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The Open Cardiovascular and Thoracic Surgery Journal, 2008, 1, 1-11                                1

                                                                                                                       Open Access
Esophageal Cancer: Optimization of Management
Oleg Kshivets*

Department of Surgery, Siauliai Public Hospital, Siauliai, Lithuania

           Abstract: Objective: We examined factors associated with generalization of esophageal cancer (EC) after complete
           esophagectomies (E).
           Methods: We analyzed data of 126 consecutive EC patients (ECP) (age = 56.8±7.9 years) operated and monitored in
           1975-2007 (males = 98, females = 28; E Ivor-Lewis = 89, E Garlock = 37; adenocarcinoma = 93, squamos = 31, mix = 2;
           T1 = 25, T2 = 38, T3 = 29, T4 = 34; N0 = 55, N1 = 23, M1a = 48; only surgery-S = 97, adjuvant chemoimmunoradiother-
           apy-AT = 29: 5-FU+ thymalin/taktivin+radiotherapy 45-50Gy). Cox regression, clustering, structural equation modeling,
           Monte Carlo, bootstrap, neural networks computing were used to determine any significant dependence.
           Results: General cumulative 5-year survival (5YS) was 50.5%, 10-year survival - 38.3%. 39 ECP (31%) lived more than 5
           years, 17 ECP - 10 years. 55 ECP (43.7%) died because of EC. AT significantly improved ECP 5YS (P = 0.023). Cox
           modeling displayed that 5YS significantly depended on: T, N, histology, stage, combined procedures, AT, age, blood cell
           subpopulations (P = 0.000-0.039). Neural networks, genetic algorithm and bootstrap simulation revealed relationships be-
           tween 5YS of ECP and N (rank = 1), sex, EC growth, T, histology, combined procedures, G, blood residual nitrogen,
           hemorrhage time, blood chlorides, AT, neutrophils, tumor size, thrombocytes, monocytes. Correct prediction of 5YS was
           100% by neural networks computing.
           Conclusions: Optimal treatment strategies are: screening/early detection; availability of experienced surgeons; aggressive
           surgery; precise prediction; AT for ECP with unfavorable prognosis.

INTRODUCTION                                                              PATIENTS AND METHODS
    The high mortality rate associated with esophageal can-                   We performed a retrospective review of prospectively
cer (EC) is primarily due to the high incidence of late stage             collected database of patients undergoing an esophagectomy
and the lack of curative management for the majority of EC                for EC between September 1975 and March 2007. 126 con-
patients (ECP). Up to 70-90% of ECP present with stage                    secutive ECP (male – 98, female – 28; age = 56.8±7.9 years,
IIB-IV disease. The role of adjuvant chemotherapy or                      tumor size = 5.4±2.5 cm) (mean±standard deviation) entered
chemoradiotherapy after complete esophagectomies in ECP                   this trial. Patients were not considered eligible if they had
with stage II-IVA remains controversial [1]. Moreover, the                stage IVB (nonregional lymph nodes metastases and distant
optimal treatment plan in general and optimal approach for                metastases), previous treatment with chemotherapy, immu-
adjuvant chemoradiotherapy in particular has not been de-                 notherapy or radiotherapy or if there were two primary tu-
fined and long-term prognosis of ECP especially with stage                mors at the time of diagnosis. Patients after non-radical pro-
III-IVA remains poor, because of local relapse and distant                cedures, postoperative died ECP were excluded to provide a
metastases, with the real 5-year survival rate after radical              homogeneous patient group. The preoperative staging proto-
procedures only 20-35% [2]. One of the approaches devel-                  col included clinical history, physical examination, complete
oped involves aggressive en-block surgery and complete                    blood count with differentials, biochemistry and electrolyte
lymphadenectomy. Another of the modern approaches de-                     panel, chest X-rays, roentgenoesophagogastroscopy, com-
veloped to enhance the efficacy of surgery is the combina-                puted tomography scan of thorax, abdominal ultrasound,
tion of chemotherapy, irradiation and immunotherapy or                    fibroesophagogastroscopy, electrocardiogram. Computed
gene therapy which offers the advantage of exposing EC cell               tomography scan of abdomen, liver and bone radionuclide
population for drugs and immune factors thus obviating can-               scan were performed whenever needed. All ECP were diag-
cer cell-cycle cytotoxic and host-immunoprotective effects                nosed with histologically confirmed EC. All had measurable
[3]. Nevertheless, very few studies have demonstrated con-                tumor and ECOG performance status 0 or 1. Before any
vincing clinical results. We developed optimal treatment                  treatment each patient was carefully examined by a medical
strategies that incorporate bolus chemotherapy, irradiation               panel composed of surgeon, chemotherapeutist and radiolo-
and immunotherapy after radical, aggressive en-block sur-                 gist to confirm the stage of disease. All patients signed a
gery.                                                                     written informed consent form approved by the local Institu-
                                                                          tional Review Board.
                                                                             The initial treatment was started with surgery. We per-
*Address correspondence to this author at the Department of Surgery,      formed two types of procedures: 89 complete esophagecto-
Siauliai Public Hospital, Siauliai, Lithuania;                            mies with lesser and partially major omentum with preserva-
E-mail: kshivets003@yahoo.com



                                                       1876-5335/08       2008 Bentham Open
2 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1                                                        Oleg Kshivets

tion of right gastroepiploic vessels and lymph node dissec-              Federation. Thymalin and taktivin are preparations from calf
tion through separate abdominal and right thoracic incision              thymus, which stimulate proliferation of blood T-cell and B-
(Ivor-Lewis) and 37 - through left thoracoabdominal incision             cell subpopulations and their response [4]. The importance
(Garlock). The present analysis was restricted to ECP with               must be stressed of using immunotherapy in combination with
complete resected tumors with negative surgical resection                chemotherapy and radiotherapy, because immune dysfunc-
margin and with N1 and celiac lymph node metastases                      tions of the cell-mediated and humoral response were induced
(M1A). Complete surgical resection consisted of esophagec-               by tumor, surgical trauma, chemotherapy and radiation [3].
tomy with one-stage intrapleural esophagogastrostomy in 61,              Such immune deficiency induced generalization of EC and
and with anastomosis on the neck in 65. EC was localized in              compromised the longterm therapeutic result. In this sense,
lower third of esophagus in 61, middle third - in 48, upper              immunotherapy may have shielded the patient from adverse
third – in 17. Among these, 40 ECP underwent combined                    side effects of treatment. Concurrent radiotherapy (60CO;
and extensive radical procedures with the resection of dia-              ROKUS, Russia) with a total tumor dose 45-50 Gy was started
phragm, pericardium, lung, liver left lobe, splenectomy. The             5-7 weeks after surgery. Radiation consisted of single daily
extent of lymphadenectomy in the upper abdominal com-                    fractions of 180-200 cGy 5 days per week for 5 weeks. The
partment and lower posterior mediastinum was identical for               treatment volume included the ipsilateral hilus, the supraclavi-
all surgical approaches and comprised a suprapancreatic                  cular fossa and the mediastinum from the incisura jugularis to
lymphadenectomy, including all lymph nodes along the                     8 cm below the carina. The lower mediastinum and upper ab-
common hepatic artery, celiac axis, and splenic artery toward            domen were included in cases of primary tumors in the lower
the splenic hilum. The left gastric artery was always tran-              third of esophagus or M1A. The resected tumor bed was in-
sected at its origin and remained with the specimen. Also                cluded in all patients. Parallel-opposed AP-PA fields were
included were all lymph nodes along the proximal two thirds              used. All fields were checked using the treatment planning
of the lesser gastric curvature and the gastric fundus, left and         program COSPO (St. Petersburg, Russia). Doses were speci-
right paracardiac nodes, distal paraesophageal nodes, and                fied at middepth for parallel-opposed technique or at the inter-
nodes in the lower posterior mediastinum up to the tracheal              section of central axes for oblique technique. No prophylactic
bifurcation. Patients with the right thoracoabdominal ap-                cranial irradiation was used.
proach had an additional formal extended mediastinal lym-
                                                                             During chemoimmunoradiotherapy antiemetics were ad-
phadenectomy comprising all nodes at the tracheal bifurca-
                                                                         ministered. Gastrointestinal side effects, particularly nausea
tion along the left and right main stem bronchi, the upper
                                                                         and vomiting, were mild, and chemoimmunoradiotherapy was
mediastinal compartment, and along the left recurrent nerve.             generally well tolerated. Severe leukopenia, neutropenia, ane-
A systematic cervical lymphadenectomy was performed rou-
                                                                         mia and trombocytopenia occurred infrequently. There were
tinely for ECP with neck anastomosis. 59 patients underwent
                                                                         no treatment-related deaths.
lymph nodal D2-dissection (in terms of gastric cancer sur-
gery). Extensive lymph nodal D3-dissection was performed                     A follow-up examination was generally done every 3
in 67 ECP. Routine two-field lymphadenectomy (in terms of                month for the first 2 years, every 6 month after that and yearly
EC surgery) was performed in 61, three-field – in 65. All                after 5 years, including a physical examination, a complete
ECP were postoperatively staged according to the TNMG-                   blood count, blood chemistry, chest roentgenography. Endo-
classification. Histological examination showed adenocarci-              scopy and abdominal ultrasound were done every 6-month for
noma in 93, squamous cell carcinoma - in 31 and mixed car-               the first 3 years and yearly after that. Zero time was the data of
cinoma - in 2 patients. The pathological TNM stage was I in              surgical procedures. No one was lost during the follow-up
22, IIA – in 24, IIB – in 13, III - in19, IVA – in 48 patients;          period and we regarded the outcome as death through personal
the pathological T stage was T1 in 25, T2 - in 38, T3 - in 29,           knowledge, physician's reports, autopsy or death certificates.
T4 - in 34 cases; the pathological N stage was N0 in 55, N1 -            Survival time (days) was measured from the date of surgery
in 23, M1A - in 48 patients. The tumor differentiation was               until death or the most-recent date of follow-up for surviving
graded as G1 in 46, G2 - in 39, G3 - in 41 cases. After surgery          patients.
postoperative chemoimmunoradiotherapy was accomplished                       Variables selected for 5-year survival and life span study
in ECP with ECOG performance status 0 or 1.                              were the input levels of 45 blood parameters, sex, age,
    All patients (126 ECP) were divided randomly between                 TNMG, cell type, and tumor size. Survival curves were esti-
the two protocol treatment: 1) surgery and adjuvant chemo-               mated by the Kaplan-Meier method. Differences in curves
immunoradiotherapy (29 ECP – group A) (age=57±1.6.5                      between groups of ECP were evaluated using a log-rank test.
years; males - 22, females - 7; tumor size=6.3±3.0 cm); 2)               Multivariate proportional hazard Cox regression, structural
surgery alone without any adjuvant treatment (97 ECP –                   equation modeling (SEPATH), Monte Carlo, bootstrap simu-
group B) (age=56.8±8.3 years; males - 76, females - 21; tu-              lation and neural networks computing were used to determine
mor size=5.1±2.3 cm) – the control group                                 any significant dependence [3, 5-10]. Neural networks com-
                                                                         puting, system, biometric and statistical analyses were con-
    Twenty-nine ECP received adjuvant chemoimmunoradio-
                                                                         ducted using CLASS-MASTER program (Stat Dialog, Inc.,
therapy which consisted of chemoimmunotherapy (5-6 cycles)
                                                                         Moscow, Russia), SANI program (Stat Dialog, Inc., Moscow,
and thoracic radiotherapy (group A). 1 cycle of bolus chemo-
                                                                         Russia), DEDUCTOR program (BaseGroup Labs, Inc., Ri-
therapy was initiated 3-5 weeks after complete esophagecto-              azan, Russia), STATISTICA and STATISTICA Neural Net-
mies and consisted of fluorouracil 500 mg/m2 intravenously
                                                                         works program (Stat Soft, Inc., Tulsa, OK, USA), MATH-
for 5 days. Immunotherapy consisted thymalin or taktivin 20
                                                                         CAD (MathSoft, Inc., Needham, MA, USA). All tests were
mg intramuscularly on days 1, 2, 3, 4 and 5. These immuno-
                                                                         considered significant when the resulting P value was less
modulators produced by Pharmaceutics of Russian Federation
                                                                         than 0.05.
(Novosibirsk) and approved by Ministry of Health of Russian
Esophageal Cancer: Optimization of Management                                       The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1   3

