Kshivets O. Expert Systems for Diagnosis and Prognosis of Malignant Neoplasms
Kshivets O. Lung Cancer Surgery: Prognosis
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Transcript of Kshivets O. Lung Cancer Surgery: Prognosis
HOMEOSTASIS NETWORKS IN PROGNOSIS OF LUNG CANCER PATIENTS SURVIVAL
Oleg Kshivets, M.D., Ph.D.Department of Surgery, Siauliai Cancer Center, Lithuania
The 9th World Conference on Lung CancerTokyo, Japan, 2000
Abstract Homeostasis networks in prognosis of lung cancer patients survival O.Kshivets. Siauliai Cancer Center, Siauliai, Lithuania Purpose: The influence of homeostasis networks on 5-year survival (5YS) and life span (LS) of lung cancer (C) patients
(LCP) after radical procedures was investigated. Methods: In a randomized trial (1970-1999) cases of radically operated and monitored consecutive 404 LCP (male=363,
female=41; pneumonectomy=175, upper lobectomy=136, lower lobectomy=66, middle lobectomy=6, bilobectomy=21) with pathologic stage II-III (T1-N0-2M0; squamos cell C=263, adenocarcinoma=116, large cell C=25; stage II=111, stage III=293; T1=118, T2=187, T3=84, T4=15; N0=223, N1=97, N2=84; G1=100, G2=104, G3=200) were reviewed. 242 LCP (age=55.9±0.5 years; LS=2417.7±42.7 days; tumor diameter: D=4.1±0.1 cm) lived more than 5 years without any features of C progressing. 162 LCP (age=56.5±0.6 years; LS=576.0±30.6 days; D=4.7±0.2 cm) died because of relapses and generalization of C during the first 5 years after radical procedures. Variables selected for 5YS study were input levels of 46 blood and biochemic parameters, coagulogram, sex, age, TNMG, cell type, D. Representativeness of all samplings was reached by means of randomization based on unrepeated random selection. Multiple correspondence analysis (A), multi-factor clustering, A of variance, confirmatory factor A, structural equation modeling and Monte Carlo simulation were used to determine any significant overall regularities between 5YS (LS) and LCP homeostasis.
Results: It was revealed that 5YS and LS of radically operated LCP (n=404) significantly depended on: 1) phase transition of early LC into invasive LC; 2) input level of blood cell subpopulations circuit; 3) ratio of C cell population quantity to blood cell subpopulations quantity in integral LCP organism (cell ratio factors: CRF); 4) LC characteristics (C cell population quantity, TNMG-system); 5) biochemic homeostasis; 6) hemostasis system; 7) anthropometric data. Structural equation modeling and Monte Carlo simulation confirmed significant overall networks between 5YS (LS) of LCP and blood cell subpopulations circuit (2=10485.5; k=169; T=4.747; P=0.000002), biochemic homeostasis (2=239.6; k=64; T=-3.64; P=0.0003), phase transition of early C into invasive C (2=5.540; k=1; T=3.711; P=0.0002), CRF (2=4017.8; k=43; T=4.377; P=0.00001), C characteristics (2=98.6; k=13; T=-4.635; P=0.000003); hemostasis system (2=211.6; k=34; T=6.814; P=0.000000); anthropometric data (2=157.3; k=8; T=3.50; P=0.0004).
