.I.for Odds Ratio Ratio Lower Upper

Const.B 2.351 .453 26.929 .0000 10.493 4.308 25.556Histology -.134 .125 1.147 .2847 .874 .683 1.119G1-3 -.199 .132 2.271 .1325 .820 .632 1.062T1-4 -.246 .130 3.562 .0597 .782 .606 1.010N0-2 -1.090 .138 62.281 .0000 .336 .256 0.441

Classification of Cases by Logistic Regression and Discriminant Analysis, n=481(5-Year Survivors--Losses) Odds Ratio=5.696

Observed Pred.Losses Pred.Survivors CorrectLosses 83 102 44.9%5-Year Survivors 37 259 87.5%

Total 120 361 71.1%

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Survival Rate of Lung Cancer Patients after Survival Rate of Lung Cancer Patients after Lobectomies and Pneumonectomies (R0) (n=511):Lobectomies and Pneumonectomies (R0) (n=511):Surgery alone………………………………..310 (60.7%)P/o Radiotherapy…………………………....102 (20%)Adjuvant Chemoimmunoradiotherapy……..99 (19.3%) Alive………………………………………….304 (59.5%)5-Year Survivors…………………………….296 (57.9%) Losses from Lung Cancer…………………..185 (36.2%)Life Span………………………………..57.7±1.9 months 5-Year Survivors after Surgery alone……...194 (62.6%)5-Year Survivors after P/o Radiotherapy.…..48 (47.1%)5-Year Survivors after Adjuvant Chemoimmunoradiotherapy…………………54 (54.5%)

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Adjuvant Therapy after Lobectomies and Pneumonectomies:Adjuvant Therapy after Lobectomies and Pneumonectomies:Adjuvant Chemoimmunoradiotherapy (n=99): 1 cycle of bolus chemotherapy (CAVT) was initiated 10-14 days after resections and consisted of Cyclophosphamid 500 mg/m2 IV on day 1, Doxorubicin 50 mg/m2 IV on day 1, Vincristin 1.4 mg/m2 IV on day 1. Immunotherapy consisted Thymalin or Taktivin 20 mg IM on days 1, 2, 3, 4 and 5. Chest radiotherapy (45-50 Gy) was administered since 7 day after 1 cycle chemoimmunotherapy at a daily dose of 1.8-2 Gy. No prophylactic cranial irradiation was used. From 2 to 3 weeks after completion of radiotherapy 3-4 courses of CAVT were repeated every 21-28 day. Chemotherapy by gemzar 1250 mg/m2 IV on day 1, 8, 15 and cisplatin 75 mg/m2 on day 1 was initiated on 14 day after surgery and was repeated every 14 day (5-6 courses). P/o Radiotherapy (n=102): Radiotherapy (60CO; ROKUS, Russia) with a total tumor dose 45-50 Gy (2-4 weeks after surgery) consisted of single daily fractions of 180-200 cGy 5 days weekly. The treatment volume included the ipsilateral hilus, the supraclavicular fossa and the mediastinum from the incisura jugularis to 5-7 cm below the carina. The lower mediastinum was included in cases of primary tumors in the lower lobes. The resected tumor bed was included in all patients. Parallel-opposed AP-PA fields were used. All fields were checked using the treatment planning program COSPO. Doses were specified at middepth for parallel-opposed technique or at the intersection of central axes for oblique technique. No prophylactic cranial irradiation was used.

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Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)

Factors Mean±SD Mean±SD (Survivors) (Losses) P n=296 n=185Life Span (Months) 86.1±34.4 18.7±12.8 0.000000Weight (kg) 71.6±10.9 67.3±11.5 0.00005Tumor Size (cm) 4.3±1.8 5.0±2.4 0.00018Eosinophils (%) 3.0±2.5 2.2±1.9 0.00029Eosinophils (abs) 0.19±0.19 0.13±0.13 0.00055Eosinophils (tot) 0.95±0.97 0.62±0.61 0.00005Seg.Neutrophils (%) 64.5±11.5 68.7±10.1 0.00005Lymphocytes (%) 25.0±9.9 22.7±8.8 0.01158Lymphocytes (abs) 1.54±0.83 1.37±0.73 0.02045 Lymphocytes (tot) 7.71±4.34 6.39±3.44 0.00050Monocytes (%) 5.2±3.1 4.4±2.6 0.00290Monocytes (abs) 0.33±0.27 0.28±0.22 0.01957Monocytes (tot) 1.67±1.35 1.32±1.14 0.00360Erythrocytes (tot) 21.05±4.43 19.41±4.77 0.00015ESS 17.6±14.4 21.1±16.5 0.01331