RESULTS                                                                                    Second, we observed good 5-year survival for ECP with
                                                                                       N0 (70%) as compared with ECP with N1-M1A (5-year sur-
    For the entire sample of 126 patients overall life span
                                                                                       vival was 33.1%) after radical procedures (P = 0.00002 by
(LS) was 1587.6±1650.3 days (mean ±standard deviation)
                                                                                       log-rank test) (Fig. 3). Accordingly, the overall 10-year sur-
(95% CI, 1296.6-1878.5; median = 895). General cumulative
                                                                                       vival for ECP with N0 reached 60% and was significantly
5 year survival was 50.5%, 10-year survival – 38.3%. 64 ECP                            superior compared to 19% for ECP with lymph node metasta-
(50.8%) were alive till now, 39 ECP (31%) lived more than 5
                                                                                       ses.
years (LS = 3544.3±1712.5 days) and 17 ECP - 10 years (LS
= 5000.1±1639 days) without any features of EC progressing.                                All parameters were analyzed in a Cox model. In accor-
55 ECP (43.7%) died because of EC during the first 5 years                             dance with this Cox model (global 2 = 124.1; Df = 31; P =
after surgery (LS = 621.4±366 days).                                                   0.00000), the sixteen variables significantly explained 5-year
                                                                                       survival of ECP after complete esophagectomies: stage, status
    For the 29 ECP in adjuvant chemoimmunoradiotherapy                                 of regional lymph nodes, tumor growth, adjuvant chemoim-
arm (group A), overall LS was 1843.2±2083.4 days (95% CI,                              munoradiotherapy, combined procedures, age, T1-4, histology
1050.7±2635.7; median = 888). For the 97 ECP in the control                            and blood cell factors (percent of segmented neutrophils and
(group B), overall LS was 1511.2±1501.5 days (95% CI,                                  lymphocytes, populations of leucocytes, eosinophils, stick and
1208.5-1813.8; median = 896) (P = 0.023 by log-rank test).                             segmented neutrophils, lymphocytes and monocytes) (Table 1).
The overall cumulative 5-year survival of ECP for group A
reached 64.1% and was significantly superior compared to                                   For comparative purposes, clinicomorphological vari-
47.0% for group B (P = 0.023 by log-rank test) (Fig. 1).                               ables of ECP (n = 94: 39 5-year survivors and 55 losses)
                                                                                       were tested by neural networks computing (4-layer percep-
    It is necessary to pay attention to two very important prog-                       tron) (Fig. 4). For more exact analysis 32 patients were ex-
nostic phenomenons. First, we found 100 % 5-years survival                             cluded from the sample, who were alive less than 5 years
for ECP with early cancer (T1N0) versus 40.5% for the others                           after complete esophagectomies without relapse. Multilayer
ECP after esophagectomies (P = 0.00001 by log-rank test)                               perceptron was trained by Levenberg-Marquardt method
(Fig. 2). Early esophageal cancer was defined, based on the                            (Fig. 5). Obviously, analyzed data provide significant infor-
final histopathologic report of the resection specimen, as tu-                         mation about EC prediction. High accuracy of classification
mor limited to the mucosa or submucosa and not extending                               – 100% (5-year survivors vs losses) was achieved in ana-
into the muscular wall of the esophagus, up to 2 cm in diame-                          lyzed sample (baseline error = 0.001, are under ROC curve =
ter with N0 [10]. Patients with stage T1N0 did not receive                             1.0). In other words it remains formally possible that reviled
adjuvant chemoimmunoradiotherapy. Correspondingly, the                                 fifteen factors might predate neoplastic generalization: N-
overall 10-year survival for ECP with the early cancer was                             status, gender, EC growth, T-status, histology, type of com-
81% and was significantly better compared to 28% for others                            bined procedures, G-status, blood residual nitrogen, hemor-
patients.                                                                              rhage time, blood chlorides, adjuvant chemoimmunoradio-


                                                              Cumulative Proportion Surviving (Kaplan-Meier)
                                                                           Complete         Censored
                                                          Esophageal Cancer Patients after Esophagectomies, n=126
                                                                          P=0.023 by log-rank test

                                                1.0
              Cumulative Proportion Surviving




                                                0.9                       Only Surgery=97
                                                0.8                       Adjuvant Chemoimmunoradiotherapy=29
                                                                                                          =

                                                0.7

                                                0.6

                                                0.5

                                                0.4

                                                0.3

                                                0.2
                                                      0          5             10                  15                  20                 25


                                                                        Years after Esophagectomies

Fig. (1). Survival of ECP after esophagectomies in group A (adjuvant chemoimmunoradiotherapy) (n = 29) and B (surgery alone) (n = 97). Sur-
vival of ECP in group A was significantly better compared with group B (P = 0.023 by log-rank).
4 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1                                                                                                            Oleg Kshivets


                                                                                                    Cumulative Proportion Surviving (Kaplan-Meier)
                                                                                                                  Complete       Censored
                                                                                                Esophageal Cancer Patients after Esophagectomies, n=126
                                                                                                               P=0.00001 by log-rank test

                                                                                 1.0
                                               Cumulative Proportion Surviving

                                                                                 0.9

                                                                                 0.8

                                                                                 0.7
                                                                                                                                            Invasive Cancer, n=106
                                                                                 0.6
                                                                                                                                            Early Cancer, n=20
                                                                                 0.5

                                                                                 0.4

                                                                                 0.3

                                                                                 0.2
                                                                                           0              5           10              15                20              25


                                                                                                              Years after Esophagectomies

Fig. (2). Survival of ECP with early cancer (n = 20) was significantly better compared with invasive cancer (n = 106) (P = 0.00001 by log-
rank).



