5-Year Survival of Lung Cancer Patients after Radical Surgery was Significantly Depended on Tumor Characteristics, Blood Cell Circuit, Cell Ratio Factors, Hemostasis System, Biochemic Homeostasis, Surgery Type, Adjuvant Treatment and Anthropometric Data
5-YEAR SURVIVAL OF UPPER THIRD ESOPHAGEAL CANCER PATIENTS WAS SIGNIFICANTLY SUPERIOR IN COMPARISON WITH MIDDLE AND LOWER THIRD ESOPHAGEAL CANCER PATIENTS AFTER RADICAL SURGERY AND STRONGLY DEPENDED ON PHASE TRANSITION EARLY-INVASIVE CANCER, LYMPH NODE METASTASES, CELL RATIO FACTORS AND ADJUVANT CHEMOIMMUNORADIOTHERAPY
5-Year Survival of Lung Cancer Patients after Radical Surgery was Significantly Depended on Tumor Characteristics, Blood Cell Circuit, Cell Ratio Factors, Hemostasis System, Biochemic Homeostasis, Surgery Type, Adjuvant Treatment and Anthropometric Data
5-YEAR SURVIVAL OF UPPER THIRD ESOPHAGEAL CANCER PATIENTS WAS SIGNIFICANTLY SUPERIOR IN COMPARISON WITH MIDDLE AND LOWER THIRD ESOPHAGEAL CANCER PATIENTS AFTER RADICAL SURGERY AND STRONGLY DEPENDED ON PHASE TRANSITION EARLY-INVASIVE CANCER, LYMPH NODE METASTASES, CELL RATIO FACTORS AND ADJUVANT CHEMOIMMUNORADIOTHERAPY
5-Year Survival of Gastric Cancer Patients after Radical Surgery was Significantly Depended on Tumor Characteristics, Blood Cell Circuit, Cell Ratio Factors, Hemostasis System and Adjuvant Treatment
Combined Esophagogastrectomies: Survival Outcomes in Patients with Local Adva...Oleg Kshivets
CONCLUSIONS: 5YS of local advanced ECP after combined radical procedures significantly depended on: tumor characteristics, blood cell circuit, cell ratio factors, biochemical factors, hemostasis system, anthropometric data and adjuvant treatment. Optimal strategies for local advanced ECP are: 1) availability of very experienced thoracoabdominal surgeons because of complexity radical procedures; 2) aggressive en block surgery and adequate lymph node dissection for completeness; 3) precise prediction; 4) AT for ECP with unfavorable prognos
5-Year Survival of Non-Small Cell Lung Cancer Patients after Radical Surgery Significantly Depended on Phase Transition “Early-Invasive Cancer”, Lymph Node Metastases and Cell Ratio Factors
NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES
Gastric Cancer: 10-Year Survival
Kshivets Oleg Surgery Department, Roshal Hospital, Moscow, Russia
CONCLUSIONS: 10-Year survival of GCP 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) GC characteristics; 9) anthropometric data; 10) surgery type. Optimal diagnosis and treatment strategies for GC are: 1) screening and early detection of GC; 2) availability of experienced abdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunotherapy for GCP with unfavorable prognosis.
5-Year Survival of Gastric Cancer Patients after Radical Surgery was Significantly Depended on Tumor Characteristics, Blood Cell Circuit, Cell Ratio Factors, Hemostasis System and Adjuvant Treatment
Combined Esophagogastrectomies: Survival Outcomes in Patients with Local Adva...Oleg Kshivets
CONCLUSIONS: 5YS of local advanced ECP after combined radical procedures significantly depended on: tumor characteristics, blood cell circuit, cell ratio factors, biochemical factors, hemostasis system, anthropometric data and adjuvant treatment. Optimal strategies for local advanced ECP are: 1) availability of very experienced thoracoabdominal surgeons because of complexity radical procedures; 2) aggressive en block surgery and adequate lymph node dissection for completeness; 3) precise prediction; 4) AT for ECP with unfavorable prognos
5-Year Survival of Non-Small Cell Lung Cancer Patients after Radical Surgery Significantly Depended on Phase Transition “Early-Invasive Cancer”, Lymph Node Metastases and Cell Ratio Factors
NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES
Gastric Cancer: 10-Year Survival
Kshivets Oleg Surgery Department, Roshal Hospital, Moscow, Russia
CONCLUSIONS: 10-Year survival of GCP 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) GC characteristics; 9) anthropometric data; 10) surgery type. Optimal diagnosis and treatment strategies for GC are: 1) screening and early detection of GC; 2) availability of experienced abdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunotherapy for GCP with unfavorable prognosis.
Paludisme grave : pourquoi doit-on développer des modèles in vitro sur le terrain ? - Conférence de la 8e édition du Cours international « Atelier Paludisme » - RAZAKANDRAINIBE Romy - Madagascar - romy@pasteur.mg
Prognostic Value of Right Ventricular Parameters in Patients with Left Ventri...carlofino
Prognostic Value of Right Ventricular Parameters in Patients with Left Ventricular Dysfunction undergoing Coronary Revascularization. A Longitudinal Study
Esophageal cancer patients’ survival after surgery significantly depended on cell ratio factors, blood cell circuit, biochemical factors, hemostasis system, adjuvant chemoimmunoradiotherapy, cancer characteristics, localization, anthropometric data
dkNET Webinar: Leveraging Computational Strategies to Identify Type 1 Diabete...dkNET
dkNET New Investigator Pilot Program in Bioinformatics Awardee Webinar Series
Presenter: Wenting Wu, PhD. Research Assistant Professor, Center for Diabetes and Metabolic Diseases, Department of Medical and Molecular Genetics, Associate Director of Data and Analytics Core for Center for Diabetes and Metabolic Diseases, Indiana University School of Medicine
Abstract
Type 1 diabetes (T1D) is an immune-mediated disease that results in insulin insufficiency and affects 0.3% of the population, including both children and adults. To support clinical trial efforts, there is an urgent need to develop reliable biomarkers capable of predicting T1D risk and guiding therapeutic interventions. Recently, whole blood bulk RNA sequencing has been used to guide T1D clinical trial design and assess response to disease modifying interventions. While the use of bulk RNA sequencing is cost-effective, these datasets provide limited information about cell specific gene expression changes. Here, we aimed to apply computational strategies to deconvolute cell type composition using cell specific gene expression references. Single-cell RNA sequencing (scRNA-seq) was conducted to profile peripheral blood mononuclear cells obtained from youth within recent T1D onset and age- and sex-matched controls and identified 31 distinct cell clusters. Using this pre-defined reference dataset, we ran computational algorithms CIBERSORTx and other deconvolution methods simultaneously to deconvolute cell proportions using public clinical trial data. We focused our initial analysis on data from the TN-20 Rituximab trial, which tested the anti-CD20 monoclonal antibody rituximab vs placebo in recent onset T1D. This talk will introduce recent advances of scRNA-seq techniques and computational deconvolution methods and demonstrate that how we apply different deconvolution approaches for secondary analysis of existing clinical trial data, in the purpose of linking cell specific immune signatures associated with drug responder status.
Upcoming webinars schedule: https://dknet.org/about/webinar
La présentation sur Nancytomique faite lors de la réunion scientifique sur le Laboratoire sans murs organisée avec le consulat de France dans le cadre de la Filière Médicale Francophone Nancy-Wuhan à la Faculté de Médecine de Wuhan et à l'Hôpital Zhongnan.
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/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: 5YS of LCP 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) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic 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 LCP with unfavorable prognosis.
Gastric Cancer: Сlinical Implementation of Artificial Intelligence, Synergeti...Oleg Kshivets
5-year survival of GCP 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) GC cell dynamics; 9) GC characteristics; 10) tumor localization; 11) anthropometric data; 12) surgery type. Optimal diagnosis and treatment strategies for GC are: 1) screening and early detection of GC; 2) availability of sufficient quantity of experienced abdominal surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunotherapy for GCP with unfavorable prognosis.