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Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)

Factors Mean±SD Mean±SD (Survivors) (Losses) P n=296 n=185Thrombotest 4.8±0.8 4.6±0.9 0.01465Fibrinogen-B 1.2±0.4 1.4±0.8 0.00052Heparin Tolerance 186.9±67.9 228.5±127.1 0.000004Prothrombin Index 93.6±8.7 99.2±8.2 0.000000Glucose 4.7±1.0 4.5±0.9 0.02299Leucocytes/CaCells 8.2±4.4 6.7±3.4 0.00006Eosinophils/CaCells 0.25±0.27 0.14±0.14 0.000000St.Neutrophils/ CaCells 0.21±0.31 0.14±0.21 0.00995 Seg.Neutrophils/CaCells 5.2±3.0 4.6±2.5 0.01393Lymphocytes/CaCells 2.1±1.4 1.5±1.0 0.000002Monocytes/CaCells 0.45±0.40 0.29±0.24 0.000003Erythrocytes/CaCells 5.7±2.4 4.7±2.1 0.000002Thrombocytes/CaCells 308.7±150.1 258.1±114.3 0.000096 Healthy Cells/CaCells 19.5±7.5 16.2±6.9 0.000002

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Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)

Factors Log-Rank Test P

O(I) vs. A(II) 0.03687G1 vs. G3 0.00061T1 vs. T2 0.00460T1 vs. T3 0.01848T1 vs. T4 0.00041T2 vs. T4 0.02097T3 vs. T4 0.03976N0 vs. N1 0.00000 N0 vs. N2 0.00000 N1 vs. N2 0.00001Stage II vs. Stage III 0.00000Surgery alone vs. P/o Radiotherapy 0.00046Ad.Chemioimmunoradiotherapy vs. P/o Radiotherapy 0.00025

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Product-Limit (Kaplan-Maier) Analysis Results in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=511)

Graph of Survival Times vs. Cum. Proportion Surviving

Survival FunctionComplete Censored

Survival Rate of Lung Cancer Patients after Lobectomies and Pneumonectomiesn=511

Survival Time (Years after Lobectomies and Pneumonectomies)

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Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)

Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored

Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511 O(I) vs. A(II) Long-rank test P=0.03685

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Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)

Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored

Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511G1 vs. G3 Long-rank test P=0.00061

Survival Time (Years after Lobectomies and Pneumonectomies)

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Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)

Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored

Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511T1 vs. T2, P=0.0046; T1 vs. T3, P=0.01848; T1 vs.T4, P=0.00041;

T2 vs. T4, P=0.02097; T3 vs. T4, P=0.03976 (by Long-rank test)

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Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)

Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored

Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511N0 vs. N1, P=0.00000; N0 vs. N2, P=0.00000

N1 vs. N2, P=0.00001 (by Long-rank test)

Survival Time (Years after Lobectomies and Pneumonectomies)

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Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)

Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored

Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511Surgery alone vs. P/o Radiotherapy, P=0.00046;

Adjuvant Chemoimmunoradiotherapy vs. P/o Radiotherapy, P=0.00025 (by Long-rank t

Survival Time (Years after Lobectomies and Pneumonectomies)

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Results of Multivariate Proportional Hazard Cox Regression Analysis:

Chi2=312.447; df=37; n=511; P=0.000000Factors Wald df P Exp(B) 95%CI for Exp(B) Lower UpperAge 7.553 1 0.006 1.018 1.005 1.031Weight 12.368 1 0.000 0.942 0.911 0.974Histology 13.631 2 0.001Histology(1) 13.271 1 0.000 0.430 0.273 0.677Histology (2) 12.094 1 0.001 0.409 0.247 0.677G1-3 5.652 2 0.059G1-3(1) 1.706 1 0.191 0.835 0.637 1.094G1-3(2) 1.113 1 0.292 1.148 0.888 1.483T1-4 9.447 3 0.024T1-4(1) 6.664 1 0.010 0.410 0.209 0.807T1-4(2) 7.778 1 0.005 0.447 0.254 0.787T1-4(3) 3.852 1 0.050 0.578 0.335 0.999N0-2 47.796 2 0.000N0-2(1) 46.895 1 0.000 0.357 0.266 0.479N0-2(2) 16.061 1 0.000 0.515 0.373 0.713

