1) The study investigated the significance of blood cell levels in early detection of lung cancer by analyzing data from 115 lung cancer patients and 120 healthy individuals.
2) Neural network analysis revealed that early lung cancer detection depended most on lymphocyte levels, followed by neutrophil levels, monocytes, and other blood cells.
3) The neural networks achieved 100% accurate detection of early lung cancer based on blood cell levels, demonstrating their potential for precise early detection.
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
Artificial Intelligence, System Analysis and Simulation Modeling in Precise Prediction of 5-Year Survival of Esophageal Cancer Patients after Complete Esophagogastrectomies
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
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
Artificial Intelligence, System Analysis and Simulation Modeling in Precise Prediction of 5-Year Survival of Esophageal Cancer Patients after Complete Esophagogastrectomies
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
Survival of Esophageal Cancer Patients was Significantly Superior in Comparison with Cardioesophageal Cancer Patients after Surgery
Kshivets Oleg Surgery Department, Roshal Hospital, Moscow, Russia
OBJECTIVE: This study aimed to determine localization influence of tumor for 5-year survival (5YS) of esophageal (EC) or cardioesophageal (CC) cancer patients (ECP, CEP) after complete en block (R0) esophagogastrectomies (EG) through left/right thoracoabdominal incision.
METHODS: We analyzed data of 543 consecutive patients (age=56.4±8.8 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2019 (m=405, f=138; ECP=259, CEP=284; esophagogastrectomies (EG) Garlock=280, EG Lewis=263, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=151; adenocarcinoma=308, squamous=225, mix=10; T1=126, T2=114, T3=178, T4=125; N0=275, N1=69, N2=199; G1=157, G2=139, G3=247; early EC=107, invasive=436; only surgery=420, adjuvant chemoimmunoradiotherapy-AT=123: 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 1892.4±2241 days and cumulative 5-year survival (5YS) reached 51.9%, 10 years – 45.7%, 20 years – 33.5%. 183 ECP lived more than 5 years (LS=4311±2419.7 days), 98 ECP – more than 10 years (LS=5903.4±2299.4 days). 224 died because of EC/CC (LS=629.2±320.1 days). 5YS of ECP (67.3%, LS=2605±2628.9 days) was significantly superior in comparison with CEP (36.4%, LS=1242.6±1558.5 days) (P=0.00000 by log-rank test). AT significantly improved 5YS (68.2% vs. 48.5%) (P=0.00033 by log-rank test). Cox modeling displayed that 5YS of ECP/CEP 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, blood cells, prothrombin index, coagulation time, residual nitrogen, blood group, Rh, glucose, protein (P=0.000-0.008). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and healthy cells/CC (rank=1), PT early-invasive EC (rank=2), PT N0—N12 (rank=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: 10-Year survival 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) anthropometric data; 10) surgery type; 11) tumor localization. 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.
NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES
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
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.
Kshivets O. Esophageal & Cardioesophageal Cancer SurgeryOleg Kshivets
ADJUVANT CHEMOIMMUNORADIO/CHEMOIMMUNOTHERAPY SIGNIFICANTLY IMPROVED 5-YEAR SURVIVAL OF ESOPHAGEAL/CARDIOESOPHAGEAL CANCER PATIENTS AFTER RADICAL SURGERY
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
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.
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
Survival of Esophageal Cancer Patients was Significantly Superior in Comparison with Cardioesophageal Cancer Patients after Surgery
Kshivets Oleg Surgery Department, Roshal Hospital, Moscow, Russia
OBJECTIVE: This study aimed to determine localization influence of tumor for 5-year survival (5YS) of esophageal (EC) or cardioesophageal (CC) cancer patients (ECP, CEP) after complete en block (R0) esophagogastrectomies (EG) through left/right thoracoabdominal incision.
METHODS: We analyzed data of 543 consecutive patients (age=56.4±8.8 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2019 (m=405, f=138; ECP=259, CEP=284; esophagogastrectomies (EG) Garlock=280, EG Lewis=263, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=151; adenocarcinoma=308, squamous=225, mix=10; T1=126, T2=114, T3=178, T4=125; N0=275, N1=69, N2=199; G1=157, G2=139, G3=247; early EC=107, invasive=436; only surgery=420, adjuvant chemoimmunoradiotherapy-AT=123: 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 1892.4±2241 days and cumulative 5-year survival (5YS) reached 51.9%, 10 years – 45.7%, 20 years – 33.5%. 183 ECP lived more than 5 years (LS=4311±2419.7 days), 98 ECP – more than 10 years (LS=5903.4±2299.4 days). 224 died because of EC/CC (LS=629.2±320.1 days). 5YS of ECP (67.3%, LS=2605±2628.9 days) was significantly superior in comparison with CEP (36.4%, LS=1242.6±1558.5 days) (P=0.00000 by log-rank test). AT significantly improved 5YS (68.2% vs. 48.5%) (P=0.00033 by log-rank test). Cox modeling displayed that 5YS of ECP/CEP 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, blood cells, prothrombin index, coagulation time, residual nitrogen, blood group, Rh, glucose, protein (P=0.000-0.008). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and healthy cells/CC (rank=1), PT early-invasive EC (rank=2), PT N0—N12 (rank=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: 10-Year survival 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) anthropometric data; 10) surgery type; 11) tumor localization. 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.