Local Advanced Esophageal Cancer (T3-4N0-2M0): Artificial Intelligence, Syner...Oleg Kshivets
5YS of local advanced ECP after combined radical procedures significantly depended on: tumor characteristics, blood cell circuit, cell ratio factors, biochemical factors, hemostasis system, anthropometric data and adjuvant treatment. Optimal strategies for local advanced ECP are: 1) availability of very experienced thoracoabdominal surgeons because of complexity radical procedures; 2) aggressive en block surgery and adequate lymph node dissection for completeness; 3) precise prediction; 4) AT for ECP with unfavorable prognosis.
Esophageal Cancer: Artificial Intelligence, Synergetics, Complex System Analy...Oleg Kshivets
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.
Kshivets Oleg Optimization of Management for Esophageal Cancer Patients (T1-...Oleg Kshivets
Optimization of Management for Esophageal Cancer Patients (T1-4N0-2M0).
Kshivets Oleg Surgery Department, Bagrationovsk Hospital, Bagrationovsk, Kaliningrad, Russia
ABSTRACT
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) pa¬tients (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 trea
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 characteristics; 9) EC cell dynamics; 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.
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) pa¬tients (ECP) (T1-4N0-2M0) 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 557 consecutive ECP (age=56.6±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2023 (m=415, f=142; esophagogastrectomies (EG) Garlock=288, EG Lewis=269, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=168; adenocarcinoma=319, squamous=228, mix=10; T1=130, T2=115, T3=184, T4=128; N0=282, N1=70, N2=205; G1=157, G2=142, G3=258; early EC=111, invasive=446; only surgery=425, adjuvant chemoimmunoradiotherapy-AT=132: 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 1876.9±2219.8 days and cumulative 5-year survival (5YS) reached 52%, 10 years – 45.5%, 20 years – 33.4%, 30 years – 26.9%. 187 ECP lived more than 5 years (LS=4271±2411.9 days), 99 ECP – more than 10 years (LS=5883±2296.6 days). 228 ECP died because of EC (LS=629.8±324.1 days). AT significantly improved 5YS (67.8% vs. 48.7%) (P=0.00084 by log-rank test). 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 early-invasive EC (2); PT N0—N12 (3), erythrocytes/CC (4), thrombocytes/CC (5); stick neutrophils/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), eosinophils/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 characteristics; 9) EC cell dynamics; 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)AT
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) pa¬tients (ECP) (T1-4N0-2M0) 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 557 consecutive ECP (age=56.6±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2023 (m=415, f=142; esophagogastrectomies (EG) Garlock=288, EG Lewis=269, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=168; adenocarcinoma=319, squamous=228, mix=10; T1=130, T2=115, T3=184, T4=128; N0=282, N1=70, N2=205; G1=157, G2=142, G3=258; early EC=111, invasive=446; only surgery=425, adjuvant chemoimmunoradiotherapy-AT=132: 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 1876.9±2219.8 days and cumulative 5-year survival (5YS) reached 52%, 10 years – 45.5%, 20 years – 33.4%, 30 years – 26.9%. 187 ECP lived more than 5 years (LS=4271±2411.9 days), 99 ECP – more than 10 years (LS=5883±2296.6 days). 228 ECP died because of EC (LS=629.8±324.1 days). AT significantly improved 5YS (67.8% vs. 48.7%) (P=0.00084 by log-rank test). 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 early-invasive EC (2); PT N0—N12 (3), erythrocytes/CC (4), thrombocytes/CC (5); stick neutrophils/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), eosinophils/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 characteristics; 9) EC cell dynamics; 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 ch
5-year survival of GCP 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) GC characteristics; 9) GC cell
dynamics; 10) tumor localization; 11) anthropometric
data; 12) surgery type. Best diagnosis and treatment
strategies for GC are: 1) screening and early detection
of GC; 2) availability of experienced abdominal
surgeons because of complexity of radical procedures;
3) aggressive en block surgery and adequate lymph
node dissection for completeness; 4) precise
prediction; 5) adjuvant chemoimmunotherapy for GCP
with unfavorable prognosis.
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for non-small cell lung cancer (LC) pa¬tients (LCP) (T1-4N0-2M0) was analyzed.
METHODS: We analyzed data of 771 consecutive LCP (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2022 (m=662, f=109; upper lobectomies=278, lower lobectomies=178, middle lobectomies=18, bilobectomies=42, pneumonectomies=255, mediastinal lymph node dissection=771; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=194; only surgery-S=620, adjuvant chemoimmunoradiotherapy-AT=151: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=322, T2=255, T3=133, T4=61; N0=518, N1=131, N2=122, M0=771; G1=195, G2=243, G3=333; squamous=418, adenocarcinoma=303, large cell=50; early LC=215, invasive LC=556; right LC=413, left LC=358; central=291; peripheral=480. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence.
RESULTS: Overall life span (LS) was 2240.9±1748.8 days and cumulative 5-year survival (5YS) reached 73%, 10 years – 64.2%, 20 years – 43%. 503 LCP lived more than 5 years (LS=3126.6±1536 days), 145 LCP – more than 10 years (LS=5068.5±1513.2 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (77.7% vs.63.4%, P=0.00001 by log-rank test). AT significantly improved 5YS (64.4% vs. 34.8%) (P=0.00003 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.035). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), eosinophils/CC (4), erythrocytes/CC (5),healthy cells/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), stick neutrophils/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: 5YS of LCP after radical procedures significantly depended on: PT early-invasive cancer; PT N0--N12; cell ratio factors; blood cell circuit; biochemical factors; hemostasis system; AT; LC characteristics; surgery type; anthropometric data.
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for non-small cell lung cancer (LC) pa¬tients (LCP) (T1-4N0-2M0) was analyzed.
METHODS: We analyzed data of 771 consecutive LCP (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2022 (m=662, f=109; upper lobectomies=278, lower lobectomies=178, middle lobectomies=18, bilobectomies=42, pneumonectomies=255, mediastinal lymph node dissection=771; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=194; only surgery-S=620, adjuvant chemoimmunoradiotherapy-AT=151: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=322, T2=255, T3=133, T4=61; N0=518, N1=131, N2=122, M0=771; G1=195, G2=243, G3=333; squamous=418, adenocarcinoma=303, large cell=50; early LC=215, invasive LC=556; right LC=413, left LC=358; central=291; peripheral=480. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence.
RESULTS: Overall life span (LS) was 2240.9±1748.8 days and cumulative 5-year survival (5YS) reached 73%, 10 years – 64.2%, 20 years – 43%. 503 LCP lived more than 5 years (LS=3126.6±1536 days), 145 LCP – more than 10 years (LS=5068.5±1513.2 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (77.7% vs.63.4%, P=0.00001 by log-rank test). AT significantly improved 5YS (64.4% vs. 34.8%) (P=0.00003 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.035). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), eosinophils/CC (4), erythrocytes/CC (5),healthy cells/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), stick neutrophils/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: 5YS of LCP 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) LC characteristics; 9) LC dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data.
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for non-small cell lung cancer (LC) pa¬tients (LCP) (T1-4N0-2M0) was analyzed.
METHODS: We analyzed data of 771 consecutive LCP (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated and monitored in 1985-2022 (m=662, f=109; upper lobectomies=278, lower lobectomies=178, middle lobectomies=18, bilobectomies=42, pneumonectomies=255, mediastinal lymph node dissection=771; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=194; only surgery-S=620, adjuvant chemoimmunoradiotherapy-AT=151: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=322, T2=255, T3=133, T4=61; N0=518, N1=131, N2=122, M0=771; G1=195, G2=243, G3=333; squamous=418, adenocarcinoma=303, large cell=50; early LC=215, invasive LC=556; right LC=413, left LC=358; central=291; peripheral=480. Variables selected for study were input levels of 45 blood parameters, sex, age, TNMG, cell type, tumor size. Regression modeling, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine significant dependence.
