Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, Biometrics and Modeling of Alive Supersystems for Best Management.
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May 01, 2025
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About This Presentation
We analyzed data of 568 consecutive ECP (age=56.7±9 years; tumor size=5.9±3.5 cm) radically operated (R0) and monitored in 1975-2025 (m=424, f=144; esophagogastrectomies (EG) Garlock=290, EG Lewis=278, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, t...
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Esophageal Cancer: Artificial Intelligence,
Synergetics, Complex System Analysis,
Biometrics and Modeling of Alive
Supersystems for Best Management.
Kshivets Oleg Surgery Department, BagrationovskHospital,
Bagrationovsk, Kaliningrad, Russia
Synergetics, Complex System Analysis,
Biometrics and Modeling of Alive
Supersystems for Best Management.
Kshivets Oleg Surgery Department, BagrationovskHospital,
Bagrationovsk, Kaliningrad, Russia
ABSTRACT
OBJECTIVE: Esophageal cancer (EC) is an extremely aggressive tumor and requires virtuoso, complex surgery, vast practical experience and will always be the
prerogative of the world's best surgeons. 5-survival (5YS) and life span after radical surgery for 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), modeling and biometric
methods in combination, because the different approaches yield complementary pieces of prognostic information.
METHODS: We analyzed data of 568 consecutive ECP (age=56.7± 9 years; tumor size=5.9± 3.5 cm) radically operated (R0) and monitored in 1975-2025 (m=424,
f=144; esophagogastrectomies (EG) Garlock=290, EG Lewis=278, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung,
trachea, pericardium, splenectomy=174; adenocarcinoma=326, squamous=232, mix=10; T1=133, T2=121, T3=186, T4=128; N0=288, N1=71, N2=209; G1=161,
G2=143, G3=264; early EC=114, invasive=454; only surgery=431, adjuvant chemoimmunoradiotherapy-AT=137: 5- FU+thymalin/taktivin+radiotherapy 45-50Gy).
Multivariate Cox modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any s ignificant dependence.
RESULTS: Overall life span (LS) was 1906.3±2278.4 days and cumulative 5- year survival (5YS) reached 53%, 10 years – 46.4%, 20 years – 33.4%, 30 years –
27.5%. 194 ECP lived more than 5 years (LS=4300.8± 2503.5 days), 105 ECP – more than 10 years (LS=5860.8± 2469.2 days). 232 ECP died because of EC
(LS=628.8± 321.8 days). AT significantly improved 5YS (60.3% vs. 43.1%) (P=0.007 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, blood cell
subpopulation, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), EC cell dynamics, T, G, histology, age, localization, prothrombin
index, coagulation time, residual nitrogen, chlorides (P=0.000-0.047). Neural networks, genetic algorithm selection and bootstrap simulation revealed
relationships between 5YS and healthy cells/CC (rank=1), erythrocytes/CC (2), PT N0—N12 (3), PT early -invasive EC (4), thrombocytes/CC (5); segmented
neutrophils/CC (6), lymphocytes/CC (7), eosinophils/CC (8), stick neutrophils/CC (9), leucocytes/CC (10), monocytes/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) availa bility of sufficient quantity of very
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.
OBJECTIVE: Esophageal cancer (EC) is an extremely aggressive tumor and requires virtuoso, complex surgery, vast practical experience and will always be the
prerogative of the world's best surgeons. 5-survival (5YS) and life span after radical surgery for 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), modeling and biometric
methods in combination, because the different approaches yield complementary pieces of prognostic information.
METHODS: We analyzed data of 568 consecutive ECP (age=56.7± 9 years; tumor size=5.9± 3.5 cm) radically operated (R0) and monitored in 1975-2025 (m=424,
f=144; esophagogastrectomies (EG) Garlock=290, EG Lewis=278, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung,
trachea, pericardium, splenectomy=174; adenocarcinoma=326, squamous=232, mix=10; T1=133, T2=121, T3=186, T4=128; N0=288, N1=71, N2=209; G1=161,
G2=143, G3=264; early EC=114, invasive=454; only surgery=431, adjuvant chemoimmunoradiotherapy-AT=137: 5- FU+thymalin/taktivin+radiotherapy 45-50Gy).
Multivariate Cox modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any s ignificant dependence.
