Kshivets O. Esophagogastric Cancer Surgery

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ARTIFICIAL INTELLIGENCE, SYSTEM ANALYSIS AND SIMULATION MODELING IN OPTIMIZATION OF TREATMENT FOR ESOPHAGOGASTRIC CANCER PATIENTS

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Kshivets O. Esophagogastric Cancer Surgery

  1. 1. ARTIFICIAL INTELLIGENCE, SYSTEM ANALYSIS AND SIMULATION MODELING IN OPTIMIZATION OF TREATMENT FOR ESOPHAGOGASTRIC CANCER PATIENTS Oleg Kshivets, MD, PhD Department of Surgery, Siauliai Public Hospital & Cancer Center, Siauliai, Lithuania The 2006 Gastrointestinal Cancers Simposium, January 26-28, 2006, San Francisco, CA, the USA
  2. 2. Abstract ARTFICIAL INTELLIGENCE, SYSTEM ANALYSIS AND SIMULATION MODELING IN OPTIMIZATION OF TREATMENT FOR ESOPHAGOGASTRIC CANCER PATIENTS Oleg Kshivets Department of Surgery, Siauliai Public Hospital & Cancer Center, Siauliai, Lithuania <ul><li>OBJECTIVE: The search of optimal treatment plan for esophagogastric cancer (EGC) patients (EGCP) with stage T1-4N1-3M0 was realized. We examined the clinicomorphologic factors associated with the low- and high-risk of generalization of EGCP after complete en block (R0) esophagogastrectomies (EG) through left and right thoracoabdominal incision. METHODS: We analyzed data of 187 consecutive EGCP (age=55.7±8.8 years; tumor size=6.8±3.3 cm) radically operated and monitored in 1975-2005 (males=138, females=49; EG Ivor-Lewis=60, EG Garlock=127; combined EG with resection of pancreas, liver, diaphragm, colon transversum, splenectomies=74; lymphadenectomy D2=80, D3=107; adenocarcinoma=109, squamos=68, mix=10; T1=27, T2=43, T3=67, T4=50; N0=75, N1=24, N2=85; N3=3; G1=54, G2=41, G3=92; only surgery-S=154, adjuvant chemoimmunotherapy-AT=33: 5-FU + thymalin/taktivin). Variables selected for 5-year survival (5YS) study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Survival curves were estimated by the Kaplan-Meier method. Differences in curves between groups of CECP were 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. RESULTS: General cumulative 5YS was 34.9%, 10-year survival – 26.1%. 72 EGCP (38.5%) were alive, 39 EGCP (life span: LS=3699.7±1617.6 days) lived more than 5 years without any features of CEC progressing. LS for AT was 2255.9±211.7 days, for S – 1324.8±1550.4 days (P=0.032, by log-rank test P=0.036). Cox modeling displayed that 5YS of EGCP (n=187) after complete EG significantly depended on: combined procedures, age, blood cell subpopulations, cell ratio factors, lymphoid infiltration of EGC, T (P=0.000-0.029). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS of EGCP and combined procedures (rank=1), lymphoid infiltration of EGC (2), EGC growth (3), T1-4 (4), histology (5), G1-3 (6), N0-3 (7), procedure type (8), gender (9), Rh-factor (10), blood coagulation time (11), blood lymphocytes (12), protein (13), neutrophils (14), age (15), blood leucocytes (16), tumor size (17), ESS (18), blood chlorides (19), prothrombin index (20). Correct prediction of EGCP survival after radical procedures was 91.7% by logistic regression (odds ratio=98.8), 92.4% by discriminant analysis and 100% by neural networks computing (area under ROC curve=1.0; error=0.0018). CONCLUSIONS: Optimal treatment strategies for EGCP are: 1) screening and early detection of EGC; 2) aggressive en block surgery for completeness; 3) precise prediction; 4) AT for EGCP with unfavorable prognosis. </li></ul>