RESULTS: Overall life span (LS) was 2240.9±1748.8 days and cumulative 5-year survival (5YS) reached 73%, 10 years – 64.2%, 20 years – 43%. 503 LCP lived more than 5 years (LS=3126.6±1536 days), 145 LCP – more than 10 years (LS=5068.5±1513.2 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (77.7% vs.63.4%, P=0.00001 by log-rank test). AT significantly improved 5YS (64.4% vs. 34.8%) (P=0.00003 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.035). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), eosinophils/CC (4), erythrocytes/CC (5),healthy cells/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), stick neutrophils/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: 5YS of LCP 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) LC characteristics; 9) LC dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data.
OBJECTIVE: 5-survival (5YS) and life span after radical surgery for esophageal cancer (EC) pa¬tients (ECP) (T1-4N0-2M0) was analyzed.
METHODS: We analyzed data of 556 consecutive ECP (age=56.5±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2022 (m=415, f=141; esophagogastrectomies (EG) Garlock=287, EG Lewis=269, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=167; adenocarcinoma=318, squamous=228, mix=10; T1=129, T2=115, T3=184, T4=128; N0=281, N1=70, N2=205; G1=157, G2=141, G3=258; early EC=110, invasive=446; only surgery=424, adjuvant chemoimmunoradiotherapy-AT=132: 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 1877±2221.6 days and cumulative 5-year survival (5YS) reached 52%, 10 years – 45%, 20 years – 33.4%, 30 years – 27%. 186 ECP lived more than 5 years (LS=4283.3±2412.6 days), 99 ECP – more than 10 years (LS=5883±2296.6 days). 227 ECP died because of EC (LS=631.8±323.4 days). AT significantly improved 5YS (60.3% vs. 42%) (P=0.0029 by log-rank test). 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=0.000-0.021). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and P PT early-invasive EC (rank=1); healthy cells/CC (2), erythrocytes/CC (3), PT N0—N12 (4) thrombocytes/CC (5); segmented neutrophils/CC (6), stick neutrophils/CC (7), lymphocytes/CC (8), monocytes/CC (9); leucocytes/CC (10); eosinophils/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 characteristics; 9) tumor localization; 10) anthropometric data; 11) 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.
Survival of Lung Cancer Patients after Lobectomies was Significantly Superior...Oleg Kshivets
OBJECTIVE: This study aimed to determine surgery type influence for 5-year survival (5YS) of non-small cell lung cancer (LC) patients (LCP) after complete en block (R0) lobectomies and pneumonectomies.
METHODS: We analyzed data of 765 consecutive patients (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated (R0) and monitored in 1985-2022 (m=659, f=106; bi/lobectomies=512, pneumonectomies=253, mediastinal lymph node dissection=765; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=192; only surgery-S=616, adjuvant chemoimmunoradiotherapy-AT=149: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=318, T2=255, T3=133, T4=59; N0=514, N1=131, N2=120, M0=765; G1=194, G2=241, G3=330; squamous=417, adenocarcinoma=298, large cell=50; early LC=212, invasive LC=553. Multivariate Cox modeling, discriminant analysis, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence.
RESULTS: Overall life span (LS) was 2240.1±1751.6 days and cumulative 5-year survival (5YS) reached 72.8%, 10 years – 64.2%, 20 years – 42.9%. 499 LCP lived more than 5 years (LS=3126.8±1540 days), 143 LCP – more than 10 years (LS=5083.3±1518.6 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (77.6% vs.63.1%, P=0.00001 by log-rank test). AT significantly improved 5YS (64.4% vs. 34.8%) (P=0.00003 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). 5YS of LCP after Lobectomies (77.6%) was significantly superior in comparison with LCP after pneumonectomies (63%) (P=0.00001 by log-rank test). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12(rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), segmented neutrophils/CC (7), lymphocytes/CC (8), monocytes/CC (9); stick neutrophils/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: 5YS of LCP 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) LC characteristics; 9) surgery type: lobectomy/pneumonectomy; 10) anthropometric data.
• Gastric cancer prognosis and cell ratio factors Oleg Kshivets
OBJECTIVE: We examined cell ratio factors (CRF) significantly affecting gastric cancer (EC) patients GCP) survival. CRF - ratio between cancer cells (CC) and blood cells subpopulations.
METHODS: We analyzed data of 799 consecutive GCP (T1-4N0-2M0) (age=57.1±9.4 years; tumor size=5.4±3.1 cm) radically operated (R0) and monitored in 1975-2022 (m=558, f=241; total gastrectomies=173, distal gastrectomies=461; proximal gastrectomies=165; combined gastrectomies=247 with resection of esophagus, pancreas, liver, duodenum, diaphragm, colon transversum, splenectomy, etc; only surgery-S=624, adjuvant chemoimmunotherapy-AT=175 (5-FU + thymalin/taktivin); T1=238, T2=220, T3=184, T4=157; N0=437, N1=109, N2=253, M0=799; G1=222, G2=164, G3=413. Variables selected for prognosis 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 GCP were evaluated using a log-rank test. Multivariate Cox modeling, discriminant analysis, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence.
RESULTS: Overall life span (LS) was 2128.9±2300.3 days and cumulative 5-year survival (5YS) reached 58.4%, 10 years – 51.9%, 20 years – 39%, 30 years – 27.2%. 318 GCP lived more than 5 years (LS=4304.5±2290.6 days), 169 GCP – more than 10 years (LS=5919.5±2020 days). 290 GCP died because of GC (LS=651±347.2 days). Cox modeling displayed that G CP survival significantly depended on CRF: healthy cells/CC, erythrocytes/CC, monocytes/CC, phase transition (PT) in terms of synergetics early—invasive cancer; PT N0--N12, age, G1-3, hemorrhage time, ESS, sex, AT, prothrombin index, residual nitrogen. Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early—invasive cancer (rank=1); PT N0--N12 (2); healthy cells/CC (3), erythrocytes/CC (4), thrombocytes/CC (5), monocytes/CC (6), segmented neutrophils/CC (7), leucocytes/CC (8), lymphocytes/CC (9), stick neutrophils/CC (10), eosinophils/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: GCP survival after radical procedures significantly depended on CRF.
Kshivets O. Lung Cancer: Early Detection and Diagnosis
1. The Open Lung Cancer Journal, 2008, 1, 1-12 1
Open Access
Early Detection and Diagnosis of Lung Cancer and Immune Circuit
Oleg Kshivets*
Thoracic Surgery Department, Klaipeda University Hospital, Klaipeda, Lithuania
Abstract: Purpose: Significance of immune cell and humoral circuit in terms of early detection and diagnosis of lung
cancer (LC) was investigated.
Methods: In retrospective trial (1987-2008) consecutive cases after surgery, monitored 533 LCP (males - 472, females -
61; pneumonectomies - 181, upper lobectomies - 138, lower lobectomies - 67, upper/lower bilobectomies - 24, middle
lobectomies - 6, segmentectomies - 76, exploratory thoracotomies and biopsies - 41) with pathologic stage I-IV (stage I -
48, stage II - 47, stage III - 321; stage IV - 117; squamous cell LC - 294, adenocarcinoma - 171, large cell LC - 48, small
cell LC - 20; T1 - 116, T2 - 168, T3 - 125, T4 - 124; N0 - 148, N1 - 144, N2 - 159; N3 - 82; G1 - 88, G2 - 166, G3 - 279;
M0 - 438; M1 - 95) and 282 patients with lung non-malignant pathology (NMP) (males - 188, females - 94; pneumonec-
tomies - 5, upper lobectomies - 96, lower lobectomies - 81, middle lobectomies - 2, segmentectomies and wedge resec-
tions - 98; non-malignant tumors - 100; abscess - 112; tuberculoma - 70) were reviewed. Variables selected for study were
input levels of immunity blood parameters, sex, age, TNMG. Thawed aliquoted samples were evaluated for IgG, IgM,
IgA, natural antibodies, circulating immune complexes. The percentage, absolute count and total population number (per
human organism) of T-lymphocytes (CD3), B-lymphocytes (CD19), helper T-lymphocytes (CD4), suppressor/cytotoxic
T-lymphocytes (CD8), killer cells (O-cells, K-cells or CD16), precursor T-cells (CD1), activated T-cells (CDw26), mono-
cytes (CD64, CD13), helper/inducer T-lymphocytes (CD4+2H), contrsuppressor T-lymphocytes (CD8+VV), CD4/CD8,
leukocytes, lymphocytes, polymorphonuclear and stabnuclear leukocytes were estimated. The laboratory blood studies
also included input levels of NST (tests of oxygen dependent metabolism of neutrophils spontaneous and stimulated by
Staphylococcus aureus or by Streptococcus pyogenes), index of stimulation of leukocytes by Staphylococcus aureus or
Streptococcus pyogenes, index of thymus function, phagocytic number, phagocyte index, index of complete phagocytosis.