NEURAL NETWORKS AND BOOTSTRAP SIMULATION IN PREDICTION OF OUTCOME OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER COMPLETE LOBECTOMIES AND PNEUMONECTOMIES
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
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.
Kshivets O. Esophageal & Cardioesophageal Cancer SurgeryOleg Kshivets
ADJUVANT CHEMOIMMUNORADIO/CHEMOIMMUNOTHERAPY SIGNIFICANTLY IMPROVED 5-YEAR SURVIVAL OF ESOPHAGEAL/CARDIOESOPHAGEAL CANCER PATIENTS AFTER RADICAL SURGERY
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
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.
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
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 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.
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.
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.
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
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.
Nomogram based estimate of axillary nodal involvement in acosog z0011Matthew Katz
Nomograms can outperform experts in predicting additional axillary nodal metastases in clinical N0 breast cancer patients with a positive sentinel node biopsy.
In ACOSOG Z0011, prior analysis showed radiation (RT) fields showed that half of all patients with confirmed RT fields used high tangents and 19% include regional nodal irradiation. We sought to evaluate two hypotheses in this secondary analysis:
1. Nomograms are valid in Z0011 and confirm similar distribution of nodal risk in two treatment arms;
2. Radiation fields including lymph nodes were not in the highest risk patients despite best clinical judgment.
I presented this research October 24, 2018 at the American Society for Radiation Oncology (ASTRO) Annual Meeting in San Antonio, Texas.
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.
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 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.
• 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.
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.
Conclusions: 10-Year survival 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) anthropometric data; 10) surgery type. 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.
10-Year survival 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.
CONCLUSIONS: 10-Year survival 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.
The Importance of Community Nursing Care.pdfAD Healthcare
NDIS and Community 24/7 Nursing Care is a specific type of support that may be provided under the NDIS for individuals with complex medical needs who require ongoing nursing care in a community setting, such as their home or a supported accommodation facility.
CHAPTER 1 SEMESTER V PREVENTIVE-PEDIATRICS.pdfSachin Sharma
This content provides an overview of preventive pediatrics. It defines preventive pediatrics as preventing disease and promoting children's physical, mental, and social well-being to achieve positive health. It discusses antenatal, postnatal, and social preventive pediatrics. It also covers various child health programs like immunization, breastfeeding, ICDS, and the roles of organizations like WHO, UNICEF, and nurses in preventive pediatrics.
Deep Leg Vein Thrombosis (DVT): Meaning, Causes, Symptoms, Treatment, and Mor...The Lifesciences Magazine
Deep Leg Vein Thrombosis occurs when a blood clot forms in one or more of the deep veins in the legs. These clots can impede blood flow, leading to severe complications.
India Clinical Trials Market: Industry Size and Growth Trends [2030] Analyzed...Kumar Satyam
According to TechSci Research report, "India Clinical Trials Market- By Region, Competition, Forecast & Opportunities, 2030F," the India Clinical Trials Market was valued at USD 2.05 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of 8.64% through 2030. The market is driven by a variety of factors, making India an attractive destination for pharmaceutical companies and researchers. India's vast and diverse patient population, cost-effective operational environment, and a large pool of skilled medical professionals contribute significantly to the market's growth. Additionally, increasing government support in streamlining regulations and the growing prevalence of lifestyle diseases further propel the clinical trials market.
Growing Prevalence of Lifestyle Diseases
The rising incidence of lifestyle diseases such as diabetes, cardiovascular diseases, and cancer is a major trend driving the clinical trials market in India. These conditions necessitate the development and testing of new treatment methods, creating a robust demand for clinical trials. The increasing burden of these diseases highlights the need for innovative therapies and underscores the importance of India as a key player in global clinical research.
CRISPR-Cas9, a revolutionary gene-editing tool, holds immense potential to reshape medicine, agriculture, and our understanding of life. But like any powerful tool, it comes with ethical considerations.
Unveiling CRISPR: This naturally occurring bacterial defense system (crRNA & Cas9 protein) fights viruses. Scientists repurposed it for precise gene editing (correction, deletion, insertion) by targeting specific DNA sequences.
The Promise: CRISPR offers exciting possibilities:
Gene Therapy: Correcting genetic diseases like cystic fibrosis.
Agriculture: Engineering crops resistant to pests and harsh environments.
Research: Studying gene function to unlock new knowledge.
The Peril: Ethical concerns demand attention:
Off-target Effects: Unintended DNA edits can have unforeseen consequences.
Eugenics: Misusing CRISPR for designer babies raises social and ethical questions.
Equity: High costs could limit access to this potentially life-saving technology.
The Path Forward: Responsible development is crucial:
International Collaboration: Clear guidelines are needed for research and human trials.
Public Education: Open discussions ensure informed decisions about CRISPR.
Prioritize Safety and Ethics: Safety and ethical principles must be paramount.
