Oleg Kshivets analyzed data from 411 patients who underwent surgery for cardioesophageal or esophageal cancer between 1975-2012. The 5-year survival rate was significantly higher for patients who received adjuvant chemotherapy or chemoradiotherapy (61.7%) compared to surgery alone (36.2%). Neural network analysis revealed that phase of cancer, nodal stage, adjuvant treatment, and cell ratios best predicted 5-year survival. Optimal management strategies include early detection, experienced surgeons, aggressive surgery with lymph node dissection, precision prediction tools, and adjuvant therapy for high-risk patients.

1. Cardioesophageal and
Esophageal Cancer:
Optimization of
Management
Oleg Kshivets, MD, PhD

2. Abstract:
Oleg Kshivets
Cardioesophageal and Esophageal Cancer:
Optimization of Management
 OBJECTIVE: Search of best treatment plan for cardioesophageal/esophageal cancer (CEC) patients
(CECP) was realized.
 METHODS: We analyzed data of 411 consecutive CECP (age=55.6±8.7 years; tumor size=6.7±3.3 cm)
radically operated (R0) and monitored in 1975-2012 (m=307, f=104; esophagogastrectomy- EG
Garlock=271, EG Lewis=140, combined EG with resection of pancreas, liver, diaphragm, colon
transversum, lung, trachea, pericardium, splenectomy=127; adenocarcinoma=216, squamous=185, mix=10;
T1=62, T2=99, T3=141, T4=109; N0=170, N1=57, M1A=184, G1=116, G2=98, G3=197; early CEC=43,
invasive=368; esophageal cancer=139, cardioesophageal cancer=272): only surgery-S=327, adjuvant
treatment-AT=84 (chemoimmunoradiotherapy=36: 5-FU+thymalin/taktivin +radiotherapy 45-50Gy,
adjuvant chemoimmunotherapy=48). Survival curves were estimated by the Kaplan-Meier method.
Differences in curves between groups of CECP were evaluated using a log-rank test. Cox modeling,
clustering, SEPATH, Monte Carlo, bootstrap simulation and neural networks computing were used to
determine any significant dependence.
RESULTS: For total of 411 CECP overall life span (LS) was 1632.2±2141.6 days, (median=783 days) and
cumulative 5-year survival (5YS) reached 40.1%, 10 years – 32.9%, 20 years – 24%. 102 CECP lived more
than 5 years without CEC progressing. 216 CECP died because of CEC during the first 5 years after
surgery. 5YS was superior significantly after AT (61.7%) compared with S (36.2%) (P=0.000 by log-rank
test). Cox modeling displayed that 5YS significantly depended on: phase transition (PT) early-invasive
CEC in term of synergetics, PT N0-N1M1A, AT, cell ratio factors (P=0.000-0.038). Neural networks
computing, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and
PT early-invasive CEC (rank=1), PT N0-N1M1A (rank=2), AT (3), segmented neutrophils/cancer cells-CC)
(4), lymphocytes/CC (5), monocytes/CC (6). Correct prediction of 5YS was 100% by neural networks
computing.
 CONCLUSIONS: Optimal management strategies for CECP are: 1) screening and early detection; 2)
availability of experienced thoracoabdominal surgeons because of complexity of radical procedures; 3)
aggressive en block surgery and adequate lymphadenectomy for completeness; 4) high-precision
prediction; 5) adjuvant treatment for CECP with unfavorable prognosis.

3. Data:
 Males………………………………………………….307
 Females………..………………………………….......104
 Age=55.6±8.7 years
 Tumor Size=6.7±3.3 cm
 Only Surgery.………………………………………...327
 Adjuvant Chemoimmunoradio/Chemoimmunotherapy
(5FU+thymalin/taktivin, 5-6 cycles+RT 45-50Gy)…..84

4. Radical Procedures:
 Left Thoracoabdominal Esophagogastrectomies
(Garlock)……………………..……………………..271
 Right Thoracoabdominal Esophagogastrectomies
 (Ivor Lewis)………………….……………………...140
 Combined Esophagogastrectomies with
 Resection of Diaphragm, Pericardium, Lung, Liver,
Pancreas, etc…………..…………..………………...127
 2-Field Lymphadenectomy….……………………..303
 3-Field Lymphadenectomy….……………………..108