Differences between groups were evaluated using multi-factor clustering, nonlinear estimation (logistic regression), struc-
tural equation modeling and Monte Carlo simulation.
Results: It was revealed that early detection of LC (stage I-II; tumor size=2.5±0.1 cm; T1-2N0M0; n=95) from NMP
(n=282) significantly (P=0.000000) depended on: 1) level of immune cell circuit ( 2=38749.1; Df=989); 2) value of
monocyte and macrophage circuit ( 2=662.8; Df=20); 3) level of humoral immunity ( 2=585.9; Df=9); 4) neutrophils cir-
cuit ( 2=5214.4; Df=77). It was also founded that diagnosis of LC (stage I-IV; tumor size=5.4±0.1 cm; T1-4N0-3M0-1;
n=533) from NMP significantly (P=0.000000) depended on: 1) value of immune cell subpopulations ( 2=80569.9;
Df=989); 2) macrophage circuit ( 2=312.1; Df=20); 3) humoral factors ( 2=243.1; Df=9); 4) neutrophils circuit
( 2=10772.3; Df=77).
Keywords: Lung cancer, immunity, early detection, diagnosis.
INTRODUCTION fluorescence techniques, computerized molecular analysis of
airway cell markers, etc. [1,2].
Theoretically the early detection (ED) of lung cancer
(LC) allows increasing the 5-year survival rate of the LC Differential diagnosis (DS) of LC from non-malignant
patients (LCP) by several times while the combined and pathology (NMP) is another very complicated branch of
complex treatment - only by 5-30% with incomparable fi- clinical oncology. In this sphere there are more illusions,
nancial expenses [1]. That is why screening programs domi- disappointments and failures than real results. That is why
nate in the long-term strategic anti-cancer programs in the the great number of LCP is treated in the hospitals for so-
USA, Japan and Europe, that is why hundred million dollars matic pathology and is observed by different physicians for
are assigned on these programs, and that is why the super many years. It means that the fate of the patient depends on
modern high technologies are tested here: spiral CT scans the first visit to a doctor and if the last is not vigilant enough,
screening, automated computerized microscopy screening, the future of the person is tragic [1]. At the same time LCP
monoclonal antibody staining techniques, fluorodeoxyglu- have been reported to have immune dysfunctions of the cell-
cose-Positron Emission Tomography, bronchoscopic auto- mediated and humoral response [3,4]. However, little is
known about value of immune system data in terms of early
detection and differential diagnosis of LC. Therefore, we
*Address correspondence to this author at the Thoracic Surgery Department, examined immune system data in LCP and in patients with
Klaipeda University Hospital, Brozynu: 5-54, Klaipeda, LT95214, Lithua- NMP (PNMP).
nia; Tel: 37060878390; E-mail: kshivets003@yahoo.com
1876-8199/08 2008 Bentham Open
2. 2 The Open Lung Cancer Journal, 2008, Volume 1 Oleg Kshivets
PATIENTS AND METHODS mononuclears and neutrophils were isolated from a freshly
drawn heparinized tube of blood. Mononuclear cells and
Venous blood samples from 815 consecutive operated
neutrophils were isolated after discontinuous density gradi-
and monitored in 1987-2008 LCP and PNMP (control group)
ents separation on Ficoll-Hypaque (3 ml of 1 solution: 10
were obtained prior to any treatment. All patients in both
portions of 33.9% Hypaque and 24 portions of 9% Ficoll + 3
groups were Europeans. 533 LCP with pathologic stage I-IV ml of 2 solution: 10 portions of 50% Hypaque and 20 por-
LCP (males - 472, females - 61; age=57.4±0.4 years)
tions of 9% Ficoll), washed in Hank’s balanced salt solution
(mean±standard error) and 282 PNMP (males - 188, females
with 10% AB group serum, resuspended and cultured with
- 94; age=50.3±0.7 years) entered this trial. All patients from
ram erythrocytes by incubation at +37°C 15 minutes without
the control group were checked and operated in the clinic for
or with immunoglobulins IgG, IgM and IgA antiserum. The
suspicion of LC. Patients were not considered eligible if they
rosette methods were used to evaluate immune cell subpopu-
had previous treatment with chemotherapy, immunotherapy lations counts. The obtained results were converted to mod-
or radiotherapy, if there were two primary tumors of the time
ern defined clusters of human leukocytes [8]. Clotted blood
of diagnosis or if patients did not leave the clinic or died
was clarified and sera collected, aliquoted, and stored at -
after surgery. Staging procedures included medical history,
80°C. Thawed aliquoted samples were evaluated for IgG,
physical examination, complete blood count with differen-
IgM, IgA, natural antibodies, circulating immune complexes
tials, biochemistry and electrolyte panel, chest X-ray (PA
(CIC). Traditionally the percentage, absolute count and total
and laterals), abdominal ultrasound, fibrobronchoscopy, population number (per human organism) of T-lymphocytes
electrocardiogram, spirometry, bronchial or transthoracic
(CD3), B-lymphocytes (CD19), helper T-lymphocytes
biopsy. Computed tomography scan of chest, upper abdomen
(CD4), suppressor/cytotoxic T-lymphocytes (CD8), killer
and brain, liver and bone radionucle scan were performed
cells (O-cells, K-cells or CD16), precursor T-cells (CD1),
whenever needed. Midiastinoscopy was not used. All LCP
activated T-cells (CDw26), monocytes (CD64, CD13),
were diagnosed with histologically confirmed non-small cell
helper/inducer T-lymphocytes (CD4+2H), contrsuppressor
lung cancer. All had measurable tumor and ECOG perform- T-lymphocytes (CD8+VV), CD4/CD8, leukocytes, lympho-
ance status 0 or 1. Before any treatment each patient was
cytes, polymorphonuclear and stabnuclear leukocytes were
carefully examined by medical panel composed of thoracic
estimated. The laboratory blood studies also included input
surgeon, chemotherapeutist, radiation oncologist and pneu-
levels of NST (tests of oxygen dependent metabolism of
mologist to confirm the stage of disease. All patients signed
neutrophils spontaneous and stimulated by Staphylococcus
a written informed consent form approved by the local Insti-
aureus or by Streptococcus pyogenes), index of stimulation
tutional Review Board. of leukocytes by Staphylococcus aureus or Streptococcus
Among 533 LCP 181 underwent pneumonectomy, 138 - pyogenes, index of thymus function, phagocytic number,
upper lobectomy, 67 - lower lobectomy, 24 - upper/lower phagocyte index, index of complete phagocytosis, immune
bilolobectomy, 6 - middle lobectomy, 76 - segmentectomy, cell ratio factors (ratio between total immune cell subpopula-
41 - exploratory thoracotomy and biopsy. All LCP under- tion number in patient organism and general number of can-
went routine systematic mediastinal nodal dissection. cer cell population).