RESULTS: Overall life span (LS) was 1906.3±2278.4 days and cumulative 5- year survival (5YS) reached 53%, 10 years – 46.4%, 20 years – 33.4%, 30 years –
27.5%. 194 ECP lived more than 5 years (LS=4300.8± 2503.5 days), 105 ECP – more than 10 years (LS=5860.8± 2469.2 days). 232 ECP died because of EC
(LS=628.8± 321.8 days). AT significantly improved 5YS (60.3% vs. 43.1%) (P=0.007 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, blood cell
subpopulation, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), EC cell dynamics, T, G, histology, age, localization, prothrombin
index, coagulation time, residual nitrogen, chlorides (P=0.000-0.047). Neural networks, genetic algorithm selection and bootstrap simulation revealed
relationships between 5YS and healthy cells/CC (rank=1), erythrocytes/CC (2), PT N0—N12 (3), PT early -invasive EC (4), thrombocytes/CC (5); segmented
neutrophils/CC (6), lymphocytes/CC (7), eosinophils/CC (8), stick neutrophils/CC (9), leucocytes/CC (10), monocytes/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) availa bility of sufficient quantity of very
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.
Data:
•Males………………………………………………… …….... 424
•Females………..…………………………….......................144
•Age=56.9±9years
•Tumor Size=5.9±3.5cm
•OnlySurgery.………………………………… …................4 31
•AdjuvantChemoimmunoradiotherapy
•(5FU+thymalin /taktivin, 5-6 cycles+ Radiotherapy
•45-50Gy)………………………..........................................137
•Males………………………………………………… …….... 424
•Females………..…………………………….......................144
•Age=56.9±9years
•Tumor Size=5.9±3.5cm
•OnlySurgery.………………………………… …................4 31
•AdjuvantChemoimmunoradiotherapy
•(5FU+thymalin /taktivin, 5-6 cycles+ Radiotherapy
•45-50Gy)………………………..........................................137
:Radical Procedures
•Esophagogastrectomies Lewis (R0)……………… ………27 8
•Esophagogastrectomies Garlock (R0)………..................290
•Combined Esophagogastrectomies with Resection
•of Pancreas, Liver, Trachea, Lung, Aorta, Vena
•Cava Superior, Colon Transversum, Diaphragm,
Pericardium, Splenectomy (R0)……………...................... 174
•2-Field Lymphadenectomy……………………………… ….365
•3-Field Lymphadenectomy.………………………….… …...203
•Esophagogastrectomies Lewis (R0)……………… ………27 8
•Esophagogastrectomies Garlock (R0)………..................290
•Combined Esophagogastrectomies with Resection
•of Pancreas, Liver, Trachea, Lung, Aorta, Vena
•Cava Superior, Colon Transversum, Diaphragm,
Pericardium, Splenectomy (R0)……………...................... 174
•2-Field Lymphadenectomy……………………………… ….365
•3-Field Lymphadenectomy.………………………….… …...203
Staging:
•T1……133 N0..….288 G1…………161
•T2……121 N1….....71 G2…………143
•T3……186 N2…...209 G3…………2 64
•T4……128 M0…..568
•Adenocarcinoma……………………………. .326
•Squamos Cell Carcinoma…………………..23 2
•Mix………………….....…………………...........10
•Early Cancer……………………………...…...11 4
•Invasive Cancer…………………………..…..45 4
•T1……133 N0..….288 G1…………161
•T2……121 N1….....71 G2…………143
•T3……186 N2…...209 G3…………2 64
•T4……128 M0…..568
•Adenocarcinoma……………………………. .326
•Squamos Cell Carcinoma…………………..23 2
•Mix………………….....…………………...........10
•Early Cancer……………………………...…...11 4
•Invasive Cancer…………………………..…..45 4
Survival Rate:
•Alive………………………………………... ........300 (52.8%)
•5-Year Survivors…………..……………………194 (34.2%)
•10-Year Survivors…………………………… …105 (18.5%)
•Losses……………………………………………2 32 (40.8%)
•General Life Span=1906. 3±2278. 4 days
•For 5-Year Survivors=4300 .8±2503 .5 days
•For 10-Year Survivors=5860.8±2469.2 days
•For Losses=628 .8±321.8 days
•Cumulative 5-Year Survival……………………….. …..53%
•Cumulative 10- Year Survival…………………………..46.4 %
•Cumulative 20- Year Survival…………………………..33.4 %
•Cumulative 30- Year Survival…………………………..27.5%
•Alive………………………………………... ........300 (52.8%)
•5-Year Survivors…………..……………………194 (34.2%)
•10-Year Survivors…………………………… …105 (18.5%)
•Losses……………………………………………2 32 (40.8%)
•General Life Span=1906. 3±2278. 4 days
•For 5-Year Survivors=4300 .8±2503 .5 days
•For 10-Year Survivors=5860.8±2469.2 days
•For Losses=628 .8±321.8 days
•Cumulative 5-Year Survival……………………….. …..53%
•Cumulative 10- Year Survival…………………………..46.4 %
•Cumulative 20- Year Survival…………………………..33.4 %
•Cumulative 30- Year Survival…………………………..27.5%
General Esophageal Cancer Patients Survival after
Complete Esophagogastrectomies (Kaplan-Meier)
(n=568 ):
Survival Function
5YS=53%; 10YS=46.4%; 20YS=33.4%; 30YS=27.5%.