                                                                                                   Cumulative Proportion Surviving (Kaplan-Meier)
                                                                                                                  Complete        Censored
                                                                                               Esophageal Cancer Patients after Esophagectomies, n=126
                                                                                                               P=0.00002 by log-rank test

                                                            1.0
             Cumulative Proportion Surviving




                                                            0.9
                                                                                                                             N1-M1A=71
                                                            0.8
                                                                                                                             N0=55
                                                            0.7

                                                            0.6

                                                            0.5

                                                            0.4

                                                            0.3

                                                            0.2

                                                            0.1
                                                                                       0              5               10               15                20                  25


                                                                                                              Years after Esophagectomies

Fig. (3). Survival of ECP with N0 (n = 55) was significantly better compared with N1-M1A metastases (n = 71) (P = 0.00002 by log-rank).

therapy, percent of stick neutrophils in blood, tumor size,                                                                  ECP after radical procedures and all recognized variables
number of thrombocytes and monocytes in blood (Table 2).                                                                     (Tables 3 and 4). Moreover, bootstrap simulation confirmed
Genetic algorithm selection and bootstrap simulation con-                                                                    the paramount value of cell ratio factors (ratio between blood
firmed significant dependence between 5-year survival of                                                                     cell subpopulations and EC cell population).
Esophageal Cancer: Optimization of Management                         The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1     5



Table 1.    Results of Multivariate Proportional Hazard Cox Regression Modeling in Prediction of ECP Survival After Esophagec-
            tomies (n = 126)

                            Variables in the Equation                               B           SE         Wald            df          P

 Segmented Neutrophils (%)                                                        0.225       0.089         6.335          1         0.012
 Lymphocytes (%)                                                                  0.235       0.087         7.257          1         0.007
 Histology                                                                                                 10.701          2         0.005
 Histology(1)                                                                     -0.893      0.273        10.693          1         0.001
 Histology(2)                                                                     -0.697      1.292         0.291          1         0.590
 Tumor Growth                                                                                               5.771          2         0.056
 Tumor Growth(1)                                                                  2.672       1.114         5.754          1         0.016
 Tumor Growth(2)                                                                  2.699       1.142         5.584          1         0.018
 Adjuvant Chemoimmunoradiotherapy                                                 -0.691      0.334         4.267          1         0.039
 Combined Operation                                                                                        15.710          5         0.008
 Combined Operation(1)                                                            -0.099      0.369         0.072          1         0.788
 Combined Operation(2)                                                            0.176       0.638         0.076          1         0.783
 Combined Operation(3)                                                            4.833       1.348        12.850          1         0.000
 Combined Operation(4)                                                            -0.209      0.699         0.090          1         0.765
 Combined Operation(5)                                                            -0.128      0.588         0.047          1         0.828
 Leucocytes (tot)                                                                 -2.961      0.815        13.212          1         0.000
 Eosinophils (tot)                                                                3.220       0.747        18.553          1         0.000
 Stick Neutrophils (tot)                                                          3.320       0.789        17.698          1         0.000
 Segmented Neutrophils (tot)                                                      3.021       0.829        13.267          1         0.000
 Lymphocytes (tot)                                                                2.814       0.810        12.085          1         0.001
 Monocytes (tot)                                                                  3.458       0.806        18.403          1         0.000
 Leucocytes/Cancer Cells                                                          0.104       0.111         0.871          1         0.351
 Segmented Neutrophils/Cancer Cells                                               -0.263      0.148         3.144          1         0.076
 T                                                                                                         16.809          3         0.001
 T(1)                                                                             -1.796      0.857         4.392          1         0.036
 T(2)                                                                             -2.799      0.721        15.054          1         0.000
 T(3)                                                                             -0.782      0.467         2.809          1         0.094
 N                                                                                                         19.295          3         0.000
 N(1)                                                                             0.108       1.265         0.007          1         0.932
 N(2)                                                                             2.470       1.324         3.479          1         0.062
 N(3)                                                                             2.065       1.135         3.312          1         0.069
 Stage                                                                                                     18.254          3         0.000
 Stage(1)                                                                         0.914       0.912         1.004          1         0.316
 Stage(2)                                                                         2.643       0.655        16.292          1         0.000
 Stage(3)                                                                         0.882       0.720         1.501          1         0.220
 Age                                                                              0.033       0.016         4.329          1         0.037
 Erythrocytes/Cancer Cells                                                        0.059       0.062         0.927          1         0.336

Table 2.    Results of Neural Networks Computing in Prediction of 5-Year Survival of ECP After Esophagectomies (n = 94: 39 5-
            Year Survivors and 55 Losses)

   NN                 Esophageal Cancer Patients After Esophagectomies Factors                Rank          Sample Error        n = 94 Ratio

   1       N                                                                                    1               0.443             436.032
   2       Gender                                                                               2               0.369             363.171
   3       Esophagus Cancer Growth                                                              3               0.294             288.790
   4       T                                                                                    4               0.267             262.995
   5       Histology                                                                            5               0.252             248.158
   6       Combined Procedures                                                                  6               0.209             205.320
   7       G                                                                                    7               0.173             170.081
   8       Blood Residual Nitrogen                                                              8               0.146             143.457
   9       Hemorrhage Time                                                                      9               0.145             142.492
   10      Blood Chlorides                                                                      10              0.122             119.974
   11      Adjuvant Chemoimmunoradiotherapy                                                     11              0.104             102.016
   12      Stick Neutrophils (%)                                                                12              0.082             80.696
   13      Tumor Size                                                                           13              0.031             30.558
   14      Thrombocytes (abs)                                                                   14              0.007              6.965
   15      Monocytes (abs)                                                                      15              0.004              3.765
                                           Baseline Error                                                         0.001
                                      Area under ROC Curve                                                        1.000
                                   Correct Classification Rate (%)                                                100.0
6 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1                                                              Oleg Kshivets



Table 3.      Results of Neural Networks Genetic Algorithm Selection in Prediction 5-Year Survival of ECP After Esophagectomies (n
              = 94: 39 5-Year Survivors and 55 Losses)

    NN                                     Esophageal Cancer Patients, n = 94 Factors                             Useful for 5-Year Survival

     1        Stick Neutrophils (%)                                                                                           Yes
     2        Monocytes (%)                                                                                                   Yes
     3        Thrombocytes (abs)                                                                                              Yes
     4        ESS                                                                                                             Yes
     5        Hemorrhage Time                                                                                                 Yes
     6        Blood Residual Nitrogen                                                                                         Yes
     7        Blood Protein                                                                                                   Yes
     8        Blood Chlorides                                                                                                 Yes
     9        Tumor Size                                                                                                      Yes
    10        Stick Neutrophils (abs)                                                                                         Yes
    11        T                                                                                                               Yes
    12        N                                                                                                               Yes
    13        Gender                                                                                                          Yes
    14        G                                                                                                               Yes
    15        Histology                                                                                                       Yes
    16        Esophagus Cancer Growth                                                                                         Yes
    17        Adjuvant Chemoimmunoradiotherapy                                                                                Yes
    18        Combined Procedures                                                                                             Yes
    19        Stick Neutrophils (tot)                                                                                         Yes
    20        Leucocytes/Cancer Cells                                                                                         Yes


Table 4.      Results of Bootstrap Simulation in Prediction of 5-Year Survival of ECP After Esophagectomies (n = 94: 39 5-Year Sur-
              vivors and 55 Losses)

                          Esophageal Cancer Patients After Esophagectomies n = 94                       Number of Samples =
                                                                                             Rank             3333                      >P
         NN
                                               Significant Factors                                         Kendall’Tau-A

         1                                  Erythrocytes/Cancer Cells                         1                0.286                 0.00004
         2                                            Stage                                   2                -0.281                0.00008
         3                                         Tumor Size                                 3                -0.274                 0.0001
         4                                  Healthy Cells/Cancer Cells                        4                0.268                  0.0002
         5                                              T                                     5                -0.268                 0.0002
         6                                  Lymphocytes/Cancer Cells                          6                0.250                  0.0003
         7                                   Leucocytes/Cancer Cells                          7                0.235                  0.0007
         8                                      Coagulation Time                              8                -0.215                 0.001
         9                                              N                                     9                -0.206                 0.003
         10                                  Eosinophils/Cancer Cells                         10               0.206                  0.003
         11                                  Monocytes/Cancer Cells                           11               0.204                  0.004
         12                                  Blood Residual Nitrogen                          12               -0.197                 0.007
         13                             Segmented Neutrophils/Cancer Cells                    13               0.191                   0.01
         14                                 Thrombocytes/Cancer Cells                         14               0.174                   0.02
         15                                      Blood Chlorides                              15               0.171                   0.02
         16                               Stick Neutrophils/Cancer Cells                      16               0.164                   0.03
         17                                   Stick Neutrophils (%)                           17               0.133                   0.05

    It is necessary to note very important law: transition of                   sis” in terms of synergetics (Figs. 6, 7). This also proves the
the early cancer into the invasive cancer as well as the cancer                 first results received earlier in the works [3,10]. Presence of
with N0 into the cancer with N1-M1A has the phase charac-                       two phase transitions is evidently shown on Kohonen self-
ter. These results testify by mathematical (Holling-Tanner)                     organizing neural networks maps (Fig. 8).
and imitating modeling of system “EC—patient homeosta-
Esophageal Cancer: Optimization of Management                         The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1   7




Fig. (4). Configuration of neural networks: 4-layer perceptron.