  3. 3. Factors: <ul><li>1) Antropometric Factors………….. 4 </li></ul><ul><li>2) Blood Analysis………………….. 26 </li></ul><ul><li>3) Hemostasis Factors…………….... 3 </li></ul><ul><li>4) Cell Ratio Factors………………... 9 </li></ul><ul><li>6) Esophagogastric Cancer Characteristics……………………... 12 </li></ul><ul><li>7) Biochemic Factors………………... 7 </li></ul><ul><li>8) Treatment Characteristics……….. 3 </li></ul><ul><li>9) Survival Data……………………… 4 </li></ul><ul><li>In All……………………………….. 68 </li></ul>
  4. 4. Main Problem of Analysis of Alive Supersystems including Combinatorial Optimization (e.g. Esophagogastric Cancer Patient Homeostasis, Search of Optimal Treatment Plan ): Phenomenon of «Combinatorial Explosion» <ul><li>Number of Clinicomorphological Factors:……...….. 68 </li></ul><ul><li>Number of Possible Combination for Random Search:……………..……………… n!=68!=2.48e+96 </li></ul><ul><li>Operation Time of IBM Blue Gene/L Supercomputer (135.5TFLOPS) ………………………… 5.8e+74 Years </li></ul><ul><li>The Age of Our Universe………..... 1.3e+10 Years </li></ul>
  5. 5. Basis: <ul><li>NP  RP  P </li></ul><ul><li>   </li></ul><ul><li>n!  n*n*2(e+n) or n log n  n </li></ul><ul><li>   </li></ul><ul><li>AI  CSA+S+B  SM </li></ul><ul><li>AI - Artificial Intelligence </li></ul><ul><li>CSA - Complex System Analysis </li></ul><ul><li>S - Statistics </li></ul><ul><li>B - biometrics </li></ul><ul><li>SM - simulation modeling </li></ul>
  6. 6. Data: <ul><li>Males………………………………… 138 </li></ul><ul><li>Females……………………………….. 49 </li></ul><ul><li>Age= 55.7±8.8 years </li></ul><ul><li>Tumor Size= 6.8±3.3 cm </li></ul><ul><li>Only Surgery…………………………. 154 </li></ul><ul><li>Adjuvant Chemoimmunotherapy (5FU+thymalin/taktivin, 5-6 cycles)….. 33 </li></ul>
  7. 7. Radical Procedures: <ul><li>Ivor-Lewis Esophagogastrectomies ….…. 60 </li></ul><ul><li>Garlock Esophagogastrectomies …..…... 127 </li></ul><ul><li>Combined Esophagogastrectomies with Resection of Diaphragm, Liver, Mesocolon, Colon Transversum, Splenectomy, Left Hemipancreatectomy, etc…………….… 74 </li></ul><ul><li>Lymphadenectomy D2…………………... 80 </li></ul><ul><li>Lymphadenectomy D3…………………. 107 </li></ul><ul><li>At All…………………………………….187 </li></ul>
  8. 8. Schemas of Procedures:
  9. 9. Staging: <ul><li>T1……27 N0..…..75 G1…………54 </li></ul><ul><li>T2……43 N1……24 G2…………41 </li></ul><ul><li>T3……67 N2……85 G3…………92 </li></ul><ul><li>T4……50 N3……..3 </li></ul><ul><li>Adenocarcinoma……....…...……………...…...109 </li></ul><ul><li>Squamos Cell Carcinoma…..…………………..68 </li></ul><ul><li>Mixed Carcinoma……...………………….……..10 </li></ul>
  10. 10. Survival: <ul><li>Alive………..……………….…. 72 (38.5%) </li></ul><ul><li>5-Year Survivors…………..….. 39 (20.9%) </li></ul><ul><li>10-Year Survivors……………... 18 (9.6%) </li></ul><ul><li>Losses from Cancer…………. 115 (61.5%) </li></ul><ul><li>General Life Span= 1276.1 ±108.3 days </li></ul><ul><li>Life Span of 5-Year Survivors= 3699.7±1617.6 days </li></ul><ul><li>Life Span after Surgery= 1324.8±1550.4 days </li></ul><ul><li>Life Span after Ad.CHIT= 2255.9211.7±211.7 days </li></ul><ul><li>Cumulative 5-Year survival=34.9% </li></ul><ul><li>Cumulative 10-Year survival=26.1% </li></ul>
