scholarly journals Esophageal Cancer: 10-Year Survival After Surgery

2021 ◽  
Author(s):  
Oleg Kshivets
Keyword(s):  
Neural Networks ◽  
Esophageal Cancer ◽  
Blood Cells ◽  
Treatment Strategies ◽  
Rank Test ◽  
Correct Prediction ◽  
Algorithm Selection ◽  
Cell Ratio ◽  
Prothrombin Index ◽  
Area Under Roc Curve

Abstract OBJECTIVE: 10-Year survival (10YS) after radical surgery for esophageal cancer (EC) patients (ECP) (T1-4N0-2M0) was analyzed. METHODS: We analyzed data of 551 consecutive ECP (age=56.5±8.9 years; tumor size=6±3.5 cm) radically operated (R0) and monitored in 1975-2021 (m=411, f=140; esophagogastrectomies (EG) Garlock=284, EG Lewis=267, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=154; adenocarcinoma=314, squamous=227, mix=10; T1=128, T2=115, T3=181, T4=127; N0=278, N1=70, N2=203; G1=157, G2=141, G3=253; early EC=109, invasive=442; only surgery=423, adjuvant chemoimmunoradiotherapy-AT=128: 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 1881.1±2230.6 days and cumulative 5-year survival (5YS) reached 52.1%, 10 years – 45.9%, 20 years – 33.7%. 184 ECP lived more than 5 years (LS=4308.7±2413.3 days), 99 ECP – more than 10 years (LS=5883±2296.6 days). 226 ECP died because of EC (LS=628.3±319.9 days). AT significantly improved 5YS (68.8% vs. 48.5%) (P=0.00025 by log-rank test). Cox modeling displayed that 10YS 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, blood cells, prothrombin index, hemorrhage time, residual nitrogen, protein (P=0.000-0.021). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 10YS and PT N0—N12 (rank=1), healthy cells/CC (2), PT early-invasive EC (3), thrombocytes/CC (4), erythrocytes/CC (5), lymphocytes/CC (6), eosinophils/CC (7), stick neutrophils/CC (8), segmented 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: 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.

Lung cancer prediction: Phase transitions and cell ratio factors

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. e22170-e22170
Author(s):  
O. Kshivets
Keyword(s):  
Lung Cancer ◽  
Neural Networks ◽  
Structural Equation ◽  
Cox Regression ◽  
Equation Modeling ◽  
Rank Test ◽  
Correct Prediction ◽  
Tumor Diameter ◽  
Cell Ratio ◽  
Bootstrap Simulation

e22170 Background: Search of precise prognostic factors for non-small lung cancer (LC) patients (LCP) was realized. Methods: In trial (1985–2008) the data of consecutive 490 LCP after complete resections R0 (age=56.7±8 years; m=439, f=51; tumor diameter: D=4.5±2.1 cm; pneumonectomies=206, lobectomies=284, combined procedures with resection of pericardium, atrium, aorta, VCS, carina, diaphragm, ribs=130; squamous=308, adenocarcinoma=147, large cell=35; T1=143, T2=217, T3=107, T4=23; N0=282, N1=115, N2=93; G1=114, G2=140, G3=236; early LC: LC till 2 cm in D with N0=58, invasive LC=432) was reviewed. Variables selected for 5-year survival (5YS) study were input levels of blood cell subpopulations, TNMG, D. Neural networks computing, Cox regression, clustering, structural equation modeling, Monte Carlo and bootstrap simulation were used to determine any significant regularity. Results: For total of 490 LCP overall life span (LS) was 1824±1304 days (median=1879) and real 5YS reached 62%, 10 years - 50.3%, 20 years - 45.3%. 304 LCP (LS=2597.3±1037 days) lived more than 5 years without LC progressing. 186 LCP (LS=559.8±383.1 days) died because of LC during first 5 years after surgery. 5YS of early LCP was significantly superior (100%) compared with invasive LCP (56.9%) (P=0.000 by log-rank test). 5YS of LCP with N0 was significantly better (78.4%) compared with LCP with N1–2 (39.9%) (P=0.000). Cox modeling displayed that 5YS significantly depended on: phase transition (PT) in terms of synergetics “early-invasive LC”, PT N0-N12, histology, G1–3, cell ratio factors: ratio between the total populations of leucocytes, lymphocytes, neutrophils and LC cells (P=0.000–0.044). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT “early-invasive LC”, (rank=1), PT N0-N12 (2), histology (3), G1–3 (4), T1–4 (5), ratio of lymphocytes/LC cells (6), healthy cells/LC cells (7), erythrocytes/LC cells (8), thrombocytes/LC cells (9), eosinophils/LC cells (10), neutrophils/LC cells (11). Correct prediction of 5YS was 100% by neural networks computing (error=0.000; urea under ROC curve=1.0). Conclusions: 5YS of LCP after radical procedures depended on: 1) PT “early-invasive LC”; 2) PT N0-N12; 3) cell ratio factors; 4) LC characteristics. No significant financial relationships to disclose.