Samplings:
Lung Cancer Patients Lived More than 5 Years after Complete Resections..…...242
Lung Cancer Patients Died Because Generalization During First 5 Years after Complete Resections.…….…………...162
In All…………………………………...404
Samplings: Adjuvant
Chemoimmunoradiotherapy…………..54 Postoperative Radiotherapy..……...…..86 Surgery Alone…………………………264 In All…………………………………...404
Radical Procedures: Pneumonectomy…………………..175 Upper/Lower Bilobectomy…………21 Upper Lobectomy…………………136 Lower Lobectomy………………….66 Middle Lobectomy………………….6 Combined Procedures……………..49 In All…………………………...….404
Main Problem of Analysis of Living Supersystems (e.g. Lung Cancer Patient Homeostasis):
Phenomenon of «Combinatorial Explosion»
Average Number of Routine Blood Parameters:….. 46 Number of Possible Combination for Random Search:
……………..………………….. n!=46!=5.5e+57 Operation Time of The 7G Superteracomputer
(1000TFLOPS) (The 21st Century)…….1.7e+35 Years
Basis NP RP P n! n*n*2(e+n) or n log n n
AI CSA+S+B SM
Model «Cancer Cells(Cr)--Human Killer Cells(Kl)»
Ćr=Cr(1-Kl·μCr/λKl); Ќl=(Kl·μCr/λKl)·[25·Cr/(4.189+ +2.5·Cr)-Cr-1];
Prognostic Role of Lung Cancer Diameter
Bivariate Histogram: Life Span of LCP and Cancer Diameter
n=404
Clinicopathologic Nucloids of Lung Cancer Patients with N0-2, n=404
Results of Cluster-Analysis of Clinicopathologic
Characteristics of Lung Cancer Patients with N0-2, n=404
Homeostasis Nucloids of Lung Cancer Patients with N0-2, n=404
Results of Cluster-Analysis of Homeostasis Data of Lung Cancer Patients with N0-2, n=404
Results of Correspondence Analysis of Pathologic Characteristics of Lung Cancer Patients with N0-2, n=404
Network-Model of Lung Cancer Patients with N0-2 (n=404)
Homeostasis Network-Model of Lung Cancer Patients with N0-2 (n=404)
Morphologic and Homeostasis Network-Model of Lung Cancer Patients with N0-2 (n=404)
Survival of Lung Cancer Patients with N0-2 (n=404)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Lung Cancer Patients, n=404 (N0-N1-N2)Global Chi2=14.34; Df=2; P=0.00077
Time (months) after complete resections
Cum
ulat
ive
Prop
ortio
n Su
rviv
ing
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 20 40 60 80 100 120 140 160 180 200
Only Complete Resections, n=264Postoperative Radiotherapy, n=86Adjuvant Chemoimmunoradiotherapy, n=54
Proportional Hazard (Cox) Regression Model of Lung Cancer Patients with N0-2, n=404
Survival Function for Mean Values of Independent VariablesProportional Hazard (Cox) Regression
Lung Cancer Patients, n=404 (N0-N1-N2)Chi2=129.33; Df=13; P=0.000000
Survival Time (Months)
Cum
ulat
ive
Prop
ortio
n Su
rviv
ing
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.05
0 20 40 60 80 100 120 140 160 180 200
Logistic Regression Model of Lung Cancer Patients with N0-2, n=404
ExpectedNormal
Frequency Distribution: ResidualsLung Cancer Patients with N0-2, n=404
Logistic Regression ModelsChi2=109.27; Df=13; P=0.0000000
No
of o
bs
0102030405060708090
100110120
-1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 1.2
Survival of Lung Cancer Patients with N0-2 (n=404)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Lung Cancer Patients, n=404 (N0-N1-N2)Global Chi2=92.32; Df=2; P=0.000000000
Time (munths) after complete resections
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 20 40 60 80 100 120 140 160 180 200
N0, n=223N1, n=97N2, n=84
Survival of Lung Cancer Patients with N1-2 (n=181)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Lung Cancer Patients, n=181 (N1-N2)Global Chi2=11.951; Df=2; P=0.00254
Time (monts) after complete resections
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 20 40 60 80 100 120 140 160
Only comlete Resections, n=89Posoperative Radiotherapy, n=59Adjuvant Chemoimmunoradiotherapy, n=33
Cluster-Analysis of Data of Early and Invasive Lung Cancer Patients
Phase Transition Early Malignancy into Invasive Cancer
Results of Monte Carlo Simulation: Phase Transition—Survival of LCP
-1.263 -1.005 -0.746 -0.488 -0.230 0.028 0.287 0.545 0.803 1.062 above
From: Monte Carlo Data -- Replication 1 (lc1.sta)Lung Cancer Patients, n=404
Chi2=1217.569; df=2; P<0.0000000 Model: Phase Transition Early Cancer-Invasive Cancer---Survival
Regularities between Dynamics Cancer Cell Population and Patient's Survival Rate
Phase Transitions in System «Homeostasis-Malignancy»
The Three Phase Transitions in the System «Malignancy-Human’s Organism»
Regression Models (Cell Ratio Factors--Life Span of LCP, n=162; 18th Degree Polynomial Fit): y=a+bx+cx2+dx 3+...
