Med Oncol (2015) 32:423 DOI 10.1007/s12032-014-0423-8
ORIGINAL PAPER
Effect of metabolic syndrome and its components on recurrence and survival in early-stage non-small cell lung cancer Ying-Sheng Wen • Xue-wen Zhang Rong-qing Qin • Lan-Jun Zhang
•
Received: 26 November 2014 / Accepted: 28 November 2014 / Published online: 5 December 2014 Ó Springer Science+Business Media New York 2014
Abstract Previous studies have indicated that clustering of components of metabolic syndrome (MetS) increases the risk for the development of several cancers such as colon, prostate, and breast cancer. However, the prognostic role of MetS in early-stage non-small cell lung cancer (NSCLC) has not been well defined. We reviewed the clinical data and pre-treatment information of MetS of 545 patients with NSCLC who underwent radical surgery and were pathologically diagnosed as stage IB of NSCLC. The influence of MetS and/or its components on survival outcome was examined using Kaplan–Meier and Cox proportional hazards analyses. The patients with MetS showed no difference in survival outcome regarding overall survival (OS) and disease-free survival (DFS) compared with patients without MetS in univariate, multivariate, and stratification analyses. However, in univariate analysis, a high high density lipoprotein level was a good prediction factor for DFS (median DFS with vs. without MetS: 124.3 vs. 115.1 months P = 0.036). Other single MetS components
showed no association with OS and DFS in early-stage NSCLC. For other clinical characteristic, the age and adjuvant therapy were the independent prognostic factors of OS in univariate and multivariate analyses. MetS and/or its components do not have significant prognostic value in early-stage NSCLC. Keywords Metabolic syndrome Non-small cell lung cancer Prognosis Abbreviations MetS Metabolic syndrome NSCLC Non-small cell lung cancer OS Overall survival DFS Disease-free survival HDL High density lipoprotein TNM Tumor-node-metastasis AJCC American joint committee on cancer ATP III Adult treatment panel III BMI Body mass index CIs Confidence intervals
Ying-Sheng Wen and Xue-wen Zhang contributed equally as first authors to this work. Y.-S. Wen R. Qin L.-J. Zhang Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, No. 561 Dongfeng Road East, Guangzhou 510060, Guangdong, People’s Republic of China Y.-S. Wen R. Qin L.-J. Zhang (&) State Key Laboratory of Oncology in South China, Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, No. 561 Dongfeng Road East, Guangzhou 510060, Guangdong, People’s Republic of China e-mail: [email protected]; [email protected] X. Zhang School of Medicine, University of Glasgow, Glasgow, UK
Introduction Metabolic syndrome (MetS) is a cluster of risk factors for cardiovascular disease and diabetes, including obesity (particularly central adiposity), dysglycemia, elevated blood pressure, elevated triglyceride levels, and low HDL cholesterol levels and high density lipoprotein as well [1, 2]. Interestingly, many epidemiological analyses have shown that MetS and/or its components are associated with the risk of certain common cancers such as liver cancer [3],
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colorectal cancer [4, 5], bladder cancer [6, 7], endometrial cancer [8–10], pancreas cancer [11, 12], breast cancer [13, 14], gastric cancer [15, 16], and lung cancer [17, 18]. The intrinsic mechanism of MetS increasing the risk of cancer may include several processes such as insulin resistance, aromatase activity, adipokine production, angiogenesis, glucose utilization, and oxidative stress/DNA damage, which can work together to increase cancer risk [1, 19]. However, the mechanisms that link MetS and cancer risk are not fully understood for now. A relationship between MetS and some cancers have been demonstrated, and some studies have been reported concerning the influence of MetS and/or its components on survival in cancers. Two studies, in South Korea and the USA, respectively, showed that MetS is a risk factor for cancer-related death in general [20, 21]. A recent study on gastric cancer showed that MetS was a significant and independent predictor of better survival in patients with advanced age or proximal tumors [22]. However, previous studies concerning digestive cancer showed opposite results. In cancers of the digestive system, MetS was positively associated with mortality from cancers in general [23]. Similar to colon cancer, both elevated glucose and diabetes mellitus, and elevated hypertension were associated with worse OS; however, dyslipidemia was associated with improved survival [24]. Additionally, in colorectal cancer, MetS was also a bad prognostic factor [25]. One study concerning gastric cancer uniformly obtained the same result in endocrine tumors [26]. MetS was also associated with poor prognosis in cancers such as breast cancer and prostate cancer [27–29]. Regarding lung cancer, some studies have described whether the body mass index (BMI) can affect survival in lung cancer, but their conclusions were different [30, 31]. In one study, diabetes was confirmed to be an independent predictor of the risk of local recurrence following resection of NSCLC [32]. To date, to our knowledge, few studies have analyzed the prognostic value of Mets in patient with NSCLC. Thus, the aim of our study was to analyze whether MetS and/or its components have any influence on survival in Chinese patients with early-stage NSCLC.
