Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, Statistics and Modeling for Optimal Management.
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This study analyzes the 5-year survival rates and life span of esophageal cancer patients after radical surgery, emphasizing the use of artificial intelligence and complex system analysis for improved outcomes. The cumulative 5-year survival rate was found to be 52.6%, with significant factors influencing survival including cancer stage, cell ratios, and adjuvant treatments. The results highlight the importance of early detection and the need for skilled surgical intervention to enhance patient survival rates.
Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, Statistics and Modeling for Optimal Management.
- 1. Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, Statistics and Modeling for Optimal Management. Kshivets Oleg Surgery Department, Bagrationovsk Hospital, Bagrationovsk, Kaliningrad, Russia
- 2. ABSTRACT OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) patients (ECP)(T1-4N0- 2M0) - alive supersysems was analyzed. The importance must be stressed of using complex system analysis, artificial intelligence (neural networks computing), simulation modeling and statistical methods in combination, because the different approaches yield complementary pieces of prognostic information. METHODS: We analyzed data of 563 consecutive ECP (age=56.6±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2024 (m=419, f=144; esophagogastrectomies (EG) Garlock=289, EG Lewis=274, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=170; adenocarcinoma=323, squamous=230, mix=10; T1=131, T2=119, T3=185, T4=128; N0=285, N1=71, N2=207; G1=161, G2=143, G3=259; early EC=112, invasive=451; only surgery=428, adjuvant chemoimmunoradiotherapy-AT=135: 5-FU+thymalin/taktivin+radiotherapy 45-50Gy). Multivariate Cox modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence. RESULTS: Overall life span (LS) was 1915.4±2284.8 days and cumulative 5-year survival (5YS) reached 52.6%, 10 years – 46.3%, 20 years – 33.3%, 30 years – 27.5%. 193 ECP lived more than 5 years (LS=4309.1±2507.4 days), 105 ECP – more than 10 years (LS=5860.8±2469.2 days). 228 ECP died because of EC (LS=629.8±324.1 days). AT significantly improved 5YS (69% vs. 49.1%) (P=0.0007 by log-rank test). 5YS of ECP of upper/3 was significantly better than others (65.3% vs.50.3%) (P=0.003). Cox modeling displayed that 5YS of ECP significantly depended on: phase transition (PT) N0—N12 in terms of synergetics, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), T, G, histology, age, AT, localization, prothrombin index, hemorrhage time, residual nitrogen, protein (P=0.000-0.019). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and healthy cells/CC (rank=1), PT N0—N12 (2), PT early-invasive EC (3), erythrocytes/CC (4), thrombocytes/CC (5); segmented neutrophils/CC (6), stick neutrophils/CC (7), lymphocytes/CC (8), eosinophils/CC (9), monocytes/CC (10), leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). CONCLUSIONS: 5-year survival of ECP after radical procedures significantly depended on: 1) PT “early-invasive cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) EC cell dynamics; 9) EC characteristics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and treatment strategies for EC are: 1) screening and early detection of EC; 2) availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for ECP with unfavorable prognosis.
- 3. Data: • Males…………………………………………………...419 • Females………..……………………………...............144 • Age=56.6±8.9 years • Tumor Size=6±3.5 cm • Only Surgery.……………………………………........428 • Adjuvant Chemoimmunoradiotherapy • (5FU+thymalin/taktivin, 5-6 cycles+ Radiotherapy • 45-50Gy)………………………...................................135
- 4. :Radical Procedures • Esophagogastrectomies Lewis (R0)…………………274 • Esophagogastrectomies Garlock (R0)………...........289 • Combined Esophagogastrectomies with Resection • of Pancreas, Liver, Trachea, Lung, Aorta, Vena • Cava Superior, Colon Transversum, Diaphragm, Pericardium, Splenectomy (R0)……………...............170 • 2-Field Lymphadenectomy…………………………….362 • 3-Field Lymphadenectomy.………………………….…201