  11. 11. General Esopagogastric Cancer Patients Survival after Complete Ivor-Lewis & Garlock Esophagogastrectomies (Kaplan-Meier) ( n=187 )
  12. 12. Results of Univariate Analysis in Prediction of Esopagogastric Cancer Patients Survival ( n=187 )
  13. 13. Results of Cox Regression Modeling in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=187 ) <ul><li>Factors Wald df P Exp(B) 95%CI for Exp(B) Lower Upper </li></ul><ul><li>Leucocytes abs 11.996 1 0.001 4.8e+13 8.7e+5 2.7e+21 </li></ul><ul><li>Seg.Neutrophils% 7.798 1 0.005 1.738 1.179 2.563 </li></ul><ul><li>Lymphocytes% 5.827 1 0.016 1.617 1.095 2.387 </li></ul><ul><li>Monocytes% 8.264 1 0.004 1.862 1.219 2.845 </li></ul><ul><li>Bilirubin 3.800 1 0.051 1.048 1.000 1.099 </li></ul><ul><li>Eosinophils abs 7.457 1 0.006 0.000 0.000 0.002 </li></ul><ul><li>St.Neutrophils abs 9.553 1 0.001 0.000 0.000 0.000 </li></ul><ul><li>Seg.Neutrophils abs 12.067 1 0.001 0.000 0.000 0.000 </li></ul><ul><li>Lymphocytes abs 10.007 1 0.002 0.000 0.000 0.000 </li></ul><ul><li>Monocytes abs 15.659 1 0.000 0.000 0.000 0.000 </li></ul><ul><li>Age 12.119 1 0.000 1.051 1.022 1.081 </li></ul><ul><li>Sex 2.395 1 0.122 1.543 0.891 2.672 </li></ul>
  14. 14. Results of Cox Regression Modeling in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=187 ) <ul><li>Factors Wald df P Exp(B) 95%CI for Exp(B) Lower Upper </li></ul><ul><li>T 6.572 3 0.087 </li></ul><ul><li>T(1) 0.209 1 0.647 0.698 0.149 3.265 </li></ul><ul><li>T(2) 5.459 1 0.019 0.340 0.138 0.841 </li></ul><ul><li>T(3) 3.636 1 0.057 0.514 0.259 1.019 </li></ul><ul><li>N 1.225 3 0.747 </li></ul><ul><li>N(1) 1.000 1 0.317 2.491 0.416 14.900 </li></ul><ul><li>N(2) 0.631 1 0.427 2.115 0.333 13.436 </li></ul><ul><li>N(3) 0.659 1 0.417 2.096 0.351 12.520 </li></ul><ul><li>Histology 2.706 2 0.258 </li></ul><ul><li>Histology(1) 1.873 1 0.171 2.677 0.653 10.969 </li></ul><ul><li>Histology (2) 2.595 1 0.107 3.313 0.771 14.229 </li></ul><ul><li>G 4.427 2 0.109 </li></ul>
  15. 15. Results of Cox Regression Modeling in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=187 ) <ul><li>Factors Wald df P Exp(B) 95%CI for Exp(B) Lower Upper </li></ul><ul><li>G(1) 3.359 1 0.067 0.593 0.339 1.037 </li></ul><ul><li>G(2) 3.503 1 0.061 0.526 0.268 1.031 </li></ul><ul><li>LIT 26.856 3 0.000 </li></ul><ul><li>LIT(1) 24.975 1 0.000 10.470 4.168 26.299 </li></ul><ul><li>LIT(2) 22.481 1 0.000 7.398 3.235 16.919 </li></ul><ul><li>LIT(3) 8.040 1 0.005 3.133 1.423 6.897 </li></ul><ul><li>Growth 8.125 2 0.017 </li></ul><ul><li>Growth(1) 7.010 1 0.008 4.454 1.474 13.458 </li></ul><ul><li>Growth(2) 3.339 1 0.068 2.835 0.927 8.672 </li></ul><ul><li>Ad.CHIT 0.053 1 0.818 0.925 0.477 1.795 </li></ul><ul><li>Comb.Operation 15.642 7 0.029 </li></ul><ul><li>Comb.Operation(1) 0.277 1 0.598 1.898 0.175 20.619 </li></ul><ul><li>Comb.Operation(2) 0.106 1 0.744 0.836 0.285 2.452 </li></ul>