                                                 Training Error Graph (Sum-squared)
                                    Esophageal Cancer Patients after Esophagectomies, n=94
                                        Baseline Errors=0.001; Area under ROC Curve=1.00
                                                          Neural Netwoks Learning

                 0.8
                                                              Train by Levenberg-Marquardt



                 0.6
         Error




                 0.4




                 0.2




                 0.0
                       0          200               400              600              800              1000             1200


                                                                    Epoch

Fig. (5). Results of neural networks training in prediction of 5-year survival of ECP (n = 94; 39 5-year survivors and 55 losses): Baseline
Errors = 0.001; Area under ROC Curve = 1.00; Correct Classification Rate = 100%.
8 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1                                                   Oleg Kshivets




Fig. (6). Results of Holling-Tenner modeling of system “EC—Lymphocytes” in prediction of ECP survival after esophagectomies.




Fig. (7). Presence of the two phase transitions “early cancer—invasive cancer” and “cancer with N0—cancer with N1-M1A” in terms of
synergetics.
Esophageal Cancer: Optimization of Management                        The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1   9




Fig. (8). Results of Kohonen self-organizing neural networks computing in prediction of ECP survival after Esophagectomies (n = 94).

    All of these differences and discrepancies were further             limit and leaves much to be desired: the average real 5-year
investigated by structural equation modeling (SEPATH) as                survival rate of radically operated ECP even after combined
well as Monte Carlo simulation. From data, summarized in                and extensive procedures is 30-35% and practically is not
Fig. (9) (Global 2 = 10691.5; Df = 1533; P = 0.000000; n =              improved during the past 30-40 years, as the great majority
94) it was revealed that the seven clusters significantly pre-          of patients has already EC with stage III-IVA [3,10,13]. And
dicted 5-year survival and life span of ECP after esophagec-            finally, modern TNM-classification is based only on cancer
tomies: 1) phase transition “early EC—invasive EC” (P =                 characteristics and does not take into account at all the fea-
0.001); 2) phase transition “EC with N0—EC with N1-                     tures of extremely complex alive supersystem – the patient’s
M1A” (P = 0.000); 3) cell ratio factors (P = 0.001); 4) EC              organism. Therefore the prediction of EC is rather inexact
characteristics (P = 0.000); 5) biochemical homeostasis (P =            and approximate with the big errors.
0.000); 6) hemostasis system (P = 0.043) and 7) combined
                                                                            Central goal of the present research was to estimate the
procedures and adjuvant chemoimmunoradiotherapy (P =
                                                                        efficiency of complete esophagectomies with lymphadenec-
0.030) (Fig. 9). It is necessary to pay attention, that both
                                                                        tomies and adjuvant chemoimmunoradiotherapy after radical
phase transitions strictly depend on blood cell circuit and cell
                                                                        surgery. The importance must be stressed of using complex
ratio factors.                                                          system analysis, artificial intelligence (neural networks com-
DISCUSSION                                                              puting) and statistical methods in combination, because the
                                                                        different approaches yield complementary pieces of prognos-
    Treatment of ECP is an extremely difficult problem. On              tic information. Not stopping in details on these supermod-
the one hand, the esophageal cancer surgery demands mas-                ern technologies because of the journal limit rules, great ad-
terly surgical technique and always will remain the privilege           vantage of the artificial intelligence methods is the opportu-
of very experienced professionals [11]. Actual surgical re-             nity to find out hidden interrelations which cannot be calcu-
moval of tumor and lymph node metastases remains basic                  lated by analytical and system methods. While huge merit of
management of this very aggressive cancer giving the real               simulation modeling is the identification of dynamics of any
chance for cure in spite of extensive research over the last 30         supersystem on the hole in time [3,10].
years in terms of chemotherapy, radiotherapy, immunother-
apy and gene therapy [1, 2, 12]. On the other hand, the effec-              Although there is no consensus on adjuvant treatment
tiveness of complete esophagectomy already reached its                  after radical procedures the two of the most commonly em-
10 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1                                                               Oleg Kshivets




Fig. (9). Significant networks between ECP (n = 94) survival, cancer characteristics, blood cell circuit, cell ratio factors, hemostasis system,
biochemic and anthropometric data, phase transition “early cancer—invasive cancer”, phase transition “cancer with N0—cancer with N1-
M1A” and treatment protocols (SEPATH network model).

ployed strategies are surgery alone and adjuvant (neoadju-                juvant treatment is no need. From this it follows the para-
vant) chemoradiotherapy with or without immunotherapy. In                 mount importance of screening and early detection of EC.
the last 10-15 years a number of new drugs have been shown
                                                                              Concerning ECP with N0 further investigations will be
to have good activity against EC, including mitomycin C,
                                                                          required to determine efficiency, compatibility and tolerance
cisplatin, doxetacel, etc. [14-16]. On the other hand new
                                                                          of new drugs and immunomodulators after esophagectomies.
immunomodulators, new adoptive immunotherapeutic mo-                      The results of the present research will offer guidance for the
dalities with lymphokineactivated killer cells, tumor-
                                                                          design of future studies.
infiltrating lymphocytes and high-dose interleukins have
been developed and antitumor effect have been successfully                   In conclusion, optimal treatment strategies for ECP are:
demonstrated in advanced malignancies [17,18].                            1) screening and early detection of EC; 2) availability of
                                                                          very experienced surgeons because of complexity radical
    Theoretically chemoimmunotherapy is most effective                    procedures; 3) aggressive en block surgery and adequate
when used in patients with a relatively low residual malig-
                                                                          lymphadenectomy for completeness; 4) precise prediction
nant cell population (approximately 1 billion cancer cells per
                                                                          and 5) AT for ECP with unfavorable prognosis.
patient) in terms of hidden micrometastases [3,10]. This is
typical clinical situation for ECP with N1-M1A after com-                 REFERENCES
plete esophagectomies. Present research only confirmed this               [1]     Graham AJ, Shrive FM, Ghali WA, et al. Defining the optimal
axiom.                                                                            treatment of locally advanced esophageal cancer: a systematic re-
                                                                                  view and decision analysis. Ann Thorac Surg 2007; 83(4): 1257-
    In summary, when adjuvant chemoimmunoradiotherapy                             64.
is applied to complete esophagectomies for EC with N1-                    [2]     Gebski V, Burmeister B, Smithers BM, Foo K, Zalcberg J, Simes J.
M1A, the following benefits should be considered: 1) possi-                       Australasian Gastro-Intestinal Trials Group. Survival benefits from
bility of total elimination of residual hidden micrometasta-                      neoadjuvant chemoradiotherapy or chemotherapy in oesophageal
ses; 2) surgery and chemoradiotherapy can result immuno-                          carcinoma: a meta-analysis. Lancet Oncol 2007; 8(3): 226-34.
                                                                          [3]     Kshivets O. Expert system in diagnosis and prognosis of malignant
suppressive state, which can be improved by immunother-                           neoplasms. Dissertation for Sc.D., Tomsk 1995; p. 486.
apy; 3) radical operated ECP with stage IIB-IVA are thought               [4]     Morozow VG, Chavinson VC. Isolation, refinement and identifica-
to be potentially good candidates for adjuvant chemoim-                           tion of immunomodulated polypeptide from calf and human thy-
munoradiotherapy as the majority of these patients would be                       mus. Biochemistry 1981; 9: 1652-9.
                                                                          [5]     Odom-Maryon T. Biostatistical methods in oncology. Cancer man-
expected to have EC progressing.                                                  agement: A multidisciplinary approach. 1st ed. Huntington, NY:
    As regards the early EC that it is all quite clear. For these                 PRP Inc. 1996; pp. 788-802.
patients only radical surgery is absolutely sufficient and ad-
Esophageal Cancer: Optimization of Management                                The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1         11

