Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

The prognostic influence of body mass index, resting energy expenditure and fasting blood glucose on postoperative patients with esophageal cancer

  • Ning Wu1,
  • Yongjun Zhu1,
  • Dhruba Kadel2,
  • Liewen Pang1,
  • Gang Chen1 and
  • Zhiming Chen1Email author
Contributed equally
BMC GastroenterologyBMC series – open, inclusive and trusted201616:142

https://doi.org/10.1186/s12876-016-0549-6

Received: 30 May 2016

Accepted: 22 October 2016

Published: 21 December 2016

Abstract

Background

Body mass index (BMI), resting energy expenditure (REE) and fasting blood glucose (FBG) are major preoperative assessments of patients’ nutrition and metabolic state. The relations and effects of these indices on esophageal cancer patients’ postoperative short-term and long-term outcomes remain controversial and unclear. We aimed to study the impact of BMI, REE and FBG in esophageal cancer patients undergoing esophagectomy.

Methods

Three hundred and six esophageal cancer patients who underwent esophagectomy were observed retrospectively. Clinical characteristics, postoperative complications and survival analysis were compared among different BMI, REE and FBG groups.

Results

There were significant linear relationships between REE, BMI and FBG indices, patients with low BMI tended to have low REE (p < 0.001) and low FBG (p = 0.003). No significant difference was found in case of mortality and postoperative complications among different groups. Low BMI (X2 = 6.141, p = 0.046), REE (X2 = 6.630, p = 0.010) and FBG (X2 = 5.379, p = 0.020) were related to poor survival. FBG ≤90 mg/dL was independently associated with poor survival (HR = 0.695; 95 % CI 0.489–0.987, p = 0.042). BMI and REE came to be stronger prognostic factors on lymph node-negative patients and proved to be independent prognostic indicators (HR = 0.540; 95 % CI 0.304–0.959, p = 0.035 and HR = 0.457; 95 % CI 0.216–0.967, p = 0.041, respectively).

Conclusions

BMI, REE and FBG are important prognostic factors in patients with esophageal cancer undergoing esophagectomy and preoperative evaluation of these indices help to determine the prognosis in these patients.

Keywords

Esophageal cancer Body mass index Resting energy expenditure Fasting blood glucose Prognosis

Background

Esophageal cancer (EC) is the eighth most common cancer and the sixth leading cause of cancer mortality worldwide [1]. Esophageal adencarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC) are the most frequent histological subtypes. ESCC is the dominant histological subtype in china [2]. The potential prognostic indicators of esophageal cancer include histological variants (histological grading, differentiation, invasion depth and classification of lymph node metastasis) and nutrition or inflammation based prognostic factors (total lymphocyte counts, neutrophil to lymphocyte ratio (NLR), serum albumin and so on). BMI, REE and FBG, which are widely used to assess preoperative nutritional and metabolic status, have also been described to be prognostic predictors in several tumors [3].

Previous studies reported that high BMI was associated with increased risk of EAC while low BMI with ESCC [4]. High BMI in surgical patients is thought to be associated with increased comorbidities and postoperative complications, but the influence of high BMI on survival in patients undergoing esophagectomy is controversial. Hayashi found patients with high BMI showed better overall survival (OS) and disease-free survival (DFS) because of the early clinical diagnosis [5]. In contrast to this, Yoon pointed out that high BMI was independently associated with two-fold worsening of DFS, and OS after surgery for EAC [6]. Blom concluded that BMI had no prognostic value on short-term and long-term outcomes [7]. Compared with the previous studies, the mean BMI in Western populations was higher and had a greater incidence rate of EAC whereas the mean BMI in Chinese population was found to be lower with predominant ESCC. The effect of low BMI on postoperative complications and long-term survival remains unclear. So our study assessed the relationship between BMI and postoperative complications and long-term survival in Chinese population.

Disorder of energy metabolism is a common phenomenon in cancer patients. The energy metabolic status among different cancers may not be the same. Many researchers assessed the resting energy expenditure on cancer patients and no unanimous conclusions have been drawn. In this study, patients’ preoperative REE was an estimated variable, and calculated by the Mifflin-St. Jeor equation [8]. REE is the sum of the metabolic activities of internal body and can reflect patient’s physiques and muscle volumes, and REE per kg total body weight (REE/kg) may reflect the diffusion and metabolic rate of muscle more accurately. So both REE and REE/kg were used to explore its effects on short-term and long-term outcomes on esophageal cancer patients.

Epidemiologic evidence suggests that elevated blood glucose is associated with many forms of cancer [9]. However, opinions toward the association between elevated blood glucose and outcomes are mixed. Elevated blood glucose may promote cancer progression and lead to poor outcomes via pathways mediated high levels of insulin and insulin-like growth factor [10]. On the other hand, some studies proposed that diabetes-related microvessel changes might play a protective role against “neoplastic” cell metastasis in cancer patients and enhance cancer prognosis [11]. For EC, the relationship between the circulating glucose levels and prognosis has never been reported. To examine effects of fasting glucose levels at time of cancer diagnosis on postoperative outcomes is another aim of this study.