Materials and methods Patient selection We reviewed consecutive non-small cell lung cancer (NSCLC) patients who underwent curative resection and were confirmed to be lymph node negative by postoperative pathological diagnosis at Sun Yat-sen University Cancer Centre in Guangzhou (Guangdong, China) between June 1999 and September 2009. We included patients with
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pathological stage IB NSCLC according to the American Joint Committee on Cancer non-small cell lung cancer tumor-node-metastasis staging system (AJCC version 7). Additionally, excluded patients included those who received any type of neoadjuvant therapy, had no complete medical record, had incomplete information about pretreatment MetS, died within 30 days of resection, had positive margins on pathology, had an inadequate (\14) total number of retrieved lymph nodes, and had a second cancer after surgery and were lost to follow-up. Finally, 545 patients meet the standards. The data of pre-treatment MetS status, clinical information, and follow-up were obtained from a review of medical records and the follow-up department of the hospital. The follow-up date was updated to January 2013. Criteria for the definition of MetS We defined MetS in this study according to the criteria of the National Cholesterol Education Program’s Adult Treatment Panel III (ATP III) (C3 of 5 criteria necessary): (1) impaired glucose regulation or diabetes mellitus with a fasting plasma glucose C110 mg/dL (6.1 mmol/L); (2) abdominal obesity: because no record of abdomen circumference was found among the clinical data, the BMI C25 kg/m2 was applied as a substitute; (3) triglycerides C150 mg/dL (1.7 mmol/L); (4) high density lipoprotein (HDL) B40 mg/dL (1.04 mmol/L) for men, B50 mg/dL (1.3 mmol/L) for women; and (5) hypertension, systolic blood pressure C130/diastolic blood pressure C80 mmHg. The data concerning each component of MetS were collected from clinical records before treatment. Statistical analysis Statistical analysis was performed using SPSS software, version 16.0 (SPSS Inc., Chicago, USA).A two tailed P value \0.05 was considered statistically significant. Differences in baseline clinical parameters between the MetS-positive and MetS-negative groups were evaluated by chi-squared test or Fisher’s exact test, Kruskal–Wallis H test, and Student’s t test. Overall survival (OS) was defined as the time interval from the date of diagnosis to death from lung cancer; diseasefree survival (DFS) was defined as the time from surgery to the earliest occurrence of relapse (locoregional or distant) or death from any cause; for patients who remained alive, the data were censored at the date of the last contact. Kaplan– Meier analysis and the log-rank test were used to compare differences in the survival rate between groups. Multivariate analysis using the Cox regression model was performed to test for the variables that were significant in the univariate analysis. Relative risks are presented with their 95 % confidence intervals (CIs).
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Results The relationship between MetS and baseline clinical characteristics Five hundred forty-five patients met the inclusion criteria and were included in the cohort. There were 100 cases (18.35 %) that met the criteria of MetS, and the remaining 445 cases (81.65 %) were classified to be without MetS. We compared the clinical characteristics between patients with and without MetS and found no significant differences in gender, age, smoking status, pathological type, differentiation, and tumor size. Detailed information and baseline clinical characteristics of the patients are listed in Table 1.
The overall five-year survival rate was approximately 73.4 %. The median OS was not reached. The median DFS was 124.3 months. Two hundred twenty-four (41.1 %) patients underwent disease relapse (locoregional or distant or death), and 168 (30.8 %) cases died at the last follow-up time. There were 40 cases (7.3 %) that were lost during the follow-up. Ninety (16.5 %) patients received adjuvant chemotherapy, and the most commonly used regimen was platinum-based drugs combined with paclitaxel (n = 63; 70.0 %), docetaxel (n = 7; 7.8 %), gemcitabine (n = 2; 2.2 %), pemetrexed (n = 2; 2.2 %), navelbine (n = 12; 13.3 %), and other (n = 4; 4.4 %). Adjuvant chemotherapy was administered for a median of two cycles (range 1–4).
Survival outcome
The impacts of Mets and/or its components on survival outcome
The median follow-up time was 66.47 months. The median age of the patients was 59 years (range 16–84 years).The overall three-year survival rate was approximately 84.8 %.
Using the Kaplan–Meier method and judging from the survival curve, we found no difference in OS and DFS for patients with MetS compared with those without MetS
Table 1 Comparison of baseline clinical characteristics according to metabolic syndrome status
Variable
With MetS
Without MetS
P value
Total
No. of patients
100 (18.35 %)
445 (81.65 %)
Age in years, mean ± SD
60.7 ± 8.9
59.5 ± 10.7
Gender Male
66 (66.00 %)
323 (72.58 %)
389
34 (34.00 %)
122 (27.41 %)
156
Never
48 (48.00 %)
177 (39.78 %)
Former
52 (52.00 %)
268 (60.22 %)
Female
545 0.254 0.188
Smoking status
0.131
Pathological type
225 320 0.676
Squamous
30 (30.00 %)
140 (31.46 %)
170
Adenocarcinoma
59 (59.00 %)
263 (59.10 %)
322
Adenosquamous
9 (9.00 %)
32 (7.19 %)
Other
2 (2.00 %)
10 (2.25 %)
Differentiation
41 12 0.399
Well or moderate
65 (65.00 %)
269 (60.45 %)
334
Poor or undifferentiated
35 (35.00 %)
176 (39.55 %)
211
17 (17.00 %) 83 (83.00 %)
104 (23.37 %) 341 (76.63 %)
Yes
16 (16.00 %)
74 (16.63 %)
No
84 (84.00 %)
371 (83.37 %)
Tumor size (cm) [4 B4
0.166
Adjuvant therapy
121 424 0.878
Visceral pleura invasion
90 455 0.459
Yes
64 (64.00 %)
267 (60.00 %)
No
36 (36.00 %)
178 (40.00 %)
Bronchial invasion
331 214 0.218
Yes
21 (21.00 %)
120 (26.97 %)
141
No
79 (79.00 %)
325 (73.03 %)
401
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Fig. 1 Kaplan–Meier survival analysis of the OS between patients with and without MetS. No difference was found in overall survival in patients with MetS compared with those without MetS (P = 0.505). The median OS of patients with MetS was 124.3 months and that of patients without MetS was not reached
Fig. 2 Kaplan–Meier survival analysis of DFS between patients with and without MetS. No difference was found in disease-free survival in patients with MetS compared with those without MetS (P = 0.474). The median DFS of patients with versus without Mets was 124.3 versus 115.1 months, respectively
(P = 0.505 and 0.474, respectively). The median OS of patients with MetS was 124.3 months and that of patients without MetS was not reached. The median DFS of patients
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with versus without Mets was 124.3 versus 115.1 months, respectively (see Figs. 1, 2). Previous studies have found that MetS and/or its components were associated with superior survival in patients with advanced age or proximal gastric cancer, and some meta-analyses have shown that MetS is a risk factor in male patients with liver cancer and female patients with pancreatic cancer. Thus, whether MetS is a potential prognostic factor in different subgroup of study such as those stratified by gender, age, and tumor size needs to be explored. Next, we performed survival analysis stratified by age, gender, smoking status, pathological type, differentiation, and tumor size, as well as by the presence or absence of adjuvant therapy, visceral pleura invasion, and bronchia invasion. However, in the above stratification analysis, MetS or its components were also found to have no significant influence on OS and DFS in early-stage NSCLC (Table 2). Because patients with MetS were not found to have any different survival outcome in OS and DFS compared with patients without MetS in the univariate and stratification analyses, we continued to compare whether other clinical factors and components of MetS were potential prognostic factors in the univariate and multivariate analyses. Univariate analysis revealed that age (P \ 0.001) and adjuvant therapy (P = 0.020) were prognostic factors for OS. Additionally, age (P = 0.008) was a prognostic factor for DFS. Thus, young patients and those who accepted adjuvant therapy had a better survival outcome. The components of MetS such as BMI, fasting plasma glucose or diabetes, blood pressure, triglyceride level, and HDL level did not influence OS. However, regarding DFS, a high HDL level was a good predicting factor (median DFS with vs. without MetS: 124.3 vs. 115.1 months, respectively; P = 0.036). Other components of MetS showed no statistically significant difference regarding DFS (Table 3). In multivariate analysis, age (P = 0.003) and adjuvant therapy (P = 0.041) were independent predicting factors of OS. Additionally, age (P = 0.039) was an independent predicting factor of DFS, similar to that observed for univariate analysis. Single components meeting the criteria of MetS were not associated with OS and DFS in multivariate analysis (Table 4).