scholarly journals Gastric Cancer: 10-Year Survival after Surgery

2021 ◽  
Vol 12 (3) ◽  
pp. 020-032
Author(s):  
Kshivets Oleg
Keyword(s):  
Neural Networks ◽  
Lymph Node ◽  
Blood Cell ◽  
Lymph Node Dissection ◽  
Tumor Size ◽  
Rank Test ◽  
Node Dissection ◽  
Cell Ratio ◽  
Log Rank Test ◽  
Cell Circuit

Methods: We analyzed data of 796 consecutive GCP (age=57.1±9.4 years; tumor size=5.4±3.1 cm) radically operated (R0) and monitored in 1975-2021 (m=556, f=240; distal gastrectomies-G=461, proximal G=165, total G=170, D2 lymph node dissection=551; combined G with resection of 1-7 adjacent organs (pancreas, liver, diaphragm, esophagus, colon transversum, splenectomy, small intestine, kidney, adrenal gland, etc.)=245; D3-4 lymph node dissection=245; only surgery-S=623, adjuvant chemoimmunotherapy-AT=173: 5FU+thymalin/taktivin; T1=237, T2=220, T3=182, T4=157; N0=435, N1=109, N2=252, M0=796; G1=222, G2=164, G3=410; early GC=164, invasive GC=632; Variables selected for 10YS 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 2130.8±2304.3 days and cumulative 5-year survival (5YS) reached 58.4%, 10 years – 52.4%, 20 years – 40.4%. 316 GCP lived more than 5 years (LS=4316.1±2292.9 days), 169 GCP – more than 10 years (LS=5919.5±2020 days). 294 GCP died because of GC (LS=640.6±347.1 days). AT significantly improved 10YS (62.3% vs. 50.5%) (P=0.0228 by log-rank test) for GCP. Cox modeling displayed that 10YS of LCP significantly depended on: phase transition (PT) early-invasive GC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, AT, blood cell circuit, prothrombin index, hemorrhage time, residual nitrogen, age, sex, procedure type (P=0.000-0.039). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 10YS and healthy cells/CC (rank=1), PT early-invasive GC (rank=2), PT N0—N12(rank=3), erythrocytes/CC (4), thrombocytes/CC (5), monocytes/CC (6), segmented neutrophils/CC (7), eosinophils/CC (8), leucocytes/CC (9), lymphocytes/CC (10), stick neutrophils/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 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.

Precise early detection of gastric cancer and blood cell circuit.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16512-e16512
Author(s):  
Oleg Kshivets
Keyword(s):  
Gastric Cancer ◽  
Neural Networks ◽  
Early Detection ◽  
Blood Cell ◽  
Structural Equation ◽  
Equation Modeling ◽  
Algorithm Selection ◽  
Bootstrap Simulation ◽  
Area Under Roc Curve ◽  
Cell Circuit

e16512 Background: Significance of blood cell circuit in terms of early detection of gastric cancer (GC) was investigated. Methods: In trial (1975-2020) consecutive cases after surgery, monitored 136 GC patients (GCP) (m = 90, f = 46; distal gastrectomies = 95, proximal gastrectomies = 34, total gastrectomies = 7) with pathologic stage IA (tumor size = 1.81±0.70 cm; adenocarcinoma = 136; T1N0M0 = 136; G1 = 67, G2 = 26, G3 = 43, 5-year survival = 100%) and 120 healthy donors (HD) (m = 69, f = 51) were reviewed. Variables selected for study were input levels of blood cell circuit, sex, age, TNMG. Differences between groups were evaluated using discriminant analysis, clustering, nonlinear estimation, structural equation modeling, Monte Carlo, bootstrap simulation and neural networks computing. Results: It was revealed that early detection of GC from HD (n = 256) significantly depended on: leucocytes (abs, total), segmented neutrophils (%, abs, total), lymphocytes (%), monocytes (%, abs, total), stick neutrophils (%, abs, total), eosinophils (%, abs, total) (P = 0.007-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of early detection of GC and lymphocytes (rank = 1), segmented neutrophils (rank = 2), monocytes (3), stick neutrophils (4), leucocytes (5), eosinophils (6). Correct detection of early GCP was 100% by neural networks computing (error = 0.000; area under ROC curve = 1.0). Conclusions: Early detection of GC from HD significantly depended on blood cell circuit.

