ISSN: 2375-3838
International Journal of Clinical Medicine Research  
Manuscript Information
 
 
Optimization of Management for Esophageal Cancer Patients with Stage T1-4N0-2M0
International Journal of Clinical Medicine Research
Vol.4 , No. 4, Publication Date: Aug. 3, 2017, Page: 30-37
11992 Views Since August 3, 2017, 11779 Downloads Since Aug. 3, 2017
 
 
Authors
 
[1]    

Oleg Kshivets, Surgery Department, Roshal Hospital, Roshal, Moscow, Russia.

 
Abstract
 

OBJECTIVE: Search of best management for esophageal cancer (EC) patients (ECP) (T1-4N0-2M0) was realized. METHODS: We analyzed data of 499 consecutive ECP (age=56.3±8.9 years; tumor size=6.3±3.4 cm) radically operated and monitored in 1975-2017 (m=365, f=134; esophagogastrectomies (EG) Garlock=280, EG Lewis=219, combined EG with resection of pancreas, liver, diaphragm, aorta, VCS, colon transversum, lung, trachea, pericardium, splenectomy=147; adenocarcinoma=284, squamous=205, mix=10; T1=92, T2=113, T3=171, T4=123; N0=234, N1=69, N2=196; G1=140, G2=123, G3=236; early EC=73, invasive=426; only surgery=382, adjuvant chemoimmunoradiotherapy-AT=117: 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 1763.2±2213.7 days and cumulative 5-year survival (5YS) reached 47.3%, 10 years – 40.7%, 20 years – 29.8%. 148 ECP lived more than 5 years (LS=4382.9±2551 days), 80 ECP – more than 10 years (LS=6027.2±2445.6 days). 223 ECP died because of EC (LS=630.2±320.5 days). AT significantly improved 5YS (67.7% vs. 43.1%) (P=0.00002 by log-rank test). Cox modeling displayed (Chi2=283.82, df=18, P=0.0000) that 5YS of ECP significantly depended on: phase transition (PT) N0—N12 in terms of synergetics, cell ratio factors (ratio between cancer cells and blood cells subpopulations), G, age, AT, localization, blood cells, prothrombin index, coagulation time, residual nitrogen (P=0.000-0.048). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT N0--N12 (rank=1), PT early-invasive EC (rank=2), T (3), AT (4), prothrombin index (5), glucose (6), healthy cells/CC (7), thrombocytes/CC (8), erythrocytes/CC (9), segmented neutrophils/CC (10), lymphocytes/CC (11), monocytes/CC (12). Correct prediction of 5YS was 100% by neural networks computing. CONCLUSIONS: Optimal management for ECP 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.


Keywords
 

Esophageal Cancer, Management, Optimization


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