Discussion In the present retrospective analysis of 545 patients with early-stage NSCLC, we were the first study assessing the relationship between MetS and clinical outcomes. In univariate and multivariate analyses, the patients with MetS showed no difference in survival outcome regarding OS and DFS compared with patients without MetS. Many studies
Med Oncol (2015) 32:423 Table 2 Stratification survival analysis between patients with and without MetS
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Hierarchical factor
Median OS (months)
Median DFS (months)
With MetS
Without MetS
P value
With MetS
Without MetS
P value
\60
nr
nr
0.691
nr
nr
0.913
C60
124.3
102.7
0.154
104.2
85.7
0.28
Male
104.8
nr
0.989
104.8
115.1
0.969
Female
124.3
nr
0.236
124.3
nr
0.211
nr
nr
0.576
nr
nr
0.603
124.3
146.1
0.768
104.8
115.1
0.616
Squamous
102.6
nr
0.47
nr
145.6
0.292
Non-squamous
nr
nr
0.785
100.4
86.8
0.912
Age in years
Gender
Smoking status Never Former Pathological type
Differentiation Well or moderate Poor or undifferentiated
104.8
nr
0.523
104.8
145.6
0.997
nr
118.4
0.076
nr
102.7
0.265
Tumor size (cm) [4
nr
nr
0.959
nr
102.7
0.622
B4
124.3
nr
0.498
104.8
145.6
0.631
Yes
nr
nr
0.516
nr
nr
0.655
No
124.3
146.1
0.327
124.3
104.5
0.331
104.8
nr
0.458
nr
104.5
0.307
124.3
nr
0.878
124.3
nr
0.899
Yes
nr
146.1
0.921
104.8
104.5
0.876
No
104.8
nr
0.475
nr
145.6
0.455
Adjuvant therapy
Visceral pleura invasion Yes No Bronchia invasion MetS metabolic syndrome, nr the median OS or DFS was not reached
have shown that, in different subgroups, the prognostic value of MetS is heterogeneous. One study indicated that MetS was associated with superior survival in patients with advanced age or proximal gastric cancer, and some meta-analyses have shown that MetS is a risk factor in male patients with liver cancer and female patients with pancreatic cancer. Additionally, in breast cancer, the result was different in ER-/PRnegative and ER-/PR-positive patients [1, 19, 22, 28]. Thus, we performed stratification analysis in our study. However, no significant difference was found among the various subgroups. For each single component of MetS, we only found that a high HDL level was a good prediction factor of DFS (median DFS with versus without MetS: 124.3 vs. 115.1 months, respectively; P = 0.036). However, its statistical significance disappeared in multivariate analysis, and other components of MetS did not show prognostic value. Many previous studies have found that MetS negatively predicted survival in prostate and breast cancers [27–29]; however, in colon cancer, the conclusion was controversial
[24, 25]. In colorectal cancer, MetS was also an adverse prognostic factor [25, 33]. Conversely, MetS was found to be a positive prognostic factor in patients with advanced age or proximal gastric cancer [22]. Regarding the components of MetS, single components of MetS such as hypertension and elevated blood glucose were associated with worse prognosis in breast cancer and colon cancer, whereas dyslipidemia was associated with improved survival in colon cancer [24, 27]. Unlike the above cancers, in our study, we obtained a negative result regarding the prognostic value of MetS or its components in lung cancer. We assumed that these tumors are more associated with the possible mechanism of MetS increasing the risk of cancer. One hypothesis is that MetS may be a surrogate marker for other cancer risk factors, such as decreased physical activity, consumption of high-calorie dense foods, high dietary fat intake, low fiber intake, and oxidative stress. Additionally, these factors were more associated with digestive and endocrine tumors. One issue of concern in
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Table 3 Results of the univariate analyses to identity factors associated with DFS and OS Variable
Number
Median OS (months)
P value
Median DFS (months)
P value
Age in years (\60/C60)
269/276
nr/104.5
\0.001
nr/86.8
0.008
Gender (male/female)
389/156
146.1/nr
0.471
115.1/124.3
0.446
Smoking status (never/former)
225/320
nr/146.1
0.149
nr/115.1
0.592
Pathological type (squamous/non-squamous)
170/375
nr/nr
0.405
145.6/100.4
0.072
Differentiation (well or moderate/poor or undifferentiated)
334/211
146.1/nr
0.447
145.3/115.1
0.613
Tumor size ([4/B4 cm)
121/424
nr/146.1
0.269
102.7/124.3
0.218
Adjuvant therapy (yes/no) Visceral pleura invasion (yes/no)
90/455 331/214
nr/146.1 nr/nr
0.020 0.939
nr/104.8 104.8/145.6
0.138 0.204
Bronchia invasion (yes/no)
141/401
146.1/nr
0.243
145.6/104.8
0.236
MetS (yes/no)
100/445
124.3/nr
0.505
124.3/145.6
0.474
Number of MetS components
0.744
0.899
0
114
nr
145.6
1
167
nr
115.1
2
164
nr
104.5
3
67
124.3
104.8
4
28
nr
nr
5
5
nr
nr
BMI (yes/no)
102/443
104.8/nr
0.852
104.8/124.3
0.493
Fasting plasma glucose or diabetes (yes/no)
102/443
nr/nr
0.796
nr/124.3
0.678
Blood pressure (yes/no)
297/248
114.4/nr
0.236
102.7/nr
0.359
Triglycerides (yes/no) HDL (yes/no)
108/437 228/317
124.3/nr nr/nr
0.772 0.262
115.1/145.6 124.3/115.1
0.688 0.036
Single component meeting the criteria of MetS
MetS metabolic syndrome, BMI body mass index, HDL high density lipoprotein, nr the median OS or DFS was not reached