Complete Censored
-5 0 5 10 15 20 25 30 35 40 45
Years after Esophagogastrectomies
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
Cumulative Proportion Surviving
Complete Esophagogastrectomies (Kaplan-Meier)
(n=568 ):
Survival Function
5YS=53%; 10YS=46.4%; 20YS=33.4%; 30YS=27.5%.
Complete Censored
-5 0 5 10 15 20 25 30 35 40 45
Years after Esophagogastrectomies
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1.1
1.2
Cumulative Proportion Surviving
Results of Univariate Analysis of Phase
Transition Early—Invasive Cancer in Prediction
of EsophagealCancer Patients Survival (n=568):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of Early ECP=100%; 5YS of Invasive ECP=39.9%;
P=0.00000.
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
Transition Early—Invasive Cancer in Prediction
of EsophagealCancer Patients Survival (n=568):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of Early ECP=100%; 5YS of Invasive ECP=39.9%;
P=0.00000.
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
Results of Univariate Analysis of Phase Transition
N0—N1-2 inPrediction of Esophageal Cancer
PatientsSurvival (n=568 ):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of ECP with N0=73.7%; 5YS of ECP with N1-2=29.9%;
P=0.00000.
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
N1-2
N0
N0—N1-2 inPrediction of Esophageal Cancer
PatientsSurvival (n=568 ):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of ECP with N0=73.7%; 5YS of ECP with N1-2=29.9%;
P=0.00000.
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
N1-2
N0
Results of Univariate Analysis of Localization
(Upper/3 vs. Others) in Prediction of
EsophagealCancerPatientsSurvival (n=568):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of Upper/3 ECP=65.7%; 5YS of Others ECP=50.3%;
P=0.00195.
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 ECP
Upper/3 ECP
(Upper/3 vs. Others) in Prediction of
EsophagealCancerPatientsSurvival (n=568):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of Upper/3 ECP=65.7%; 5YS of Others ECP=50.3%;
P=0.00195.
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 ECP
Upper/3 ECP
Results of Univariate Analysis of Localization
(Cardioesophageal vs. Esophageal) in
Prediction of EsophagealCancerPatients
Survival (n=568):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of ECP=67.9%; 5YS of Cardioesophageal CP=37.6%;
P=0.00000.
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
Esophageal CP
Cardioesophageal CP
(Cardioesophageal vs. Esophageal) in
Prediction of EsophagealCancerPatients
Survival (n=568):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of ECP=67.9%; 5YS of Cardioesophageal CP=37.6%;
P=0.00000.
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
Esophageal CP
Cardioesophageal CP
Results of Univariate Analysis of Adjuvant
Treatment (Adjuvant
Chemoimmunoradiotherapy vs Surgery along)
in Prediction of EsophagealCancerPatients
Survival (n=568):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of ECP after Adjuvant Chemoimmunoradiotherapy=68.5%;
5YS of ECP after Surgery=49.6%;
P=0.0012.
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 Chemoimmunoradiotherapy
Only Surgery
Treatment (Adjuvant
Chemoimmunoradiotherapy vs Surgery along)
in Prediction of EsophagealCancerPatients
Survival (n=568):
Cumulative Proportion Surviving (Kaplan-Meier)
5YS of ECP after Adjuvant Chemoimmunoradiotherapy=68.5%;
5YS of ECP after Surgery=49.6%;
P=0.0012.
