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NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG
CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES PNEUMONECTOMIES
Oleg Kshivets, MD, PhDOleg Kshivets, MD, PhD
Surgery Department,Siauliai Cancer Center, LithuaniaSurgery Department,Siauliai Cancer Center, LithuaniaThe Society of Cardiothoracic Surgeons of Great Britain and Ireland AnnualThe Society of Cardiothoracic Surgeons of Great Britain and Ireland Annual
ScientificScientific Meeting Meeting,, London London, the UK, March, the UK, March 5-8, 2005. 5-8, 2005.
AbstractAbstractNEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OFNON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES Oleg Kshivets Surgery Department, Siauliai Cancer Center, LithuaniaOBJECTIVE: 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).
Factors:1) Antropometric Factors…………...42) Blood Analysis…………………...263) Hemostasis Factors……………….84) Cell Ratio Factors………………...9 5) Lung Cancer Characteristics…….86) Biochemic Factors………………...57) Treatment Characteristics……….58) Survival Data……………………...3 In All……………………………….68
Main Problem of Analysis of Alive Supersystems Main Problem of Analysis of Alive Supersystems (e.g. Lung Cancer Patient Homeostasis):(e.g. Lung Cancer Patient Homeostasis):
Phenomenon of «Combinatorial Explosion» Phenomenon of «Combinatorial Explosion»
Number of Clinicomorphological Factors:……...….. 68Number of Possible Combination for Random Search:……………..………………….. n!=68!=2.48e+96 Operation Time of IBM Blue Gene/L Supercomputer (70.72TFLOPS) ………………………….1.11e+75 YearsThe Age of Our Universe……….....1.3e+10Years
Basis:Basis:
NP RP P n! n*n*2(e+n) or n log n n AI CSA+S+B SM
Antropometric Factors:
Male………….…………..460Female………..……………51Age……..…….57.1±0.4 yearsWeight………...……70±05 kgHeight…………168.5 ±0.3 cm
Radical Procedures:Radical Procedures:Pneumonectomy………………..212Upper/Lower Bilobectomy…...…26Upper Lobectomy…………...…173Lower Lobectomy……………….93Middle Lobectomy………….…….7In All…………………………....511
Combined & Extensive Radical Procedures with Resection of Pericardium, Left Atrium, Aorta, Vena Cava Superior, Vena Azygos, Carina, Trachea, Diaphragm, Chest Wall, Ribs, etc.…………………….143
Sistematic MediastinalSistematic MediastinalLymph Node-N2 Lymph Node-N2 Dissection…………..Dissection…………..386386
Staging:Staging:
T1…..143 N0..…297 G1…..122T2…..225 N1…..116 G2…..144T3…..112 N2……98 G3…..245T4……31 Stage II...171 Stage III...340Squamous Cell Carcinoma…..……….329Adenocarcinoma………………………144Large Cell Carcinoma………………….38Central…………211 Peripherical…..300
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 .265909G1-3 .816419 .995129 2.32995 .127570T1-4 .818500 .992559 3.54892 .060194N0-2 .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 25.556Histology -.134 .125 1.147 .2847 .874 .683 1.119G1-3 -.199 .132 2.271 .1325 .820 .632 1.062T1-4 -.246 .130 3.562 .0597 .782 .606 1.010N0-2 -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 CorrectLosses 83 102 44.9%5-Year Survivors 37 259 87.5%
Total 120 361 71.1%
Survival Rate of Lung Cancer Patients after Survival Rate of Lung Cancer Patients after Lobectomies and Pneumonectomies (R0) (n=511):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%)
Adjuvant Therapy after Lobectomies and Pneumonectomies: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/m2 IV on day 1, Doxorubicin 50 mg/m2 IV on day 1, Vincristin 1.4 mg/m2 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/m2 IV on day 1, 8, 15 and cisplatin 75 mg/m2 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 (60CO; 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.
Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)
Factors Mean±SD Mean±SD (Survivors) (Losses) P n=296 n=185Life Span (Months) 86.1±34.4 18.7±12.8 0.000000Weight (kg) 71.6±10.9 67.3±11.5 0.00005Tumor Size (cm) 4.3±1.8 5.0±2.4 0.00018Eosinophils (%) 3.0±2.5 2.2±1.9 0.00029Eosinophils (abs) 0.19±0.19 0.13±0.13 0.00055Eosinophils (tot) 0.95±0.97 0.62±0.61 0.00005Seg.Neutrophils (%) 64.5±11.5 68.7±10.1 0.00005Lymphocytes (%) 25.0±9.9 22.7±8.8 0.01158Lymphocytes (abs) 1.54±0.83 1.37±0.73 0.02045 Lymphocytes (tot) 7.71±4.34 6.39±3.44 0.00050Monocytes (%) 5.2±3.1 4.4±2.6 0.00290Monocytes (abs) 0.33±0.27 0.28±0.22 0.01957Monocytes (tot) 1.67±1.35 1.32±1.14 0.00360Erythrocytes (tot) 21.05±4.43 19.41±4.77 0.00015ESS 17.6±14.4 21.1±16.5 0.01331
Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)
Factors Mean±SD Mean±SD (Survivors) (Losses) P n=296 n=185Thrombotest 4.8±0.8 4.6±0.9 0.01465Fibrinogen-B 1.2±0.4 1.4±0.8 0.00052Heparin Tolerance 186.9±67.9 228.5±127.1 0.000004Prothrombin Index 93.6±8.7 99.2±8.2 0.000000Glucose 4.7±1.0 4.5±0.9 0.02299Leucocytes/CaCells 8.2±4.4 6.7±3.4 0.00006Eosinophils/CaCells 0.25±0.27 0.14±0.14 0.000000St.Neutrophils/ CaCells 0.21±0.31 0.14±0.21 0.00995 Seg.Neutrophils/CaCells 5.2±3.0 4.6±2.5 0.01393Lymphocytes/CaCells 2.1±1.4 1.5±1.0 0.000002Monocytes/CaCells 0.45±0.40 0.29±0.24 0.000003Erythrocytes/CaCells 5.7±2.4 4.7±2.1 0.000002Thrombocytes/CaCells 308.7±150.1 258.1±114.3 0.000096 Healthy Cells/CaCells 19.5±7.5 16.2±6.9 0.000002
Significant Factors between Lung Cancer Losses & 5-Year Survivors (n=481)
Factors Log-Rank Test P
O(I) vs. A(II) 0.03687G1 vs. G3 0.00061T1 vs. T2 0.00460T1 vs. T3 0.01848T1 vs. T4 0.00041T2 vs. T4 0.02097T3 vs. T4 0.03976N0 vs. N1 0.00000 N0 vs. N2 0.00000 N1 vs. N2 0.00001Stage II vs. Stage III 0.00000Surgery alone vs. P/o Radiotherapy 0.00046Ad.Chemioimmunoradiotherapy vs. P/o Radiotherapy 0.00025
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
Survival FunctionComplete Censored
Survival Rate of Lung Cancer Patients after Lobectomies and Pneumonectomiesn=511
Survival Time (Years after Lobectomies and Pneumonectomies)
Cum
ulat
ive
Prop
ortio
n Su
rviv
ing
0.350.400.450.500.550.600.650.700.750.800.850.900.951.001.051.101.15
0 5 10 15 20 25
Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511 O(I) vs. A(II) Long-rank test P=0.03685
Survival Time (Years after Lobectomies and Pneumonectomies)
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 2 4 6 8 10 12 14 16 18 20 22
O(I) A(II) B(III) AB(IV)
Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511G1 vs. G3 Long-rank test P=0.00061
Survival Time (Years after Lobectomies and Pneumonectomies)
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 2 4 6 8 10 12 14 16 18 20 22
G1 G2 G3
Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511T1 vs. T2, P=0.0046; T1 vs. T3, P=0.01848; T1 vs.T4, P=0.00041;
T2 vs. T4, P=0.02097; T3 vs. T4, P=0.03976 (by Long-rank test)
Survival Time (Years after Lobectomies and Pneumonectomies)
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 2 4 6 8 10 12 14 16 18 20 22
T1 T2 T3 T4
Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511N0 vs. N1, P=0.00000; N0 vs. N2, P=0.00000