So the purpose of the study is to investigate the prognostic value using combined assessment of BMI, REE and FBG in esophageal cancer patients.

Methods

Patients

Patients who underwent esophagectomy and lymph node dissections during Sep 1, 2003 to Dec 31, 2008 were observed. Twenty-three patients who had palliative or R1/R2 resections were excluded. Patients who had histology other than SCC or AC (one lymphoma, one melanoma, one neuroendocrine carcinoma, one stromal tumor and two small cell carcinoma) were excluded. Patients who received neoadjuvant therapy were also excluded. Three hundred and six patients with histologic documentation of AC or SCC were included. All patients provided written consent and this retrospective study was approved by the Institutional Review Board of Huashan Hospital, Fudan University.

Clinical data

Preoperative staging was performed in all patients by means of barium meal test, fibro-gastroscopy, computed tomography of the chest and abdomen and ultrasound of the neck and retroperitoneal lymph nodes. Some patients also received whole body positron emission tomography (PET)-CT scanning. All patients were assessed for physiological ability to undergo esophagectomy. These evaluations included pulmonary function test, cardiac function test and nutritional assessment.

One hundred and eighty-six patients with tumors in middle or lower thoracic esophagus and no evidence of lymph node involvement in the superior mediastinum or neck region received transthoracic esophagectomy via left thoracotomy which also included a two-field lymphadenectomy; 53 patients with tumors in the middle or upper thoracic esophagus and possible lymph node metastasis in the superior mediastinum or neck region received McKeown 3-hole esophagectomy with three-field lymphadenectomy; 67 patients with tumors in the esophagogastric junction received esophagogastrectomy through median laparotomy.

TNM staging was performed according to the AJCC 7th edition guidelines. Patients were followed up every 6 months for the first 3 years and then annually. Survival time was measured as the time from the date of surgery to the date of death or the latest follow-up time. Endoscopy, CT, PET-CT and Radionuclide bone scan were performed if recurrent or metastatic disease was suspected.

Patients’ weight and height were measured at their first hospitalization. BMI was calculated as weight in kilograms divided by height in meters squared.

REE was calculated by Mifflin-St. Jeor equation. The applied technique to calculate BMI is as follows: for males = 10 * weight (kg) + 6.25 * height (cm) - 5 * age (y) + 5; for females = 10 * weight (kg) + 6.25 * height (cm) - 5 * age (y) - 161. Both REE and REE/kg were calculated.

The serum FBG concentration of patients was measured in the morning during the first hospitalization by hexokinase method after fasting for 10 h. Serum albumin was measured by means of the bromocresol purple method using automated equipments, and all patients were screened and excluded from acute and chronic liver disease. The complete blood count test (leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, basophil, platelet counts, and hemoglobin) was carried out by an automated haematology analyser within one week prior to surgery. NLR was calculated as the ratio of neutrophils to lymphocytes in peripheral blood. These reagents and equipments were convenience-validated and standardized in our central clinical laboratory.

The 6-month preoperative weight loss was also measured and patients were divided into three categories: No/Little (loss of 0 to 5 % body weight), Middle (loss of 5 to 10 % body weight) and Large (loss more than 10 % body weight).

During the first few days after surgery, patients were treated with total parenteral nutrition. An initial dose of 5–10 kcal.day−1.kg−1 of enteral nutrition was supplied via a duodenum or jejunum feeding tube from the 2nd or 3rd postoperative day and gradually increased to the full dose of 25–30 kcal.day−1.kg−1. Some patients with low BMI or low serum albumin levels were treated with full dose of enteral nutrition from one week before surgery to the tenth day after surgery.

Statistical analysis

All statistical analysis was performed with SPSS 16.0. Spearman rank order correlation coefficient (Spearman’s rho) for nonparametric data was used. Univariate analysis of survival was performed using Kaplan-Meier method and log-rank test to estimate the prognostic value. Multivariate analysis of survival was performed using Cox-regression model to estimate hazard ratios (HRs) with 95 % confidence intervals (CI) and identify independent prognostic factors. The level of significance was set to p < 0.05.

Results

Patient characteristics

The clinical characteristics and 5-years survival rate are summarized in Table 1. The median follow-up time was 37 months. The overall 1-, 3- and 5-year survival rate was 86.6, 60.8 and 47.1 % respectively.
Table 1

Patient characteristics and univariate analysis

Factors

 

N

5-year survival (%)

p

Age, year

≤65

210

53.3

0.003

>65

96

34.6

 

Sex

Male

235

44.0

0.039

Female

71

57.8

 

Histology

AC

98

49.7

0.590

SCC

208

45.7

 

Surgical type

Transthoracic

186

47.0

0.701

McKeown

53

40.4

 

Transabdominal

67

51.2

 

Differentiation

Well

38

61.9

0.000

Moderately

173

55.1

 

Poorly

95

24.9

 

T stage

Tis/T1

31

82.2

0.000

T2

65

62.1

 

T3

159

43.3

 

T4a

51

17.1

 