  16. 16. Results of Cox Regression Modeling in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=187 ) <ul><li>Factors Wald df P Exp(B) 95%CI for Exp(B) Lower Upper </li></ul><ul><li>Comb.Operation(3) 0.010 1 0.921 0.964 0.462 2.010 </li></ul><ul><li>Comb.Operation(4) 0.391 1 0.532 2.189 0.188 25.499 </li></ul><ul><li>Comb.Operation(5) 2.137 1 0.144 0.066 0.002 2.530 </li></ul><ul><li>Comb.Operation(6) 5.912 1 0.015 0.282 0.102 0.782 </li></ul><ul><li>Comb.Operation(7) 5.397 1 0.020 0.403 0.187 0.868 </li></ul><ul><li>Leucocytes tot 11.703 1 0.001 0.002 0.000 0.063 </li></ul><ul><li>Eosinophils tot 9.777 1 0.002 236.031 7.683 7250.741 </li></ul><ul><li>St.Neutrophils tot 11.859 1 0.001 1327.21 22.157 79500.164 </li></ul><ul><li>Seg.Neutrophils tot 11.620 1 0.001 671.327 15.904 28338.054 </li></ul><ul><li>Lymphocytes tot 10.340 1 0.001 489.133 11.224 21315.845 </li></ul><ul><li>Monocytes tot 12.286 1 0.000 1182.16 22.621 61778.951 </li></ul><ul><li>Erythrocytes/CC 9.065 1 0.003 2.334 1.344 4.052 </li></ul><ul><li>Leucocytes/CC 12.148 1 0.000 82.119 6.885 979.461 </li></ul>
  17. 17. Results of Cox Regression Modeling in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=187 ) <ul><li>Factors Wald df P Exp(B) 95%CI for Exp(B) Lower Upper </li></ul><ul><li>Eosinophils/CC 8.187 1 0.004 0.001 0.000 0.098 </li></ul><ul><li>St.Neutrophils/CC 9.572 1 0.002 0.001 0.000 0.082 </li></ul><ul><li>Seg.Neutrophils/CC 11.517 1 0.001 0.012 0.001 0.152 </li></ul><ul><li>Lymphocytes/CC 11.919 1 0.001 0.010 0.001 0.137 </li></ul><ul><li>ESS 0.155 1 0.694 0.996 0.974 1.018 </li></ul><ul><li>Hemorrhage Time 0.247 1 0.619 1.005 0.986 1.025 </li></ul><ul><li>Coagulation Time 0.246 1 0.620 1.000 0.999 1.002 </li></ul><ul><li>Glucose 2.061 1 0.151 0.814 0.614 1.078 </li></ul><ul><li>Prothrombin Index 2.087 1 0.149 1.016 0.994 1.038 </li></ul><ul><li>Protein 0.377 1 0.539 0.991 0.963 1.020 </li></ul><ul><li>Chlorids 2.356 1 0.125 0.972 0.937 1.008 </li></ul><ul><li>Procedure Type 0.144 1 0.705 1.136 0.588 2.194 </li></ul><ul><li>Tumor Size 1.239 1 0.266 1.074 0.947 1.217 </li></ul>
  18. 18. Results of Discriminant Analysis in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=145) <ul><li>Discriminant Function Analysis Summary </li></ul><ul><li>Wilks' Lambda: 0.368 approx. F (38,106)=4.799 p< 0.0000 </li></ul><ul><li>Wilks' Partial F-remove P-level </li></ul><ul><li>Lambda Lambda (1,421) </li></ul><ul><li>LIT .504565 .728493 39.5059 .000000 </li></ul><ul><li>Comb.Operation .401326 .915895 9.73383 .002331 </li></ul><ul><li>Growth .383276 .959026 4.52881 .035646 </li></ul><ul><li>Bilirubin .378520 .971076 3.15724 .078459 </li></ul><ul><li>Hemorrhage Time .376209 .977042 2.49077 .117496 </li></ul><ul><li>Glucose .374393 .981781 1.96709 .163679 </li></ul><ul><li>Tumor Size .373801 .983336 1.79632 .183024 </li></ul><ul><li>Rh .372606 .986489 1.45181 .230921 </li></ul><ul><li>Lymphocytes tot .372370 .987114 1.38371 .242105 </li></ul><ul><li>G .372264 .987395 1.35321 .247330 </li></ul><ul><li>Chlorids .371829 .988551 1.22771 .270361 </li></ul><ul><li>St.Neutrophils% .371649 .989029 1.17587 .280658 </li></ul><ul><li>Lymphocytes% .371501 .989423 1.13315 .289523 </li></ul><ul><li>Seg.Neutrophils% .371366 .989783 1.09417 .297929 </li></ul><ul><li>Protein .370786 .991332 0.92686 .337870 </li></ul><ul><li>N0-3 .369973 .993510 0.69240 .407220 </li></ul><ul><li>T1-4 .368469 .997565 0.25878 .612019 </li></ul>