Among all LCP, 55 LCP underwent combined and extensive
Multi-factor clustering, structural equation modeling
radical procedures with the resection of pericardium, atrium,
(SEPATH) and Monte Carlo simulation were used to deter-
part of aorta, part of vena cava superior, vena azygos, carina,
mine any significant dependence [9,10,11,12]. System, bio-
diaphragm, chest wall, ribs, etc.
metric and statistical analyses were conducted using
Of the 282 PNMP, surgical procedures consisted of CLASS-MASTER (Stat Dialog, Inc., Moscow, Russia),
pneumonectomy in 5, upper lobectomy - in 96, lower lobec- SANI (Stat Dialog, Inc., Moscow, Russia) and STATIS-
tomy - in 81, middle lobectomy - in 2, segmentectomy or TICA (Stat Soft, Inc., Tulsa, OK, the USA). All tests were
wedge resection - in 98. considered significant when the resulting P value was less
than 0.05.
The histological diagnosis of LC was based on the crite-
ria of the World Health Organization [5,6]. Histological ex-
amination showed squamous cell LC in 294, adenocarci- RESULTS
noma - in 171, large cell LC - in 48 and small LC - in 20 The immunological characteristics of the cohort studied
patients. The pathological TNM stage I was in 48, II - in 47, are summarized in Tables 1-8. These Tables show descrip-
III - in 321, IV - in 117 patients; the pathological T stage was tive statistics of important pre-treatment variables such as
T1 in 116, T2 - in 168, T3 - in 125, T4 - in 124 cases; the factors of T-, B-, K-cell and monocyte/macrophage circuit
pathological N stage was N0 in 148, N1 - in 144, N2 - in (Tables 1-4). Reported also is date of humoral immunity and
159, N3 - in 82 patients; the M0 was in 438, M1 - in 95 neutrophil circuit (Tables 5-8). In terms of ED no statistical
cases. The tumor differentiation was graded as G1 in 88, G2 difference was found in T-cells, K-cells, CD1, CDw26,
- in 166, G3 - in 279 cases. CD4+2H, CD8+VV, CD4, CD8, CD4/CD8, lymphocytes,
Among 282 PNMP the histological analysis displayed index thymus function, phagocyte index, phagocyte number,
benign tumors in 100, chronical abscess - in 112, tubercu- index complete phagocytosis, titters of IgG, IgA, natural
loma - in 70 patients. antibodies, circulating immune complexes, NST spontaneous
and NST stimulated Staphylococcus aureus and Streptococ-
Baseline venous blood samples for immunology studies cus pyogenes, index stimulation by Staphylococcus aureus,
were taken on the first morning prior to any treatment. All leucocytes, stab neutrophils between groups. The input level
immunologic parameters measured using traditional well- of B-cells (P=0.024-0.001), monocytes (P=0.048-0.001),
regulated immunodiagnostic methods [7]. Venous blood
3. Early Detection and Diagnosis of Lung Cancer and Immune Circuit The Open Lung Cancer Journal, 2008, Volume 1 3
titters of IgM (P=0.021), index stimulation by Streptococcus In terms of DS the baseline number of T-cells, K-cells,
pyogenes (P=0.024) and the number of total segmented neu- CD1, CDw26, CD8+VV, CD4/CD8, index thymus function,
trophils (P=0.040) differed significantly in their capability to phagocyte index, phagocyte number, index complete phago-
recognize the small LC with stage I-II (T1-2N0M0; n=95; cytosis, titter of IgG, natural antibodies, circulating immune
tumor size=2.5±0.1 cm) (Tables 1, 3, 5 and 7). Accordingly, complexes, NST-tests, indexes of stimulation of leukocytes
we revealed the direct significant correlations between ED did not differ significantly between the two groups of pa-
and 9 lab tests. The obvious correlation with ED was signifi- tients (Tables 2, 4, 6 and 8).
cantly related to the count of B-cells (r=-0.12-0.17; P=0.024-
In group of LCP with stage I-IV (T1-4N0-3M0-1; n=533;
0.001), monocytes (r=-0.10-0.17; P=0.048-0.001), titter of
tumor size=5.4±0.1 cm) the percent of B-cells (P=0.009), the
IgM (r=0.12; P=0.021), index stimulation by Streptococcus
count of monocytes (P=0.045-0.000), leucocytes (P=0.000)
pyogenes (r=0.12; P=0.024) and the number of total seg- and neutrophils (P=0.010-0.000) were remarkably increased
mented neutrophils (r=-0.11; P=0.040) (Tables 9 and 10, Fig.
but the CD4+2H (P=0.034-0.027), CD4 (P=0.030), CD8
1).
count (P=0.015-0.012) and the percent of lymphocytes
Table 1. Factors of T-, B- and K-Cell Circuit Between LCP and NMP in Terms of Early Detection
LCP st I-II n=95 NMP n=282
NN Factors P
Mean SD Mean SD
1 T-cells (%) 53.62 12.82 52.84 11.97 0.590
9
2 T-cells (abs)*10 /l 0.94 0.49 0.93 0.46 0.942
3 T-cells (tot)*109 4.63 2.45 4.50 2.56 0.680
4 B-cells (%) 18.34 8.32 16.46 6.46 0.024*
5 B-cells (abs)*109/l 0.39 0.44 0.29 0.14 0.001*
6 B-cells (tot)*109 1.94 2.21 1.44 0.76 0.001*
7 K-cells (%) 26.86 11.49 29.25 10.84 0.068
8 K-cells (abs)*109/l 0.55 0.65 0.55 0.30 0.910
9 K-cells (tot)*109 2.65 3.15 2.71 1.66 0.805
10 CD1 (%) 9.17 9.90 8.11 8.96 0.333
9
11 CD1 (abs)*10 /l 0.17 0.23 0.15 0.20 0.372
12 CD1 (tot)*109 0.84 1.16 0.71 0.88 0.243
13 CDw26 (%) 6.32 8.70 6.20 6.50 0.893
9
14 CDw26 (abs)*10 /l 0.10 0.16 0.10 0.11 0.792
9
15 CDw26 (tot)*10 0.49 0.77 0.48 0.60 0.890
16 CD4+2H (%) 34.37 13.74 33.78 14.59 0.729
17 CD4+2H (abs)*109/l 0.61 0.42 0.59 0.38 0.713
9
18 CD4+2H (tot) *10 2.96 1.94 2.87 1.94 0.681
19 CD8+VV (%) 32.34 16.55 30.32 16.98 0.315
9
20 CD8+VV (abs)*10 /l 0.58 0.46 0.55 0.46 0.534
9
21 CD8+VV (tot) *10 2.89 2.30 2.63 2.13 0.324
22 CD4 (%) 44.00 16.28 44.01 15.95 0.997
23 CD4 (abs)*109/l 0.76 0.47 0.78 0.46 0.760
9
24 CD4 (tot) *10 3.76 2.33 3.78 2.38 0.944
25 CD8 (%) 14.80 8.87 13.46 7.79 0.163
9
26 CD8 (abs)*10 /l 0.25 0.20 0.25 0.20 0.968
27 CD8 (tot) *109 1.24 0.99 1.22 0.98 0.814
28 Lymphocytes (%) 30.98 11.23 33.07 11.43 0.121
9
29 Lymphocytes (abs)*10 /l 1.82 1.31 1.77 0.81 0.725
9
30 Lymphocytes (tot) *10 8.95 6.48 8.66 4.37 0.623
31 CD4/CD8 6.50 10.85 6.90 10.73 0.751
32 Index Thymus Function 1.08 0.59 0.99 0.40 0.090
4. 4 The Open Lung Cancer Journal, 2008, Volume 1 Oleg Kshivets
Table 2. Factors of T-, B- and K-Cell Circuit Between LCP and NMP in Terms of Diagnosis
LCP st I-IV n=533 NMP n=282
NN Factors P
Mean SD Mean SD
1 T-cells (%) 52.26 13.35 52.84 11.97 0.544
9
2 T-cells (abs)*10 /l 0.87 0.46 0.93 0.46 0.088
9
3 T-cells (tot)*10 4.18 2.35 4.50 2.56 0.071
4 B-cells (%) 17.89 7.74 16.46 6.46 0.009*
5 B-cells (abs)*109/l 0.32 0.25 0.29 0.14 0.064
9
6 B-cells (tot)*10 1.55 1.25 1.44 0.76 0.179