Lymphocytes/CC--Life Span of LCP; n=162; r=0.259;P=0.000
Lymphocytes/Cancer Cells
Life
Spa
n (D
ays)
0.0 0.9 1.8 2.7 3.6 4.5 5.4
Monocytes/CC--Life Span of LCP; n=162; r=0.350;p=0.000
Monocytes/Cancer Cells
Life
Spa
n (D
ays)
0.0 0.2 0.5 0.7 0.9 1.2 1.4
Segmented Neutrophils/CC--Life Span of LCP; n=162;r=0.271; P=0.000
Segmented Neutrophils/Cancer Cells
Life
Spa
n (D
ays)
0.1 3.3 6.5 9.7 12.9 16.1 19.4
Leukocytes/CC--Life Span of LCP; n=162; r=0.266;P=0.000
Leukocytes/Cancer Cells
Life
Spa
n (D
ays)
0.2 4.1 8.1 12.0 16.0 19.9 23.9
Regression Models (Cell Ratio Factors--Life Span of LCP, n=162; 18th Degree Polynomial Fit): y=a+bx+cx2+dx 3+...
Erhytrocytes/CC--Life Span of LCP; n=162; r=0.391;P=0.000
Erhytrocytes/Cancer Cells
Life
Spa
n (D
ays)
0.0 2.0 4.0 6.0 8.0 10.0 12.0
Thrombocytes/CC--Life Span of LCP; n=162; r=0.435;P=0.0000
Thrombocytes/Cancer Cells
Life
Spa
n (D
ays)
7.3 110.3 213.4 316.4 419.4 522.5 625.5
Healthy Cells/CC--Life Span of LCP; n=162; r=0.321;P=0.000
Healthy Cells/Cancer Cells
Life
Spa
n (D
ays)
0.8 7.2 13.5 19.8 26.2 32.5 38.8
Regression Models (Cell Ratio Factors--Life Span of LCP, n=162; 15th Degree Polynomial Fit): y=a+bx+cx2+dx 3+...
Eosinophils/CC--Life Span of LCP; n=162; r=0.278;P=0.000
Eosinophils/Cancer Cells
Life
Spa
n (D
ays)
0.0 0.1 0.3 0.4 0.5 0.6 0.8
Stick Neutrophils/CC--Life Span of LCP; n=162; r=0.283;P=0.000
Stick Neutrophils/Cancer Cells
Life
Spa
n (D
ays)
0.0 0.1 0.3 0.4 0.5 0.7 0.8
Cell Ratio Factors in Prognosis of 5-Year Survival Lung Cancer Patients
Normal Probability PlotNormalized Residuals
Lung Cancer Patients (n=404) Model: Cell Ratio Factors-Survival
Value
Exp
ecte
d N
orm
al V
alue
-3
-2
-1
0
1
2
3
-4 -2 0 2 4 6 8 10 12 14
Results of Monte Carlo Simulation:Cell Ratio Factors—Survival of LCP
-0,046 0,209 0,463 0,718 0,973 1,227 1,482 1,736 1,991 2,245 above
From: Monte Carlo Data -- Replication 1 (lc1.sta)Lung Cancer Patients (n=404)
Cell Ratio Factors in Prediction LCP Survival
Results of Structural Equation Modeling
Normal Probability Plot (Conf.Modeling)Normalized Residuals
Lung Cancer Patients (n=404)
Model: Survival-Blood Cell Circuit-Cancer-Biochem.Homeostasis
Value
Exp
ecte
d N
orm
al V
alue
-3,5
-2,5
-1,5
-0,5
0,5
1,5
2,5
3,5
-16 -12 -8 -4 0 4 8 12 16
Networks Between Lung Cancer Patients Survival and System “Cancer- Homeostasis”
Superoncoprognosis-1.0SUPERONCOPROGNOSIS-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
Conclusions: 5-year survival and life span of lung cancer patients (n=404)
after complete resections significantly depended on: 1) phase transition of early cancer into invasive cancer; 2) input level of blood cell subpopulations circuit; 3) cell ratio factors: ratio of cancer cell population number to
blood cell subpopulations number in integral lung cancer patient organism;
4) cancer characteristics (cancer cell population number, TNMG-system);
5) the data of blood biochemical homeostasis; 6) hemostasis system; 7) anthropometric data.
