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Kshivets O. Lung Cancer Surgery

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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

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

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  • 1. NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES     Oleg Kshivets, MD, PhD Surgery Department,Siauliai Cancer Center, Lithuania The Society of Cardiothoracic Surgeons of Great Britain and Ireland Annual Scientific Meeting , London , the UK, March 5-8, 2005.
  • 2. Abstract
    • NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF
    • NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES Oleg Kshivets Surgery Department, Siauliai Cancer Center, Lithuania
    • OBJECTIVE: 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).
  • 3. Factors:
    • 1) Antropometric Factors…………... 4
    • 2) Blood Analysis…………………... 26
    • 3) Hemostasis Factors………………. 8
    • 4) Cell Ratio Factors………………... 9
    • 5) Lung Cancer Characteristics……. 8
    • 6) Biochemic Factors………………... 5
    • 7) Treatment Characteristics………. 5
    • 8) Survival Data……………………... 3
    • In All………………………………. 68
  • 4. Main Problem of Analysis of Alive Supersystems (e.g. Lung Cancer Patient Homeostasis): Phenomenon of «Combinatorial Explosion»
    • Number of Clinicomorphological Factors:……...….. 68
    • Number of Possible Combination for Random Search:……………..………………….. n!=68!=2.48e+96
    • Operation Time of IBM Blue Gene/L Supercomputer (70.72TFLOPS) …………………………. 1.11e+75 Years
    • The Age of Our Universe………..... 1.3e+10Years
  • 5. Basis:
    • NP  RP  P
    •   
    • n!  n*n*2(e+n) or n log n  n
    •   
    • AI  CSA+S+B  SM
  • 6. Antropometric Factors:
    • Male………….………….. 460
    • Female………..…………… 51
    • Age……..……. 57.1±0.4 years
    • Weight………...…… 70±05 kg
    • Height………… 168.5 ±0.3 cm
  • 7. Radical Procedures:
    • Pneumonectomy……………….. 212
    • Upper/Lower Bilobectomy…...… 26
    • Upper Lobectomy…………...… 173
    • Lower Lobectomy………………. 93
    • Middle Lobectomy………….……. 7
    • In All………………………….... 511
  • 8. Combined & E xtensive R adical P rocedures with R esection of P ericardium, L eft A trium, A orta, V ena C ava S uperior, V ena A zygos, C arina, Trachea, D iaphragm, C hest W all , Ribs, etc.……………………. 143 Sistematic Mediastinal Lymph Node-N2 Dissection………….. 386
  • 9. Staging:
    • T1…..143 N0..…297 G1…..122
    • T2…..225 N1…..116 G2…..144
    • T3…..112 N2……98 G3…..245
    • T4……31 Stage II...171 Stage III...340
    • Squamous Cell Carcinoma…..……….329
    • Adenocarcinoma………………………144
    • Large Cell Carcinoma………………….38
    • Central…………211 Peripherical…..300
  • 10. 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 .265909
    • G1-3 .816419 .995129 2.32995 .127570
    • T1-4 .818500 .992559 3.54892 .060194
    • N0-2 .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 25.556
    • Histology -.134 .125 1.147 .2847 .874 .683 1.119
    • G1-3 -.199 .132 2.271 .1325 .820 .632 1.062
    • T1-4 -.246 .130 3.562 .0597 .782 .606 1.010
    • N0-2 -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 Correct
    • Losses 83 102 44.9%
    • 5-Year Survivors 37 259 87.5%
    • Total 120 361 71 .1%
  • 11. Survival Rate of Lung Cancer Patients after 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%)
  • 12. 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/m 2 IV on day 1, Doxorubicin 50 mg/m 2 IV on day 1, Vincristin 1.4 mg/m 2 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/m 2 IV on day 1, 8, 15 and cisplatin 75 mg/m 2 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 ( 60 CO; 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.