N1 vs. N2, P=0.00001 (by Long-rank test)
Survival Time (Years after Lobectomies and Pneumonectomies)
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 2 4 6 8 10 12 14 16 18 20 22
N0 N1 N2
Cumulative Proportion Lung Cancer Patients Surviving (Kaplan-Meier) (n=511)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Survival of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511Surgery alone vs. P/o Radiotherapy, P=0.00046;
Adjuvant Chemoimmunoradiotherapy vs. P/o Radiotherapy, P=0.00025 (by Long-rank t
Survival Time (Years after Lobectomies and Pneumonectomies)
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 2 4 6 8 10 12 14 16 18 20 22
Surgery alone P/o Radiotherapy Adjuvant Chemoimmunoradiotherapy
Results of Multivariate Proportional Hazard Cox Regression Analysis:
Chi2=312.447; df=37; n=511; P=0.000000Factors Wald df P Exp(B) 95%CI for Exp(B) Lower UpperAge 7.553 1 0.006 1.018 1.005 1.031Weight 12.368 1 0.000 0.942 0.911 0.974Histology 13.631 2 0.001Histology(1) 13.271 1 0.000 0.430 0.273 0.677Histology (2) 12.094 1 0.001 0.409 0.247 0.677G1-3 5.652 2 0.059G1-3(1) 1.706 1 0.191 0.835 0.637 1.094G1-3(2) 1.113 1 0.292 1.148 0.888 1.483T1-4 9.447 3 0.024T1-4(1) 6.664 1 0.010 0.410 0.209 0.807T1-4(2) 7.778 1 0.005 0.447 0.254 0.787T1-4(3) 3.852 1 0.050 0.578 0.335 0.999N0-2 47.796 2 0.000N0-2(1) 46.895 1 0.000 0.357 0.266 0.479N0-2(2) 16.061 1 0.000 0.515 0.373 0.713
Results of Multivariate Proportional Hazard Cox Regression Analysis:
Chi2=312.447; df=37; n=511; P=0.000000Factors Wald df P Exp(B) 95%CI for Exp(B) Lower UpperTumor Size 2.720 1 0.099 1.086 0.985 1.199Thrombocytes 4.271 1 0.039 0.990 0.980 0.999Seg.Neutrophils(%) 2.776 1 0.096 1.034 0.994 1.076Lymphocytes(%) 4.431 1 0.035 1.049 1.003 1.097ESS 10.559 1 0.001 0.987 0.980 0.995Prothrombin Index 34.344 1 0.000 1.034 1.023 1.046Bilirubin 5.394 1 0.020 1.041 1.006 1.076Recalcification Time 9.152 1 0.002 0.996 0.993 0.999Heparin Tolerance 29.782 1 0.000 1.003 1.002 1.005Ad.CHIRT 33.555 1 0.000 2.920 2.032 4.196Leucocytes/CaCells 8.214 1 0.004 0.731 0.590 0.906Thrombocytes/CaCells 1.976 1 0.160 0.998 0.996 1.001Eosinophils/CaCells 47.796 1 0.037 3.444 1.080 10.976Seg.Neutrophils/CaCells 46.895 1 0.003 1.555 1.160 2.084Healthy Cells/CaCells 4.514 1 0.034 1.057 1.004 1.112
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 0.923Lymphocytes (tot) 8.676 1 0.003 0.816 0.713 0.934Leucocytes (tot) 11.348 1 0.001 1.189 1.075 1.315Eosinophils (tot) 5.908 1 0.015 0.691 0.512 0.931Thrombocytes (tot) 11.146 1 0.001 1.003 1.001 1.005Operation 1.544 4 0.819Operation(1) 0.458 1 0.499 0.863 0.563 1.322Operation(2) 0.389 1 0.533 0.867 0.554 1.358Operation(3) 0.001 1 0.980 0.994 0.620 1.593Operation(4) 0.057 1 0.811 0.896 0.364 2.203Surgery alone 3.066 1 0.080 1.265 0.972 1.645Fibrinogen 4.180 1 0.041 1.078 1.003 1.158
Results of Multifactor Analysis in Prediction of Lung Cancer Results of Multifactor Analysis in Prediction of Lung Cancer
Patients Survival after Lobectomies and Pneumonectomies (n=511)Patients Survival after Lobectomies and Pneumonectomies (n=511) Factor Loadings, Factor 1 vs. Factor 2