N stage

N0

156

67.5

0.000

N1

73

38.6

 

N2

52

14.2

 

N3-4

25

9.5

 

TNM stage

0-I

42

80.5

0.000

II

118

66.5

 

III

146

21.3

 

Weight lost

No/Little

203

46.5

0.555

Middle

50

56.8

 

Large

53

41.7

 

Adjuvant Chemoradiation

Yes

78

41.7

0.187

No

228

48.8

 

Albumin

<35 g/l

36

26.7

0.000

35–40 g/l

132

41.6

 

>40 g/l

138

57.8

 

Lymphocyte

<1.1*109

42

48.7

0.780

1.1–3.2*109

228

47.5

 

>3.2*109

36

42.6

 

NLR

<5

289

47.1

0.787

≥5

17

47.1

 

REE/kg

<23.2

245

50.4

0.024

≥23.2

61

35.2

 

REE

Low

154

40.4

0.010

High

152

55.3

 

FBG

Low

108

35.0

0.020

High

198

51.7

 

BMI

Low

81

36.8

0.046

Normal

186

49.1

 

High

39

62.8

 

CI confidence interval, OR odds ratio

The results were in bold, if the 95 % CI excluded 1 or p<0.05

The BMI distribution was as follows: low (<20 kg/m2), n = 81 (26.5 %); normal (20–25 kg/m2), n = 186 (60.8 %) and high (>25 kg/m2), n = 39 (12.7 %). The median REE was 1387.5 kcal day−1 for male and 1064.0 kcal day−1 for female where we defined the median REE as the cutoff point and stratified patients into low REE group (male < 1387.5 and female <1064.0), n = 154 (50.3 %) and high REE group (male ≥1387.5 and female ≥1064.0), n = 152 (49.7 %). The median REE/kg was 21.49 kcal.day−1.kg−1. Compared with 245 (80.1 %) patients with REE/kg < 23.2, 61 (19.9 %) patients with REE/kg ≥23.2 had significant worse survival, so 23.2 kcal.day−1.kg−1 was set as the cutoff point. We divided the patients into two groups according to serum FBG concentration where 108 patients (35.3 %) with low FBG (≤90 mg/dL) and 198 patients (64.7 %) with high FBG (>90 mg/dL).

Patient characteristics by BMI, REE, REE/kg and FBG

As shown in Table 2. Spearman’s rho indicated that patients with age > 65 years (p < 0.001) and advanced T-stage (p = 0.040) were more likely to fall in the low REE class. Smoking patients were more likely to be associated with low BMI class (p = 0.013), low FBG class (p = 0.039) but high REE/kg class (p = 0.001).
Table 2

Associations among characteristics, BMI, REE, REE/kg and FBG

Factors

BMI, kg/m2

REE, kcal day−1

REE/kg, kcal day−1

FBG, mg/dL

<20

20–25

>25

p

Low

High

p

Low

High

p

≤90

>90

p

81

186

39

154

152

245

61

108

198

Age

  ≤ 65

50

134

26

0.332

87

123

0.000

157

53

0.001

73

137

0.774

  > 65

31

52

13

 

67

29

 

88

8

 

35

61

 

Sex

 Male

65

141

29

0.408

118

117

0.942

174

61

0.000

88

147

0.153

 Female

16

45

10

 

36

35

 

71

0

 

20

51

 

Histology

 SCC

54

132

22

0.561

103

105

0.682

165

43

0.639

81

127

0.052

 AC

27

54

17

 

51

47

 

80

18

 

27

71

 

Differentiation

 Well

7

28

3

0.869

19

19

0.507

31

7

0.552

14

24

0.557

 Moderately

50

98

25

 

91

82

 

140

33

 

63

110

 

 Poorly

24

60

11

 

44

51

 

74

21

 

31

64

 

T stage

 Tis/T1

8

19

4

0.172

12

19

0.040

27

4

0.124

12

19

0.499

 T2

14

42

9

 

30

35

 

54

11

 

22

43

 

 T3

42

93

24

 

81

78

 

126

33

 

50

109

 

 T4a

17

32

2

 

31

20

 

38

13

 

24

27

 

N stage

 N0

36

98

22

0.241

73

83

0.476

131

25

0.262

54

102

0.551

 N1

20

44

9

 

42

31

 

55

18

 

28

45

 

 N2

20

27

5

 

26

26

 

38

14

 

22

30

 

 N3-4

5

17

3

 

13

12

 

21

4

 

4

21

 

Bad habits

 Smoking

51

86

17

 

77

77

0.909

112

42

0.001

63

91

0.039

 Drinking

26

60

11

 