  • 13. Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)
    • Factors Mean±SD Mean±SD
    • (Survivors) (Losses) P
    • n=296 n=185
    • Life Span (Months) 86.1±34.4 18.7±12.8 0.000000
    • Weight (kg) 71.6±10.9 67.3±11.5 0.00005
    • Tumor Size (cm) 4.3±1.8 5.0±2.4 0.00018
    • Eosinophils (%) 3.0±2.5 2.2±1.9 0.00029
    • Eosinophils (abs) 0.19±0.19 0.13±0.13 0.00055
    • Eosinophils (tot) 0.95±0.97 0.62±0.61 0.00005
    • Seg.Neutrophils (%) 64.5±11.5 68.7±10.1 0.00005
    • Lymphocytes (%) 25.0±9.9 22.7±8.8 0.01158
    • Lymphocytes (abs) 1.54±0.83 1.37±0.73 0.02045
    • Lymphocytes (tot) 7.71±4.34 6.39±3.44 0.00050
    • Monocytes (%) 5.2±3.1 4.4±2.6 0.00290
    • Monocytes (abs) 0.33±0.27 0.28±0.22 0.01957
    • Monocytes (tot) 1.67±1.35 1.32±1.14 0.00360
    • Erythrocytes (tot) 21.05±4.43 19.41±4.77 0.00015
    • ESS 17.6±14.4 21.1±16.5 0.01331
  • 14. Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)
    • Factors Mean±SD Mean±SD
    • (Survivors) (Losses) P
    • n=296 n=185
    • Thrombotest 4.8±0.8 4.6±0.9 0.01465
    • Fibrinogen-B 1.2±0.4 1.4±0.8 0.00052
    • Heparin Tolerance 186.9±67.9 228.5±127.1 0.000004
    • Prothrombin Index 93.6±8.7 99.2±8.2 0.000000
    • Glucose 4.7±1.0 4.5±0.9 0.02299
    • Leucocytes/CaCells 8.2±4.4 6.7±3.4 0.00006
    • Eosinophils/CaCells 0.25±0.27 0.14±0.14 0.000000
    • St.Neutrophils/ CaCells 0.21±0.31 0.14±0.21 0.00995
    • Seg.Neutrophils/CaCells 5.2±3.0 4.6±2.5 0.01393
    • Lymphocytes/CaCells 2.1±1.4 1.5±1.0 0.000002
    • Monocytes/CaCells 0.45±0.40 0.29±0.24 0.000003
    • Erythrocytes/CaCells 5.7±2.4 4.7±2.1 0.000002
    • Thrombocytes/CaCells 308.7±150.1 258.1±114.3 0.000096
    • Healthy Cells/CaCells 19.5±7.5 16.2±6.9 0.000002
  • 15. Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)
    • Factors Log-Rank Test P
    • O(I) vs. A(II) 0.03687
    • G1 vs. G3 0.00061
    • T1 vs. T2 0.00460
    • T1 vs. T3 0.01848
    • T1 vs. T4 0.00041
    • T2 vs. T4 0.02097
    • T3 vs. T4 0.03976
    • N0 vs. N1 0.00000 N0 vs. N2 0.00000
    • N1 vs. N2 0.00001
    • Stage II vs. Stage III 0.00000
    • Surgery alone vs. P/o Radiotherapy 0.00046
    • Ad.Chemioimmunoradiotherapy vs. P/o Radiotherapy 0.00025
  • 16. 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
  • 17. Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
  • 18. Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
  • 19. Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
  • 20. Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
  • 21. Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
  • 22. 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
    • Age 7.553 1 0.006 1.018 1.005 1.031
    • Weight 12.368 1 0.000 0.942 0.911 0.974
    • Histology 13.631 2 0.001
    • Histology(1) 13.271 1 0.000 0.430 0.273 0.677
    • Histology (2) 12.094 1 0.001 0.409 0.247 0.677
    • G1-3 5.652 2 0.059
    • G1-3(1) 1.706 1 0.191 0.835 0.637 1.094
    • G1-3(2) 1.113 1 0.292 1.148 0.888 1.483
    • T1-4 9.447 3 0.024
    • T1-4(1) 6.664 1 0.010 0.410 0.209 0.807
    • T1-4(2) 7.778 1 0.005 0.447 0.254 0.787
    • T1-4(3) 3.852 1 0.050 0.578 0.335 0.999
    • N0-2 47.796 2 0.000
    • N0-2(1) 46.895 1 0.000 0.357 0.266 0.479
    • N0-2(2) 16.061 1 0.000 0.515 0.373 0.713
  • 23. 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
    • Tumor Size 2.720 1 0.099 1.086 0.985 1.199
    • Thrombocytes 4.271 1 0.039 0.990 0.980 0.999
    • Seg.Neutrophils(%) 2.776 1 0.096 1.034 0.994 1.076
    • Lymphocytes(%) 4.431 1 0.035 1.049 1.003 1.097
    • ESS 10.559 1 0.001 0.987 0.980 0.995
    • Prothrombin Index 34.344 1 0.000 1.034 1.023 1.046
    • Bilirubin 5.394 1 0.020 1.041 1.006 1.076
    • Recalcification Time 9.152 1 0.002 0.996 0.993 0.999
    • Heparin Tolerance 29.782 1 0.000 1.003 1.002 1.005
    • Ad.CHIRT 33.555 1 0.000 2.920 2.032 4.196
    • Leucocytes/CaCells 8.214 1 0.004 0.731 0.590 0.906