Rotation: Varimax normalizedExtraction: Principal components
Prediction of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=511
Factor 1
Fact
or 2
SEX
AGE
MASSA
GROUTHHIST
G
T
N12_0
D
ERHB
CP
THR L
E
P
S
LYM M EABS
PABSSABS
LYMABS MABS
SOE
COAG_B
T_HEMGLU
PI
BILIR TIMSULPROT T_RECTHR_T
FIBR_BFIBR
TOL_HEP
OPER
GAMMACHT_IT_R
SURGERY
ER_CC
THR__CCL_CC
E_CC
P_CC
S_CCLYM_CC
M_CC
MASS_CC
ER_TOT
THR_TOT L_TOT
E_TOT
P_TOTS_TOT
LYM_TOTM_TOTSU5 LS
-1.0
-0.6
-0.2
0.2
0.6
1.0
1.4
-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0
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< 0.0000Wilks' Partial F-remove P-level Lambda Lambda (1,421)
Ad.CHTITR .607564 .989364 4.52592 .033966PI .621404 .967328 14.2193 .000186N0-2 .675599 .889731 52.1766 .000000Recalcificat.Time .613179 .980303 8.45919 .003824Fibrinogen-B .613035 .980533 8.35821 .004038G1-3 .605988 .991937 3.42216 .065027Histology .606000 .991917 3.43069 .064695T1-4 .602375 .997886 0.89167 .345566Growth .603213 .996500 1.47861 .224673Tumor Size .601970 .998557 0.60837 .435841weight .604121 .995002 2.11483 .146623Erythrocytes .602821 .997148 1.20419 .273113Protein .602782 .997212 1.17719 .278550P/o RT .601136 .999942 0.02449 .875716Surgery alone .601688 .999026 0.41053 .522049Operation type .603138 .996624 1.42627 .233047Lymphocytes .601366 .999560 0.18539 .667001Leucocytes/CC .601948 .998594 0.59281 .441766
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 1029324Growth -.313 .267 1.378 .2405 .731 .432 1.235Histology -.347 .154 5.053 .0250 .707 .521 .957G1-3 -.240 .148 2.656 .1039 .786 .588 1.051T1-4 -.027 .198 0.020 .8879 .972 .659 1.435N0-2 -1.191 .164 52.87 .0000 .304 .220 .419S.Neut.(abs) -.137 .052 7.004 .0084 .872 .788 .965Mon. (abs) 1.604 .572 7.852 .0050 4.972 1.615 15.313ESS -.013 .008 2.454 .1179 .987 .972 1.003Proth.Index -.071 .014 26.80 .0000 .932 .907 .957Operation -.141 .113 1.545 .2145 .869 .695 1.085P/o RT -.019 .627 0.001 .9752 .981 .286 3.360Ad.CHIRT 1.256 .600 4.385 .0368 3.510 1.080 11.405Surg. alone .159 .703 0.051 .8213 1.172 .294 4.670Healt.C/CC .035 .023 2.320 .1284 1.036 .990 1.084
Results of Clustering in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
Logical Formulas based on Simple MeanLosses: 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)
Results of Multifactor Clustering of Clinicomorphologic Factors in Prediction of Results of Multifactor Clustering of Clinicomorphologic Factors in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
Results of Results of CorrespondenceCorrespondence Analysis in Prediction of Analysis in Prediction of LungLung Cancer Cancer Patients Survival after Lobectomies and Pneumonectomies (n=Patients Survival after Lobectomies and Pneumonectomies (n=481481))
Results of Results of CorrespondenceCorrespondence Analysis in Prediction of Analysis in Prediction of LungLung Cancer Cancer Patients Survival after Lobectomies and Pneumonectomies (n=Patients Survival after Lobectomies and Pneumonectomies (n=481481))
Results of Results of CorrespondenceCorrespondence Analysis in Prediction of Analysis in Prediction of LungLung Cancer Cancer Patients Survival after Lobectomies and Pneumonectomies (n=Patients Survival after Lobectomies and Pneumonectomies (n=481481))