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Results of Multivariate Proportional Hazard Cox Regression Analysis:

Chi2=312.447; df=37; n=511; P=0.000000Factors Wald df P Exp(B) 95%CI for Exp(B) Lower UpperTumor Size 2.720 1 0.099 1.086 0.985 1.199Thrombocytes 4.271 1 0.039 0.990 0.980 0.999Seg.Neutrophils(%) 2.776 1 0.096 1.034 0.994 1.076Lymphocytes(%) 4.431 1 0.035 1.049 1.003 1.097ESS 10.559 1 0.001 0.987 0.980 0.995Prothrombin Index 34.344 1 0.000 1.034 1.023 1.046Bilirubin 5.394 1 0.020 1.041 1.006 1.076Recalcification Time 9.152 1 0.002 0.996 0.993 0.999Heparin Tolerance 29.782 1 0.000 1.003 1.002 1.005Ad.CHIRT 33.555 1 0.000 2.920 2.032 4.196Leucocytes/CaCells 8.214 1 0.004 0.731 0.590 0.906Thrombocytes/CaCells 1.976 1 0.160 0.998 0.996 1.001Eosinophils/CaCells 47.796 1 0.037 3.444 1.080 10.976Seg.Neutrophils/CaCells 46.895 1 0.003 1.555 1.160 2.084Healthy Cells/CaCells 4.514 1 0.034 1.057 1.004 1.112

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Results of Multivariate Proportional Hazard Cox Regression Analysis:

Chi2=312.447; df=37; n=511; P=0.000000

Factors Wald df P Exp(B) 95%CI for Exp(B)Lower Upper

Seg.Neutrophils (tot) 10.971 1 0.001 0.821 0.731 0.923Lymphocytes (tot) 8.676 1 0.003 0.816 0.713 0.934Leucocytes (tot) 11.348 1 0.001 1.189 1.075 1.315Eosinophils (tot) 5.908 1 0.015 0.691 0.512 0.931Thrombocytes (tot) 11.146 1 0.001 1.003 1.001 1.005Operation 1.544 4 0.819Operation(1) 0.458 1 0.499 0.863 0.563 1.322Operation(2) 0.389 1 0.533 0.867 0.554 1.358Operation(3) 0.001 1 0.980 0.994 0.620 1.593Operation(4) 0.057 1 0.811 0.896 0.364 2.203Surgery alone 3.066 1 0.080 1.265 0.972 1.645Fibrinogen 4.180 1 0.041 1.078 1.003 1.158

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Results of Multifactor Analysis in Prediction of Lung Cancer Results of Multifactor Analysis in Prediction of Lung Cancer

Patients Survival after Lobectomies and Pneumonectomies (n=511)Patients Survival after Lobectomies and Pneumonectomies (n=511) Factor Loadings, Factor 1 vs. Factor 2

Rotation: Varimax normalizedExtraction: Principal components

Prediction of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511

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Results of Discriminant Analysis in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Discriminant Function Analysis Summary

Wilks' Lambda: 0.601 approx. F (59,421)=4.735 p< 0.0000Wilks' Partial F-remove P-level Lambda Lambda (1,421)

Ad.CHTITR .607564 .989364 4.52592 .033966PI .621404 .967328 14.2193 .000186N0-2 .675599 .889731 52.1766 .000000Recalcificat.Time .613179 .980303 8.45919 .003824Fibrinogen-B .613035 .980533 8.35821 .004038G1-3 .605988 .991937 3.42216 .065027Histology .606000 .991917 3.43069 .064695T1-4 .602375 .997886 0.89167 .345566Growth .603213 .996500 1.47861 .224673Tumor Size .601970 .998557 0.60837 .435841weight .604121 .995002 2.11483 .146623Erythrocytes .602821 .997148 1.20419 .273113Protein .602782 .997212 1.17719 .278550P/o RT .601136 .999942 0.02449 .875716Surgery alone .601688 .999026 0.41053 .522049Operation type .603138 .996624 1.42627 .233047Lymphocytes .601366 .999560 0.18539 .667001Leucocytes/CC .601948 .998594 0.59281 .441766

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Results of Logistic Regression Analysis in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Chi2=158.07; df=14; P=0.00000; Odds ratio=9.71