46

51

0.490

74

23

0.261

38

59

0.355

Comorbidities

 Highblood

12

35

12

0.063

27

32

0.437

50

9

0.318

16

43

0.145

 Copd

12

18

5

0.478

24

11

0.022

29

6

0.662

13

22

0.809

 Cardiovascular disease

2

5

0

0.551

6

1

0.058

5

2

0.564

7

0

0.000

 Arrhythmia

7

16

8

0.129

14

17

0.546

27

4

0.303

14

17

0.227

 Diabetes

15

41

18

0.006

35

39

0.551

66

8

0.024

0

74

0.000

Mortality

1

5

1

0.970

6

1

0.058

6

1

0.706

3

4

0.673

Postoperative complications

 Fistula

6

6

3

0.083

12

3

0.182

9

6

0.259

6

9

0.825

 Sepsis

9

6

6

0.208

15

6

0.260

12

9

0.125

9

12

0.673

 Pneumonia

7

11

8

0.615

16

10

0.892

20

6

0.676

8

18

0.233

 Respiratory insufficiency

6

9

6

0.846

14

7

0.692

18

3

0.504

7

14

0.122

 Arrhythmia

14

33

8

0.661

30

25

0.419

45

10

0.720

18

37

0.491

 Cardiac insufficiency

8

38

4

0.068

30

20

0.950

42

8

0.125

12

38

0.136

Albumin

  < 35 g/l

16

19

1

0.001

29

7

0.000

26

10

0.009

20

16

0.000

 35–40 g/

38

78

16

 

68

64

 

99

33

 

55

77

 

  > 40 g/l

27

89

22

 

57

81

 

120

18

 

33

105

 

Lymphocyte

  < 1.1*109

13

26

3

0.092

23

19

0.031

34

8

0.305

15

27

0.401

 1.1–3.2

64

133

32

 

121

108

 

179

50

 

84

145

 

  > 3.2

4

27

4

 

10

25

 

32

3

 

9

26

 

NLR

  < 5

73

179

37

0.135

144

145

0.473

233

56

0.316

101

188

0.603

  ≥ 5

8

7

2

 

10

7

 

12

5

 

7

10

 

Weight lost

 No/Little

45

125

33

0.001

103

100

0.731

171

32

0.006

66

137

0.543

 Middle

14

33

3

 

21

29

 

38

12

 

25

25

 

 Large

22

28

3

 

30

23

 

36

17

 

17

36

 

FBG

 Low

37

64

7

0.003

65

43

0.011

79

29

0.025

   

 High

44

122

32

 

89

109

 

166

32

    

REE

 Low

71

82

1

0.000

   

107

47

0.000

   

 High

10

104

38

    

138

14

    

REE/kg

 Low

32

174

39

0.000

         

 High

49

12

0

          

CI confidence interval, OR odds ratio

The results were in bold, if the 95 % CI excluded 1 or p<0.05

It was interesting to explore the relationship between REE and REE/kg. Both high REE and low REE/kg patients were found to have better survival, which was consistent with the spearman correlation analysis that found patients with high REE tended to have lower REE/kg (p < 0.001).

There were significant linear relations between BMI, REE, and FBG, patients with low BMI tended to have low REE (p < 0.001) and low FBG (p = 0.003). The trend of a linear association between REE and FBG could also be seen (p = 0.011).

There were close relations between REE/kg and weight lost or BMI, patients with high REE/kg have been found to lose more weight (p = 0.006) and have lower BMI (p < 0.001).

Low FBG was more likely to be seen in patients with high REE/kg (p = 0.025) and low albumin (p < 0.001).

Comorbidities, postoperative mortality and postoperative complications

Preoperative comorbidities, mortality and postoperative complications among different groups of BMI, REE, REE/kg and FBG were presented in Table 2. COPD appeared to be more frequent in low REE patients (p = 0.022), and diabetes was more common in high BMI patients (p = 0.006). All the seven patients with cardiovascular disease belonged to low FBG class (p < 0.001). Observing the short-term outcomes, no significant difference was found in postoperative mortality and major postoperative complications among different BMI, REE, REE/kg and FBG groups.

Nutrition or inflammation-based prognostic factors

Univariate analysis of nutrition or inflammation-based prognostic factors found to be serum albumin (p < 0.001), but not Total lymphocyte counts (p = 0.780) or NLR (p = 0.787), which was positively related to survival. The spearman correlation analysis found higher serum albumin levels were observed in high BMI, REE and FBG but in low REE/kg groups.

Univariate, multivariate and subgroup analysis

To evaluate the prognostic factors potentially related to survival, univariate analysis was applied (Table 1) and found no statistical associations of histologic subtype, surgical type, weight loss and adjuvant chemoradiation with OS. The prognostic factors were age, sex, differentiation, T-stage, N-stage, BMI (X2 = 6.141, p = 0.046, Fig. 1), albumin (X2 = 19.761, p < 0.001, Fig. 2), REE (X2 = 6.630, p = 0.010), REE/kg (X2 = 5.063, p = 0.024, Fig. 3) and FBG (X2 = 5.379, p = 0.020, Fig. 4). Patients with low BMI, REE, FBG and high REE/kg had significant worse survival.
Fig. 1