    • Thrombocytes/CaCells 1.976 1 0.160 0.998 0.996 1.001
    • Eosinophils/CaCells 47.796 1 0.037 3.444 1.080 10.976
    • Seg.Neutrophils/CaCells 46.895 1 0.003 1.555 1.160 2.084
    • Healthy Cells/CaCells 4.514 1 0.034 1.057 1.004 1.112
  • 24. 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 0.923
    • Lymphocytes (tot) 8.676 1 0.003 0.816 0.713 0.934
    • Leucocytes (tot) 11.348 1 0.001 1.189 1.075 1.315
    • Eosinophils (tot) 5.908 1 0.015 0.691 0.512 0.931
    • Thrombocytes (tot) 11.146 1 0.001 1.003 1.001 1.005
    • Operation 1.544 4 0.819
    • Operation(1) 0.458 1 0.499 0.863 0.563 1.322
    • Operation(2) 0.389 1 0.533 0.867 0.554 1.358
    • Operation(3) 0.001 1 0.980 0.994 0.620 1.593
    • Operation(4) 0.057 1 0.811 0.896 0.364 2.203
    • Surgery alone 3.066 1 0.080 1.265 0.972 1.645
    • Fibrinogen 4.180 1 0.041 1.078 1.003 1.158
  • 25. Results of Multifactor Analysis in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=511)
  • 26. 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< 0.0000
    • Wilks' Partial F-remove P-level
    • Lambda Lambda (1,421)
    • Ad. CHTITR .607564 .989364 4.52592 .033966
    • PI .621404 .967328 14.2193 .000186
    • N 0-2 .675599 .889731 52.1766 .000000
    • Recalcificat.Time .613179 .980303 8.45919 .003824
    • Fibrinogen-B .613035 .980533 8.35821 .004038
    • G1-3 .605988 .991937 3.42216 .065027
    • Histology .606000 .991917 3.43069 .064695
    • T1-4 .602375 .997886 0.89167 .345566
    • Growth .603213 .996500 1.47861 .224673
    • Tumor Size .601970 .998557 0.60837 .435841
    • weight .604121 .995002 2.11483 .146623
    • Erythrocytes .602821 .997148 1.20419 .273113
    • Protein .602782 .997212 1.17719 .278550
    • P/o RT .601136 .999942 0.02449 .875716
    • Surgery alone .601688 .999026 0.41053 .522049
    • Operation type .603138 .996624 1.42627 .233047
    • Lymphocytes .601366 .999560 0.18539 .667001
    • Leucocytes/CC .601948 .998594 0.59281 .441766
  • 27. 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 1029324
    • Growth -.313 .267 1.378 .2405 .731 .432 1.235
    • Histology -.347 .154 5.053 .0250 .707 .521 .957
    • G1-3 -.240 .148 2.656 .1039 .786 .588 1.051
    • T1-4 -.027 .198 0.020 .8879 .972 .659 1.435
    • N0-2 -1.191 .164 52.87 .0000 .304 .220 .419
    • S.Neut.(abs) -.137 .052 7.004 .0084 .872 .788 .965
    • Mon. (abs) 1.604 .572 7.852 .0050 4.972 1.615 15.313
    • ESS -.013 .008 2.454 .1179 .987 .972 1.003
    • Proth.Index -.071 .014 26.80 .0000 .932 .907 .957
    • Operation -.141 .113 1.545 .2145 .869 .695 1.085
    • P/o RT -.019 .627 0.001 .9752 .981 .286 3.360
    • Ad.CHIRT 1.256 .600 4.385 .0368 3.510 1.080 11.405
    • Surg. alone .159 .703 0.051 .8213 1.172 .294 4.670
    • Healt.C/CC .035 .023 2.320 .1284 1.036 .990 1.084
  • 28. Results of Clustering in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
    • Logic al Formulas based on Simple Mean
    • Losses:
    • 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)
  • 29. Results of Multifactor Clustering of Clinicomorphologic Factors in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 30. Results of Correspondence Analysis in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n= 481 )
  • 31. Results of Correspondence Analysis in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n= 481 )
  • 32. Results of Correspondence Analysis in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n= 481 )
  • 33. Results of Correspondence Analysis in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n= 481 )
  • 34. 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
  • 35. Classification Tree in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 36. Neural Networks in Prediction of Lung Cancer Patients Survival after 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 Selection
    • Useful 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
  • 37. 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 Ratio