CRISPR offers a powerful tool for a better future, but responsible development and addressing ethical concerns are essential. By prioritizing safety, fostering open dialogue, and ensuring equitable access, we can harness CRISPR's power for the benefit of all. (2998 characters)
The dimensions of healthcare quality refer to various attributes or aspects that define the standard of healthcare services. These dimensions are used to evaluate, measure, and improve the quality of care provided to patients. A comprehensive understanding of these dimensions ensures that healthcare systems can address various aspects of patient care effectively and holistically. Dimensions of Healthcare Quality and Performance of care include the following; Appropriateness, Availability, Competence, Continuity, Effectiveness, Efficiency, Efficacy, Prevention, Respect and Care, Safety as well as Timeliness.
Antibiotic Stewardship by Anushri Srivastava.pptxAnushriSrivastav
Stewardship is the act of taking good care of something.
Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antimicrobials (including antibiotics), improves patient outcomes, reduces microbial resistance, and decreases the spread of infections caused by multidrug-resistant organisms.
WHO launched the Global Antimicrobial Resistance and Use Surveillance System (GLASS) in 2015 to fill knowledge gaps and inform strategies at all levels.
ACCORDING TO apic.org,
Antimicrobial stewardship is a coordinated program that promotes the appropriate use of antimicrobials (including antibiotics), improves patient outcomes, reduces microbial resistance, and decreases the spread of infections caused by multidrug-resistant organisms.
ACCORDING TO pewtrusts.org,
Antibiotic stewardship refers to efforts in doctors’ offices, hospitals, long term care facilities, and other health care settings to ensure that antibiotics are used only when necessary and appropriate
According to WHO,
Antimicrobial stewardship is a systematic approach to educate and support health care professionals to follow evidence-based guidelines for prescribing and administering antimicrobials
In 1996, John McGowan and Dale Gerding first applied the term antimicrobial stewardship, where they suggested a causal association between antimicrobial agent use and resistance. They also focused on the urgency of large-scale controlled trials of antimicrobial-use regulation employing sophisticated epidemiologic methods, molecular typing, and precise resistance mechanism analysis.
Antimicrobial Stewardship(AMS) refers to the optimal selection, dosing, and duration of antimicrobial treatment resulting in the best clinical outcome with minimal side effects to the patients and minimal impact on subsequent resistance.
According to the 2019 report, in the US, more than 2.8 million antibiotic-resistant infections occur each year, and more than 35000 people die. In addition to this, it also mentioned that 223,900 cases of Clostridoides difficile occurred in 2017, of which 12800 people died. The report did not include viruses or parasites
VISION
Being proactive
Supporting optimal animal and human health
Exploring ways to reduce overall use of antimicrobials
Using the drugs that prevent and treat disease by killing microscopic organisms in a responsible way
GOAL
to prevent the generation and spread of antimicrobial resistance (AMR). Doing so will preserve the effectiveness of these drugs in animals and humans for years to come.
being to preserve human and animal health and the effectiveness of antimicrobial medications.
to implement a multidisciplinary approach in assembling a stewardship team to include an infectious disease physician, a clinical pharmacist with infectious diseases training, infection preventionist, and a close collaboration with the staff in the clinical microbiology laboratory
to prevent antimicrobial overuse, misuse and abuse.
to minimize the developme
Medical Technology Tackles New Health Care Demand - Research Report - March 2...pchutichetpong
M Capital Group (“MCG”) predicts that with, against, despite, and even without the global pandemic, the medical technology (MedTech) industry shows signs of continuous healthy growth, driven by smaller, faster, and cheaper devices, growing demand for home-based applications, technological innovation, strategic acquisitions, investments, and SPAC listings. MCG predicts that this should reflects itself in annual growth of over 6%, well beyond 2028.
According to Chris Mouchabhani, Managing Partner at M Capital Group, “Despite all economic scenarios that one may consider, beyond overall economic shocks, medical technology should remain one of the most promising and robust sectors over the short to medium term and well beyond 2028.”
There is a movement towards home-based care for the elderly, next generation scanning and MRI devices, wearable technology, artificial intelligence incorporation, and online connectivity. Experts also see a focus on predictive, preventive, personalized, participatory, and precision medicine, with rising levels of integration of home care and technological innovation.
The average cost of treatment has been rising across the board, creating additional financial burdens to governments, healthcare providers and insurance companies. According to MCG, cost-per-inpatient-stay in the United States alone rose on average annually by over 13% between 2014 to 2021, leading MedTech to focus research efforts on optimized medical equipment at lower price points, whilst emphasizing portability and ease of use. Namely, 46% of the 1,008 medical technology companies in the 2021 MedTech Innovator (“MTI”) database are focusing on prevention, wellness, detection, or diagnosis, signaling a clear push for preventive care to also tackle costs.
In addition, there has also been a lasting impact on consumer and medical demand for home care, supported by the pandemic. Lockdowns, closure of care facilities, and healthcare systems subjected to capacity pressure, accelerated demand away from traditional inpatient care. Now, outpatient care solutions are driving industry production, with nearly 70% of recent diagnostics start-up companies producing products in areas such as ambulatory clinics, at-home care, and self-administered diagnostics.