Table 4 Results of the multivariate analyses to identify factors associated with DFS and OS
MetS metabolic syndrome, BMI body mass index, HDL high density lipoprotein
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Variable
Overall survival
Disease-free survival
Hazard ratio (95 % CI)
P value
Hazard ratio (95 % CI)
P value
Age in years (\60/C60)
1.663 (1.194–2.317)
0.003
1.343 (1.015–1.779)
0.039
Gender (male/female)
1.128 (0.717–1.773)
0.603
0.910 (0.619–1.337)
0.630
Smoking status (never/former)
1.280 (0.857–1.910)
0.228
1.053 (0.745–1.489)
0.770
Pathological type (squamous/nonsquamous)
0.832 (0.571–1.213)
0.339
0.716 (0.510–1.005)
0.054
Differentiation (well or moderate/poor or undifferentiated)
0.859 (0.616–1.198)
0.369
0.894 (0.670–1.194)
0.449
Tumor size ([4/B4 cm)
1.269 (0.879–1.834)
0.204
1.365 (0.989–1.886)
0.059
Adjuvant therapy (yes/no)
0.588 (0.353–0.979)
0.041
0.791 (0.535–1.168)
0.238
Visceral pleura invasion (yes/no)
0.979 (0.702–1.365)
0.901
1.141 (0.850–1.532)
0.381
Bronchia invasion (yes/no)
0.873 (0.583–1.309)
0.512
1.021 (0.722–1.444)
0.906
MetS (yes/no)
0.665 (0.349–1.265)
0.213
0.955 (0.536–1.700)
0.876
BMI (yes/no)
1.298 (0.810–2.080)
0.278
0.942 (0.615–1.444)
0.785
Fasting plasma glucose or diabetes (yes/ no)
1.080 (0.715–1.633)
0.713
1.099 (0.770–1.570)
0.602
Blood pressure (yes/no)
1.139 (0.809–1.605)
0.455
1.081 (0.809–1.445)
0.599
Triglycerides (yes/no)
1.187 (0.742–1.898)
0.475
1.080 (0.708–1.648)
0.721
HDL (yes/no)
0.900 (0.636–1.274)
0.552
0.777 (0.572–1.057)
0.108
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this study is that the mechanism of MetS promotes the cancer development/growth is not well defined, especially for lung cancers. For now, the plasma glucose, BMI/waist circumference, and triglycerides were confirmed to relate with different complementary processes (angiogenic, cell migration, mitogenic, DNA damage, antiapoptotic) that can work together to promote cancer development/growth. Additional characteristics of the MetS, such as increased HDL and hypertension, are also correlated with cancer growth, but a direct mechanism for these associations has not been confirmed. However, the MetS as a syndrome of aggregating these components will make the mechanism (antagonism or synergy) more complicated and whether the relationship with lung cancer exists needs to be clearly understood. Another hypothesis is the different versions of the definition of MetS in various studies. Thus, whether MetS has prognostic value in early-stage lung cancer needs further investigation. In the present study, Mets was not associated with pathological type and differentiation status of the tumor. This finding differs from that obtained for prostate cancer which showed more aggressive tumors in patients with MetS [29]. Colon cancer also showed a more aggressive tumor type in patients with MetS; however, in breast cancer, the results were inconsistent [34–36]. By contrast, MetS was associated with better tumor cell differentiation in patients with early-stage gastric cancer [22]. Some studies have investigated the association between MetS and/or its components and lung cancer risk. Epidemiological analysis indicated that MetS and/or its components are somewhat associated with a higher risk of lung cancer incidence [17–19]. One study concerning prognosis indicated that obese patients had superior outcomes earlier compared with normal patients but later experienced increased hazard. Another study showed that a high BMI in lung cancer patients after resection has protective effects [30–32]. Additionally, one study confirmed that diabetes was an independent predictor of the risk of local recurrence following resection of NSCLC. Considering the above studies of prognosis focused mostly on a single component of MetS, no study has addressed the impact of MetS on survival in lung cancer. Thus far, our study is the first to investigate the association between MetS and survival outcome in NSCLC. In our study, we addressed the limitations of previous analyses by including uniform staging and selection of early-stage patients with good performance status avoiding cachexy of cancer. Inevitably, there were some limitations in our study. It was a retrospective study, and we did not obtain the relevant therapy concerning MetS and cannot know whether good control of MetS led to the negative result of this study. Thus, more sufficient and dependable evidence are needed to confirm our conclusion. However,
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our study provides clues and directions for future research in this area. In conclusion, in our study, MetS and/or its components do not have significant prognostic value in early-stage NSCLC. Additional investigation is warranted to confirm these findings. For other clinical characteristic, the age and adjuvant therapy were the independent prognostic factors of OS. Acknowledgments This research was supported by Grants from the Ministry of Science and Technology of China (No. 2012AA021503). Conflict of interest
We declare that we have no conflict of interest.