Survival curves of BMI classes

Fig. 2

Survival curves of albumin classes

Fig. 3

Survival curves of REE/kg classes

Fig. 4

Survival curves of FBG classes

Variables significant (age, sex, differentiation, T-stage, N-stage, albumin, BMI, REE, REE/kg and FBG) in Univariate analysis were included in a multivariate analysis (Table 3), which did not show a significant association between BMI (HR = 0.945; 95 % CI 0.660–1.351, p = 0.755), REE (HR = 1.101; 95 % CI 0.718–1.688, p = 0.660) or REE/kg (HR = 1.164; 95 % CI 0.717–1.890, p = 0.540) and OS. Age, differentiation, T-stage, N-stage, albumin (HR = 0.757; 95 % CI 0.589–0.973, p = 0.030) and FBG (HR = 0.695; 95 % CI 0.489–0.987, p = 0.042) were independent prognostic factors.
Table 3

Multivariate prognostic analysis

Factors

All patients

N0 patients

N1-4 patients

P

OR

95 % CI

P

OR

95 % CI

P

OR

95 % CI

Age

0.001

1.844

1.279–2.661

0.286

1.417

0.747–2.689

0.005

1.982

1.228–3.200

Sex

0.229

0.757

0.481–1.191

0.016

0.309

0.119–0.803

0.465

0.818

0.478–1.401

Differentiation

0.004

1.560

1.154–2.107

0.761

0.921

0.542–1.564

0.002

1.885

1.267–2.805

T stage

0.005

1.463

1.125–1.903

0.024

1.611

1.065–2.436

0.018

1.528

1.076–2.168

N stage

0.000

1.610

1.366–1.898

-

-

-

0.056

1.317

0.992–1.749

BMI

0.755

0.945

0.660–1.351

0.035

0.540

0.304–0.959

0.789

0.939

0.594–1.485

REE

0.660

1.101

0.718–1.688

0.041

0.457

0.216–0.967

0.163

1.493

0.851–2.619

REE/kg

0.540

1.164

0.717–1.890

0.060

2.054

0.971–4.343

0.739

0.905

0.503–1.628

FBG

0.042

0.695

0.489–0.987

0.632

0.863

0.474–1.574

0.043

0.627

0.399–0.985

Albumin

0.030

0.757

0.589–0.973

0.863

0.960

0.605–1.524

0.198

0.819

0.604–1.110

CI confidence interval, OR odds ratio

The results were in bold, if the 95 % CI excluded 1 or p<0.05

In order to assess the impact of BMI and REE on different tumor stages, we divided patients into subgroups on the basis of N-stage (N0 vs. N1-4). Patients with higher BMI and REE had significantly better OS in subgroup of N0 (X2 = 15.507 p < 0.001 and X2 = 14.717, p < 0.001, respectively), but no statistical significance in subgroup of N1-4 (X2 = 1.952, P = 0.377 and X2 = 0.386, p = 0.534, respectively). Multivariate analysis of subgroups revealed BMI (HR = 0.540; 95 % CI 0.304–0.959, p = 0.035) and REE (HR = 0.457; 95 % CI 0.216–0.967, p = 0.041) were independent prognostic factors for N0 patients but not for N1-4 patients.

Discussion

Our study identified that FBG level ≤90 mg/dL was independently associated with poor survival and also confirmed that advanced cancer stages remain the most powerful prognostic factors. In addition, we observed that BMI, REE and FBG were significant prognostic factors, but the prognostic value of BMI and REE is not the same between different lymph node metastasis statuses. For metastatic esophageal cancers, the most important prognostic factors were FBG, albumin and cancer staging including differentiation and invasion depth whereas BMI and REE did not significantly affect the OS. However, for non-metastatic esophageal cancers, BMI and REE were important risk factors and proved to be independent prognostic indicators.

Total lymphocyte counts, NLR and serum albumin were recognized as nutrition based or inflammation-based prognostic factors. Among the cancer patients, those with digestive tract malignancies were more likely to suffer from hypoalbuminaemia, which has been attributed to increased catabolism, obstruction of the digestive tract and the systemic inflammatory response [12]. The combined use of albumin and serum C-reactive protein were introduced by the Glasgow prognostic score [13, 14] and the combined use of albumin and lymphocyte counts have been mentioned by the Onodera’s prognostic nutritional index [15]. Hypoalbuminaemia has been shown to correlate with ideal body weight, weight loss, body cell mass and poor prognostic in cancer patients [16]. In our cohort, hypoalbuminaemia associated with weight loss, low REE and low FBG. Patients with serum albumin levels <35 g/l had the 5-year survival rate of 26.7 %, compared to 57.8 % in patients with serum albumin > 40 g/l. Serum albumin was proved to be an independent significant prognostic factor by multivariate analysis even after adjusting for potential confounding factors. To assess the impact of albumin on different tumor stages, we divided patients into subgroups by N-stage (N0 vs. N1-4), and found hypoalbuminaemia as a worse survival factor in both N0 group (X2 = 11.078, p = 0.004) and N1-4 group (X2 = 7.236, p = 0.027). But the multivariate prognostic analysis for subgroups of N0 and N1-4 exhibited that serum albumin as a weaker prognostic value than other potential prognostic factors. It may be explained by the different clinical characteristics of each subgroup which may impact on the prognostic value.