Est. S.E. Wald P Odds 95.0% C.I.for Odds Ratio Ratio Lower Upper

Const.B 7.987 2.981 7.181 .0074 2943.597 8.418 1029324Growth -.313 .267 1.378 .2405 .731 .432 1.235Histology -.347 .154 5.053 .0250 .707 .521 .957G1-3 -.240 .148 2.656 .1039 .786 .588 1.051T1-4 -.027 .198 0.020 .8879 .972 .659 1.435N0-2 -1.191 .164 52.87 .0000 .304 .220 .419S.Neut.(abs) -.137 .052 7.004 .0084 .872 .788 .965Mon. (abs) 1.604 .572 7.852 .0050 4.972 1.615 15.313ESS -.013 .008 2.454 .1179 .987 .972 1.003Proth.Index -.071 .014 26.80 .0000 .932 .907 .957Operation -.141 .113 1.545 .2145 .869 .695 1.085P/o RT -.019 .627 0.001 .9752 .981 .286 3.360Ad.CHIRT 1.256 .600 4.385 .0368 3.510 1.080 11.405Surg. alone .159 .703 0.051 .8213 1.172 .294 4.670Healt.C/CC .035 .023 2.320 .1284 1.036 .990 1.084

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Results of Clustering in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Logical Formulas based on Simple MeanLosses: N2 ( 6.7%) & 74.00 <= PI ( 12.0%) <= 120.00 & 72.60 <= Heparin Tolerance ( 5.7%) <= 796.20 & 0.00 <= Eosinophils/CaCells ( 6.5%) <= 0.69 & 3.33 <= Healthy Cells/CaCells ( 5.9%) <= 35.65

Objects 185 Error1 = 0.63 (117) Error2 = 0.08 (24)5-Year Survivors: no N2 ( 6.7%) & 60.00 <= PI ( 12.0%) <= 119.00 & 24.00 <= Heparin Tolerance ( 5.7%) <= 484.20 & 0.00 <= Eosinophils/CaCells ( 6.5%) <= 1.53 & 4.17 <= Helthy Cells/CaCells ( 5.9%) <= 40.00

Objects 296 Error1 = 0.08 (24) Error2 = 0.57 (105)

Page 29: Kshivets O. Lung Cancer Surgery

Results of Multifactor Clustering of Clinicomorphologic Factors in Prediction of Results of Multifactor Clustering of Clinicomorphologic Factors in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Page 30: Kshivets O. Lung Cancer Surgery

Results of Results of CorrespondenceCorrespondence Analysis in Prediction of Analysis in Prediction of LungLung Cancer Cancer Patients Survival after Lobectomies and Pneumonectomies (n=Patients Survival after Lobectomies and Pneumonectomies (n=481481))

Page 31: Kshivets O. Lung Cancer Surgery

Results of Results of CorrespondenceCorrespondence Analysis in Prediction of Analysis in Prediction of LungLung Cancer Cancer Patients Survival after Lobectomies and Pneumonectomies (n=Patients Survival after Lobectomies and Pneumonectomies (n=481481))

Page 32: Kshivets O. Lung Cancer Surgery

Results of Results of CorrespondenceCorrespondence Analysis in Prediction of Analysis in Prediction of LungLung Cancer Cancer Patients Survival after Lobectomies and Pneumonectomies (n=Patients Survival after Lobectomies and Pneumonectomies (n=481481))

Page 33: Kshivets O. Lung Cancer Surgery

Results of Results of CorrespondenceCorrespondence Analysis in Prediction of Analysis in Prediction of LungLung Cancer Cancer Patients Survival after Lobectomies and Pneumonectomies (n=Patients Survival after Lobectomies and Pneumonectomies (n=481481))

Page 34: Kshivets O. Lung Cancer Surgery

Classification Tree in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Losses 5-year survivors

Total 185 296 Correct Classification Rate=79.2%Correct 120 261 Wrong 65 35

Predictor Variable Importance RankingsDependent variable: Losses---5-Year Survivors (n=481)

Rankings on scale from 0=low importance to 100=high importancePrediction of Lung Cancer Patients Survival after Lobectomies & Pneumonectomies

Predictor variable

Ran

king

0

20

40

60

80

100

SEX

GR

OU

THH

IST G T

N12

_0TR

EAT

AG

EM

ASS

A D ER HB

THR L E P S

LYM M

SOE

CO

AG

_BT_

HEM

GLU PI

BILI

RPR

OT

T_R

ECTH

R_T

FIBR

_BFI

BRTO

L_H

EPER

_CC

THR

__C

CL_

CC

E_C

CP_

CC

S_C

CLY

M_C

CM

_CC

MA

SS_C

CER

_TO

TTH

R_T

OT

L_TO

TE_

TOT

P_TO

TS_

TOT

LYM

_TO

TM

_TO

T

Page 35: Kshivets O. Lung Cancer Surgery

Classification Tree in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Classification Tree for Lung Cancer Patients SurvivalPrediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomie

Number of splits = 11; Number of terminal nodes = 12

1

2 3

4 5

6 7 8 9

10 11 12 13 14 15

16 17 18 19

20 21

22 23

N12_0=N2

PI107.64

PI94.369 AGE 58.021

FIBR_B 1.8848 N12_0=N1 LYM 14.523

N12_0=N1,N2 TOL_HEP 244.95

MASSA 67.48

G=G3

92 389

346 43

178 168 23 20

150 28 51 117 5 15

8 20 36 15

16 20

9 11

l>5

d<5 l>5

l>5 l>5

l>5 l>5 l>5 d<5

l>5 l>5 d<5 l>5 l>5 d<5

d<5 l>5 d<5 d<5

d<5 l>5

d<5 l>5

d<5l>5

Page 36: Kshivets O. Lung Cancer Surgery

Neural Networks in Prediction of Lung Cancer Patients Survival after Neural Networks in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Lobectomies and Pneumonectomies (n=481)

Losses 5-year survivors Baseline Errors=0.0456;Total 185 296 Area under ROC curve=0.996;

Correct 184 296 Correct Classification Rate=99.8%Wrong 1 0

Genetic Algorithm SelectionUseful for Sex G1-3 T1-4 N0-2 Tumor Size Seg.Neutrophils(%) Lymphocytes(%) ESS Survival Yes Yes Yes Yes Yes Yes Yes Yes Useful for Prothr.Index Protein Ad.CHIRT Thromb./CC Eosin./CC Lymph./CC HealC/CC Survival Yes Yes Yes Yes Yes Yes Yes

Training Error Graph (Sum-squared)Prediction of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=481

Network: (MLP) Error=0.0456Area under ROC curve=0.996

Correct Classification Rate=99.8%

Epoch

Erro

r

0.0

0.2

0.4

0.6

0 20 40 60 80

Training by Levenberg-Marquardt, n=481

Page 37: Kshivets O. Lung Cancer Surgery

Results of Neural Networks Computing in Prediction of Lung Cancer Patients Survival after Lobectomies and

Pneumonectomies (n=481)

Error=0.0456; Area under ROC Curve=0.996; Correct Classification Rate=99.8%

Factor Rank Error RatioN0-2 1 0.470 10.317Growth 2 0.414 9.069Surgery alone 3 0.387 8.480T1-4 4 0.313 6.863Operation type 5 0.312 6.853G1-3 6 0.311 6.814Histology 7 0.292 6.404P/o RT 8 0.218 4.774Ad.CHIRT 9 0.209 4.579ESS 10 0.175 3.838Protein 11 0.175 3.836Prothr.Index 12 0.150 3.285

Factor Rank Error RatioSex 13 0.129 2.829Seg.Neutr.(%) 14 0.106 2.326Tumor Size 15 0.091 2.001Lymph. (%) 16 0.089 1.958Monocytes/CC 17 0.080 1.749Thromb./CC 18 0.078 1.704Eosinoph./CC 19 0.075 1.650Health.C/CC 20 0.072 1.570Leucocytes/CC 21 0.064 1.397Glucose 22 0.046 1.005Lymph./CC 23 0.046 1.004Bilirubin24 0.046 1.000

Page 38: Kshivets O. Lung Cancer Surgery

Results of Neural Networks Computing in Prediction of Lung Cancer Patients Survival with N0 after Lobectomies and

Pneumonectomies (n=274)

Error=0.00318; Area under ROC Curve=1.0; Correct Classification Rate=100%

Factor Rank Error RatioSurgery alone 1 0.289 90.726Growth 2 0.232 72.022T1-4 3 0.210 65.877G1-3 4 0.180 56.593Histology 5 0.158 49.643Oper. Type 6 0.129 40.481Heparin Tol. 7 0.125 39.354Sex 8 0.109 34.264P/o RT 9 0.100 31.362Ad.CHIRT 10 0.077 24.167Fibrinogen 11 0.046 14.307Tumor Size 12 0.045 14.126