- 5. Staging: • T1……131 N0..….285 G1…………161 • T2……119 N1….....71 G2…………143 • T3……185 N2…...207 G3…………259 • T4……128 M0…..563 • Adenocarcinoma…………………………….323 • Squamos Cell Carcinoma…………………..230 • Mix………………….....…………………...........10 • Early Cancer……………………………...…...112 • Invasive Cancer…………………………..…..451
- 6. Survival Rate: • Alive……………………………………….....296 (52.6%) • 5-Year Survivors…………..……………….193 (34.3%) • 10-Year Survivors………………………….105 (18.7%) • Losses………………………………………..228 (40.5%) • General Life Span=1915.4±2284.8 days • For 5-Year Survivors=4309.1±2507.4 days • For 10-Year Survivors=5860.8±2469.2 days • For Losses=629.8±324.1 days • Cumulative 5-Year Survival……………………..52.6% • Cumulative 10-Year Survival…………………....46.3% • Cumulative 20-Year Survival…………………....33.3% • Cumulative 30-Year Survival…………………....27.5%
- 7. General Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (Kaplan-Meier) (n=563): Survival Function 5YS=52.6%; 10YS=46.3%; 20YS=33.3%; 30YS=27.5%. Complete Censored -5 0 5 10 15 20 25 30 35 40 45 Years after Esophagogastrectomies 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Cumulative Proportion Surviving
- 8. Results of Univariate Analysis of Phase Transition Early—Invasive Cancer in Prediction of Esophageal Cancer Patients Survival (n=563): Cumulative Proportion Surviving (Kaplan-Meier) P=0.000 Complete Censored 0 5 10 15 20 25 30 35 40 45 50 Years after Esophagogastrectomies 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Cumulative Proportion Surviving Invasive ECP Early ECP
- 9. Results of Univariate Analysis of Phase Transition N0—N1-2 in Prediction of Esophageal Cancer Patients Survival (n=563): Cumulative Proportion Surviving (Kaplan-Meier) P=0.000 Complete Censored 0 5 10 15 20 25 30 35 40 45 50 Time 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Cumulative Proportion Surviving N0 N1-2
- 10. Results of Univariate Analysis of Localization (Upper/3 vs. Others) in Prediction of Esophageal Cancer Patients Survival (n=563): Cumulative Proportion Surviving (Kaplan-Meier) P=0.000 Complete Censored 0 5 10 15 20 25 30 35 40 45 50 Years after Esophagogastrectomies 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Cumulative Proportion Surviving Others Upper/3
- 11. Results of Univariate Analysis of Localization (Cardioesophageal vs. Esophageal) in Prediction of Esophageal Cancer Patients Survival (n=563): Cumulative Proportion Surviving (Kaplan-Meier) P=0.000 Complete Censored 0 5 10 15 20 25 30 35 40 45 50 Years after Esophagogastrectomies 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Cumulative Proportion Surviving Cardioesophageal CP Esophageal CP
- 12. Results of Univariate Analysis of Adjuvant Treatment (Adjuvant Chemoimmunoradiotherapy vs Surgery along) in Prediction of Esophageal Cancer Patients Survival (n=563): Cumulative Proportion Surviving (Kaplan-Meier) P=0.00375 Complete Censored 0 5 10 15 20 25 30 35 40 45 50 Years after Esophagogastrectomies 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Cumulative Proportion Surviving Adjuvant Chemoradiotherapy Surgery along
- 13. Results of Cox Regression Modeling in Prediction of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=563): Cox Regression, ECP=563 Parameter Estimate Standard Error Chi- square P value 95% Lower CL 95% Upper CL Hazard Ratio Segmented Neutrophils (%) 0.060757 0.017913 11.50399 0.000694 0.02565 0.095867 1.062641 Hemorrhage of Blood 0.001559 0.000400 15.16684 0.000098 0.00077 0.002343 1.001560 Protein 0.020805 0.008677 5.74991 0.016489 0.00380 0.037811 1.021023 Residual Nitrogen 0.046396 0.010866 18.23261 0.000020 0.02510 0.067693 1.047490 Prothrombin Index 0.021704 0.006456 11.30163 0.000774 0.00905 0.034358 1.021942 Segmented Neutrophils (abs) -0.761788 0.204580 13.86576 0.000196 -1.16276 -0.360820 0.466831 Lymphocytes (abs) 0.546870 0.228784 5.71370 0.016833 0.09846 0.995277 1.727836 T1-4 0.418271 0.094110 19.75331 0.000009 0.23382 0.602724 1.519332 PT N0---N12 0.642382 0.161510 15.81930 0.000070 0.32583 0.958936 1.901004 Age 0.028998 