Results of Results of CorrespondenceCorrespondence Analysis in Prediction of Analysis in Prediction of LungLung Cancer Cancer Patients Survival after Lobectomies and Pneumonectomies (n=Patients Survival after Lobectomies and Pneumonectomies (n=481481))
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
Predictor Variable Importance RankingsDependent variable: Losses---5-Year Survivors (n=481)
Rankings on scale from 0=low importance to 100=high importancePrediction of Lung Cancer Patients Survival after Lobectomies & Pneumonectomies
Predictor variable
Ran
king
0
20
40
60
80
100
SEX
GR
OU
THH
IST G T
N12
_0TR
EAT
AG
EM
ASS
A D ER HB
THR L E P S
LYM M
SOE
CO
AG
_BT_
HEM
GLU PI
BILI
RPR
OT
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Classification Tree in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
Classification Tree for Lung Cancer Patients SurvivalPrediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomie
Number of splits = 11; Number of terminal nodes = 12
1
2 3
4 5
6 7 8 9
10 11 12 13 14 15
16 17 18 19
20 21
22 23
N12_0=N2
PI107.64
PI94.369 AGE 58.021
FIBR_B 1.8848 N12_0=N1 LYM 14.523
N12_0=N1,N2 TOL_HEP 244.95
MASSA 67.48
G=G3
92 389
346 43
178 168 23 20
150 28 51 117 5 15
8 20 36 15
16 20
9 11
l>5
d<5 l>5
l>5 l>5
l>5 l>5 l>5 d<5
l>5 l>5 d<5 l>5 l>5 d<5
d<5 l>5 d<5 d<5
d<5 l>5
d<5 l>5
d<5l>5
Neural Networks in Prediction of Lung Cancer Patients Survival after Neural Networks in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)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 SelectionUseful 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
Training Error Graph (Sum-squared)Prediction of Lung Cancer Patients after Lobectomies and Pneumonectomies, n=481
Network: (MLP) Error=0.0456Area under ROC curve=0.996
Correct Classification Rate=99.8%
Epoch
Erro
r
0.0
0.2
0.4
0.6
0 20 40 60 80
Training by Levenberg-Marquardt, n=481
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 RatioN0-2 1 0.470 10.317Growth 2 0.414 9.069Surgery alone 3 0.387 8.480T1-4 4 0.313 6.863Operation type 5 0.312 6.853G1-3 6 0.311 6.814Histology 7 0.292 6.404P/o RT 8 0.218 4.774Ad.CHIRT 9 0.209 4.579ESS 10 0.175 3.838Protein 11 0.175 3.836Prothr.Index 12 0.150 3.285
Factor Rank Error RatioSex 13 0.129 2.829Seg.Neutr.(%) 14 0.106 2.326Tumor Size 15 0.091 2.001Lymph. (%) 16 0.089 1.958Monocytes/CC 17 0.080 1.749Thromb./CC 18 0.078 1.704Eosinoph./CC 19 0.075 1.650Health.C/CC 20 0.072 1.570Leucocytes/CC 21 0.064 1.397Glucose 22 0.046 1.005Lymph./CC 23 0.046 1.004Bilirubin24 0.046 1.000
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 RatioSurgery alone 1 0.289 90.726Growth 2 0.232 72.022T1-4 3 0.210 65.877G1-3 4 0.180 56.593Histology 5 0.158 49.643Oper. Type 6 0.129 40.481Heparin Tol. 7 0.125 39.354Sex 8 0.109 34.264P/o RT 9 0.100 31.362Ad.CHIRT 10 0.077 24.167Fibrinogen 11 0.046 14.307Tumor Size 12 0.045 14.126
Factor Rank Error RatioColor Index 13 0.036 11.361Prothr.Index 14 0.032 10.013Thrombocytes 15 0.029 9.193Recalc.Time 16 0.028 8.727Lymphocytes 17 0.019 6.094Erythrocytes 18 0.015 4.608Protein 19 0.012 3.758ESS 20 0.012 3.736Bilirubin21 0.010 3.271Eosinophils 22 0.009 2.827Eryth./CC 23 0.007 2.334Age 24 0.007 2.190