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 Chemoimmunoradiotherapy
Only Surgery
Results of Cox Regression Modeling in Prediction of Esophageal
Cancer Patients Survival after Complete
Esophagogastrectomies (n=568 ):
CoxRegressions, n=568 B SE Wald dfSig.Exp(B)
Eosinophils (%) .188.067 7.7721.005 1.207
Stick Neutrophils (%) .213.070 9.3781.002 1.238
Segmented Neutrophils (%) .189.061 9.5391.002 1.208
Lymphocytes (%) .169.061 7.6871.006 1.184
Monocytes (%) .194.064 9.1561.002 1.214
Time of Hemorrhage .001.000 8.8851.003 1.001
Residual Nitrogen .029.006 19.9201.000 1.029
Bilirubin .035.009 14.3711.000 1.036
Chlorides -.020.009 4.9811.026 .981
Prothrombin Index .017.004 14.9371.000 1.017
EC Cell Dynamics .059.023 6.3761.012 1.060
T1-4 .153.067 5.2181.022 1.165
Phase Transition N0--- N1_2 .402.108 13.8331.000 1.495
Age .037.006 44.5801.000 1.038
Histology -.213.092 5.3261.021 .808
G1-3 .198.060 10.7411.001 1.219
Localization (Upper/3 vs Others) -.559.129 18.7461.000 .572
Leucocytes/ Cancer Cells 1.151.506 5.1751.023 3.162
Eosinophils/ Cancer Cells -1.216.611 3.9591.047 .296
Stick Neutrophils/ Cancer Cells -1.482.583 6.4631.011 .227
Segmented Neutrophils/ Cancer Cells -1.150.513 5.0371.025 .317
Lymphocytes/ Cancer Cells -1.093.500 4.7821.029 .335
Monocytes/ Cancer Cells -1.209.501 5.8391.016 .298
Cancer Patients Survival after Complete
Esophagogastrectomies (n=568 ):
CoxRegressions, n=568 B SE Wald dfSig.Exp(B)
Eosinophils (%) .188.067 7.7721.005 1.207
Stick Neutrophils (%) .213.070 9.3781.002 1.238
Segmented Neutrophils (%) .189.061 9.5391.002 1.208
Lymphocytes (%) .169.061 7.6871.006 1.184
Monocytes (%) .194.064 9.1561.002 1.214
Time of Hemorrhage .001.000 8.8851.003 1.001
Residual Nitrogen .029.006 19.9201.000 1.029
Bilirubin .035.009 14.3711.000 1.036
Chlorides -.020.009 4.9811.026 .981
Prothrombin Index .017.004 14.9371.000 1.017
EC Cell Dynamics .059.023 6.3761.012 1.060
T1-4 .153.067 5.2181.022 1.165
Phase Transition N0--- N1_2 .402.108 13.8331.000 1.495
Age .037.006 44.5801.000 1.038
Histology -.213.092 5.3261.021 .808
G1-3 .198.060 10.7411.001 1.219
Localization (Upper/3 vs Others) -.559.129 18.7461.000 .572
Leucocytes/ Cancer Cells 1.151.506 5.1751.023 3.162
Eosinophils/ Cancer Cells -1.216.611 3.9591.047 .296
Stick Neutrophils/ Cancer Cells -1.482.583 6.4631.011 .227
Segmented Neutrophils/ Cancer Cells -1.150.513 5.0371.025 .317
Lymphocytes/ Cancer Cells -1.093.500 4.7821.029 .335
Monocytes/ Cancer Cells -1.209.501 5.8391.016 .298
Results of Neural Networks and Monte Carlo
Computingin Prediction of Esophageal Cancer
Patients Survival after Complete
Esophagogastrectomies (n=426
):
Corect Classification Rate=100%
Error=0.000
Area under ROC Curve=1.000
Factors n=426 (Neural Networks) Rank Sensitivity
Healthy Cells/Cancer Cells 1 29695
Erythrocytes/ Cancer Cells 2 20934
Phase Transition N0---N12 3 19263
Phase Transition Early---Invasive Esophageal Cancer 4 15337
Thrombocytes/ Cancer Cells 5 13175
Segmented Neutrophils/ Cancer Cells 6 10633
Lymphocytes/ Cancer Cells 7 5688
Eosinophils/ Cancer Cells 8 5414
Stick Neutrophils/ Cancer Cells 9 4868
Leucocytes/ Cancer Cells 10 4601
Monocytes/ Cancer Cells 11 3705
Computingin Prediction of Esophageal Cancer
Patients Survival after Complete
Esophagogastrectomies (n=426
):
Corect Classification Rate=100%
Error=0.000
Area under ROC Curve=1.000
Factors n=426 (Neural Networks) Rank Sensitivity
Healthy Cells/Cancer Cells 1 29695
Erythrocytes/ Cancer Cells 2 20934
Phase Transition N0---N12 3 19263
Phase Transition Early---Invasive Esophageal Cancer 4 15337
Thrombocytes/ Cancer Cells 5 13175
Segmented Neutrophils/ Cancer Cells 6 10633
Lymphocytes/ Cancer Cells 7 5688
Eosinophils/ Cancer Cells 8 5414
Stick Neutrophils/ Cancer Cells 9 4868
Leucocytes/ Cancer Cells 10 4601
Monocytes/ Cancer Cells 11 3705
Results of Bootstrap Simulationin Prediction
of Esophageal Cancer Patients Survival after