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ORIGINAL PAPER
Effect of metabolic syndrome and its components on recurrence and survival in early-stage non-small cell lung cancer Ying-Sheng Wen • Xue-wen Zhang Rong-qing Qin • Lan-Jun Zhang
•
Received: 26 November 2014 / Accepted: 28 November 2014 / Published online: 5 December 2014 Ó Springer Science+Business Media New York 2014
Abstract Previous studies have indicated that clustering of components of metabolic syndrome (MetS) increases the risk for the development of several cancers such as colon, prostate, and breast cancer. However, the prognostic role of MetS in early-stage non-small cell lung cancer (NSCLC) has not been well defined. We reviewed the clinical data and pre-treatment information of MetS of 545 patients with NSCLC who underwent radical surgery and were pathologically diagnosed as stage IB of NSCLC. The influence of MetS and/or its components on survival outcome was examined using Kaplan–Meier and Cox proportional hazards analyses. The patients with MetS showed no difference in survival outcome regarding overall survival (OS) and disease-free survival (DFS) compared with patients without MetS in univariate, multivariate, and stratification analyses. However, in univariate analysis, a high high density lipoprotein level was a good prediction factor for DFS (median DFS with vs. without MetS: 124.3 vs. 115.1 months P = 0.036). Other single MetS components
showed no association with OS and DFS in early-stage NSCLC. For other clinical characteristic, the age and adjuvant therapy were the independent prognostic factors of OS in univariate and multivariate analyses. MetS and/or its components do not have significant prognostic value in early-stage NSCLC. Keywords Metabolic syndrome Non-small cell lung cancer Prognosis Abbreviations MetS Metabolic syndrome NSCLC Non-small cell lung cancer OS Overall survival DFS Disease-free survival HDL High density lipoprotein TNM Tumor-node-metastasis AJCC American joint committee on cancer ATP III Adult treatment panel III BMI Body mass index CIs Confidence intervals
Ying-Sheng Wen and Xue-wen Zhang contributed equally as first authors to this work. Y.-S. Wen R. Qin L.-J. Zhang Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, No. 561 Dongfeng Road East, Guangzhou 510060, Guangdong, People’s Republic of China Y.-S. Wen R. Qin L.-J. Zhang (&) State Key Laboratory of Oncology in South China, Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, No. 561 Dongfeng Road East, Guangzhou 510060, Guangdong, People’s Republic of China e-mail: [email protected]; [email protected] X. Zhang School of Medicine, University of Glasgow, Glasgow, UK
Introduction Metabolic syndrome (MetS) is a cluster of risk factors for cardiovascular disease and diabetes, including obesity (particularly central adiposity), dysglycemia, elevated blood pressure, elevated triglyceride levels, and low HDL cholesterol levels and high density lipoprotein as well [1, 2]. Interestingly, many epidemiological analyses have shown that MetS and/or its components are associated with the risk of certain common cancers such as liver cancer [3],
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colorectal cancer [4, 5], bladder cancer [6, 7], endometrial cancer [8–10], pancreas cancer [11, 12], breast cancer [13, 14], gastric cancer [15, 16], and lung cancer [17, 18]. The intrinsic mechanism of MetS increasing the risk of cancer may include several processes such as insulin resistance, aromatase activity, adipokine production, angiogenesis, glucose utilization, and oxidative stress/DNA damage, which can work together to increase cancer risk [1, 19]. However, the mechanisms that link MetS and cancer risk are not fully understood for now. A relationship between MetS and some cancers have been demonstrated, and some studies have been reported concerning the influence of MetS and/or its components on survival in cancers. Two studies, in South Korea and the USA, respectively, showed that MetS is a risk factor for cancer-related death in general [20, 21]. A recent study on gastric cancer showed that MetS was a significant and independent predictor of better survival in patients with advanced age or proximal tumors [22]. However, previous studies concerning digestive cancer showed opposite results. In cancers of the digestive system, MetS was positively associated with mortality from cancers in general [23]. Similar to colon cancer, both elevated glucose and diabetes mellitus, and elevated hypertension were associated with worse OS; however, dyslipidemia was associated with improved survival [24]. Additionally, in colorectal cancer, MetS was also a bad prognostic factor [25]. One study concerning gastric cancer uniformly obtained the same result in endocrine tumors [26]. MetS was also associated with poor prognosis in cancers such as breast cancer and prostate cancer [27–29]. Regarding lung cancer, some studies have described whether the body mass index (BMI) can affect survival in lung cancer, but their conclusions were different [30, 31]. In one study, diabetes was confirmed to be an independent predictor of the risk of local recurrence following resection of NSCLC [32]. To date, to our knowledge, few studies have analyzed the prognostic value of Mets in patient with NSCLC. Thus, the aim of our study was to analyze whether MetS and/or its components have any influence on survival in Chinese patients with early-stage NSCLC.