Patents:1. Kshivets O.M. Method of Screening and Differential Diagnosis of Malignant Neoplasms. Patent
from 27.04.92; N2045072: 28pp.2. Kshivets O.M. Method of Prognosis of Survival Rate of Radically Operated Patients with
Malignant Neoplasms. Patent from 10.02.94; N2101704: 24pp. 3. Kshivets O.M. Method of Prognosis of Survival Rate of Non-Radically Operated Patients with
Malignant Neoplasms. Patent from 14.03.94; N2104536: 10pp. 4. Kshivets O.M. Method of Early and Differential Immunodiagnosis of Malignant Neoplasms.
Patent from 24.10.95; N2107290: 12pp. 5. Kshivets O.M. Method of Immunodiagnosis of Distant Metastases for Patients with Malignant
Neoplasms. Patent from 06.10.95; N2107295: 8pp. 6. Kshivets O.M. Method of Immunodiagnosis of Generalization for Patients with Malignant
Neoplasms. Patent from 09.10.95; N2107294: 12pp. 7. Kshivets O.M. Method of Immunodiagnosis of Early and Invasive Malignancy for Patients.
Patent from 04.05.95: N2107293: 14pp. 8. Kshivets O.M. Method of Differential Diagnosis of Malignancy and Pre-Cancer or Non-
Malignant Pathology. Patent from 08.11.94; N2114431: 18pp. 9. Kshivets O.M. Method of Measuring the Size of Malignant Neoplasms and Total Number of
Malignant Cells in Oncopatient’s Organism Based on the Homeostasis Parameters. Patent from 04.05.95; N2135996: 8pp.
Patents:10. Kshivets O.M. Method of Diagnosis of Distant Metastases for Patients with
Malignant Neoplasms. Patent from 03.11.95; N2134878: 12pp. 11. Kshivets O.M. Method of Diagnosis of Generalization for Patients with Malignant
Neoplasms. Patent from 20.10.95; N2132059: 12pp. 12. Kshivets O.M. Method of Diagnosis of Early and Invasive Malignancy for a Single
Patient. Patent from 06.10.95; N2133466: 13pp. 13. Kshivets O.M. Method of Diagnosis of Malignant Neoplasms Metastasizing in
Regional Lymphatic Nodules for a Concrete Patient. Patent from 29.09.95; N2131606: 10pp.
14. Kshivets O.M. Method of Measuring the Size of the Malignancy and Total Number of Malignant Cells in the Oncopatient’s Organism Based on the Immunogram. Patent from 04.05.95; N2135995: 9pp.
15. Kshivets O.M. Method of Immunodiagnosis of Regional Metastases for Patients with Malignant Neoplasms. Patent from 06.10.95; N2131607: 9pp.
Address:
Oleg Kshivets, M.D., Ph.D. Thoracic Surgeon Department of Surgery Siauliai Cancer Center Tilzes:42-16, Siauliai, LT78206, Lithuania Tel. (37041)416614 Fax (37041)526430 [email protected] [email protected] http//:myprofile.cos.com/Kshivets