P63.01 Lymph Node Metastases of Lung Cancer and Blood Cell Circuit

Abstract

IntroductionSignificance of blood cell circuit in terms of detection of non-small cell lung cancer (LC) patients (LCP) with lymph node metastases was investigated.MethodsWe analyzed data of 757 consecutive LCP (age=57.6±8.2 years; tumor size=4.1±2.4 cm) radically operated (R0) and monitored in 1985-2020 (m=654, f=103; upper lobectomies=272, lower lobectomies=176, middle lobectomies=18, bilobectomies=42, pneumonectomies=249, mediastinal lymph node dissection=757; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=192; T1=317, T2=251, T3=132, T4=57; N0=509, N1=130, N2=118, M0=757; G1=194, G2=238, G3=325; squamous=415, adenocarcinoma=292, large cell=50. 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.ResultsIt was revealed that separation of LCP with lymph node metastases (n=248) from LCP without metastases (n=509) significantly depended on: leucocytes (abs, total), segmented neutrophils (%, abs, total), lymphocytes (%), ESS, Rh, coagulation time, prothrombin index, fibrinogen, heparin tolerance, cell ratio factors (CRF) (ratio between cancer cells- CC and blood cells subpopulations), T, G, tumor size (P=0.047-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of lymph node metastases and CRF: healthy cells/CC (rank=1), segmented neutrophils/CC (2), leucocytes/CC (3), erythrocytes/CC (4), lymphocytes/CC (5), thrombocytes/CC (6), eosinophils/CC (7), monocytes/CC (8), stick neutrophils/CC (9). Correct classification N0—N12 was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).ConclusionLymph node metastases significantly depended on blood cell circuit.Keywordslung cancer, lymph node metastases, blood cell circuit IntroductionSignificance of blood cell circuit in terms of detection of non-small cell lung cancer (LC) patients (LCP) with lymph node metastases was investigated. Significance of blood cell circuit in terms of detection of non-small cell lung cancer (LC) patients (LCP) with lymph node metastases was investigated. MethodsWe analyzed data of 757 consecutive LCP (age=57.6±8.2 years; tumor size=4.1±2.4 cm) radically operated (R0) and monitored in 1985-2020 (m=654, f=103; upper lobectomies=272, lower lobectomies=176, middle lobectomies=18, bilobectomies=42, pneumonectomies=249, mediastinal lymph node dissection=757; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=192; T1=317, T2=251, T3=132, T4=57; N0=509, N1=130, N2=118, M0=757; G1=194, G2=238, G3=325; squamous=415, adenocarcinoma=292, large cell=50. 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. We analyzed data of 757 consecutive LCP (age=57.6±8.2 years; tumor size=4.1±2.4 cm) radically operated (R0) and monitored in 1985-2020 (m=654, f=103; upper lobectomies=272, lower lobectomies=176, middle lobectomies=18, bilobectomies=42, pneumonectomies=249, mediastinal lymph node dissection=757; combined procedures with resection of trachea, carina, atrium, aorta, VCS, vena azygos, pericardium, liver, diaphragm, ribs, esophagus=192; T1=317, T2=251, T3=132, T4=57; N0=509, N1=130, N2=118, M0=757; G1=194, G2=238, G3=325; squamous=415, adenocarcinoma=292, large cell=50. 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. ResultsIt was revealed that separation of LCP with lymph node metastases (n=248) from LCP without metastases (n=509) significantly depended on: leucocytes (abs, total), segmented neutrophils (%, abs, total), lymphocytes (%), ESS, Rh, coagulation time, prothrombin index, fibrinogen, heparin tolerance, cell ratio factors (CRF) (ratio between cancer cells- CC and blood cells subpopulations), T, G, tumor size (P=0.047-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of lymph node metastases and CRF: healthy cells/CC (rank=1), segmented neutrophils/CC (2), leucocytes/CC (3), erythrocytes/CC (4), lymphocytes/CC (5), thrombocytes/CC (6), eosinophils/CC (7), monocytes/CC (8), stick neutrophils/CC (9). Correct classification N0—N12 was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). It was revealed that separation of LCP with lymph node metastases (n=248) from LCP without metastases (n=509) significantly depended on: leucocytes (abs, total), segmented neutrophils (%, abs, total), lymphocytes (%), ESS, Rh, coagulation time, prothrombin index, fibrinogen, heparin tolerance, cell ratio factors (CRF) (ratio between cancer cells- CC and blood cells subpopulations), T, G, tumor size (P=0.047-0.000). Neural networks computing, genetic algorithm selection and bootstrap simulation revealed relationships of lymph node metastases and CRF: healthy cells/CC (rank=1), segmented neutrophils/CC (2), leucocytes/CC (3), erythrocytes/CC (4), lymphocytes/CC (5), thrombocytes/CC (6), eosinophils/CC (7), monocytes/CC (8), stick neutrophils/CC (9). Correct classification N0—N12 was 100% by neural networks computing (area under ROC curve=1.0; error=0.0). ConclusionLymph node metastases significantly depended on blood cell circuit. Lymph node metastases significantly depended on blood cell circuit.