Complete Esophagogastrectomies (n=426
):
Bootstrap Simulation n=426
Significant Factors
(Number of Samples=3333)
Rank Kendall’Tau-A P<
Healthy Cells/Cancer Cells 1 0.306 0.000
Esophageal Cancer Cell Dynamics 2 -0.305 0.000
Erythrocytes/Cancer Cells 3 0.300 0.000
T1-4 4 -0.300 0.000
Leucocytes/Cancer Cells 5 0.291 0.000
Lymphocytes/Cancer Cells 6 0.280 0.000
Segmented Neutrophils/Cancer Cells 7 0.276 0.000
Residual Nitrogen 8 -0.276 0.000
PT N0---N12 9 -0.231 0.000
Monocytes/Cancer Cells 10 0.228 0.000
Coagulation Time 11 -0.227 0.000
PT Early---Invasive Cancer 12 -0.218 0.000
Esophageal/Cardioesophageal Cancer 13 -0.191 0.000
Eosinophils/Cancer Cells 14 0.174 0.000
Chlorides 15 0.167 0.000
Thrombocytes/Cancer Cells 16 0.158 0.000
G1-3 17 -0.138 0.000
Stick Neutrophils/Cancer Cells 18 0.134 0.000
Erythrocytes (tot) `19 0.110 0.000
Tumor Growth 20 -0.103 0.000
Weight 21 0.101 0.000
Combined Procedures 22 0.092 0.01
Procedures Type 23 -0.085 0.01
Localization 24 0.070 0.05
Glucose 25 0.068 0.05
Prothrombin Index 26 -0.067 0.05
of Esophageal Cancer Patients Survival after
Complete Esophagogastrectomies (n=426
):
Bootstrap Simulation n=426
Significant Factors
(Number of Samples=3333)
Rank Kendall’Tau-A P<
Healthy Cells/Cancer Cells 1 0.306 0.000
Esophageal Cancer Cell Dynamics 2 -0.305 0.000
Erythrocytes/Cancer Cells 3 0.300 0.000
T1-4 4 -0.300 0.000
Leucocytes/Cancer Cells 5 0.291 0.000
Lymphocytes/Cancer Cells 6 0.280 0.000
Segmented Neutrophils/Cancer Cells 7 0.276 0.000
Residual Nitrogen 8 -0.276 0.000
PT N0---N12 9 -0.231 0.000
Monocytes/Cancer Cells 10 0.228 0.000
Coagulation Time 11 -0.227 0.000
PT Early---Invasive Cancer 12 -0.218 0.000
Esophageal/Cardioesophageal Cancer 13 -0.191 0.000
Eosinophils/Cancer Cells 14 0.174 0.000
Chlorides 15 0.167 0.000
Thrombocytes/Cancer Cells 16 0.158 0.000
G1-3 17 -0.138 0.000
Stick Neutrophils/Cancer Cells 18 0.134 0.000
Erythrocytes (tot) `19 0.110 0.000
Tumor Growth 20 -0.103 0.000
Weight 21 0.101 0.000
Combined Procedures 22 0.092 0.01
Procedures Type 23 -0.085 0.01
Localization 24 0.070 0.05
Glucose 25 0.068 0.05
Prothrombin Index 26 -0.067 0.05
Results of Kohonen Self-Organizing Neural
Networks Computing in Prediction of
Esophageal CancerPatientsSurvival after
Complete Esophagogastrectomies (n=426):
Networks Computing in Prediction of
Esophageal CancerPatientsSurvival after
Complete Esophagogastrectomies (n=426):
Esophageal Cancer Cell Dynamics:
Prognostic Equation Models of Esophageal
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
Prognostic Equation Models of Esophageal
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
Prognostic Equation Models of Esophageal
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
Prognostic Equation Models of Esophageal
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
SEPATH Modeling in Prediction of Esophageal
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
Cancer Patients Survival after Complete
Esophagogastrectomies (n=426):
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:
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:
Optimal diagnosis and treatment
strategies for ECP are:
1) Screening and Early Detection
of EC;
2) Availability of Sufficient Quantity
of Very Experienced Thoraco-
abdominal 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:
strategies for ECP are:
1) Screening and Early Detection
of EC;
2) Availability of Sufficient Quantity
of Very Experienced Thoraco-
abdominal 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:
Consultant Thoracic, Abdominal, General Surgeon &
Surgical Oncologist
e-mail: [email protected]
skype: okshivets
http: //www.ctsnet.org/home/okshivets
Oleg Kshivets, MD,PhD
Surgical Oncologist
e-mail: [email protected]
skype: okshivets
http: //www.ctsnet.org/home/okshivets
Oleg Kshivets, MD,PhD
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