7 K-cells (%) 30.84 29.49 29.25 10.84 0.382
9
8 K-cells (abs)*10 /l 0.52 0.45 0.55 0.30 0.285
9
9 K-cells (tot)*10 2.49 2.28 2.71 1.66 0.157
10 CD1 (%) 8.74 9.72 8.11 8.96 0.368
9
11 CD1 (abs)*10 /l 0.15 0.20 0.15 0.20 0.954
9
12 CD1 (tot)*10 0.73 1.01 0.71 0.88 0.814
13 CDw26 (%) 6.05 6.94 6.20 6.50 0.762
9
14 CDw26 (abs)*10 /l 0.10 0.13 0.10 0.11 0.970
15 CDw26 (tot)*109 0.47 0.67 0.48 0.60 0.844
16 CD4+2H (%) 31.79 14.72 33.78 14.59 0.089
9
17 CD4+2H (abs)*10 /l 0.53 0.36 0.59 0.38 0.034*
9
18 CD4+2H (tot) *10 2.56 1.82 2.87 1.94 0.027*
19 CD8+VV (%) 30.60 17.44 30.32 16.98 0.827
20 CD8+VV (abs)*109/l 0.52 0.42 0.55 0.46 0.387
9
21 CD8+VV (tot) *10 2.51 2.09 2.63 2.13 0.429
22 CD4 (%) 42.31 16.32 44.01 15.95 0.156
9
23 CD4 (abs)*10 /l 0.71 0.44 0.78 0.46 0.055
24 CD4 (tot) *109 3.41 2.25 3.78 2.38 0.030*
25 CD8 (%) 12.93 7.93 13.46 7.79 0.356
9
26 CD8 (abs)*10 /l 0.22 0.17 0.25 0.20 0.015*
9
27 CD8 (tot) *10 1.05 0.81 1.22 0.98 0.012*
28 Lymphocytes (%) 28.04 11.12 33.07 11.43 0.000*
29 Lymphocytes (abs)*109/l 1.70 0.91 1.77 0.81 0.234
9
30 Lymphocytes (tot) *10 8.16 4.74 8.66 4.37 0.140
31 CD4/CD8 6.50 9.80 6.90 10.73 0.591
32 Index Thymus Function 1.01 0.48 0.99 0.40 0.090
(P=0.000) were decreased significantly in comparison with of IgM (r=0.09; P=0.012) and IgA (r=-0.13; P=0.000) (Ta-
PNMP (n=282) (Tables 2, 4, 6 and 8). The Table 6 also bles 9 and 10, Fig. 2).
shows that LCP with stage I-IV had strong evidence of de- The relationships between gender, age, weight, height
creasing of IgM (P=0.012) and increasing of IgA (P=0.000).
and ED/DS of the groups are summarized in Table 9.
In addition, we found direct significant correlations between
DS and 20 lab tests: the percent of B-cells (r=-0.09; All significant variables were also evaluated in a tradi-
P=0.008) and lymphocytes (r=0.21; P=0.000), the count of tional multivariate logistic regression analysis. All parame-
CD4+2H (r=0.07-0.08; P=0.034-0.27), CD4 (r=0.08; ters were analyzed in a logistic regression model in accor-
P=0.030), CD8 (r=0.08-0.09; P=0.015-0.012), monocytes dance with Tables 1-10. In terms of ED it was revealed that
(r=-0.07-0.14; P=0.045-0.000), leucocytes (r=-0.13-0.17; logistic regression model based on 9 lab tests (the percent,
P=0.000), neutrophils (r=-0.09-0.22; P=0.010-0.000), titters absolute and total count of B-cells, monocytes, titter of IgM,
5. Early Detection and Diagnosis of Lung Cancer and Immune Circuit The Open Lung Cancer Journal, 2008, Volume 1 5
Table 3. Factors of Monocyte and Macrophage Circuit Between LCP and NMP in Terms of Early Detection
LCP st I-II n=95 NMP n=282
NN Factors P
Mean SD Mean SD
1 Monocytes (%) 3.45 2.92 2.87 2.29 0.048*
9
2 Monocytes (abs)*10 /l 0.22 0.22 0.16 0.14 0.003*
3 Monocytes (tot) *109 1.08 1.10 0.76 0.70 0.001*
4 Phagocyte Index 21.84 14.64 23.05 15.89 0.512
5 Phagocyte Number 3.96 2.27 4.17 2.62 0.477
6 Index Complete Phagocytosis 1.09 0.59 1.01 0.50 0.187
Table 4. Factors of Monocyte and Macrophage Circuit Between LCP and NMP in Terms of Diagnosis
LCP st I-IV n=533 NMP n=282
NN Factors P
Mean SD Mean SD
1 Monocytes (%) 3.24 2.57 2.87 2.29 0.045*
2 Monocytes (abs)*109/l 0.21 0.21 0.16 0.14 0.000*
9
3 Monocytes (tot) *10 1.01 1.06 0.76 0.70 0.000*
4 Phagocyte Index 22.29 15.15 23.05 15.89 0.501
5 Phagocyte Number 4.14 2.46 4.17 2.62 0.860
6 Index Complete Phagocytosis 1.02 0.49 1.01 0.50 0.653
Table 5. Factors of Humoral Immunity Between LCP and NMP in Terms of Early Detection
LCP st I-II n=95 NMP n=282
NN Factors P
Mean SD Mean SD
1 IgG (g/l) 10.57 2.93 10.52 2.23 0.880
2 IgM (g/l) 1.56 0.51 1.72 0.62 0.021*
3 IgA (g/l) 2.38 0.94 2.26 0.85 0.206
4 Natural Antibodies 25.01 26.13 23.82 20.35 0.648
5 Circulating Immune Complexes 25.33 20.60 25.80 23.51 0.862
Table 6. Factors of Humoral Immunity Between LCP and NMP in Terms of Diagnosis
LCP st I-IV n=533 NMP n=282
NN Factors P
Mean SD Mean SD
1 IgG (g/l) 10.70 2.84 10.52 2.23 0.372
2 IgM (g/l) 1.61 0.58 1.72 0.62 0.012*
3 IgA (g/l) 2.52 1.02 2.26 0.85 0.000*
4 Natural Antibodies 27.31 26.54 23.82 20.35 0.055
5 Circulating Immune Complexes 24.47 19.36 25.80 23.51 0.388
6. 6 The Open Lung Cancer Journal, 2008, Volume 1 Oleg Kshivets
Table 7. Factors of Neutrophil Circuit Between LCP and NMP in Terms of Early Detection
LCP st I-II n=95 NMP n=282
NN Factors P
Mean SD Mean SD
NST spontaneous
1 7.64 6.60 7.93 6.93 0.727
NST stimulated Staphylococcus aureus
2 8.49 9.34 8.55 8.60 0.955
NST stimulated Streptococcus
3 10.49 9.65 10.58 9.05 0.939
Pyogenes
4 Index Stimulation by Staphylococcus aureus 1.02 0.72 1.45 2.09 0.052
5 Index Stimulation by Streptococcus pyogenes 1.37 0.94 1.89 2.13 0.024*
9
6 Leukocytes (abs)*10 /l 5.88 2.47 5.47 1.85 0.086
7 Leukocytes (tot)*109 29.17 13.09 26.73 10.19 0.061
8 Stab Neutrophils (%) 1.06 1.31 0.97 1.58 0.598
9
9 Stab Neutrophils (abs)*10 /l 0.07 0.13 0.06 0.12 0.404
9
10 Stab Neutrophils (tot)*10 0.35 0.65 0.28 0.57 0.300
11 Segmented Neutrophils (%) 61.53 11.58 59.47 11.75 0.139
9
12 Segmented Neutrophils (abs)*10 /l 3.61 1.58 3.29 1.41 0.064
9
13 Segmented Neutrophils (tot)*10 17.92 8.46 16.06 7.28 0.040*
Table 8. Factors of Neutrophil Circuit Between LCP and NMP in Terms of Diagnosis
LCP st I-IV n=533 NMP n=282
NN Factors P
Mean SD Mean SD
NST spontaneous
1 8.65 8.49 7.93 6.93 0.217
NST stimulated Staphylococcus aureus
2 9.36 9.98 8.55 8.60 0.248
NST stimulated Streptococcus
3 11.13 9.46 10.58 9.05 0.425
Pyogenes
4 Index Stimulation by Staphylococcus aureus 1.35 1.51 1.45 2.09 0.441
5 Index Stimulation by Streptococcus pyogenes 1.76 1.72 1.89 2.13 0.365
9
6 Leukocytes (abs)*10 /l 6.31 2.48 5.47 1.85 0.000*
9
7 Leukocytes (tot)*10 30.09 12.52 26.73 10.19 0.000*
8 Stab Neutrophils (%) 1.27 1.57 0.97 1.58 0.010*
9
9 Stab Neutrophils (abs)*10 /l 0.09 0.18 0.06 0.12 0.003*
9
10 Stab Neutrophils (tot)*10 0.44 0.78 0.28 0.57 0.003*
11 Segmented Neutrophils (%) 64.23 11.48 59.47 11.75 0.000*
12 Segmented Neutrophils (abs)*109/l 4.10 1.88 3.29 1.41 0.000*
9
13 Segmented Neutrophils (tot)*10 19.49 9.06 16.06 7.28 0.000*
index stimulation by Streptococcus pyogenes and the total and IgA) was significantly capable to diagnose LC with
count of segmented neutrophils) significantly recognized stage T1-4N0-3M0-1 from NMP ( 2=108.075; Df=20;
small LC with stage T1-2N0M0 from NMP ( 2=27.543; P=0.00000001; n=815) (Table 12).