  19. 19. Results of Logistic Regression Analysis in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=145) Chi2=105.09; df=18; P=0.00000; Odds ratio=98.813 <ul><li> Est. S.E. Wald P Odds 95.0% C.I.for Odds Ratio Ratio Lower Upper </li></ul><ul><li>Const.B -17.44 10.37 2.832 .0949 .000 .000 .000 </li></ul><ul><li>Rh 1.693 1.24 1.878 .1730 5.436 .471 62.690 </li></ul><ul><li>ESS .457 .033 1.900 .1705 1.047 .980 1.118 </li></ul><ul><li>Rrotein .082 .051 2.585 .1104 .786 .588 1.051 </li></ul><ul><li>Clorids .075 .067 1.248 .2661 1.078 .944 1.232 </li></ul><ul><li>T1-4 -.341 .543 .394 .5315 .711 .243 2.082 </li></ul><ul><li>N0-3 .446 .370 1.452 .2305 1.562 .751 3.251 </li></ul><ul><li>LIT 2.090 .484 18.643 .0000 8.083 3.102 21.065 </li></ul><ul><li>G1-3 -.655 .490 1.787 .1837 .519 .197 1.340 </li></ul><ul><li>Growth 2.071 .848 6.280 .0135 8.389 1.564 44.989 </li></ul><ul><li>Comb.Oper. -.606 .184 10.904 .0012 .545 .379 .784 </li></ul><ul><li>Histology .538 .800 .453 .5023 1.713 .352 8.345 </li></ul>
  20. 20. Prognostic SEPATH-Model of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=145)
  21. 21. Neural Networks in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=145) <ul><li>Losses 5-year survivors Baseline Errors=0.0018; </li></ul><ul><li>Total 106 39 Area under ROC curve=1 .00; </li></ul><ul><li>Correct 106 39 Correct Classification Rate= 100% </li></ul><ul><li>Wrong 0 0 </li></ul><ul><li>Genetic Algorithm Selection </li></ul><ul><li>Useful for Comb.Oper. ESS Rh T1-4 N0-3 Age Sex Histology Leucocytes Growth </li></ul><ul><li>Survival Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes </li></ul><ul><li>Useful for Hemor.Time Glucose Protein Chlorids Tumor Size St.Neutroph. Lymphocytes </li></ul><ul><li>Survival Yes Yes Yes Yes Yes Yes Yes </li></ul>
  22. 22. Results of Neural Networks Computing in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=145) Error=0.0018; Area under ROC Curve=1.00; Correct Classification Rate=100% <ul><li>Factor Rank Error Ratio </li></ul><ul><li>Comb.Operat. 1 0.279 152.6 </li></ul><ul><li>LIT 2 0.276 151.2 </li></ul><ul><li>Growth 3 0.147 80.29 </li></ul><ul><li>T1-4 4 0.131 72.00 </li></ul><ul><li>Histology 5 0.106 57.83 </li></ul><ul><li>G1-3 6 0.097 53.28 </li></ul><ul><li>N0-3 7 0.085 46.61 </li></ul><ul><li>Proced. Type 8 0.072 39.76 </li></ul><ul><li>Sex 9 0.063 34.44 </li></ul><ul><li>Rh 10 0.052 28.71 </li></ul><ul><li>Coagul.Time 11 0.021 11.74 </li></ul><ul><li>Lymphoc.abs 12 0.008 4.300 </li></ul><ul><li>Factor Rank Error Ratio </li></ul><ul><li>Protein 13 0.006 3.058 </li></ul><ul><li>Seg.Neutr.abs 14 0.003 1.601 </li></ul><ul><li>Lymphocytes%15 0.003 1.412 </li></ul><ul><li>Age 16 0.002 1.348 </li></ul><ul><li>Leucocytes 17 0.002 1.292 </li></ul><ul><li>Seg.Neutr.% 18 0.002 1.240 </li></ul><ul><li>Tumor Size 19 0.002 1.125 </li></ul><ul><li>ESS 20 0.002 1.105 </li></ul><ul><li>St.Neutr.abs 21 0.002 1.089 </li></ul><ul><li>Chlorids 22 0.002 1.087 </li></ul><ul><li>Prothr.Index 23 0.002 1.064 </li></ul><ul><li>Glucose 24 0.002 1.018 </li></ul>
