Abstract 1433P
Background
We examined factors significantly affecting esophageal cancer (EC) cell dynamics.
Methods
We analyzed data of 553 consecutive EC patients (ECP) (age=56.5±8.9 years; tumor size=6±3.5 cm) radically operated and monitored in 1975-2021 (m=413, f=140; esophagogastrectomies (EG) Garlock=286, EG Lewis=267, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=153; adenocarcinoma=316, squamous=227, mix=10; T1=128, T2=115, T3=183, T4=127; N0=279, N1=70, N2=204; G1=157, G2=141, G3=255; early EC=110, invasive=443; only surgery=423, adjuvant chemoimmunoradiotherapy-AT=130: 5-FU+thymalin/taktivin+radiotherapy 45-50Gy). Variables selected for 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 ECP were evaluated using a log-rank test. Regression, multivariate Cox modeling, multi-factor clustering, discriminant analysis, structural equation modeling, Monte Carlo, bootstrap simulation and neural networks computing were used to determine any significant dependence.
Results
Overall life span (LS) was 1880.1±2226.6 days and cumulative 5-year survival (5YS) reached 52%, 10 years – 45.6%, 20 years – 33.4%. AT significantly improved 5YS (67.9% vs. 48.5%) (P=0.00039 by log-rank test). Regression modeling displayed EC cell dynamics significantly depended on: phase transition (PT) N0—N12 in terms of synergetics, histology, G, EC growth, age, gender, localization, Hb, blood cells, glucose, residual nitrogen (P=0.000-0.033). Neural networks simulation revealed relationships between EC cell dynamics and blood eosinophils (rank=1), erythrocytes (2), monocytes (3), segmented neutrophils (4), thrombocytes (5), stick neutrophils (6), ESS (7), age (8), Hb (9), lymphocytes (10), protein (11), leucocytes (12). Prediction was 87-91% by neural networks computing.
Conclusions
Esophageal cancer cell dynamics significantly depended on blood cell circuit, biochemical factors, hemostasis system, cancer characteristics, anthropometric data.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Kshivets Oleg.
Funding
Has not received any funding.
Disclosure
The author has declared no conflicts of interest.