[6]     Mirkin BG. A sequential fitting procedure for linear data analysis       [13]    Stilidi I, Davydov M, Bokhyan V, Suleymanov E. Subtotal
        models. J Classification 1990; 7: 167-96.                                        esophagectomy with extended 2-field lymph node dissection for
[7]     Joreskog KG, Sorbom D. Recent development in structural equa-                    thoracic esophageal cancer. Eur J Cardiothorac Surg 2003; 23(3):
        tion modeling. J Market Res 1982; 19: 404-16.                                    415-20.
[8]     Bostwick DG, Burke HB. Prediction of individual patient outcome          [14]    Lerut T, Coosemans W, Decker G et al. Diagnosis and therapy in
        in cancer: comparison of artificial neural networks and Kaplan-                  advanced cancer of the esophagus and the gastroesophageal junc-
        Meier methods. Cancer 2001; 91(8): 1643-6.                                       tion. Curr Opin Gastroenterol 2006; 22(4): 437-41.
[9]     Husmeier D. The Bayesian evidence scheme for regularizing prob-          [15]    Refaely Y, Krasna MJ. Multimodality therapy for esophageal can-
        ability-density estimating neural networks. Neural Comput 2000;                  cer. Surg Clin North Am 2002; 82(4): 729-46.
        12(11): 2685-717.                                                        [16]    Luketich JD, Schauer P, Urso K, et al. Future directions in eso-
[10]    Kshivets O. Optimization of diagnosis process for patients with                  phageal cancer. Chest 1998; 113(1 Suppl): 120S-122S.
        malignant neoplasms. Dissertation for PhD. St. Petersburg 1992;          [17]    Yano T, Sugio K, Yamazaki K, et al. Postoperative adjuvant adop-
        p. 354.                                                                          tive immunotherapy with lymph node-LAK cells and IL-2 for
[11]    Chernousov AF, Bogopolsky PM, Kurbanov FS. Esophageal sur-                       pathologic stage I non-small cell lung cancer. Lung Cancer 1999;
        gery. M.: Moscow Publishers 2000; p. 352.                                        26: 143-8.
[12]    D'Journo XB, Doddoli C, Michelet P, et al. Transthoracic esoph-          [18]    Kshivets O. Immune cell and humoral circuit in prediction of non-
        agectomy for adenocarcinoma of the oesophagus: standard versus                   small cell lung cancer patients survival after complete resections. J
        extended two-field mediastinal lymphadenectomy? Eur J Car-                       Tumor Marker Oncol 2001; 16(2): 161-74.
        diothorac Surg 2005; 27(4): 697-704.


Received: August 4, 2008                                          Revised: August 25, 2008                                        Accepted: August 29, 2008


© Oleg Kshivets; Licensee Bentham Open.
This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-
nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

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Kshivets O. Esophageal Cancer Surgery