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 RatioGrowth 1 0.326 479.79Oper.Type 2 0.311 458.33G1-3 3 0.304 448.13Surgery alone 4 0.270 397.90Prothr.Index 5 0.201 296.07T1-4 6 0.194 285.29P/o RT 7 0.181 266.85Histology 8 0.156 230.13Ad.CHIRT 9 0.139 204.86Heparin Tol. 10 0.133 195.71Thrombocytes 11 0.095 139.76Fibrinogen 12 0.094 138.29
Factor Rank Error RatioRecalc.Time 13 0.092 135.66Sg.Neutrophils 14 0.058 85.353Tumor Size 15 0.036 53.551Eosinophils 16 0.013 19.082Lymphocytes 17 0.010 14.699Glucose 18 0.009 13.404Erythrocytes 19 0.008 11.934Monocytes 20 0.007 10.742Weight 21 0.007 10.361Leucocytes 22 0.003 4.969Age 23 0.002 2.991Hemoglobin 24 0.002 2.819
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 RatioAd.CHIRT 1 0.304 362.21P/o RT 2 0.236 282.08Surgery alone 3 0.189 225.69Histology 4 0.188 223.93T1-4 5 0.183 217.82Oper.Type 6 0.178 211.96Prothr.Index 7 0.169 201.18G1-3 8 0.159 189.62Growth 9 0.145 173.45Monocytes % 10 0.124 147.55Bilirubin11 0.119 141.68Sex 12 0.104 124.44
Factor Rank Error RatioSg.Neutrophils 13 0.056 66.814Leucocytes 14 0.025 30.316Lymphocytes 15 0.025 29.263Monocytes abs 16 0.015 18.396Sg.Neutr./CC 17 0.013 15.026Hemor.Time 18 0.009 10.996Monocytes/CC 19 0.007 8.408ESS 20 0.006 7.094Recalc.Time 21 0.005 5.700Glucose 22 0.004 4.221Heparin Tol. 23 0.003 4.117Lymphocytes t 24 0.002 2.819
Decision Tree in Prediction of Lung Cancer Patients Survival with N0 (n=274) and with N2
(n=92) after Lobectomies and Pneumonectomies
Results of Kohonen Self-Organizing Neural Networks Computing in Prediction of Lung Cancer Patients Survival
with N0 (n=274) and with N2 (n=92) after Lobectomies and Pneumonectomies
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Prediction of Lung Cancer Patients Survival with N0, n=297 Surgery alone vs. P/o RT, P=0.021 by long-rank test
Years after Lobectomies and Pneumonectomies
Cum
ulat
ive
Prop
ortio
n Su
rviv
ing
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0 2 4 6 8 10 12 14 16 18 20 22
Surgery alone P/o RT Ad. CHIRT
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)
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)
Cumulative Proportion Surviving (Kaplan-Meier)Complete Censored
Prediction of Lung Cancer Patients Survival with N1-2, n=214Ad.CHIRT vs. Surgery alone P=0.0001 by long-rank test
Ad.CHIRT vs. P/o RT P=0.0010 by long-rank test
Years after Lobectomies and Pneumonectomies
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 2 4 6 8 10 12 14 16 18
Surgery alone P/o RT Ad.CHIRT
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) Cumulative Proportion Surviving (Kaplan-Meier)
Complete CensoredPrediction of Lung Cancer Patients Survival with N1, n=116
Ad.CHIRT vs. Surgery alone, P=0.004 by long-rank test
Years after Lobectomies and Pneumonectomies
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 2 4 6 8 10 12 14 16
Surgery alone P/o RT Ad.CHIRT
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) Cumulative Proportion Surviving (Kaplan-Meier)