  23. 23. Results of Bootstrap Simulation in Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=145) <ul><li>Number of Samples=3333 </li></ul><ul><li>Significant Factors Rank Kendall’s Tau-A P< </li></ul><ul><li>LIT 1 0.2954 0.000 </li></ul><ul><li>Tumor Size 2 -0.1797 0.002 </li></ul><ul><li>Lymphocytes/CC 3 0.1749 0.002 </li></ul><ul><li>T1-4 4 -0.1742 0.002 </li></ul><ul><li>Healthy Cells/CC 5 0.1722 0.002 </li></ul><ul><li>Erythrocytes/CC 6 0.1688 0.004 </li></ul><ul><li>Leucocytes/CC 7 0.1673 0.004 </li></ul><ul><li>Thrombocytes/CC 8 0.1459 0.008 </li></ul><ul><li>N0-3 9 -0.1455 0.008 </li></ul><ul><li>Seg.Neutrophils/CC 10 0.1429 0.008 </li></ul><ul><li>Monocytes/CC 11 0.1258 0.02 </li></ul><ul><li>Procedure Type 12 -0.1130 0.04 </li></ul><ul><li>G1-3 13 -0.1126 0.05 </li></ul>
  24. 24. Prediction of Esophagogastric Cancer Patients Survival after Complete Esophagogastrectomies (n=145) <ul><li>Classification of Cases by Logistic Regression, n=145 </li></ul><ul><li>(5-Year Survivors--Losses) Odds Ratio=98.813 </li></ul><ul><li>Observed Pred.Losses Pred.Survivors Correct </li></ul><ul><li>Losses 102 4 96.2% </li></ul><ul><li>5-Year Survivors 8 31 79.5% </li></ul><ul><li>Total 110 35 91.7% </li></ul><ul><li>Classification of Cases by Discriminant Analysis, n=145 </li></ul><ul><li>(5-Year Survivors--Losses) </li></ul><ul><li>Observed Pred.Losses Pred.Survivors Correct </li></ul><ul><li>Losses 102 4 96.2% </li></ul><ul><li>5-Year Survivors 7 32 82.1% </li></ul><ul><li>Total 110 36 92 .4% </li></ul><ul><li>Classification of Cases by Neural Networks, n=145 </li></ul><ul><li>(5-Year Survivors--Losses) </li></ul><ul><li>Observed Pred.Losses Pred.Survivors Correct </li></ul><ul><li>Losses 106 0 100% </li></ul><ul><li>5-Year Survivors 0 39 100% </li></ul><ul><li>Total 106 39 100 % </li></ul>
  25. 25. Ratio Lymphocytes to Cancer Cells Populations in Prediction 5-Year Survival of Esophagogastric Cancer Patients after Complete Esophagogastrectomies (n=145)
  26. 26. Holling-Tenner Models of Esophagogastric Cancer Cell Population and Cytotoxic Cell Population Dynamics
  27. 27. Esophagogastric Cancer Dynamics
  28. 28. Conclusions: <ul><li>Optimal treatment strategies for esophagogastric cancer patients are: </li></ul><ul><li>1) screening and early detection of esophagogastric cancer; </li></ul><ul><li>2) aggressive en block surgery for completeness; 3) precise prediction; </li></ul><ul><li>4) adjuvant chemioimmunotherapy for esophagogastric cancer patients with unfavorable prognosis. </li></ul>
  29. 29. <ul><li>Oleg Kshivets, M.D., Ph.D. Consultant Thoracic/Abdominal/General Surgeon & Surgical Oncologist, Department of Surgery, Siauliai Public Hospital & Cancer Center, Tilzes:42-16, LT78206 Siauliai, Lithuania </li></ul><ul><li>Tel. (37041)416614; Fax 1(270)9687098 </li></ul><ul><li>kshivets@yahoo.com, http//:myprofile.cos.com/Kshivets </li></ul>

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