Materials and methods Patient selection We reviewed consecutive non-small cell lung cancer (NSCLC) patients who underwent curative resection and were confirmed to be lymph node negative by postoperative pathological diagnosis at Sun Yat-sen University Cancer Centre in Guangzhou (Guangdong, China) between June 1999 and September 2009. We included patients with
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pathological stage IB NSCLC according to the American Joint Committee on Cancer non-small cell lung cancer tumor-node-metastasis staging system (AJCC version 7). Additionally, excluded patients included those who received any type of neoadjuvant therapy, had no complete medical record, had incomplete information about pretreatment MetS, died within 30 days of resection, had positive margins on pathology, had an inadequate (\14) total number of retrieved lymph nodes, and had a second cancer after surgery and were lost to follow-up. Finally, 545 patients meet the standards. The data of pre-treatment MetS status, clinical information, and follow-up were obtained from a review of medical records and the follow-up department of the hospital. The follow-up date was updated to January 2013. Criteria for the definition of MetS We defined MetS in this study according to the criteria of the National Cholesterol Education Program’s Adult Treatment Panel III (ATP III) (C3 of 5 criteria necessary): (1) impaired glucose regulation or diabetes mellitus with a fasting plasma glucose C110 mg/dL (6.1 mmol/L); (2) abdominal obesity: because no record of abdomen circumference was found among the clinical data, the BMI C25 kg/m2 was applied as a substitute; (3) triglycerides C150 mg/dL (1.7 mmol/L); (4) high density lipoprotein (HDL) B40 mg/dL (1.04 mmol/L) for men, B50 mg/dL (1.3 mmol/L) for women; and (5) hypertension, systolic blood pressure C130/diastolic blood pressure C80 mmHg. The data concerning each component of MetS were collected from clinical records before treatment. Statistical analysis Statistical analysis was performed using SPSS software, version 16.0 (SPSS Inc., Chicago, USA).A two tailed P value \0.05 was considered statistically significant. Differences in baseline clinical parameters between the MetS-positive and MetS-negative groups were evaluated by chi-squared test or Fisher’s exact test, Kruskal–Wallis H test, and Student’s t test. Overall survival (OS) was defined as the time interval from the date of diagnosis to death from lung cancer; diseasefree survival (DFS) was defined as the time from surgery to the earliest occurrence of relapse (locoregional or distant) or death from any cause; for patients who remained alive, the data were censored at the date of the last contact. Kaplan– Meier analysis and the log-rank test were used to compare differences in the survival rate between groups. Multivariate analysis using the Cox regression model was performed to test for the variables that were significant in the univariate analysis. Relative risks are presented with their 95 % confidence intervals (CIs).
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Results The relationship between MetS and baseline clinical characteristics Five hundred forty-five patients met the inclusion criteria and were included in the cohort. There were 100 cases (18.35 %) that met the criteria of MetS, and the remaining 445 cases (81.65 %) were classified to be without MetS. We compared the clinical characteristics between patients with and without MetS and found no significant differences in gender, age, smoking status, pathological type, differentiation, and tumor size. Detailed information and baseline clinical characteristics of the patients are listed in Table 1.
The overall five-year survival rate was approximately 73.4 %. The median OS was not reached. The median DFS was 124.3 months. Two hundred twenty-four (41.1 %) patients underwent disease relapse (locoregional or distant or death), and 168 (30.8 %) cases died at the last follow-up time. There were 40 cases (7.3 %) that were lost during the follow-up. Ninety (16.5 %) patients received adjuvant chemotherapy, and the most commonly used regimen was platinum-based drugs combined with paclitaxel (n = 63; 70.0 %), docetaxel (n = 7; 7.8 %), gemcitabine (n = 2; 2.2 %), pemetrexed (n = 2; 2.2 %), navelbine (n = 12; 13.3 %), and other (n = 4; 4.4 %). Adjuvant chemotherapy was administered for a median of two cycles (range 1–4).
Survival outcome
The impacts of Mets and/or its components on survival outcome
The median follow-up time was 66.47 months. The median age of the patients was 59 years (range 16–84 years).The overall three-year survival rate was approximately 84.8 %.
Using the Kaplan–Meier method and judging from the survival curve, we found no difference in OS and DFS for patients with MetS compared with those without MetS
Table 1 Comparison of baseline clinical characteristics according to metabolic syndrome status
Variable
With MetS
Without MetS
P value
Total
No. of patients
100 (18.35 %)
445 (81.65 %)
Age in years, mean ± SD
60.7 ± 8.9
59.5 ± 10.7
Gender Male
66 (66.00 %)
323 (72.58 %)
389
34 (34.00 %)
122 (27.41 %)
156
Never
48 (48.00 %)
177 (39.78 %)
Former
52 (52.00 %)
268 (60.22 %)
Female
545 0.254 0.188
Smoking status
0.131
Pathological type
225 320 0.676
Squamous
30 (30.00 %)
140 (31.46 %)
170
Adenocarcinoma
59 (59.00 %)
263 (59.10 %)
322
Adenosquamous
9 (9.00 %)
32 (7.19 %)
Other
2 (2.00 %)
10 (2.25 %)
Differentiation
41 12 0.399
Well or moderate
65 (65.00 %)
269 (60.45 %)
334
Poor or undifferentiated
35 (35.00 %)
176 (39.55 %)
211
17 (17.00 %) 83 (83.00 %)
104 (23.37 %) 341 (76.63 %)
Yes
16 (16.00 %)
74 (16.63 %)
No
84 (84.00 %)
371 (83.37 %)
Tumor size (cm) [4 B4
0.166
Adjuvant therapy
121 424 0.878
Visceral pleura invasion
90 455 0.459
Yes
64 (64.00 %)
267 (60.00 %)
No
36 (36.00 %)
178 (40.00 %)
Bronchial invasion
331 214 0.218
Yes
21 (21.00 %)
120 (26.97 %)
141
No
79 (79.00 %)
325 (73.03 %)
401
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Fig. 1 Kaplan–Meier survival analysis of the OS between patients with and without MetS. No difference was found in overall survival in patients with MetS compared with those without MetS (P = 0.505). The median OS of patients with MetS was 124.3 months and that of patients without MetS was not reached
Fig. 2 Kaplan–Meier survival analysis of DFS between patients with and without MetS. No difference was found in disease-free survival in patients with MetS compared with those without MetS (P = 0.474). The median DFS of patients with versus without Mets was 124.3 versus 115.1 months, respectively
(P = 0.505 and 0.474, respectively). The median OS of patients with MetS was 124.3 months and that of patients without MetS was not reached. The median DFS of patients
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with versus without Mets was 124.3 versus 115.1 months, respectively (see Figs. 1, 2). Previous studies have found that MetS and/or its components were associated with superior survival in patients with advanced age or proximal gastric cancer, and some meta-analyses have shown that MetS is a risk factor in male patients with liver cancer and female patients with pancreatic cancer. Thus, whether MetS is a potential prognostic factor in different subgroup of study such as those stratified by gender, age, and tumor size needs to be explored. Next, we performed survival analysis stratified by age, gender, smoking status, pathological type, differentiation, and tumor size, as well as by the presence or absence of adjuvant therapy, visceral pleura invasion, and bronchia invasion. However, in the above stratification analysis, MetS or its components were also found to have no significant influence on OS and DFS in early-stage NSCLC (Table 2). Because patients with MetS were not found to have any different survival outcome in OS and DFS compared with patients without MetS in the univariate and stratification analyses, we continued to compare whether other clinical factors and components of MetS were potential prognostic factors in the univariate and multivariate analyses. Univariate analysis revealed that age (P \ 0.001) and adjuvant therapy (P = 0.020) were prognostic factors for OS. Additionally, age (P = 0.008) was a prognostic factor for DFS. Thus, young patients and those who accepted adjuvant therapy had a better survival outcome. The components of MetS such as BMI, fasting plasma glucose or diabetes, blood pressure, triglyceride level, and HDL level did not influence OS. However, regarding DFS, a high HDL level was a good predicting factor (median DFS with vs. without MetS: 124.3 vs. 115.1 months, respectively; P = 0.036). Other components of MetS showed no statistically significant difference regarding DFS (Table 3). In multivariate analysis, age (P = 0.003) and adjuvant therapy (P = 0.041) were independent predicting factors of OS. Additionally, age (P = 0.039) was an independent predicting factor of DFS, similar to that observed for univariate analysis. Single components meeting the criteria of MetS were not associated with OS and DFS in multivariate analysis (Table 4).