Df=9; P=0.001; n=377) (Table 11). Accordingly, the logistic
All of these differences and discrepancies were further
regression model based on 20 lab tests (the percent of B-cells investigated by SEPATH analysis (structural equation mod-
and lymphocytes, the absolute and total count of CD4+2H,
eling) and multi-factor clustering. The values are shown in
CD8 and leukocytes, the total count of CD4, the percent,
Tables 13 and 14. It was revealed that ED of LC with stage
absolute and total count of monocytes, stab and segmented
I-II (tumor size=2.5±0.1 cm; T1-2N0M0; n=95) from NMP
neutrophils, (r=-0.09-0.22; P=0.010-0.000), the titters of IgM
(n=282) significantly (P=0.000000) depended on: 1) level of
7. Early Detection and Diagnosis of Lung Cancer and Immune Circuit The Open Lung Cancer Journal, 2008, Volume 1 7
Table 9. Correlations Between Early Detection (n=377) and Diagnosis of LC (n=815) and Factors (LCP---NMP)
ED n=377 DS n=815
NN Factors
r P r P
1 Gender 0.18 0.000* 0.27 0.000*
2 Age (years) -0.33 0.000* -0.34 0.000*
3 Weight (kg) -0.05 0.358 0.05 0.140
4 Height (cm) -0.13 0.010* -0.11 0.001*
5 T-cells (%) -0.03 0.590 0.02 0.544
9
6 T-cells (abs)*10 /l -0.00 0.942 0.06 0.080
9
7 T-cells (tot)*10 -0.02 0.660 0.06 0.071
8 B-cells (%) -0.12 0.024* -0.09 0.008*
9
9 B-cells (abs)*10 /l -0.16 0.001* -0.06 0.064
10 B-cells (tot)*109 -0.17 0.001* -0.05 0.179
11 K-cells (%) 0.09 0.068 -0.03 0.382
9
12 K-cells (abs)*10 /l 0.01 0.909 0.04 0.285
9
13 K-cells (tot)*10 0.01 0.803 0.05 0.157
14 CD1 (%) -0.05 0.333 -0.01 0.814
15 CD1 (abs)*109/l -0.05 0.372 -0.03 0.368
9
16 CD1 (tot)*10 -0.06 0.243 0.00 0.954
17 CDw26 (%) -0.01 0.893 0.01 0.762
9
18 CDw26 (abs)*10 /l -0.01 0.792 -0.00 0.970
19 CDw26 (tot)*109 -0.01 0.890 0.01 0.844
20 CD4+2H (%) -0.02 0.681 0.06 0.067
9
21 CD4+2H (abs)*10 /l -0.02 0.729 0.07 0.034*
22 CD4+2H (tot)*109 -0.02 0.713 0.08 0.027*
23 CD8+VV (%) -0.05 0.315 -0.01 0.826
9
24 CD8+VV (abs)*10 /l -0.03 0.534 0.03 0.367
25 CD8+VV (tot)*109 -0.05 0.324 0.03 0.429
26 CD4 (%) 0.00 0.944 0.05 0.156
9
27 CD4 (abs) *10 /l 0.00 0.997 0.07 0.055
9
28 CD4 (tot) *10 0.02 0.760 0.08 0.030*
29 CD8 (%) -0.07 0.163 0.03 0.356
30 CD8 (abs) *109/l -0.00 0.968 0.08 0.015*
31 CD8 (tot) *109 -0.01 0.814 0.09 0.012*
32 Lymphocytes (%) 0.08 0.121 0.21 0.000*
9
33 Lymphocytes (abs)*10 /l -0.02 0.725 0.04 0.234
9
34 Lymphocytes (tot) *10 -0.03 0.623 0.05 0.140
35 CD4/CD8 0.02 0.751 0.02 0.591
36 Index Thymus Function -0.09 0.090 -0.02 0.594
immune cell circuit ( 2=38749.1; Df=989); 2) value of Df=989); 2) macrophage circuit ( 2=312.1; Df=20); 3) hu-
monocyte and macrophage circuit ( 2=662.8; Df=20); 3) moral factors ( 2=243.1; Df=9); 4) neutrophils circuit
level of humoral immunity ( 2=585.9; Df=9); 4) neutrophils ( 2=10772.3; Df=77). Monte Carlo simulation confirmed
circuit ( 2=5214.4; Df=77). It was also founded that DS of significant (P=0.000000) overall networks between ED and
LC with stage I-IV (tumor size=5.4±0.1 cm; T1-4N0-3M0-1; DS of LC and the cell immunity circuit, the humoral immu-
n=533) from NMP significantly (P=0.000000) depended on: nity data, macrophage and neutrophil circuit (Fig. 3).
1) value of immune cell subpopulations ( 2=80569.9;
8. 8 The Open Lung Cancer Journal, 2008, Volume 1 Oleg Kshivets
Table 10. Correlations Between Early Detection (n=377) and Diagnosis of LC (n=815) and Factors (LCP---NMP)
ED n=377 DS n=815
NN Factors
r P r P
37 Monocytes (%) -0.10 0.048* -0.07 0.045*
9
38 Monocytes (abs)*10 /l -0.15 0.003* -0.14 0.000*
39 Monocytes (tot)*109 -0.17 0.001* -0.13 0.000*
40 Phagocyte Index 0.03 0.512 0.02 0.501
41 Phagocytic Number 0.04 0.477 0.01 0.860
42 Index Complete Phagocytosis -0.07 0.187 -0.02 0.653
43 IgG (g/l) -0.01 0.880 -0.03 0.372
44 IgM (g/l) 0.12 0.021* 0.09 0.012*
45 IgA (g/l) -0.07 0.206 -0.13 0.000*
46 Natural Antibodies -0.02 0.648 -0.07 0.055
47 Circulating Immune Complexes (CIC) 0.01 0.862 0.03 0.388
48 NST spontaneous 0.02 0.727 -0.04 0.217
49 NST stimulated Staphylococcus aureus 0.00 0.955 -0.04 0.248
50 NST stimulated Streptococcus pyogenes 0.00 0.939 -0.03 0.425
51 Index Stimulation Staphylococcus aureus 0.10 0.052 0.03 0.447
52 Index Stimulation Streptococcus pyogenes 0.12 0.024* 0.03 0.365
9
53 Leukocytes (abs)*10 /l -0.09 0.086 -0.17 0.000*
9
54 Leukocytes (tot)*10 -0.10 0.062 -0.13 0.000*
55 Stab Neutrophils (%) -0.03 0.598 -0.09 0.010*
56 Stab Neutrophils (abs)*109/l -0.04 0.404 -0.10 0.003*
9
57 Stab Neutrophils (tot)*10 -0.05 0.300 -0.10 0.003*
58 Segmented Neutrophils (%) -0.08 0.139 -0.19 0.000*
9
59 Segmented Neutrophils (abs)*10 /l -0.10 0.064 -0.22 0.000*
60 Segmented Neutrophils (tot)*109 -0.11 0.040* -0.19 0.000*
DISCUSSION 2. The clinical utility of some immune cell and humoral
markers are feasible in ED and DS of LC and may be
This study aimed to assess, in the large populations of
defined, in general, moderate.