    • N0-2 1 0.470 10.317
    • Growth 2 0.414 9.069
    • Surgery alone 3 0.387 8.480
    • T1-4 4 0.313 6.863
    • Operation type 5 0.312 6.853
    • G1-3 6 0.311 6.814
    • Histology 7 0.292 6.404
    • P/o RT 8 0.218 4.774
    • Ad.CHIRT 9 0.209 4.579
    • ESS 10 0.175 3.838
    • Protein 11 0.175 3.836
    • Prothr.Index 12 0.150 3.285
    • Factor Rank Error Ratio
    • Sex 13 0.129 2.829
    • Seg.Neutr.(%) 14 0.106 2.326
    • Tumor Size 15 0.091 2.001
    • Lymph. (%) 16 0.089 1.958
    • Monocytes/CC 17 0.080 1.749
    • Thromb./CC 18 0.078 1.704
    • Eosinoph./CC 19 0.075 1.650
    • Health.C/CC 20 0.072 1.570
    • Leucocytes/CC 21 0.064 1.397
    • Glucose 22 0.046 1.005
    • Lymph./CC 23 0.046 1.004
    • Bilirubin 24 0.046 1.000
  • 38. 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 Ratio
    • Surgery alone 1 0.289 90.726
    • Growth 2 0.232 72.022
    • T1-4 3 0.210 65.877
    • G1-3 4 0.180 56.593
    • Histology 5 0.158 49.643
    • Oper. Type 6 0.129 40.481
    • Heparin Tol. 7 0.125 39.354
    • Sex 8 0.109 34.264
    • P/o RT 9 0.100 31.362
    • Ad.CHIRT 10 0.077 24.167
    • Fibrinogen 11 0.046 14.307
    • Tumor Size 12 0.045 14.126
    • Factor Rank Error Ratio
    • Color Index 13 0.036 11.361
    • Prothr.Index 14 0.032 10.013
    • Thrombocytes 15 0.029 9.193
    • Recalc.Time 16 0.028 8.727
    • Lymphocytes 17 0.019 6.094
    • Erythrocytes 18 0.015 4.608
    • Protein 19 0.012 3.758
    • ESS 20 0.012 3.736
    • Bilirubin 21 0.010 3.271
    • Eosinophils 22 0.009 2.827
    • Eryth./CC 23 0.007 2.334
    • Age 24 0.007 2.190
  • 39. 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 Ratio
    • Growth 1 0.326 479.79
    • Oper.Type 2 0.311 458.33
    • G1-3 3 0.304 448.13
    • Surgery alone 4 0.270 397.90
    • Prothr.Index 5 0.201 296.07
    • T1-4 6 0.194 285.29
    • P/o RT 7 0.181 266.85
    • Histology 8 0.156 230.13
    • Ad.CHIRT 9 0.139 204.86
    • Heparin Tol. 10 0.133 195.71
    • Thrombocytes 11 0.095 139.76
    • Fibrinogen 12 0.094 138.29
    • Factor Rank Error Ratio
    • Recalc.Time 13 0.092 135.66
    • Sg.Neutrophils 14 0.058 85.353
    • Tumor Size 15 0.036 53.551
    • Eosinophils 16 0.013 19.082
    • Lymphocytes 17 0.010 14.699
    • Glucose 18 0.009 13.404
    • Erythrocytes 19 0.008 11.934
    • Monocytes 20 0.007 10.742
    • Weight 21 0.007 10.361
    • Leucocytes 22 0.003 4.969
    • Age 23 0.002 2.991
    • Hemoglobin 24 0.002 2.819
  • 40. 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 Ratio
    • Ad.CHIRT 1 0.304 362.21
    • P/o RT 2 0.236 282.08
    • Surgery alone 3 0.189 225.69
    • Histology 4 0.188 223.93
    • T1-4 5 0.183 217.82
    • Oper.Type 6 0.178 211.96
    • Prothr.Index 7 0.169 201.18
    • G1-3 8 0.159 189.62
    • Growth 9 0.145 173.45
    • Monocytes % 10 0.124 147.55
    • Bilirubin 11 0.119 141.68
    • Sex 12 0.104 124.44
    • Factor Rank Error Ratio
    • Sg.Neutrophils 13 0.056 66.814
    • Leucocytes 14 0.025 30.316
    • Lymphocytes 15 0.025 29.263
    • Monocytes abs 16 0.015 18.396
    • Sg.Neutr./CC 17 0.013 15.026
    • Hemor.Time 18 0.009 10.996
    • Monocytes/CC 19 0.007 8.408
    • ESS 20 0.006 7.094
    • Recalc.Time 21 0.005 5.700
    • Glucose 22 0.004 4.221
    • Heparin Tol. 23 0.003 4.117
    • Lymphocytes t 24 0.002 2.819
  • 41. Decision Tree in Prediction of Lung Cancer Patients Survival with N0 (n=274) and with N2 (n=92) after Lobectomies and Pneumonectomies
  • 42. Results of Kohonen Self-Organizing Neural Networks Computing in Prediction of Lung Cancer Patients Survival with N 0 (n=274) and with N2 (n=92) after Lobectomies and Pneumonectomies
  • 43. 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)
  • 44. 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)
  • 45. 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)
  • 46. 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)