As a particular nonspecific marker of systemic inflammation, an elevated NLR is hypothesized to be associated with poor survival in various solid tumors [17]. But for esophageal cancer, its effect on long-term outcome is still controversial [18, 19]. Most of previous studies did not find the positive predictive values of NLR in patients with esophageal cancer [20, 21]. In this study, there was no significant difference in survival as the NLR cutoff value taken as five because many previous literatures reported optimal cutoff value as five [22]. We also did not find the prognostic value of total lymphocyte counts in patients with esophageal cancer.

A few studies focused on the influence of BMI on postoperative outcomes in patients with EC and had shown contradictory results, varying from no differences in postoperative complications and mortality to a higher incidence of individual complications (such as respiratory complications and anastomotic leak) in high BMI patients [57]. In our study, we found no difference of the frequency of postoperative complications and mortality among different BMI patients. In addition, patients with a high BMI had a higher frequency of diabetes. Smoking patients appeared to have a lower BMI. Although smoking is the preventable cause for esophageal cancer, but it was not observed to be a poor prognostic factor in our finding.

Previous studies had revealed contradictory results regarding the association between BMI and long-term outcome in esophageal cancer patients [47, 2325]. Most of these studies were conducted in western populations that have a high incidence rate of EAC, which occurs more frequently in patients with a high BMI. But the main type in Chinese populations is ESCC (67.9 % in our data). The population is prone to be lean (26.5 % with BMI < 20 and only 12.7 % with BMI > 25 in our data) compared to Western populations. Based on our data, compared with normal patients, we found a significantly worse OS in low BMI patients and a significantly better OS in high BMI patients on a univariate analysis. The prognostic effect of BMI seems to be more valuable on lymph node-negative patients than lymph node-positive patients and proved to be independent prognostic indicators.

High blood glucose level makes patients more susceptible to certain postoperative complications such as surgical site infections, sepsis, myocardial ischemia and so on [26]. But no similar studies were reported concerning esophageal cancer. Based on our date, FBG did not affect the risk of all-cause mortality and postoperative complications. Our study found low FBG level and hypoalbuminaemia are inter-related. In the class of albumin <35 g/l, only 44.4 % (16/36) patients had the FBG > 90 mg/dL, but in the class of albumin >40 g/l, almost 76.1 % (105/138) patients had the FBG > 90 mg/dL, and both hypoalbuminaemia and low FBG level were proved to be worse survival factors. It is easy to measure and monitor FBG or serum albumin in clinical research, so both FBG and serum albumin can easily be used for survival prognosis, and researchers can choose the appropriate method according to their laboratory conditions. To assess the impact of FBG on prognosis in patients with esophageal cancer, both the univariate and multivariate analysis proved that low FBG level (≤90 mg/dL) was independently associated with poor OS. These finding is consistent with previous studies which suggested that hyperglycemia related microvessel changes may have a protective effect against neoplastic cell spread and metastasis in patients with malignant tumors such as non-small cell lung cancer and so on [27, 28].

REE is believed to be elevated in several types of tumors, It has been hypothesized that increased energy expenditure may contribute to the development of malnutrition and weight loss [29]. Our study found patients with a low REE had significantly worse survival compared with high REE (5-year survival rate: 40.4 % vs 55.3 %, p = 0.010). In addition, there was no significant association of REE with postoperative complications and mortality. To our knowledge, it is the first demonstration of the prognostic value of estimated REE in postoperative patients with EC. Our study also observed a significant linear correlation between BMI and REE (p < 0.001), showing that patients with low BMI tended to have low REE. As the estimated REE largely depends on patients’ weight and height, the worse prognosis for low REE patients may reflect that these patients are under-nourished and are likely to have poor prognosis as a result. In addition, patients with low REE tended to be associated with advanced T-stages, so we concluded that the advanced tumor stages may be another reason to explain the low REE patients’ worse survival.

We also explore the relationship between REE and REE/kg. We found the effect of REE on patient survival was opposite to that of REE/kg. Low REE as well as high REE/kg was found to be a potential worse prognostic indicator. The existing hypothesis of REE is, the sum of the metabolic activities of internal organs, muscle, bone, and adipose tissue and can reflect patient’s physiques and muscle volumes, but REE/kg may reflect the diffusion, consumption and metabolic rate of muscle. So patients with high REE/kg have been found to lose more weight, have lower BMI and have a worse survival, this finding is consistent with the hypothesis.

In this research, low FBG was significantly associated with low BMI, albumin and REE, a potential explanation might be proposed. Individuals with esophageal cancer commonly experience metabolic abnormalities. The abnormal state of insulin (hyperinsulinemia or insulin resistance) is one cause, and it promotes cancer growth and progression through its effects on the insulin and insulin-like growth factor pathways [30]. Meanwhile, diabetic microangiopathy render the vascular basal membrane less digestible by tumor cells, which may play a role in impeding neoplastic cell spread and metastasis.

Following are the main limitations in our study. First, this is a retrospective study and the sample size is not large. Second, all-cause mortality is used instead of disease-specific deaths, the latter is difficult to confirm. Third, we only chose R0 patients, so our results may not be suitable for all patients.