Complete CensoredPrediction of Lung Cancer Patients Survival with N2, n=98 Ad.CHIRT vs. Surgery alone, P=0.0004 by long-rank test
Ad.CHIRT vs. P/o RT, P=0.0002 by long-rank test
Years after Lobectomies and Pneumonectomies
Cum
ulat
ive
Prop
ortio
n Su
rviv
ing
0.00.10.20.30.40.50.60.70.80.91.0
0 2 4 6 8 10 12 14 16 18
Surgery alone P/o RT Ad.CHIRT
Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
Number of Samples=3333Significant Factors Rank Kendall’s Tau-A PN0-2 1 -0.2080 0.000000Lymphocytes/CaCells 2 0.1737 0.000000Erythrocytes/CaCells 3 0.1731 0.000000Prothrombin Index 4 0.1709 0.000000Erythrocytes (tot) 5 0.1576 0.000000Thrombocytes/CaCells 6 0.1474 0.000001Leucocytes/CaCells 7 0.1431 0.000003Lymphocytes (tot) 8 0.1217 0.000067Eosinophils/CaCells 9 0.1209 0.000081Healthy Cells/CaCells 10 0.1172 0.000113Weight 11 0.1144 0.000124Monocytes/CaCells 12 0.1134 0.000172
Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
Number of Samples=3333Significant Factors Rank Kendall’s Tau-A PSegmented Neutrophils (%) 13 -0.1003 0.000421Eosinophils (tot) 14 0.0944 0.001310Tumor Size 15 -0.0837 0.006102Eosinophils (%) 16 0.0836 0.006164T1-4 17 -0.0817 0.008210Monocytes (tot) 18 0.0805 0.008354 Heparin Tolerance 19 -0.0782 0.010123Eosinophils (abs) 20 0.0770 0.011639Monocytes (%) 21 0.0711 0.012002G1-3 22 -0.0701 0.024204Glucose 23 0.0600 0.049998
Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
Results of Bootstrap simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)
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 CorrectLosses 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 CorrectLosses 128 57 69.2%5-Year Survivors 33 263 88.9%Total 161 320 81.3%
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 CorrectLosses 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 CorrectLosses 184 1 99.5%5-Year Survivors 0 296 100.0%Total 184 297 99.8%
Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations Populations & & Blood Glucose Level Blood Glucose Level in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Patients
Survival Survival (n= (n=481481))
Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations Populations & & Blood Glucose Level Blood Glucose Level in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Patients
Survival Survival (n= (n=481481))
Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations Populations & & Blood Glucose Level Blood Glucose Level in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Patients
Survival Survival (n= (n=481481))
Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Ratio of Erythrocytes, Leucocytes, Eosinophils, Healthy Cells and Cancer Cell Populations Populations & & Blood Glucose Level Blood Glucose Level in in Prediction Prediction of Lung Cancer of Lung Cancer Patients Patients
Survival Survival (n= (n=481481))
Networks between Clinicopathologic, Biochemic, Hemostasis & Hematologic Data and 5-Networks between Clinicopathologic, Biochemic, Hemostasis & Hematologic Data and 5-Year Survival of Lung cancer Patients after Lobectomies and Pneumonectomies (n=481)Year Survival of Lung cancer Patients after Lobectomies and Pneumonectomies (n=481)