Discussion In the present retrospective analysis of 545 patients with early-stage NSCLC, we were the first study assessing the relationship between MetS and clinical outcomes. In univariate and multivariate analyses, the patients with MetS showed no difference in survival outcome regarding OS and DFS compared with patients without MetS. Many studies
Med Oncol (2015) 32:423 Table 2 Stratification survival analysis between patients with and without MetS
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Hierarchical factor
Median OS (months)
Median DFS (months)
With MetS
Without MetS
P value
With MetS
Without MetS
P value
\60
nr
nr
0.691
nr
nr
0.913
C60
124.3
102.7
0.154
104.2
85.7
0.28
Male
104.8
nr
0.989
104.8
115.1
0.969
Female
124.3
nr
0.236
124.3
nr
0.211
nr
nr
0.576
nr
nr
0.603
124.3
146.1
0.768
104.8
115.1
0.616
Squamous
102.6
nr
0.47
nr
145.6
0.292
Non-squamous
nr
nr
0.785
100.4
86.8
0.912
Age in years
Gender
Smoking status Never Former Pathological type
Differentiation Well or moderate Poor or undifferentiated
104.8
nr
0.523
104.8
145.6
0.997
nr
118.4
0.076
nr
102.7
0.265
Tumor size (cm) [4
nr
nr
0.959
nr
102.7
0.622
B4
124.3
nr
0.498
104.8
145.6
0.631
Yes
nr
nr
0.516
nr
nr
0.655
No
124.3
146.1
0.327
124.3
104.5
0.331
104.8
nr
0.458
nr
104.5
0.307
124.3
nr
0.878
124.3
nr
0.899
Yes
nr
146.1
0.921
104.8
104.5
0.876
No
104.8
nr
0.475
nr
145.6
0.455
Adjuvant therapy
Visceral pleura invasion Yes No Bronchia invasion MetS metabolic syndrome, nr the median OS or DFS was not reached
have shown that, in different subgroups, the prognostic value of MetS is heterogeneous. One study indicated that MetS was associated with superior survival in patients with advanced age or proximal gastric cancer, and some meta-analyses have shown that MetS is a risk factor in male patients with liver cancer and female patients with pancreatic cancer. Additionally, in breast cancer, the result was different in ER-/PRnegative and ER-/PR-positive patients [1, 19, 22, 28]. Thus, we performed stratification analysis in our study. However, no significant difference was found among the various subgroups. For each single component of MetS, we only found that a high HDL level was a good prediction factor of DFS (median DFS with versus without MetS: 124.3 vs. 115.1 months, respectively; P = 0.036). However, its statistical significance disappeared in multivariate analysis, and other components of MetS did not show prognostic value. Many previous studies have found that MetS negatively predicted survival in prostate and breast cancers [27–29]; however, in colon cancer, the conclusion was controversial
[24, 25]. In colorectal cancer, MetS was also an adverse prognostic factor [25, 33]. Conversely, MetS was found to be a positive prognostic factor in patients with advanced age or proximal gastric cancer [22]. Regarding the components of MetS, single components of MetS such as hypertension and elevated blood glucose were associated with worse prognosis in breast cancer and colon cancer, whereas dyslipidemia was associated with improved survival in colon cancer [24, 27]. Unlike the above cancers, in our study, we obtained a negative result regarding the prognostic value of MetS or its components in lung cancer. We assumed that these tumors are more associated with the possible mechanism of MetS increasing the risk of cancer. One hypothesis is that MetS may be a surrogate marker for other cancer risk factors, such as decreased physical activity, consumption of high-calorie dense foods, high dietary fat intake, low fiber intake, and oxidative stress. Additionally, these factors were more associated with digestive and endocrine tumors. One issue of concern in
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Med Oncol (2015) 32:423
Table 3 Results of the univariate analyses to identity factors associated with DFS and OS Variable
Number
Median OS (months)
P value
Median DFS (months)
P value
Age in years (\60/C60)
269/276
nr/104.5
\0.001
nr/86.8
0.008
Gender (male/female)
389/156
146.1/nr
0.471
115.1/124.3
0.446
Smoking status (never/former)
225/320
nr/146.1
0.149
nr/115.1
0.592
Pathological type (squamous/non-squamous)
170/375
nr/nr
0.405
145.6/100.4
0.072
Differentiation (well or moderate/poor or undifferentiated)
334/211
146.1/nr
0.447
145.3/115.1
0.613
Tumor size ([4/B4 cm)
121/424
nr/146.1
0.269
102.7/124.3
0.218
Adjuvant therapy (yes/no) Visceral pleura invasion (yes/no)
90/455 331/214
nr/146.1 nr/nr
0.020 0.939
nr/104.8 104.8/145.6
0.138 0.204
Bronchia invasion (yes/no)
141/401
146.1/nr
0.243
145.6/104.8
0.236
MetS (yes/no)
100/445
124.3/nr
0.505
124.3/145.6
0.474
Number of MetS components
0.744
0.899
0
114
nr
145.6
1
167
nr
115.1
2
164
nr
104.5
3
67
124.3
104.8
4
28
nr
nr
5
5
nr
nr
BMI (yes/no)
102/443
104.8/nr
0.852
104.8/124.3
0.493
Fasting plasma glucose or diabetes (yes/no)
102/443
nr/nr
0.796
nr/124.3
0.678
Blood pressure (yes/no)
297/248
114.4/nr
0.236
102.7/nr
0.359
Triglycerides (yes/no) HDL (yes/no)
108/437 228/317
124.3/nr nr/nr
0.772 0.262
115.1/145.6 124.3/115.1
0.688 0.036
Single component meeting the criteria of MetS