Conclusion

In conclusion, it is the first article to explore the prognostic significance of BMI, REE and FBG among patients with EC. FBG level ≤90 mg/dL was independently associated with poor survival for all patients. BMI and REE were important prognostic factors and the value was significant on lymph node negative patients. Therefore it is advisable that the combined assessment of BMI, REE and FBG can be used for a better preoperative assessment and prognostic evaluation in esophageal cancer patients.

Abbreviations

AC: 

Adencarcinoma

BMI: 

Body mass index

CI: 

Confidence interval

CT: 

Computer tomography

DFS: 

Disease-free survival

EAC: 

Esophageal adencarcinoma

EC: 

Esophageal cancer

ESCC: 

Esophageal squamous cell carcinoma

FBG: 

Fasting blood glucose

HR: 

Hazard ratio

NLR: 

Neutrophil to lymphocyte ratio

OS: 

Overall survival

PET: 

Positron emission tomography

REE: 

Resting energy expenditure

SCC: 

Squamous cell carcinoma

Declarations

Acknowledgements

Not applicable.

Funding

None.

Availability of data and materials

Relevant raw data from this study can be readily available to any scientist wishing to use them for non-commercial purposes per request from the authors.

Authors’ contributions

NW, YJZ and ZMC: study design; NW, DK, LWP, GC and ZMC: data acquisition, data analysis, drafting of manuscript; All authors read and approved the final manuscript.

Competing interests

The authors declare that they have neither financial competing interests nor non-financial (political, personal, religious, ideological, academic, intellectual, commercial or any other) competing interests. The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

The study was approved by the Institutional Review Board of Huashan Hospital, Fudan University. Informed consent to participate in study was taken from the patients prior to enrolment.

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Department of Cardio-thoracic Surgery, HuaShan Hospital of Fudan University
(2)
Department of General Surgery, HuaShan Hospital of Fudan University