Results of Monte Carlo Simulation in Prediction of Lung Cancer Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Patients Survival after Lobectomies and Pneumonectomies (n=481)
-1.958 -1.684 -1.411 -1.138 -0.865 -0.592 -0.318 -0.045 0.228 0.501 above
From: Monte Carlo DataPrediction of Lung Cancer Patients Survival after Lobectomies & Pneumonectomies
Chi2=64.411; df=35; P=0.00178; n=481
Results of Monte Carlo Simulation in Prediction of Lung Cancer Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Patients Survival after Lobectomies and Pneumonectomies (n=481)
-0.441 0.003 0.447 0.891 1.335 1.78 2.224 2.668 3.112 3.556 above
From: Monte Carlo DataPrediction of Lung Cancer Patients Survival after Lobectomies & Pneumonectomies
Chi2=28.09; df=14; P=0.0139; n=481
Results of Monte Carlo Simulation in Prediction of Lung Cancer Results of Monte Carlo Simulation in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Patients Survival after Lobectomies and Pneumonectomies (n=481)
-0.407 -0.025 0.356 0.737 1.118 1.5 1.881 2.262 2.643 3.025 above
From: Monte Carlo DataPrediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomie
Chi2=41.0; df=27; P=0.0412; n=481
SEPATH Networks in Prediction of Lung Cancer Patients SEPATH Networks in Prediction of Lung Cancer Patients Survival after Lobectomies and Pneumonectomies (n=481)Survival after Lobectomies and Pneumonectomies (n=481)
Holling-Tenner Models of Alive Supersystem “Lung Cancer-Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell PopulationCytotoxic Cell Population”
Holling-Tenner Models of Alive Supersystem “Lung Cancer-Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell PopulationCytotoxic Cell Population”
Holling-Tenner Models of Alive Supersystem “Lung Cancer-Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell PopulationCytotoxic Cell Population”
0 2 4 6 8 10 12
0.1
10
100
Early Cancer; 5-Year Survival=100%Invasive Cancer, Stage II; 5-Year Survival=76%Invasive Cancer, Stage III; 5-Year Survival=53%Generalization; 5-Year Survival=0%
Model "Lung Cancer---Cytotoxic Cells"
Lung Cancer Cell Population
Cyt
otox
ic C
ell P
opul
atio
n
11
0.473
X1 3
X2 3
X3 3
X4 3
110.082 X1 2 X2 2
X3 2 X4 2
Holling-Tenner Models of Alive Supersystem “Lung Cancer-Holling-Tenner Models of Alive Supersystem “Lung Cancer-Cytotoxic Cell PopulationCytotoxic Cell Population”
0 100 200 300 400
0.1
10
100
Cytotoxic CellsLung Cancer Cells
Model "Lung Cancer---Cytotoxic Cells"
Time
Lung
Cel
l Pop
ulat
ion
Dyn
amic
s11
0.185
X1 2
X1 3
3000 X1 1
Lung Cancer Dynamics
SUPERONCOPROGNOSIS-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: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.
Patents:1. Kshivets O.M. Method of Prognosis of
Survival Rate of Radically Operated Patients with Malignant Neoplasms. Patent from 10.02.94; N2101704: 24pp.
2. Kshivets O.M. Method of Prognosis of Survival Rate of Non-Radically Operated Patients with Malignant Neoplasms. Patent from 14.03.94; N2104536: 10pp.
Address:
Oleg Kshivets, M.D., Ph.D.Thoracic Surgeon, Dep.of Surgery, Siauliai Cancer CenterTilzes:42-16, Siauliai, LT5400, LithuaniaTel. (37041)416614 Fax 1(270)9687098
kshivets@yahoo.comhttp//:myprofile.cos.com/Kshivets