Factor Rank Error RatioColor Index 13 0.036 11.361Prothr.Index 14 0.032 10.013Thrombocytes 15 0.029 9.193Recalc.Time 16 0.028 8.727Lymphocytes 17 0.019 6.094Erythrocytes 18 0.015 4.608Protein 19 0.012 3.758ESS 20 0.012 3.736Bilirubin21 0.010 3.271Eosinophils 22 0.009 2.827Eryth./CC 23 0.007 2.334Age 24 0.007 2.190

Page 39: Kshivets O. Lung Cancer Surgery

Results of Neural Networks Computing in Prediction of Lung Cancer Patients Survival with N1 after Lobectomies and

Pneumonectomies (n=115)

Error=0.0007; Area under ROC Curve=1.0; Correct Classification Rate=100%

Factor Rank Error RatioGrowth 1 0.326 479.79Oper.Type 2 0.311 458.33G1-3 3 0.304 448.13Surgery alone 4 0.270 397.90Prothr.Index 5 0.201 296.07T1-4 6 0.194 285.29P/o RT 7 0.181 266.85Histology 8 0.156 230.13Ad.CHIRT 9 0.139 204.86Heparin Tol. 10 0.133 195.71Thrombocytes 11 0.095 139.76Fibrinogen 12 0.094 138.29

Factor Rank Error RatioRecalc.Time 13 0.092 135.66Sg.Neutrophils 14 0.058 85.353Tumor Size 15 0.036 53.551Eosinophils 16 0.013 19.082Lymphocytes 17 0.010 14.699Glucose 18 0.009 13.404Erythrocytes 19 0.008 11.934Monocytes 20 0.007 10.742Weight 21 0.007 10.361Leucocytes 22 0.003 4.969Age 23 0.002 2.991Hemoglobin 24 0.002 2.819

Page 40: Kshivets O. Lung Cancer Surgery

Results of Neural Networks Computing in Prediction of Lung Cancer Patients Survival with N2 after Lobectomies and

Pneumonectomies (n=92)

Error=0.0008; Area under ROC Curve=1.0; Correct Classification Rate=100%

Factor Rank Error RatioAd.CHIRT 1 0.304 362.21P/o RT 2 0.236 282.08Surgery alone 3 0.189 225.69Histology 4 0.188 223.93T1-4 5 0.183 217.82Oper.Type 6 0.178 211.96Prothr.Index 7 0.169 201.18G1-3 8 0.159 189.62Growth 9 0.145 173.45Monocytes % 10 0.124 147.55Bilirubin11 0.119 141.68Sex 12 0.104 124.44

Factor Rank Error RatioSg.Neutrophils 13 0.056 66.814Leucocytes 14 0.025 30.316Lymphocytes 15 0.025 29.263Monocytes abs 16 0.015 18.396Sg.Neutr./CC 17 0.013 15.026Hemor.Time 18 0.009 10.996Monocytes/CC 19 0.007 8.408ESS 20 0.006 7.094Recalc.Time 21 0.005 5.700Glucose 22 0.004 4.221Heparin Tol. 23 0.003 4.117Lymphocytes t 24 0.002 2.819

Page 41: Kshivets O. Lung Cancer Surgery

Decision Tree in Prediction of Lung Cancer Patients Survival with N0 (n=274) and with N2

(n=92) after Lobectomies and Pneumonectomies

Page 42: Kshivets O. Lung Cancer Surgery

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

with N0 (n=274) and with N2 (n=92) after Lobectomies and Pneumonectomies

Page 43: Kshivets O. Lung Cancer Surgery

Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored

Prediction of Lung Cancer Patients Survival with N0, n=297 Surgery alone vs. P/o RT, P=0.021 by long-rank test

Years after Lobectomies and Pneumonectomies

Cum

ulat

ive

Prop

ortio

n Su

rviv

ing

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 2 4 6 8 10 12 14 16 18 20 22

Surgery alone P/o RT Ad. CHIRT

Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) with N0 (n=297), with N1-2 (n=214), with N1 (n=116) and

with N2 (n=98)

Page 44: Kshivets O. Lung Cancer Surgery

Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) with N0 (n=297), with N1-2 (n=214), with N1 (n=116) and

with N2 (n=98)

Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored

Prediction of Lung Cancer Patients Survival with N1-2, n=214Ad.CHIRT vs. Surgery alone P=0.0001 by long-rank test