scholarly journals Non-small cell lung cancer: 10-year survival after surgery

2021 ◽  
Vol 12 (2) ◽  
pp. 246-260
Author(s):  
Oleg Kshivets
Keyword(s):  
Lung Cancer ◽  
Neural Networks ◽  
Lymph Node ◽  
Small Cell ◽  
Rank Test ◽  
Node Dissection ◽  
Small Cell Lung ◽  
Cell Ratio ◽  
Log Rank Test ◽  
Cell Circuit

Objective: 10-Year survival (10YS) after radical surgery for non-small cell lung cancer (LC) pa­tients (LCP) (T1-4N0-2M0) was analyzed. Methods: We analyzed data of 768 consecutive LCP (age=57.6±8.3 years; tumor size=4.1±2.4 cm) radically operated (R0) and monitored in 1985-2021 (m=660, f=108; upper lobectomies=277, lower lobectomies=177, middle lobectomies=18, bilobectomies=42, pneumonectomies=254, mediastinal lymph node dissection=768; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=193; only surgery-S=618, adjuvant chemoimmunoradiotherapy-AT=150: CAV/gemzar + cisplatin + thymalin/taktivin + radiotherapy 45-50Gy; T1=320, T2=255, T3=133, T4=60; N0=516, N1=131, N2=121, M0=768; G1=194, G2=243, G3=331; squamous=417, adenocarcinoma=301, large cell=50; early LC=214, invasive LC=554; right LC=412, left LC=356; central=290; peripheral=478. Variables selected for 10YS 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 LCP were evaluated using a log-rank test. Multivariate Cox modeling, analysis, clustering, SEPATH, Monte Carlo, bootstrap and neural networks computing were used to determine any significant dependence. Results: Overall life span (LS) was 2244.9±1750.3 days and cumulative 5-year survival (5YS) reached 72.9%, 10 years – 64.3%, 20 years – 43.1%. 502 LCP lived more than 5 years (LS=3128.7±1536.8 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). AT significantly improved 10YS (52.4% vs. 27.7%) (P=0.00002 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 10YS 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, weight, color index (P=0.000-0.039). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 10YS and PT early-invasive LC (rank=1), thrombocytes/CC (rank=2), PT N0—N12(rank=3), segmented neutrophils/CC (4), healthy cells/CC (5), lymphocytes/CC (6), erythrocytes/CC (7), stick 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. 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.

scholarly journals Deep Malaria Parasite Detection in Thin Blood Smear Microscopic Images

2021 ◽  
Vol 11 (5) ◽  
pp. 2284
Author(s):  
Asma Maqsood ◽  
Muhammad Shahid Farid ◽  
Muhammad Hassan Khan ◽  
Marcin Grzegorzek
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Red Blood Cells ◽  
Convolutional Neural Networks ◽  
Blood Cells ◽  
Superior Performance ◽  
Learning Models ◽  
Infected Female ◽  
The World ◽  
Augmentation Techniques

Malaria is a disease activated by a type of microscopic parasite transmitted from infected female mosquito bites to humans. Malaria is a fatal disease that is endemic in many regions of the world. Quick diagnosis of this disease will be very valuable for patients, as traditional methods require tedious work for its detection. Recently, some automated methods have been proposed that exploit hand-crafted feature extraction techniques however, their accuracies are not reliable. Deep learning approaches modernize the world with their superior performance. Convolutional Neural Networks (CNN) are vastly scalable for image classification tasks that extract features through hidden layers of the model without any handcrafting. The detection of malaria-infected red blood cells from segmented microscopic blood images using convolutional neural networks can assist in quick diagnosis, and this will be useful for regions with fewer healthcare experts. The contributions of this paper are two-fold. First, we evaluate the performance of different existing deep learning models for efficient malaria detection. Second, we propose a customized CNN model that outperforms all observed deep learning models. It exploits the bilateral filtering and image augmentation techniques for highlighting features of red blood cells before training the model. Due to image augmentation techniques, the customized CNN model is generalized and avoids over-fitting. All experimental evaluations are performed on the benchmark NIH Malaria Dataset, and the results reveal that the proposed algorithm is 96.82% accurate in detecting malaria from the microscopic blood smears.