MetS metabolic syndrome, BMI body mass index, HDL high density lipoprotein, nr the median OS or DFS was not reached
Table 4 Results of the multivariate analyses to identify factors associated with DFS and OS
MetS metabolic syndrome, BMI body mass index, HDL high density lipoprotein
123
Variable
Overall survival
Disease-free survival
Hazard ratio (95 % CI)
P value
Hazard ratio (95 % CI)
P value
Age in years (\60/C60)
1.663 (1.194–2.317)
0.003
1.343 (1.015–1.779)
0.039
Gender (male/female)
1.128 (0.717–1.773)
0.603
0.910 (0.619–1.337)
0.630
Smoking status (never/former)
1.280 (0.857–1.910)
0.228
1.053 (0.745–1.489)
0.770
Pathological type (squamous/nonsquamous)
0.832 (0.571–1.213)
0.339
0.716 (0.510–1.005)
0.054
Differentiation (well or moderate/poor or undifferentiated)
0.859 (0.616–1.198)
0.369
0.894 (0.670–1.194)
0.449
Tumor size ([4/B4 cm)
1.269 (0.879–1.834)
0.204
1.365 (0.989–1.886)
0.059
Adjuvant therapy (yes/no)
0.588 (0.353–0.979)
0.041
0.791 (0.535–1.168)
0.238
Visceral pleura invasion (yes/no)
0.979 (0.702–1.365)
0.901
1.141 (0.850–1.532)
0.381
Bronchia invasion (yes/no)
0.873 (0.583–1.309)
0.512
1.021 (0.722–1.444)
0.906
MetS (yes/no)
0.665 (0.349–1.265)
0.213
0.955 (0.536–1.700)
0.876
BMI (yes/no)
1.298 (0.810–2.080)
0.278
0.942 (0.615–1.444)
0.785
Fasting plasma glucose or diabetes (yes/ no)
1.080 (0.715–1.633)
0.713
1.099 (0.770–1.570)
0.602
Blood pressure (yes/no)
1.139 (0.809–1.605)
0.455
1.081 (0.809–1.445)
0.599
Triglycerides (yes/no)
1.187 (0.742–1.898)
0.475
1.080 (0.708–1.648)
0.721
HDL (yes/no)
0.900 (0.636–1.274)
0.552
0.777 (0.572–1.057)
0.108
Med Oncol (2015) 32:423
this study is that the mechanism of MetS promotes the cancer development/growth is not well defined, especially for lung cancers. For now, the plasma glucose, BMI/waist circumference, and triglycerides were confirmed to relate with different complementary processes (angiogenic, cell migration, mitogenic, DNA damage, antiapoptotic) that can work together to promote cancer development/growth. Additional characteristics of the MetS, such as increased HDL and hypertension, are also correlated with cancer growth, but a direct mechanism for these associations has not been confirmed. However, the MetS as a syndrome of aggregating these components will make the mechanism (antagonism or synergy) more complicated and whether the relationship with lung cancer exists needs to be clearly understood. Another hypothesis is the different versions of the definition of MetS in various studies. Thus, whether MetS has prognostic value in early-stage lung cancer needs further investigation. In the present study, Mets was not associated with pathological type and differentiation status of the tumor. This finding differs from that obtained for prostate cancer which showed more aggressive tumors in patients with MetS [29]. Colon cancer also showed a more aggressive tumor type in patients with MetS; however, in breast cancer, the results were inconsistent [34–36]. By contrast, MetS was associated with better tumor cell differentiation in patients with early-stage gastric cancer [22]. Some studies have investigated the association between MetS and/or its components and lung cancer risk. Epidemiological analysis indicated that MetS and/or its components are somewhat associated with a higher risk of lung cancer incidence [17–19]. One study concerning prognosis indicated that obese patients had superior outcomes earlier compared with normal patients but later experienced increased hazard. Another study showed that a high BMI in lung cancer patients after resection has protective effects [30–32]. Additionally, one study confirmed that diabetes was an independent predictor of the risk of local recurrence following resection of NSCLC. Considering the above studies of prognosis focused mostly on a single component of MetS, no study has addressed the impact of MetS on survival in lung cancer. Thus far, our study is the first to investigate the association between MetS and survival outcome in NSCLC. In our study, we addressed the limitations of previous analyses by including uniform staging and selection of early-stage patients with good performance status avoiding cachexy of cancer. Inevitably, there were some limitations in our study. It was a retrospective study, and we did not obtain the relevant therapy concerning MetS and cannot know whether good control of MetS led to the negative result of this study. Thus, more sufficient and dependable evidence are needed to confirm our conclusion. However,
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our study provides clues and directions for future research in this area. In conclusion, in our study, MetS and/or its components do not have significant prognostic value in early-stage NSCLC. Additional investigation is warranted to confirm these findings. For other clinical characteristic, the age and adjuvant therapy were the independent prognostic factors of OS. Acknowledgments This research was supported by Grants from the Ministry of Science and Technology of China (No. 2012AA021503). Conflict of interest
We declare that we have no conflict of interest.
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