Ad.CHIRT vs. P/o RT P=0.0010 by long-rank test

Years after Lobectomies and Pneumonectomies

Cum

ulat

ive

Prop

ortio

n Su

rviv

ing

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 2 4 6 8 10 12 14 16 18

Surgery alone P/o RT Ad.CHIRT

Page 45: Kshivets O. Lung Cancer Surgery

Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) with N0 (n=297), with N1-2 (n=214), with N1 (n=116) and

with N2 (n=98) Cumulative Proportion Surviving (Kaplan-Meier)

Complete CensoredPrediction of Lung Cancer Patients Survival with N1, n=116

Ad.CHIRT vs. Surgery alone, P=0.004 by long-rank test

Years after Lobectomies and Pneumonectomies

Cum

ulat

ive

Prop

ortio

n Su

rviv

ing

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0 2 4 6 8 10 12 14 16

Surgery alone P/o RT Ad.CHIRT

Page 46: Kshivets O. Lung Cancer Surgery

Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) with N0 (n=297), with N1-2 (n=214), with N1 (n=116) and

with N2 (n=98) Cumulative Proportion Surviving (Kaplan-Meier)

Complete CensoredPrediction of Lung Cancer Patients Survival with N2, n=98 Ad.CHIRT vs. Surgery alone, P=0.0004 by long-rank test

Ad.CHIRT vs. P/o RT, P=0.0002 by long-rank test

Years after Lobectomies and Pneumonectomies

Cum

ulat

ive

Prop

ortio

n Su

rviv

ing

0.00.10.20.30.40.50.60.70.80.91.0

0 2 4 6 8 10 12 14 16 18

Surgery alone P/o RT Ad.CHIRT

Page 47: Kshivets O. Lung Cancer Surgery

Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Number of Samples=3333Significant Factors Rank Kendall’s Tau-A PN0-2 1 -0.2080 0.000000Lymphocytes/CaCells 2 0.1737 0.000000Erythrocytes/CaCells 3 0.1731 0.000000Prothrombin Index 4 0.1709 0.000000Erythrocytes (tot) 5 0.1576 0.000000Thrombocytes/CaCells 6 0.1474 0.000001Leucocytes/CaCells 7 0.1431 0.000003Lymphocytes (tot) 8 0.1217 0.000067Eosinophils/CaCells 9 0.1209 0.000081Healthy Cells/CaCells 10 0.1172 0.000113Weight 11 0.1144 0.000124Monocytes/CaCells 12 0.1134 0.000172

Page 48: Kshivets O. Lung Cancer Surgery

Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Number of Samples=3333Significant Factors Rank Kendall’s Tau-A PSegmented Neutrophils (%) 13 -0.1003 0.000421Eosinophils (tot) 14 0.0944 0.001310Tumor Size 15 -0.0837 0.006102Eosinophils (%) 16 0.0836 0.006164T1-4 17 -0.0817 0.008210Monocytes (tot) 18 0.0805 0.008354 Heparin Tolerance 19 -0.0782 0.010123Eosinophils (abs) 20 0.0770 0.011639Monocytes (%) 21 0.0711 0.012002G1-3 22 -0.0701 0.024204Glucose 23 0.0600 0.049998

Page 49: Kshivets O. Lung Cancer Surgery

Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Page 50: Kshivets O. Lung Cancer Surgery

Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Page 51: Kshivets O. Lung Cancer Surgery

Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Page 52: Kshivets O. Lung Cancer Surgery

Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Classification of Cases by Logistic Regression, n=481(5-Year Survivors--Losses) Odds Ratio=9.71

Observed Pred.Losses Pred.Survivors CorrectLosses 114 71 61.6%5-Year Survivors 42 254 85.8%Total 156 325 76.6%

Classification of Cases by Discriminant Analysis, n=481(5-Year Survivors--Losses)

Observed Pred.Losses Pred.Survivors CorrectLosses 128 57 69.2%5-Year Survivors 33 263 88.9%Total 161 320 81.3%

Page 53: Kshivets O. Lung Cancer Surgery

Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)

Classification of Cases by Clastering, n=481(5-Year Survivors--Losses)

Observed Pred.Losses Pred.Survivors CorrectLosses 151 34 81.6%5-Year Survivors 16 280 94.6%Total 167 314 89.6%

Classification of Cases by Neural Networks, n=481(5-Year Survivors--Losses)

Observed Pred.Losses Pred.Survivors CorrectLosses 184 1 99.5%5-Year Survivors 0 296 100.0%Total 184 297 99.8%