  • 1. The Open Cardiovascular and Thoracic Surgery Journal, 2008, 1, 1-11 1 Open Access Esophageal Cancer: Optimization of Management Oleg Kshivets* Department of Surgery, Siauliai Public Hospital, Siauliai, Lithuania Abstract: Objective: We examined factors associated with generalization of esophageal cancer (EC) after complete esophagectomies (E). Methods: We analyzed data of 126 consecutive EC patients (ECP) (age = 56.8±7.9 years) operated and monitored in 1975-2007 (males = 98, females = 28; E Ivor-Lewis = 89, E Garlock = 37; adenocarcinoma = 93, squamos = 31, mix = 2; T1 = 25, T2 = 38, T3 = 29, T4 = 34; N0 = 55, N1 = 23, M1a = 48; only surgery-S = 97, adjuvant chemoimmunoradiother- apy-AT = 29: 5-FU+ thymalin/taktivin+radiotherapy 45-50Gy). Cox regression, clustering, structural equation modeling, Monte Carlo, bootstrap, neural networks computing were used to determine any significant dependence. Results: General cumulative 5-year survival (5YS) was 50.5%, 10-year survival - 38.3%. 39 ECP (31%) lived more than 5 years, 17 ECP - 10 years. 55 ECP (43.7%) died because of EC. AT significantly improved ECP 5YS (P = 0.023). Cox modeling displayed that 5YS significantly depended on: T, N, histology, stage, combined procedures, AT, age, blood cell subpopulations (P = 0.000-0.039). Neural networks, genetic algorithm and bootstrap simulation revealed relationships be- tween 5YS of ECP and N (rank = 1), sex, EC growth, T, histology, combined procedures, G, blood residual nitrogen, hemorrhage time, blood chlorides, AT, neutrophils, tumor size, thrombocytes, monocytes. Correct prediction of 5YS was 100% by neural networks computing. Conclusions: Optimal treatment strategies are: screening/early detection; availability of experienced surgeons; aggressive surgery; precise prediction; AT for ECP with unfavorable prognosis. INTRODUCTION PATIENTS AND METHODS The high mortality rate associated with esophageal can- We performed a retrospective review of prospectively cer (EC) is primarily due to the high incidence of late stage collected database of patients undergoing an esophagectomy and the lack of curative management for the majority of EC for EC between September 1975 and March 2007. 126 con- patients (ECP). Up to 70-90% of ECP present with stage secutive ECP (male – 98, female – 28; age = 56.8±7.9 years, IIB-IV disease. The role of adjuvant chemotherapy or tumor size = 5.4±2.5 cm) (mean±standard deviation) entered chemoradiotherapy after complete esophagectomies in ECP this trial. Patients were not considered eligible if they had with stage II-IVA remains controversial [1]. Moreover, the stage IVB (nonregional lymph nodes metastases and distant optimal treatment plan in general and optimal approach for metastases), previous treatment with chemotherapy, immu- adjuvant chemoradiotherapy in particular has not been de- notherapy or radiotherapy or if there were two primary tu- fined and long-term prognosis of ECP especially with stage mors at the time of diagnosis. Patients after non-radical pro- III-IVA remains poor, because of local relapse and distant cedures, postoperative died ECP were excluded to provide a metastases, with the real 5-year survival rate after radical homogeneous patient group. The preoperative staging proto- procedures only 20-35% [2]. One of the approaches devel- col included clinical history, physical examination, complete oped involves aggressive en-block surgery and complete blood count with differentials, biochemistry and electrolyte lymphadenectomy. Another of the modern approaches de- panel, chest X-rays, roentgenoesophagogastroscopy, com- veloped to enhance the efficacy of surgery is the combina- puted tomography scan of thorax, abdominal ultrasound, tion of chemotherapy, irradiation and immunotherapy or fibroesophagogastroscopy, electrocardiogram. Computed gene therapy which offers the advantage of exposing EC cell tomography scan of abdomen, liver and bone radionuclide population for drugs and immune factors thus obviating can- scan were performed whenever needed. All ECP were diag- cer cell-cycle cytotoxic and host-immunoprotective effects nosed with histologically confirmed EC. All had measurable [3]. Nevertheless, very few studies have demonstrated con- tumor and ECOG performance status 0 or 1. Before any vincing clinical results. We developed optimal treatment treatment each patient was carefully examined by a medical strategies that incorporate bolus chemotherapy, irradiation panel composed of surgeon, chemotherapeutist and radiolo- and immunotherapy after radical, aggressive en-block sur- gist to confirm the stage of disease. All patients signed a gery. written informed consent form approved by the local Institu- tional Review Board. The initial treatment was started with surgery. We per- *Address correspondence to this author at the Department of Surgery, formed two types of procedures: 89 complete esophagecto- Siauliai Public Hospital, Siauliai, Lithuania; mies with lesser and partially major omentum with preserva- E-mail: kshivets003@yahoo.com 1876-5335/08 2008 Bentham Open
  • 2. 2 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 Oleg Kshivets tion of right gastroepiploic vessels and lymph node dissec- Federation. Thymalin and taktivin are preparations from calf tion through separate abdominal and right thoracic incision thymus, which stimulate proliferation of blood T-cell and B- (Ivor-Lewis) and 37 - through left thoracoabdominal incision cell subpopulations and their response [4]. The importance (Garlock). The present analysis was restricted to ECP with must be stressed of using immunotherapy in combination with complete resected tumors with negative surgical resection chemotherapy and radiotherapy, because immune dysfunc- margin and with N1 and celiac lymph node metastases tions of the cell-mediated and humoral response were induced (M1A). Complete surgical resection consisted of esophagec- by tumor, surgical trauma, chemotherapy and radiation [3]. tomy with one-stage intrapleural esophagogastrostomy in 61, Such immune deficiency induced generalization of EC and and with anastomosis on the neck in 65. EC was localized in compromised the longterm therapeutic result. In this sense, lower third of esophagus in 61, middle third - in 48, upper immunotherapy may have shielded the patient from adverse third – in 17. Among these, 40 ECP underwent combined side effects of treatment. Concurrent radiotherapy (60CO; and extensive radical procedures with the resection of dia- ROKUS, Russia) with a total tumor dose 45-50 Gy was started phragm, pericardium, lung, liver left lobe, splenectomy. The 5-7 weeks after surgery. Radiation consisted of single daily extent of lymphadenectomy in the upper abdominal com- fractions of 180-200 cGy 5 days per week for 5 weeks. The partment and lower posterior mediastinum was identical for treatment volume included the ipsilateral hilus, the supraclavi- all surgical approaches and comprised a suprapancreatic cular fossa and the mediastinum from the incisura jugularis to lymphadenectomy, including all lymph nodes along the 8 cm below the carina. The lower mediastinum and upper ab- common hepatic artery, celiac axis, and splenic artery toward domen were included in cases of primary tumors in the lower the splenic hilum. The left gastric artery was always tran- third of esophagus or M1A. The resected tumor bed was in- sected at its origin and remained with the specimen. Also cluded in all patients. Parallel-opposed AP-PA fields were included were all lymph nodes along the proximal two thirds used. All fields were checked using the treatment planning of the lesser gastric curvature and the gastric fundus, left and program COSPO (St. Petersburg, Russia). Doses were speci- right paracardiac nodes, distal paraesophageal nodes, and fied at middepth for parallel-opposed technique or at the inter- nodes in the lower posterior mediastinum up to the tracheal section of central axes for oblique technique. No prophylactic bifurcation. Patients with the right thoracoabdominal ap- cranial irradiation was used. proach had an additional formal extended mediastinal lym- During chemoimmunoradiotherapy antiemetics were ad- phadenectomy comprising all nodes at the tracheal bifurca- ministered. Gastrointestinal side effects, particularly nausea tion along the left and right main stem bronchi, the upper and vomiting, were mild, and chemoimmunoradiotherapy was mediastinal compartment, and along the left recurrent nerve. generally well tolerated. Severe leukopenia, neutropenia, ane- A systematic cervical lymphadenectomy was performed rou- mia and trombocytopenia occurred infrequently. There were tinely for ECP with neck anastomosis. 59 patients underwent no treatment-related deaths. lymph nodal D2-dissection (in terms of gastric cancer sur- gery). Extensive lymph nodal D3-dissection was performed A follow-up examination was generally done every 3 in 67 ECP. Routine two-field lymphadenectomy (in terms of month for the first 2 years, every 6 month after that and yearly EC surgery) was performed in 61, three-field – in 65. All after 5 years, including a physical examination, a complete ECP were postoperatively staged according to the TNMG- blood count, blood chemistry, chest roentgenography. Endo- classification. Histological examination showed adenocarci- scopy and abdominal ultrasound were done every 6-month for noma in 93, squamous cell carcinoma - in 31 and mixed car- the first 3 years and yearly after that. Zero time was the data of cinoma - in 2 patients. The pathological TNM stage was I in surgical procedures. No one was lost during the follow-up 22, IIA – in 24, IIB – in 13, III - in19, IVA – in 48 patients; period and we regarded the outcome as death through personal the pathological T stage was T1 in 25, T2 - in 38, T3 - in 29, knowledge, physician's reports, autopsy or death certificates. T4 - in 34 cases; the pathological N stage was N0 in 55, N1 - Survival time (days) was measured from the date of surgery in 23, M1A - in 48 patients. The tumor differentiation was until death or the most-recent date of follow-up for surviving graded as G1 in 46, G2 - in 39, G3 - in 41 cases. After surgery patients. postoperative chemoimmunoradiotherapy was accomplished Variables selected for 5-year survival and life span study in ECP with ECOG performance status 0 or 1. were the input levels of 45 blood parameters, sex, age, All patients (126 ECP) were divided randomly between TNMG, cell type, and tumor size. Survival curves were esti- the two protocol treatment: 1) surgery and adjuvant chemo- mated by the Kaplan-Meier method. Differences in curves immunoradiotherapy (29 ECP – group A) (age=57±1.6.5 between groups of ECP were evaluated using a log-rank test. years; males - 22, females - 7; tumor size=6.3±3.0 cm); 2) Multivariate proportional hazard Cox regression, structural surgery alone without any adjuvant treatment (97 ECP – equation modeling (SEPATH), Monte Carlo, bootstrap simu- group B) (age=56.8±8.3 years; males - 76, females - 21; tu- lation and neural networks computing were used to determine mor size=5.1±2.3 cm) – the control group any significant dependence [3, 5-10]. Neural networks com- puting, system, biometric and statistical analyses were con- Twenty-nine ECP received adjuvant chemoimmunoradio- ducted using CLASS-MASTER program (Stat Dialog, Inc., therapy which consisted of chemoimmunotherapy (5-6 cycles) Moscow, Russia), SANI program (Stat Dialog, Inc., Moscow, and thoracic radiotherapy (group A). 1 cycle of bolus chemo- Russia), DEDUCTOR program (BaseGroup Labs, Inc., Ri- therapy was initiated 3-5 weeks after complete esophagecto- azan, Russia), STATISTICA and STATISTICA Neural Net- mies and consisted of fluorouracil 500 mg/m2 intravenously works program (Stat Soft, Inc., Tulsa, OK, USA), MATH- for 5 days. Immunotherapy consisted thymalin or taktivin 20 CAD (MathSoft, Inc., Needham, MA, USA). All tests were mg intramuscularly on days 1, 2, 3, 4 and 5. These immuno- considered significant when the resulting P value was less modulators produced by Pharmaceutics of Russian Federation than 0.05. (Novosibirsk) and approved by Ministry of Health of Russian