0.007691 14.21475 0.000163 0.01392 0.044073 1.029423 Weight -0.034970 0.013244 6.97240 0.008278 -0.06093 -0.009013 0.965634 Histology -0.285581 0.125754 5.15725 0.023150 -0.53205 -0.039108 0.751577 G1-3 0.426268 0.091239 21.82750 0.000003 0.24744 0.605094 1.531532 Adjuvant Chemoimmunoradiotherapy -0.870165 0.190510 20.86250 0.000005 -1.24356 -0.496772 0.418882 Segmented Neutrophils (tot) 0.124208 0.040804 9.26585 0.002335 0.04423 0.204183 1.132252 Leucocytes/Cancer Cells -0.132461 0.037769 12.30035 0.000453 -0.20649 -0.058436 0.875937 Monocytes/Cancer Cells 1.046746 0.401192 6.80736 0.009078 0.26042 1.833067 2.848367 Upper/3 vs Others -0.456165 0.195540 5.44218 0.019656 -0.83942 -0.072914 0.633709 Eosinophils (abs) 0.887039 0.450614 3.87504 0.049009 0.00385 1.770226 2.427929
- 14. Results of Neural Networks and Monte Carlo Computing in Prediction of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=421): Corect Classification Rate=100% Error=0.000 Area under ROC Curve=1.000 Factors n=421 (Neural Networks) Rank Sensitivity Healthy Cells/Cancer Cells 1 47967 Phase Transition N0---N12 2 32041 Phase Transition Early---Invasive Esophageal Cancer 3 32029 Erythrocytes/ Cancer Cells 4 21816 Thrombocytes/ Cancer Cells 5 20377 Segmented Neutrophils/ Cancer Cells 6 16849 Stick Neutrophils/ Cancer Cells 7 11869 Lymphocyes/ Cancer Cells 8 10648 Eosinophils/ Cancer Cells 9 10401 Monocytes/ Cancer Cells 10 9258 Leucocytes/ Cancer Cells 11 9196
- 15. Results of Bootstrap Simulation in Prediction of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=421): Significant Factors (Number of Samples=3333) Rank Kendal Tau-A P Tumor Size 1 -0.308 0.000 Healthy Cells/Cancer Cells 2 0.305 0.000 T1-4 3 -0.299 0.000 Erythrocytes/Cancer Cells 4 0.299 0.000 Leucocytes/Cancer Cells 5 0.290 0.000 Thrombocytes/Cancer Cells 6 0.285 0.000 Lymphocytes/Cancer Cells 7 0.281 0.000 Residual Nitrogen 8 -0.275 0.000 Segmented Neutrophils/Cancer Cells 9 0.273 0.000 Phase Transition N0---N12 10 -0.239 0.000 Hemorrhage Time 11 -0.228 0.000 Monocytes/Cancer Cells 12 0.227 0.000 Phase Transition Early---Invasive Cancer 13 -0.222 0.000 Esophageal/Cardioesophageal Cancer 14 -0.191 0.000 Operation Type 15 -0.187 0.000 Eosinophils/Cancer Cells 16 0.173 0.000 Stick Neutrophils/Cancer Cells 17 0.144 0.001 G1-3 18 -0.140 0.001 Tumor Growth 19 -0.113 0.01 Erythrocytes 20 0.100 0.01 Combined Procedure 21 0.095 0.01 Weight 22 0.092 0.01 Localization 23 0.069 0.05
- 16. Results of Kohonen Self-Organizing Neural Networks Computing in Prediction of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=421):
- 17. Esophageal Cancer Cell Dynamics:
- 18. Prognostic Equation Models of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=421):
- 19. Prognostic Equation Models of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=421):
- 20. Prognostic Equation Models of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=421):
- 21. Prognostic Equation Models of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=421):
- 22. SEPATH Modeling in Prediction of Esophageal Cancer Patients Survival after Complete Esophagogastrectomies (n=421):
- 23. 5-year survival of ECP after radical procedures significantly depended on: 1) PT “Early-Invasive Cancer”; 2) PT N0--N12; 3) Cell Ratio Factors; 4) Blood Cell Circuit; 5) Biochemical Factors; 6) Hemostasis System; 7) Adjuvant Treatment; 8) EC Characteristics; 9) EC Cell Dynamics; 10) Tumor Localization; 11) Anthropometric Data; 12) Surgery Type. Conclusion:
- 24. Optimal diagnosis and treatment strategies for ECP are: 1) Screening and Early Detection of EC; 2) Availability of Sufficient Quantity of Very Experienced Thoracoabdominal Surgeons because of Extreme Complexity of Radical Procedures; 3) Aggressive en block Surgery and Adequate Lymph Node Dissection for Completeness; 4) Precise Prediction; 5) Adjuvant Chemoimmunoradiotherapy for ECP with Unfavorable Prognosis. Conclusion:
- 25. Address: Oleg Kshivets, M.D.,Ph.D. Consultant Thoracic, Abdominal, General Surgeon & Surgical Oncologist • e-mail: okshivets@yahoo.com • skype: okshivets • http: //www.ctsnet.org/home/okshivets