LCP, the real diagnostic value of immune cell and humoral
markers in comparison with the large population of PNMP. 3. At ED and DS of LC the complex of recognized im-
The importance must be stressed of using complex system mune markers is better than any single factor.
analysis, statistical and biometrical methods in combination, 4. Immune cell subpopulations and humoral factors
because the different approaches yield complementary pieces communicate knotty with each other.
of diagnostic information [1].
To explain such results we entertained the hypothesis that
Its main findings can be summarized as follows: immune cell and humoral circuit regulate cancer dynamics
1. LCP even with the first and second stages had certain and participate in host defense mechanism against tumor.
changes of immunological parameters and their rela- Disbalance and deficiency of immune cells and humoral fac-
tionships, while these changes were detected even at tors as well as deregulation of their networks can lead to
early LC when the effectiveness of the treatment tumor appearance and tumor progression. It is clear that
process (5-year survival after complete resections) these relationships discrepancies in immune cell and hu-
tends to be 80-100%. The data of immunological ho- moral circuit are remarkable tests for recognition LC. As
meostasis of patients with an early LC significantly shown in our results, the number of immune markers tends
differed from non-malignant pathology, that is ho- to be more frequently abnormal when the disease is ad-
meostasis of a patient with the non-malignant pathol- vanced and this effect is enough for reaching a statistically
ogy principally distinguished from the homeostasis of significant conclusion. In agreement with our findings, re-
a patient with early LC. cent studies have demonstrated some defects and impaired
9. Early Detection and Diagnosis of Lung Cancer and Immune Circuit The Open Lung Cancer Journal, 2008, Volume 1 9
Fig. (1). Significant networks between factors of immune cell and humoral circuit and early detection of LC (LCP with stage T1-2N0M0,
n=95---PNMP, n=282).
Fig. (2). Significant networks between factors of immune cell and humoral circuit and diagnosis of LC (LCP with stage T1-4N0-3M0-1,
n=533---PNMP, n=282).
effector function of T-cell subpopulations, K-cells, lym- from patients with various malignancies including LCP
phokin-activated killer cells and monocytes/macrophages [1,13-18].
10. 10 The Open Lung Cancer Journal, 2008, Volume 1 Oleg Kshivets
Table 11. Results of Logistic Regression Modeling in Early Detection of LC (n=95) from NMP (n=282)
2
NN Significant Immune Factors: =27.543; Df=9; P=0.0011407; Estimate
Const.B0 1.34429
1 B-cells (%) -0.01543
2 B-cells (abs)*109/l -3.80134
9
3 B-cells (tot)*10 0.45341
4 Monocytes (%) 0.00167
9
5 Monocytes (abs)*10 /l 2.36224
6 Monocytes (tot) *109 -0.70182
7 IgM (g/l) 0.44811
8 Index Stimulation by Streptococcus pyogenes 0.18113
9
9 Segmented Neutrophils (tot)*10 -0.01816
Table 12. Results of Logistic Regression Modeling in Diagnosis of LC (n=533) from NMP (n=282)
2
NN Significant Immune Factors: =108.075; Df=20; P=0.0000000; Estimate
Const.B0 4.67194
1 B-cells (%) -0.02946
2 CD4+2H (abs)*109/l 3.17501
9
3 CD4+2H (tot) *10 -0.57679
9
4 CD4 (tot) *10 0.09542
9
5 CD8 (abs)*10 /l 3.60816
6 CD8 (tot) *109 -0.41372
7 Lymphocytes (%) -0.03025
8 Monocytes (%) 0.07468
9
9 Monocytes (abs)*10 /l -0.39635
10 Monocytes (tot) *109 -0.53516
11 IgM (g/l) 0.43660
12 IgA (g/l) -0.37333
9
13 Leukocytes (abs)*10 /l -1.40877
14 Leukocytes (tot)*109 0.22663
15 Stab Neutrophils (%) -0.08793
9
16 Stab Neutrophils (abs)*10 /l 3.97775
9
17 Stab Neutrophils (tot)*10 -0.64340
18 Segmented Neutrophils (%) -0.05288
9
19 Segmented Neutrophils (abs)*10 /l 1.09895
9
20 Segmented Neutrophils (tot)*10 -0.18262
The main conclusion that can be drown from the present immunity networks differed significantly in their capability
results is that there were 4 basic hidden clusters of immunity to recognize early LC as well as advanced LC from NMP.
networks between system “immune homeostasis—lung can-
The rational for the investigation was that immunodiag-
cer”: 1) the level of T-, B- and K-cell subpopulations circuit;
nosis is likely to be reliable for separation of LCP including
2) the value of monocyte/macrophage circuit; 3) the level of
stage I-II from NMP for surgery, and because these patients
humoral immunity; 4) the value of neutrophil circuit. These
would be expected to have the better outcome.
11. Early Detection and Diagnosis of Lung Cancer and Immune Circuit The Open Lung Cancer Journal, 2008, Volume 1 11
Table 13. Results of Structural Equation Modeling and Monte Carlo Simulation in Early Detection of LC Stage I-II (n=95) from
NMP (n=282)
2
NN Networks Df P
1 T-, B-, K-cells Circuit/Early Detection 38749.1 989 0.000000*
2 Monocyte-Macrophage Circuit/Early Detection 662.8 20 0.000000*
3 Humoral Immunity/Early Detection 585.9 9 0.000000*
4 Neutrophils Circuit/Early Detection 5214.4 77 0.000000*
5 T-, B-, K-cells Circuit/Monocyte-Macrophage Circuit 39424.6 1125 0.000000*
6 T-, B-, K-cells Circuit/Humoral Immunity 39080.3 1224 0.000000*
7 T-, B-, K-cells Circuit/Neutrophils Circuit 38381.3 1216 0.000000*
8 Monocyte-Macrophage Circuit/Humoral Immunity 160.9 54 0.000000*
9 Monocyte-Macrophage Circuit/Neutrophils Circuit 5831.0 170 0.000000*
10 Humoral Immunity/ Neutrophils Circuit 5161.8 134 0.000000*
Table 14. Results of Structural Equation Modeling and Monte Carlo Simulation in Diagnosis of LC Stage I-IV (n=533) from NMP
(n=282)
2
NN Networks Df P
1 T-, B-, K-cells Circuit/Diagnosis 80569.9 989 0.000000*
2 Monocyte-Macrophage Circuit/Diagnosis 312.1 20 0.000000*
3 Humoral Immunity/Diagnosis 243.1 9 0.000000*
4 Neutrophils Circuit/Diagnosis 10772.3 77 0.000000*
5 T-, B-, K-cells Circuit/Monocyte-Macrophage Circuit 82709.1 1125 0.000000*
6 T-, B-, K-cells Circuit/Humoral Immunity 81232.2 1224 0.000000*
7 T-, B-, K-cells Circuit/Neutrophils Circuit 78126.0 1216 0.000000*
8 Monocyte-Macrophage Circuit/Humoral Immunity 227.5 54 0.000000*
9 Monocyte-Macrophage Circuit/Neutrophils Circuit 2506.1 170 0.000000*
10 Humoral Immunity/ Neutrophils Circuit 10876.6 134 0.000000*
Fig. (3). Significant networks between immune cell and humoral circuit and early detection and diagnosis of LC.