  • 3. Esophageal Cancer: Optimization of Management The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 3 RESULTS Second, we observed good 5-year survival for ECP with N0 (70%) as compared with ECP with N1-M1A (5-year sur- For the entire sample of 126 patients overall life span vival was 33.1%) after radical procedures (P = 0.00002 by (LS) was 1587.6±1650.3 days (mean ±standard deviation) log-rank test) (Fig. 3). Accordingly, the overall 10-year sur- (95% CI, 1296.6-1878.5; median = 895). General cumulative vival for ECP with N0 reached 60% and was significantly 5 year survival was 50.5%, 10-year survival – 38.3%. 64 ECP superior compared to 19% for ECP with lymph node metasta- (50.8%) were alive till now, 39 ECP (31%) lived more than 5 ses. years (LS = 3544.3±1712.5 days) and 17 ECP - 10 years (LS = 5000.1±1639 days) without any features of EC progressing. All parameters were analyzed in a Cox model. In accor- 55 ECP (43.7%) died because of EC during the first 5 years dance with this Cox model (global 2 = 124.1; Df = 31; P = after surgery (LS = 621.4±366 days). 0.00000), the sixteen variables significantly explained 5-year survival of ECP after complete esophagectomies: stage, status For the 29 ECP in adjuvant chemoimmunoradiotherapy of regional lymph nodes, tumor growth, adjuvant chemoim- arm (group A), overall LS was 1843.2±2083.4 days (95% CI, munoradiotherapy, combined procedures, age, T1-4, histology 1050.7±2635.7; median = 888). For the 97 ECP in the control and blood cell factors (percent of segmented neutrophils and (group B), overall LS was 1511.2±1501.5 days (95% CI, lymphocytes, populations of leucocytes, eosinophils, stick and 1208.5-1813.8; median = 896) (P = 0.023 by log-rank test). segmented neutrophils, lymphocytes and monocytes) (Table 1). The overall cumulative 5-year survival of ECP for group A reached 64.1% and was significantly superior compared to For comparative purposes, clinicomorphological vari- 47.0% for group B (P = 0.023 by log-rank test) (Fig. 1). ables of ECP (n = 94: 39 5-year survivors and 55 losses) were tested by neural networks computing (4-layer percep- It is necessary to pay attention to two very important prog- tron) (Fig. 4). For more exact analysis 32 patients were ex- nostic phenomenons. First, we found 100 % 5-years survival cluded from the sample, who were alive less than 5 years for ECP with early cancer (T1N0) versus 40.5% for the others after complete esophagectomies without relapse. Multilayer ECP after esophagectomies (P = 0.00001 by log-rank test) perceptron was trained by Levenberg-Marquardt method (Fig. 2). Early esophageal cancer was defined, based on the (Fig. 5). Obviously, analyzed data provide significant infor- final histopathologic report of the resection specimen, as tu- mation about EC prediction. High accuracy of classification mor limited to the mucosa or submucosa and not extending – 100% (5-year survivors vs losses) was achieved in ana- into the muscular wall of the esophagus, up to 2 cm in diame- lyzed sample (baseline error = 0.001, are under ROC curve = ter with N0 [10]. Patients with stage T1N0 did not receive 1.0). In other words it remains formally possible that reviled adjuvant chemoimmunoradiotherapy. Correspondingly, the fifteen factors might predate neoplastic generalization: N- overall 10-year survival for ECP with the early cancer was status, gender, EC growth, T-status, histology, type of com- 81% and was significantly better compared to 28% for others bined procedures, G-status, blood residual nitrogen, hemor- patients. rhage time, blood chlorides, adjuvant chemoimmunoradio- Cumulative Proportion Surviving (Kaplan-Meier) Complete Censored Esophageal Cancer Patients after Esophagectomies, n=126 P=0.023 by log-rank test 1.0 Cumulative Proportion Surviving 0.9 Only Surgery=97 0.8 Adjuvant Chemoimmunoradiotherapy=29 = 0.7 0.6 0.5 0.4 0.3 0.2 0 5 10 15 20 25 Years after Esophagectomies Fig. (1). Survival of ECP after esophagectomies in group A (adjuvant chemoimmunoradiotherapy) (n = 29) and B (surgery alone) (n = 97). Sur- vival of ECP in group A was significantly better compared with group B (P = 0.023 by log-rank).
  • 4. 4 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 Oleg Kshivets Cumulative Proportion Surviving (Kaplan-Meier) Complete Censored Esophageal Cancer Patients after Esophagectomies, n=126 P=0.00001 by log-rank test 1.0 Cumulative Proportion Surviving 0.9 0.8 0.7 Invasive Cancer, n=106 0.6 Early Cancer, n=20 0.5 0.4 0.3 0.2 0 5 10 15 20 25 Years after Esophagectomies Fig. (2). Survival of ECP with early cancer (n = 20) was significantly better compared with invasive cancer (n = 106) (P = 0.00001 by log- rank). Cumulative Proportion Surviving (Kaplan-Meier) Complete Censored Esophageal Cancer Patients after Esophagectomies, n=126 P=0.00002 by log-rank test 1.0 Cumulative Proportion Surviving 0.9 N1-M1A=71 0.8 N0=55 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 5 10 15 20 25 Years after Esophagectomies Fig. (3). Survival of ECP with N0 (n = 55) was significantly better compared with N1-M1A metastases (n = 71) (P = 0.00002 by log-rank). therapy, percent of stick neutrophils in blood, tumor size, ECP after radical procedures and all recognized variables number of thrombocytes and monocytes in blood (Table 2). (Tables 3 and 4). Moreover, bootstrap simulation confirmed Genetic algorithm selection and bootstrap simulation con- the paramount value of cell ratio factors (ratio between blood firmed significant dependence between 5-year survival of cell subpopulations and EC cell population).
  • 5. Esophageal Cancer: Optimization of Management The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 5 Table 1. Results of Multivariate Proportional Hazard Cox Regression Modeling in Prediction of ECP Survival After Esophagec- tomies (n = 126) Variables in the Equation B SE Wald df P Segmented Neutrophils (%) 0.225 0.089 6.335 1 0.012 Lymphocytes (%) 0.235 0.087 7.257 1 0.007 Histology 10.701 2 0.005 Histology(1) -0.893 0.273 10.693 1 0.001 Histology(2) -0.697 1.292 0.291 1 0.590 Tumor Growth 5.771 2 0.056 Tumor Growth(1) 2.672 1.114 5.754 1 0.016 Tumor Growth(2) 2.699 1.142 5.584 1 0.018 Adjuvant Chemoimmunoradiotherapy -0.691 0.334 4.267 1 0.039 Combined Operation 15.710 5 0.008 Combined Operation(1) -0.099 0.369 0.072 1 0.788 Combined Operation(2) 0.176 0.638 0.076 1 0.783 Combined Operation(3) 4.833 1.348 12.850 1 0.000 Combined Operation(4) -0.209 0.699 0.090 1 0.765 Combined Operation(5) -0.128 0.588 0.047 1 0.828 Leucocytes (tot) -2.961 0.815 13.212 1 0.000 Eosinophils (tot) 3.220 0.747 18.553 1 0.000 Stick Neutrophils (tot) 3.320 0.789 17.698 1 0.000 Segmented Neutrophils (tot) 3.021 0.829 13.267 1 0.000 Lymphocytes (tot) 2.814 0.810 12.085 1 0.001 Monocytes (tot) 3.458 0.806 18.403 1 0.000 Leucocytes/Cancer Cells 0.104 0.111 0.871 1 0.351 Segmented Neutrophils/Cancer Cells -0.263 0.148 3.144 1 0.076 T 16.809 3 0.001 T(1) -1.796 0.857 4.392 1 0.036 T(2) -2.799 0.721 15.054 1 0.000 T(3) -0.782 0.467 2.809 1 0.094 N 19.295 3 0.000 N(1) 0.108 1.265 0.007 1 0.932 N(2) 2.470 1.324 3.479 1 0.062 N(3) 2.065 1.135 3.312 1 0.069 Stage 18.254 3 0.000 Stage(1) 0.914 0.912 1.004 1 0.316 Stage(2) 2.643 0.655 16.292 1 0.000 Stage(3) 0.882 0.720 1.501 1 0.220 Age 0.033 0.016 4.329 1 0.037 Erythrocytes/Cancer Cells 0.059 0.062 0.927 1 0.336 Table 2. Results of Neural Networks Computing in Prediction of 5-Year Survival of ECP After Esophagectomies (n = 94: 39 5- Year Survivors and 55 Losses) NN Esophageal Cancer Patients After Esophagectomies Factors Rank Sample Error n = 94 Ratio 1 N 1 0.443 436.032 2 Gender 2 0.369 363.171 3 Esophagus Cancer Growth 3 0.294 288.790 4 T 4 0.267 262.995 5 Histology 5 0.252 248.158 6 Combined Procedures 6 0.209 205.320 7 G 7 0.173 170.081 8 Blood Residual Nitrogen 8 0.146 143.457 9 Hemorrhage Time 9 0.145 142.492 10 Blood Chlorides 10 0.122 119.974 11 Adjuvant Chemoimmunoradiotherapy 11 0.104 102.016 12 Stick Neutrophils (%) 12 0.082 80.696 13 Tumor Size 13 0.031 30.558 14 Thrombocytes (abs) 14 0.007 6.965 15 Monocytes (abs) 15 0.004 3.765 Baseline Error 0.001 Area under ROC Curve 1.000 Correct Classification Rate (%) 100.0
  • 6. 6 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 Oleg Kshivets Table 3. Results of Neural Networks Genetic Algorithm Selection in Prediction 5-Year Survival of ECP After Esophagectomies (n = 94: 39 5-Year Survivors and 55 Losses) NN Esophageal Cancer Patients, n = 94 Factors Useful for 5-Year Survival 1 Stick Neutrophils (%) Yes 2 Monocytes (%) Yes 3 Thrombocytes (abs) Yes 4 ESS Yes 5 Hemorrhage Time Yes 6 Blood Residual Nitrogen Yes 7 Blood Protein Yes 8 Blood Chlorides Yes 9 Tumor Size Yes 10 Stick Neutrophils (abs) Yes 11 T Yes 12 N Yes 13 Gender Yes 14 G Yes 15 Histology Yes 16 Esophagus Cancer Growth Yes 17 Adjuvant Chemoimmunoradiotherapy Yes 18 Combined Procedures Yes 19 Stick Neutrophils (tot) Yes 20 Leucocytes/Cancer Cells Yes Table 4. Results of Bootstrap Simulation in Prediction of 5-Year Survival of ECP After Esophagectomies (n = 94: 39 5-Year Sur- vivors and 55 Losses) Esophageal Cancer Patients After Esophagectomies n = 94 Number of Samples = Rank 3333 >P NN Significant Factors Kendall’Tau-A 1 Erythrocytes/Cancer Cells 1 0.286 0.00004 2 Stage 2 -0.281 0.00008 3 Tumor Size 3 -0.274 0.0001 4 Healthy Cells/Cancer Cells 4 0.268 0.0002 5 T 5 -0.268 0.0002 6 Lymphocytes/Cancer Cells 6 0.250 0.0003 7 Leucocytes/Cancer Cells 7 0.235 0.0007 8 Coagulation Time 8 -0.215 0.001 9 N 9 -0.206 0.003 10 Eosinophils/Cancer Cells 10 0.206 0.003 11 Monocytes/Cancer Cells 11 0.204 0.004 12 Blood Residual Nitrogen 12 -0.197 0.007 13 Segmented Neutrophils/Cancer Cells 13 0.191 0.01 14 Thrombocytes/Cancer Cells 14 0.174 0.02 15 Blood Chlorides 15 0.171 0.02 16 Stick Neutrophils/Cancer Cells 16 0.164 0.03 17 Stick Neutrophils (%) 17 0.133 0.05 It is necessary to note very important law: transition of sis” in terms of synergetics (Figs. 6, 7). This also proves the the early cancer into the invasive cancer as well as the cancer first results received earlier in the works [3,10]. Presence of with N0 into the cancer with N1-M1A has the phase charac- two phase transitions is evidently shown on Kohonen self- ter. These results testify by mathematical (Holling-Tanner) organizing neural networks maps (Fig. 8). and imitating modeling of system “EC—patient homeosta-