5. Staging:
 T1……62 N0..…170 G1…………116
 T2……99 N1……57 G2…………..98
 T3…..141 N2…..184 G3…………197
 T4…..109 M1……..0
 Adenocarcinoma………..................................216
 Squamos Cell Carcinoma……………………185
 Mix Carcinoma..……………………………….10
 Early Cancer……43
 Invasive Cancer…….368

6. Survival Rate:
 Alive………………………………………....170 (41%)
 5-Year Survivors…………..……………….102 (24.8%)
 10-Year Survivors…………………………...54 (13%)
 Losses………………………………….……216 (52.6%)
 General Life Span=1632.2±2141.6 days
 For 5-Year Survivors=4491.3±2679.0 days
 For 10-Year Survivors=6228.6±2632.2 days
 For Losses=648.6±387.8 days
 Cumulative 5-Year Survival………………..40.1%
 Cumulative 10-Year Survival………………32.9%

7. General Esophageal/Cardioesophageal Cancer Patients Survival
after Complete Esophagogastrectomies (Kaplan-Meier) (n=411)

8. Results of Univariate Analysis of Phase Transition Early—Invasive
Cancer in Prediction of Esophageal/Cardioesophageal Cancer
Patients Survival (n=411)

9. Results of Univariate Analysis of Phase Transition N0—N1-2 in
Prediction of Esophageal/Cardioesophageal Cancer Patients
Survival (n=411)

10. Results of Univariate Analysis of Adjuvant Therapy in Prediction
of Esophageal/Cardioesophageal Cancer Patients Survival (n=411)

11. Results of Univariate Analysis of Tumor Localization in Prediction of
Esophageal/Cardioesophageal Cancer Patients Survival (n=411)

12. Results of Univariate Analysis of Tumor Hystology in Prediction of
Esophageal/Cardioesophageal Cancer Patients Survival (n=411)

13. Results of Univariate Analysis of Tumor Growth in Prediction of
Esophageal/Cardioesophageal Cancer Patients Survival (n=411)

14. Results of Discriminant
Fanction Analysis in
Prediction of
Esophageal/Cardioesophageal
Cancer Patients Survival after
Surgery (n=318)

15. Results of Multi-Factor Clustering
of Clinicopathological Data in
Prediction of
Esophageal/Cardioesophageal
Cancer Patients Survival after
Complete Esophagectomies (n=318)

16. Results of Cox Regression Modeling in
Prediction of
Esophageal/Cardioesophageal Cancer
Patients Survival after Surgery (n=411)

17. Results of Neural Networks Computing
in Prediction of
Esophageal/Cardioesophageal Cancer
Patients Survival after Complete
Esophagogastrectomies (n=318)

18. Results of Bootstrap Simulation in
Prediction of
Esophageal/Cardioesophageal
Cancer Patients Survival after
Complete Esophagectomies
(n=318)

19. Holling-Tenner Models of
Esophageal/Cardioesophageal Cancer
Cell Population and Cytotoxic Cell Population Dynamics

20. Results of Kohonen Self-Organizing Neural
Networks Computing in Prediction of
Esophageal/Cardioesophageal Cancer Patients
Survival after Complete Esophagogastrectomies (n=318)

21. Esophageal/Cardioesophageal
Cancer Dynamics

22. Results of Structurul Equation Modeling
in Prediction of
Esophageal/Cardioesophageal Cancer Patients Survival after
Esophagectomies, n=318

23. Conclusions:
 Optimal management strategies for esophageal and
cardioesophageal cancer patients are:
 1) screening and early detection;
 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) high-precision prediction;
 5) adjuvant treatment for esophageal and
cardioesophageal cancer patients with unfavorable
prognosis.

24. Address:
Oleg Kshivets, M.D., Ph.D.
Consultant Thoracic, Abdominal,
General Surgeon & Surgical
Oncologist
 e-mail: okshivets@yahoo.com
 skype: okshivets
 http: //www.ctsnet.org/home/okshivets