References

  1. Kamangar F, Dores GM, Anderson WF. Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. J Clin Oncol. 2006;24:2137–50.View ArticlePubMedGoogle Scholar
  2. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61:69–90.View ArticlePubMedGoogle Scholar
  3. Harvie MN, Howell A, Thatcher N, Baildam A, Campbell I. Energy balance in patients with advanced NSCLC, metastatic melanoma and metastatic breast cancer receiving chemotherapy-a longitudinal study. Br J Cancer. 2005;92:673–80.View ArticlePubMedPubMed CentralGoogle Scholar
  4. Smith M, Zhou M, Whitlock G, Yang G, Offer A, Hui G, et al. Esophageal cancer and body mass index: results from a prospective study of 220,000 men in China and a meta-analysis of published studies. Int J Cancer. 2008;122:1604–10.View ArticlePubMedGoogle Scholar
  5. Hayashi Y, Correa AM, Hofstetter WL, Vaporciyan AA, Rice DC, Walsh GL, et al. The influence of high body mass index on the prognosis of patients with esophageal cancer after surgery as primary therapy. Cancer. 2010;116:5619–27.View ArticlePubMedGoogle Scholar
  6. Yoon HH, Lewis MA, Shi Q, Khan M, Cassivi SD, Diasio RB, et al. Prognostic impact of body mass index stratified by smoking status in patients with esophageal adenocarcinoma. J Clin Oncol. 2011;29:4561–7.View ArticlePubMedPubMed CentralGoogle Scholar
  7. Blom RL, Lagarde SM, Klinkenbijl JH, Busch OR, van Berge Henegouwen MI. A high body mass index in esophageal cancer patients does not influence postoperative outcome or long-term survival. Ann Surg Oncol. 2012;19:766–71.View ArticlePubMedGoogle Scholar
  8. Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990;51:241–7.PubMedGoogle Scholar
  9. Rapp K, Schroeder J, Klenk J, Ulmer H, Concin H, Diem G, et al. Fasting blood glucose and cancer risk in a cohort of more than 140,000 adults in Austria. Diabetologia. 2006;49:945–52.View ArticlePubMedGoogle Scholar
  10. LeRoith D, Novosyadlyy R, Gallagher EJ, Lann D, Vijayakumar A, Yakar S. Obesity and type 2 diabetes are associated with an increased risk of developing cancer and a worse prognosis; epidemiological and mechanistic evidence. Exp Clin Endocrinol Diabetes. 2008;116:S4–6.View ArticlePubMedGoogle Scholar
  11. Nerlich AG, Hagedorn HG, Boheim M, Schleicher ED. Patients with diabetes-induced microangiopathy show a reduced frequency of carcinomas. In Vivo. 1998;12:667–70.PubMedGoogle Scholar
  12. Diakos CI, Charles KA, McMillan DC, Clarke SJ. Cancer-related inflammation and treatment effectiveness. Lancet Oncol. 2014;15:493–503.View ArticleGoogle Scholar
  13. Proctor MJ, Morrison DS, Talwar D, Balmer SM, O’Reilly DS, Foulis AK, et al. An inflammation-based prognostic score (mGPS) predicts cancer survival independent of tumour site: a Glasgow Inflammation Outcome Study. Br J Cancer. 2011;104:726–34.View ArticlePubMedPubMed CentralGoogle Scholar
  14. McMillan DC. The systemic inflammation-based Glasgow Prognostic Score: a decade of experience in patients with cancer. Cancer Treat Rev. 2013;39:534–40.View ArticlePubMedGoogle Scholar
  15. Onodera T, Goseki N, Kosaki G. Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients. Nihon Geka Gakkai Zasshi. 1984;85:1001–5.PubMedGoogle Scholar
  16. McMillan DC, Watson WS, O’Gorman P, Preston T, Scott HR, McArdle CS. Albumin concentrations are primarily determined by the body cell mass and the systemic inflammatory response in cancer patients with weight loss. Nutr Cancer. 2001;39:210–3.View ArticlePubMedGoogle Scholar
  17. Templeton AJ, McNamara MG, SŠeruga B, Vera-Badillo FE, Aneja P, Ocaña A, et al. Prognostic role of neutrophil-to-lymphocyte ratio in solid tumors: a systematic review and meta-analysis. J Natl Cancer Inst. 2014;106:dju124.View ArticlePubMedGoogle Scholar
  18. Han LH, Jia YB, Song QX, Wang JB, Wang NN, Cheng YF. The prognostic significance of preoperative lymphocyte-monocyte ratio in patients with resectable esophageal squamous cell carcinoma. Asian Pac J Cancer Prev. 2015;16:2245–50.View ArticlePubMedGoogle Scholar
  19. Xie X, Luo KJ, Hu Y, Wang JY, Chen J. Prognostic value of preoperative platelet-lymphocyte and neutrophil-lymphocyte ratio in patients undergoing surgery for esophageal squamous cell cancer. Dis Esophagus. 2014;19. doi: 10.1111/dote.12296Google Scholar
  20. Rashid F, Waraich N, Bhatti I, Saha S, Khan RN, Ahmed J, et al. A pre-operative elevated neutrophil: lymphocyte ratio does not predict survival from oesophageal cancer resection. World J Surg Oncol. 2010;8:1.View ArticlePubMedPubMed CentralGoogle Scholar
  21. Dutta S, Crumley AB, Fullarton GM, Horgan PG, McMillan DC. Comparison of the prognostic value of tumour- and patient-related factors in patients undergoing potentially curative resection of oesophageal cancer. World J Surg. 2011;35:1861–6.View ArticlePubMedGoogle Scholar
  22. Guthrie GJ, Charles KA, Roxburgh CS, Horgan PG, McMillan DC, Clarke SJ. The systemic inflammation-based neutrophil-lymphocyte ratio: experience in patients with cancer. Crit Rev Oncol Hematol. 2013;88:218–30.View ArticlePubMedGoogle Scholar
  23. Grotenhuis BA, Wijnhoven BP, Hotte GJ, van der Stok EP, Tilanus HW, van Lanschot JJ. Prognostic value of body mass index on short-term and long-term outcome after resection of esophageal cancer. World J Surg. 2010;34:2621–7.View ArticlePubMedPubMed CentralGoogle Scholar
  24. Melis M, Weber JM, McLoughlin JM, Siegel EM, Hoffe S, Shridhar R, et al. An elevated body mass index does not reduce survival after esophagectomy for cancer. Ann Surg Oncol. 2011;18:824–31.View ArticlePubMedGoogle Scholar
  25. Morgan MA, Lewis WG, Hopper AN, Escofet X, Harvard TJ, Brewster AE, et al. Prognostic significance of body mass indices for patients undergoing esophagectomy for cancer. Dis Esophagus. 2007;20:29–35.View ArticlePubMedGoogle Scholar
  26. Rehman HU, Mohammed K. Preoperative management of diabetic patients. Curr Surg. 2003;60:607–11.View ArticlePubMedGoogle Scholar
  27. De Giorgio R, Barbara G, Cecconi A, Corinaldesi R, Mancini AM. Diabetes is associated with longer survival rates in patients with malignant tumors. Arch Intern Med. 2000;160:2217.View ArticlePubMedGoogle Scholar
  28. Bartling B, Simm A, Sohst A, Silber RE, Hofmann HS. Effect of diabetes mellitus on the outcome of patients with resected non-small cell lung carcinoma. Gerontology. 2011;57:497–501.View ArticlePubMedGoogle Scholar
  29. Johnson G, Salle A, Lorimier G, Laccourreye L, Enon B, Blin V, et al. Cancer cachexia: measured and predicted resting energy expenditures for nutritional needs evaluation. Nutrition. 2008;24:443–50.View ArticlePubMedGoogle Scholar
  30. Cannata D, Fierz Y, Vijayakumar A, LeRoith D. Type 2 diabetes and cancer: what is the connection? Mt Sinai J Med. 2010;77:197–213.View ArticlePubMedGoogle Scholar

Copyright

© The Author(s). 2016

Advertisement