  • 7. Esophageal Cancer: Optimization of Management The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 7 Fig. (4). Configuration of neural networks: 4-layer perceptron. Training Error Graph (Sum-squared) Esophageal Cancer Patients after Esophagectomies, n=94 Baseline Errors=0.001; Area under ROC Curve=1.00 Neural Netwoks Learning 0.8 Train by Levenberg-Marquardt 0.6 Error 0.4 0.2 0.0 0 200 400 600 800 1000 1200 Epoch Fig. (5). Results of neural networks training in prediction of 5-year survival of ECP (n = 94; 39 5-year survivors and 55 losses): Baseline Errors = 0.001; Area under ROC Curve = 1.00; Correct Classification Rate = 100%.
  • 8. 8 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 Oleg Kshivets Fig. (6). Results of Holling-Tenner modeling of system “EC—Lymphocytes” in prediction of ECP survival after esophagectomies. Fig. (7). Presence of the two phase transitions “early cancer—invasive cancer” and “cancer with N0—cancer with N1-M1A” in terms of synergetics.
  • 9. Esophageal Cancer: Optimization of Management The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 9 Fig. (8). Results of Kohonen self-organizing neural networks computing in prediction of ECP survival after Esophagectomies (n = 94). All of these differences and discrepancies were further limit and leaves much to be desired: the average real 5-year investigated by structural equation modeling (SEPATH) as survival rate of radically operated ECP even after combined well as Monte Carlo simulation. From data, summarized in and extensive procedures is 30-35% and practically is not Fig. (9) (Global 2 = 10691.5; Df = 1533; P = 0.000000; n = improved during the past 30-40 years, as the great majority 94) it was revealed that the seven clusters significantly pre- of patients has already EC with stage III-IVA [3,10,13]. And dicted 5-year survival and life span of ECP after esophagec- finally, modern TNM-classification is based only on cancer tomies: 1) phase transition “early EC—invasive EC” (P = characteristics and does not take into account at all the fea- 0.001); 2) phase transition “EC with N0—EC with N1- tures of extremely complex alive supersystem – the patient’s M1A” (P = 0.000); 3) cell ratio factors (P = 0.001); 4) EC organism. Therefore the prediction of EC is rather inexact characteristics (P = 0.000); 5) biochemical homeostasis (P = and approximate with the big errors. 0.000); 6) hemostasis system (P = 0.043) and 7) combined Central goal of the present research was to estimate the procedures and adjuvant chemoimmunoradiotherapy (P = efficiency of complete esophagectomies with lymphadenec- 0.030) (Fig. 9). It is necessary to pay attention, that both tomies and adjuvant chemoimmunoradiotherapy after radical phase transitions strictly depend on blood cell circuit and cell surgery. The importance must be stressed of using complex ratio factors. system analysis, artificial intelligence (neural networks com- DISCUSSION puting) and statistical methods in combination, because the different approaches yield complementary pieces of prognos- Treatment of ECP is an extremely difficult problem. On tic information. Not stopping in details on these supermod- the one hand, the esophageal cancer surgery demands mas- ern technologies because of the journal limit rules, great ad- terly surgical technique and always will remain the privilege vantage of the artificial intelligence methods is the opportu- of very experienced professionals [11]. Actual surgical re- nity to find out hidden interrelations which cannot be calcu- moval of tumor and lymph node metastases remains basic lated by analytical and system methods. While huge merit of management of this very aggressive cancer giving the real simulation modeling is the identification of dynamics of any chance for cure in spite of extensive research over the last 30 supersystem on the hole in time [3,10]. years in terms of chemotherapy, radiotherapy, immunother- apy and gene therapy [1, 2, 12]. On the other hand, the effec- Although there is no consensus on adjuvant treatment tiveness of complete esophagectomy already reached its after radical procedures the two of the most commonly em-
  • 10. 10 The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 Oleg Kshivets Fig. (9). Significant networks between ECP (n = 94) survival, cancer characteristics, blood cell circuit, cell ratio factors, hemostasis system, biochemic and anthropometric data, phase transition “early cancer—invasive cancer”, phase transition “cancer with N0—cancer with N1- M1A” and treatment protocols (SEPATH network model). ployed strategies are surgery alone and adjuvant (neoadju- juvant treatment is no need. From this it follows the para- vant) chemoradiotherapy with or without immunotherapy. In mount importance of screening and early detection of EC. the last 10-15 years a number of new drugs have been shown Concerning ECP with N0 further investigations will be to have good activity against EC, including mitomycin C, required to determine efficiency, compatibility and tolerance cisplatin, doxetacel, etc. [14-16]. On the other hand new of new drugs and immunomodulators after esophagectomies. immunomodulators, new adoptive immunotherapeutic mo- The results of the present research will offer guidance for the dalities with lymphokineactivated killer cells, tumor- design of future studies. infiltrating lymphocytes and high-dose interleukins have been developed and antitumor effect have been successfully In conclusion, optimal treatment strategies for ECP are: demonstrated in advanced malignancies [17,18]. 1) screening and early detection of EC; 2) availability of very experienced surgeons because of complexity radical Theoretically chemoimmunotherapy is most effective procedures; 3) aggressive en block surgery and adequate when used in patients with a relatively low residual malig- lymphadenectomy for completeness; 4) precise prediction nant cell population (approximately 1 billion cancer cells per and 5) AT for ECP with unfavorable prognosis. patient) in terms of hidden micrometastases [3,10]. This is typical clinical situation for ECP with N1-M1A after com- REFERENCES plete esophagectomies. Present research only confirmed this [1] Graham AJ, Shrive FM, Ghali WA, et al. Defining the optimal axiom. treatment of locally advanced esophageal cancer: a systematic re- view and decision analysis. Ann Thorac Surg 2007; 83(4): 1257- In summary, when adjuvant chemoimmunoradiotherapy 64. is applied to complete esophagectomies for EC with N1- [2] Gebski V, Burmeister B, Smithers BM, Foo K, Zalcberg J, Simes J. M1A, the following benefits should be considered: 1) possi- Australasian Gastro-Intestinal Trials Group. Survival benefits from bility of total elimination of residual hidden micrometasta- neoadjuvant chemoradiotherapy or chemotherapy in oesophageal ses; 2) surgery and chemoradiotherapy can result immuno- carcinoma: a meta-analysis. Lancet Oncol 2007; 8(3): 226-34. [3] Kshivets O. Expert system in diagnosis and prognosis of malignant suppressive state, which can be improved by immunother- neoplasms. Dissertation for Sc.D., Tomsk 1995; p. 486. apy; 3) radical operated ECP with stage IIB-IVA are thought [4] Morozow VG, Chavinson VC. Isolation, refinement and identifica- to be potentially good candidates for adjuvant chemoim- tion of immunomodulated polypeptide from calf and human thy- munoradiotherapy as the majority of these patients would be mus. Biochemistry 1981; 9: 1652-9. [5] Odom-Maryon T. Biostatistical methods in oncology. Cancer man- expected to have EC progressing. agement: A multidisciplinary approach. 1st ed. Huntington, NY: As regards the early EC that it is all quite clear. For these PRP Inc. 1996; pp. 788-802. patients only radical surgery is absolutely sufficient and ad-
  • 11. Esophageal Cancer: Optimization of Management The Open Cardiovascular and Thoracic Surgery Journal, 2008, Volume 1 11 [6] Mirkin BG. A sequential fitting procedure for linear data analysis [13] Stilidi I, Davydov M, Bokhyan V, Suleymanov E. Subtotal models. J Classification 1990; 7: 167-96. esophagectomy with extended 2-field lymph node dissection for [7] Joreskog KG, Sorbom D. Recent development in structural equa- thoracic esophageal cancer. Eur J Cardiothorac Surg 2003; 23(3): tion modeling. J Market Res 1982; 19: 404-16. 415-20. [8] Bostwick DG, Burke HB. Prediction of individual patient outcome [14] Lerut T, Coosemans W, Decker G et al. Diagnosis and therapy in in cancer: comparison of artificial neural networks and Kaplan- advanced cancer of the esophagus and the gastroesophageal junc- Meier methods. Cancer 2001; 91(8): 1643-6. tion. Curr Opin Gastroenterol 2006; 22(4): 437-41. [9] Husmeier D. The Bayesian evidence scheme for regularizing prob- [15] Refaely Y, Krasna MJ. Multimodality therapy for esophageal can- ability-density estimating neural networks. Neural Comput 2000; cer. Surg Clin North Am 2002; 82(4): 729-46. 12(11): 2685-717. [16] Luketich JD, Schauer P, Urso K, et al. Future directions in eso- [10] Kshivets O. Optimization of diagnosis process for patients with phageal cancer. Chest 1998; 113(1 Suppl): 120S-122S. malignant neoplasms. Dissertation for PhD. St. Petersburg 1992; [17] Yano T, Sugio K, Yamazaki K, et al. Postoperative adjuvant adop- p. 354. tive immunotherapy with lymph node-LAK cells and IL-2 for [11] Chernousov AF, Bogopolsky PM, Kurbanov FS. Esophageal sur- pathologic stage I non-small cell lung cancer. Lung Cancer 1999; gery. M.: Moscow Publishers 2000; p. 352. 26: 143-8. [12] D'Journo XB, Doddoli C, Michelet P, et al. Transthoracic esoph- [18] Kshivets O. Immune cell and humoral circuit in prediction of non- agectomy for adenocarcinoma of the oesophagus: standard versus small cell lung cancer patients survival after complete resections. J extended two-field mediastinal lymphadenectomy? Eur J Car- Tumor Marker Oncol 2001; 16(2): 161-74. diothorac Surg 2005; 27(4): 697-704. Received: August 4, 2008 Revised: August 25, 2008 Accepted: August 29, 2008 © Oleg Kshivets; Licensee Bentham Open. This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by- nc/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.