Page 54: Kshivets O. Lung Cancer Surgery

Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations Populations & & Blood Glucose Level Blood Glucose Level in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Patients

Survival Survival (n= (n=481481))

Page 55: Kshivets O. Lung Cancer Surgery

Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations Populations & & Blood Glucose Level Blood Glucose Level in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Patients

Survival Survival (n= (n=481481))

Page 56: Kshivets O. Lung Cancer Surgery

Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations Populations & & Blood Glucose Level Blood Glucose Level in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Patients

Survival Survival (n= (n=481481))

Page 57: Kshivets O. Lung Cancer Surgery

Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations Populations & & Blood Glucose Level Blood Glucose Level in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Patients

Survival Survival (n= (n=481481))

Page 58: Kshivets O. Lung Cancer Surgery

Networks between Clinicopathologic, Biochemic, Hemostasis & Hematologic Data and 5-Networks between Clinicopathologic, Biochemic, Hemostasis & Hematologic Data and 5-Year Survival of Lung cancer Patients after Lobectomies and Pneumonectomies (n=481)Year Survival of Lung cancer Patients after Lobectomies and Pneumonectomies (n=481)

Page 59: Kshivets O. Lung Cancer Surgery

Results of Monte Carlo Simulation in Prediction of Lung Cancer Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Patients Survival after Lobectomies and Pneumonectomies (n=481)

-1.958 -1.684 -1.411 -1.138 -0.865 -0.592 -0.318 -0.045 0.228 0.501 above

From: Monte Carlo DataPrediction of Lung Cancer Patients Survival after Lobectomies & Pneumonectomies

Chi2=64.411; df=35; P=0.00178; n=481

Page 60: Kshivets O. Lung Cancer Surgery

Results of Monte Carlo Simulation in Prediction of Lung Cancer Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Patients Survival after Lobectomies and Pneumonectomies (n=481)

-0.441 0.003 0.447 0.891 1.335 1.78 2.224 2.668 3.112 3.556 above

From: Monte Carlo DataPrediction of Lung Cancer Patients Survival after Lobectomies & Pneumonectomies

Chi2=28.09; df=14; P=0.0139; n=481

Page 61: Kshivets O. Lung Cancer Surgery

Results of Monte Carlo Simulation in Prediction of Lung Cancer Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Patients Survival after Lobectomies and Pneumonectomies (n=481)

-0.407 -0.025 0.356 0.737 1.118 1.5 1.881 2.262 2.643 3.025 above

From: Monte Carlo DataPrediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomie

Chi2=41.0; df=27; P=0.0412; n=481

Page 62: Kshivets O. Lung Cancer Surgery

SEPATH Networks in Prediction of Lung Cancer Patients SEPATH Networks in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Survival after Lobectomies and Pneumonectomies (n=481)

Page 63: Kshivets O. Lung Cancer Surgery

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

Page 64: Kshivets O. Lung Cancer Surgery

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

Page 65: Kshivets O. Lung Cancer Surgery

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

Page 66: Kshivets O. Lung Cancer Surgery

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

Page 67: Kshivets O. Lung Cancer Surgery

Lung Cancer Dynamics

Page 68: Kshivets O. Lung Cancer Surgery

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

Page 69: Kshivets O. Lung Cancer Surgery

Conclusions:Conclusions:It was revealed that 5-year survival and life span of lung cancer patients after complete lobectomies and pneumonectomies significantly depended on: 1) lung cancer characteristics;2) level of blood cell subpopulations circuit; 3) cell ratio factors (ratio of total lung cancer cell population to blood cell subpopulations; 4) hemostasis system; 5) biochemic homeostasis; 6) adjuvant treatment.

Page 70: Kshivets O. Lung Cancer Surgery

Patents:1.  Kshivets O.M. Method of Prognosis of

Survival Rate of Radically Operated Patients with Malignant Neoplasms. Patent from 10.02.94; N2101704: 24pp.

2. Kshivets O.M. Method of Prognosis of Survival Rate of Non-Radically Operated Patients with Malignant Neoplasms. Patent from 14.03.94; N2104536: 10pp.

Page 71: Kshivets O. Lung Cancer Surgery

Address:

Oleg Kshivets, M.D., Ph.D.Thoracic Surgeon, Dep.of Surgery, Siauliai Cancer CenterTilzes:42-16, Siauliai, LT5400, LithuaniaTel. (37041)416614 Fax 1(270)9687098

[email protected]//:myprofile.cos.com/Kshivets