  • 47. Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
    • Number of Samples=3333
    • Significant Factors Rank Kendall’s Tau-A P
    • N0-2 1 -0.2080 0.000000
    • Lymphocytes/CaCells 2 0.1737 0.000000
    • Erythrocytes/CaCells 3 0.1731 0.000000
    • Prothrombin Index 4 0.1709 0.000000
    • Erythrocytes (tot) 5 0.1576 0.000000
    • Thrombocytes/CaCells 6 0.1474 0.000001
    • Leucocytes/CaCells 7 0.1431 0.000003
    • Lymphocytes (tot) 8 0.1217 0.000067
    • Eosinophils/CaCells 9 0.1209 0.000081
    • Healthy Cells/CaCells 10 0.1172 0.000113
    • Weight 11 0.1144 0.000124
    • Monocytes/CaCells 12 0.1134 0.000172
  • 48. Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
    • Number of Samples=3333
    • Significant Factors Rank Kendall’s Tau-A P
    • Segmented Neutrophils (%) 13 -0.1003 0.000421
    • Eosinophils (tot) 14 0.0944 0.001310
    • Tumor Size 15 -0.0837 0.006102
    • Eosinophils (%) 16 0.0836 0.006164
    • T1-4 17 -0.0817 0.008210
    • Monocytes (tot) 18 0.0805 0.008354 Heparin Tolerance 19 -0.0782 0.010123
    • Eosinophils (abs) 20 0.0770 0.011639
    • Monocytes (%) 21 0.0711 0.012002
    • G1-3 22 -0.0701 0.024204
    • Glucose 23 0.0600 0.049998
  • 49. Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 50. Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 51. Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 52. 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 Correct
    • Losses 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 Correct
    • Losses 128 57 69.2%
    • 5-Year Survivors 33 263 88.9%
    • Total 161 320 81 .3%
  • 53. 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 Correct
    • Losses 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 Correct
    • Losses 184 1 99.5%
    • 5-Year Survivors 0 296 100.0%
    • Total 184 297 99 .8%
  • 54. Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations & Blood Glucose Level in Prediction of Lung Cancer Patients Survival (n= 481 )
  • 55. Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations & Blood Glucose Level in Prediction of Lung Cancer Patients Survival (n= 481 )
  • 56. Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations & Blood Glucose Level in Prediction of Lung Cancer Patients Survival (n= 481 )
  • 57. Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations & Blood Glucose Level in Prediction of Lung Cancer Patients Survival (n= 481 )
  • 58. Networks between Clinicopathologic, Biochemic, Hemostasis & Hematologic Data and 5-Year Survival of Lung cancer Patients after Lobectomies and Pneumonectomies (n=481)
  • 59. Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 60. Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 61. Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 62. SEPATH Networks in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
  • 63. Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell Population ”
  • 64. Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell Population ”
  • 65. Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell Population ”
  • 66. Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell Population ”
  • 67. Lung Cancer Dynamics
  • 68.  
  • 69. 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.
  • 70. Patents:
    • 1.  Kshivets O.M. Method of Prognosis of Survival Rate of Radically Operated P atients with Malignant Neoplasms. Patent from 10.02.94 ; N2101704 : 24pp.
    • 2. Kshivets O.M. Method of Prognosis of Survival Rate of Non-Radically Operated P atients with Malignant Neoplasms. Patent from 14.03.94 ; N2104536 : 10pp.
  • 71. Address:
    • Oleg Kshivets, M.D., Ph.D.
    • Thoracic Surgeon, Dep.of Surgery, Siauliai Cancer Center
    • Tilzes:42-16, Siauliai, LT5400, Lithuania
    • Tel. (37041)416614 Fax 1(270)9687098
    • [email_address]
    • http//:myprofile.cos.com/Kshivets

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