EFEKTIVITAS PEMBERIAN INFUSED WATER KURMA TERHADAP PENINGKATAN KADAR HEMOGLOBIN REMAJA PUTRI KEBIDANAN POLTEKKES MEDAN TAHUN 2020

2021 ◽  
Vol 2 (1) ◽  
pp. 64-69
Author(s):  
HIJRA HIDAYANA ◽  
Suswati Suswati
Keyword(s):  
Red Blood Cells ◽  
Adolescent Girls ◽  
Blood Cells ◽  
The Body ◽  
Rank Test ◽  
Plain Water ◽  
P Value ◽  
Signed Rank ◽  
Wilcoxon Signed Rank Test ◽  
Signed Rank Test

Hemoglobin is the red pigment-protein contained in red blood cells. The function of hemoglobin is to transport oxygen from the lungs and in the bloodstream to be carried to the tissues. Hemoglobin can increase by increasing the intake of iron in the body. One way to increase hemoglobin can be done by giving method Infused Water Dates. Infused water is a drink consisting of plain water with fresh fruit added and soaking or settling together for a certain time. The making of infused water is carried out by soaking for a period of 0 to 12 hours, so that the infused water becomes a liquid medium that carries more nutrients than ordinary water and will be more easily absorbed by cells and distributed throughout the body (Sidauruk, 2018 ). In several studies, it is stated that dates can increase hemoglobin levels in the blood. Where dates contain iron, vitamin A, vitamin C, protein to form red blood cells. With the method, Infused Water the date palm water becomes alkaline so that it can accelerate the absorption process in the body. The purpose of this study was to determine the effectiveness of dates infused water provision to increase hemoglobin levels of midwifery adolescent girls at Medan Health Polytechnic in 2020. This research was quasi-experimental study using the One Group Pretest-Posttest Without Control Design approach. The sample in this study were 20 respondents of midwifery adolescent girls from Medan Health Polytechnic, using the technique of purposive sampling. The statistical test used wa the Wilcoxon Signed Rank Test because the data was not normal. The results of the Wilcoxon Signed Rank Test obtained the value of P-Value = 0.001. So it can be concluded that the date infused water  is effective in increasing hemoglobin levels of midwifery adolescent girls at Medan Health Polytechnic in 2020.   Keywords: Dates Infused Water, Increased Hemoglobin Levels, Girls Adolescent

scholarly journals Advances in targeted therapy for esophageal cancer

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Yan-Ming Yang ◽  
Pan Hong ◽  
Wen Wen Xu ◽  
Qing-Yu He ◽  
Bin Li
Keyword(s):  
Esophageal Cancer ◽  
Epidermal Growth Factor Receptor ◽  
Growth Factor ◽  
Epidermal Growth Factor ◽  
Targeted Therapies ◽  
Treatment Strategies ◽  
Growth Factor Receptor ◽  
Immune Checkpoints ◽  
Her 2 ◽  
Epidermal Growth

Abstract Esophageal cancer (EC) is one of the most lethal cancers in the world, and its morbidity and mortality rates rank among the top ten in China. Currently, surgical resection, radiotherapy and chemotherapy are the primary clinical treatments for esophageal cancer. However, outcomes are still unsatisfactory due to the limited efficacy and severe adverse effects of conventional treatments. As a new type of approach, targeted therapies have been confirmed to play an important role in the treatment of esophageal cancer; these include cetuximab and bevacizumab, which target epidermal growth factor receptor (EGFR) and vascular endothelial growth factor (VEGF), respectively. In addition, other drugs targeting surface antigens and signaling pathways or acting on immune checkpoints have been continuously developed. For example, trastuzumab, a monoclonal antibody targeting human epidermal growth factor receptor 2 (HER-2), has been approved by the Food and Drug Administration (FDA) as a first-line treatment of HER-2-positive cancer. Moreover, the PD-L1 inhibitor pembrolizumab has been approved as a highly efficient drug for patients with PD-L1-positive or advanced esophageal squamous cell carcinoma (ESCC). These novel drugs can be used alone or in combination with other treatment strategies to further improve the treatment efficacy and prognosis of cancer patients. Nevertheless, adverse events, optimal dosages and effective combinations still need further investigation. In this review, we expound an outline of the latest advances in targeted therapies of esophageal cancer and the mechanisms of relevant drugs, discuss their efficacy and safety, and provide a clinical rationale for precision medicine in esophageal cancer.

Endoscopically defined treatment strategies in patients with locally advanced esophageal cancer

1994 ◽  
Vol 8 (5) ◽  
pp. 384-388
Author(s):  
J. A. Greager ◽  
P. E. Donahue ◽  
K. Reichard ◽  
V. Kucich ◽  
M. Lubienski ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Locally Advanced ◽  
Treatment Strategies ◽  
Advanced Esophageal Cancer ◽  
Locally Advanced Esophageal Cancer
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