Effect of adipose tissue volume on prognosis in patients with non-small cell lung cancer

Clinical Imaging 50 (2018) 308–313

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Effect of adipose tissue volume on prognosis in patients with non-small cell lung cancer Jeong Won Leea, Ho Sung Leeb, Ju Ock Nab, Sang Mi Leec,

T

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a Department of Nuclear Medicine, Catholic Kwandong University College of Medicine, International St. Mary's Hospital, Simgok-ro 100 Gil 25, Seo-gu, Incheon 22711, Republic of Korea b Department of Internal Medicine, Soonchunhyang Univeristy Cheonan Hospital, 23-20, Byeongmyeong-dong, Dongnam-gu, Cheonan, Chungcheongnam-do 31151, Republic of Korea c Department of Nuclear Medicine, Soonchunhyang University Cheonan Hospital, 23-20, Byeongmyeong-dong, Dongnam-gu, Cheonan, Chungcheongnam-do 31151, Republic of Korea

A R T I C LE I N FO

A B S T R A C T

Keywords: Lung cancer F-18 fluorodeoxyglucose Positron emission tomography Adipose tissue Prognosis

Objective: This study evaluated the relationship between adipose tissue volume and survival in patients with non-small cell lung cancer (NSCLC). Methods: We retrospectively included 171 NSCLC patients who underwent staging 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and subsequent curative surgical resection or definite chemoradiotherapy. Maximum standardized uptake value (SUV) of lung cancer normalized by lean body mass (SULmax) and volume and mean SUV of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) were derived from PET/CT images. The relationships of volume and mean SUV of SAT and VAT with survival were assessed. Results: Of the 171 patients, 79 (46.2%) experienced disease progression and 61 patients (35.7%) died during follow-up. SULmax had significant negative correlation with SAT volume (p = 0.003), but not with VAT volume and mean SUV of SAT and VAT (p > 0.05). On multivariate analysis, advanced TNM stage and high SULmax were significantly related with worse progression-free survival (PFS) and high SAT volume was significantly associated with better PFS (p < 0.05). Patient subgroups of high SULmax (> 4.6) and low SAT volume (< 75 cm3) had the highest disease progression rate of 61.7%, while other patient subgroups showed rates between 21.1 and 33.3%. SAT volume was significantly related with overall survival on univariate analysis, but failed to show significance on multivariate analysis. Only TNM stage was an independent prognostic factor for overall survival. Conclusion: SAT volume had significant favorable effect on PFS in patients with NSCLC.

1. Introduction The prevalence of obesity has increased globally over the past several decades and has become a significant public health problem. There is growing evidence that obesity elevates the risk of cancer and progression via metabolic and inflammatory mediators and adipose inflammation [1]. In various kinds of cancers including colon, breast, ovary, and pancreatic cancers, obese patients have a worse prognosis than normal weight individuals [2–4]. In contrast to most kinds of malignancies, recent studies with non-small cell lung cancer (NSCLC) and renal cell carcinoma have documented favorable prognosis in obese patients compared to normal weight/underweight patients, which is referred to as obesity paradox [2,5–8]. The exact mechanisms of the

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obesity paradox in NSCLC remain debatable. Differences in the biological characteristics of tumors and nutritional status between obese and normal weight patients have been speculated as causes of the phenomenon [5,9]. In renal cell carcinoma, tumors in obese patients are reported to display less aggressive features on gene expression analysis [8]. Currently, 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) is a widely used non-invasive imaging modality for staging, assessing treatment response, and predicting prognosis in patients with NSCLC [10–13]. High FDG uptake in NSCLC is related with worse prognosis; however, consistent with the obesity paradox, the prognostic value of tumor FDG uptake is also affected by the body mass index (BMI) [9]. Furthermore, in recent

Corresponding author at: Soonchunhyang Univeristy Cheonan Hospital, 23-20 Byeongmyeong-dong, Dongnam-gu, Cheonan, Chungcheongnam-do 31151, Republic of Korea. E-mail address: [email protected] (S.M. Lee).

https://doi.org/10.1016/j.clinimag.2018.05.006 Received 7 February 2018; Received in revised form 24 April 2018; Accepted 1 May 2018 0899-7071/ © 2018 Elsevier Inc. All rights reserved.

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blood glucose level of < 150 mg/dL before FDG injection. PET/CT scans were performed from the skull base to the proximal femur approximately 60 min after the intravenous injection of 4.07 MBq/kg of FDG. Initially, low-dose CT scan without contrast-enhancement was performed at 100 mA and 120 kVp. Subsequently, PET data were acquired at a 1.5 min for each bed position. PET images were reconstructed with an iterative algorithm using TrueX and time-of-flight reconstruction with attenuation correction (two iterations and 21 subsets).

studies, FDG uptake of adipose tissue, which reflects glucose metabolism in adipose tissue, showed significant relationship with tumor stage, FDG uptake of primary tumor, and clinical outcome [14–16]. Considering the significant association between BMI and NSCLC prognosis, the amount and FDG uptake of adipose tissue might influence prognosis in patients with NSCLC. However, no published study has evaluated the clinical implication of the volume and FDG uptake of adipose tissue in NSCLC. In the present retrospective study, we measured volume and FDG uptake of subcutaneous (SAT) and visceral adipose tissue (VAT) separately and investigated their relationship with clinical outcomes in patients with NSCLC.

2.3. FDG PET/CT image analysis FDG PET/CT images of all patients were retrospectively analyzed using a United States Food and Drug Administration-approved DICOM viewer (OsiriX MD for Mac OS; Pixmeo, Geneva, Switzerland) without knowledge of clinical outcomes. Initially, a spheroid-shaped volume of interest (VOI) was drawn over the primary tumor lesion and the maximum standardized uptake value (SUV) of primary cancer lesion was calculated. SUV normalized by body weight is strongly affected by body weight. Accordingly, we used SUV normalized by lean body mass (SUL), which is more consistent across a population, to representing the FDG uptake of primary cancer lesion [18,19]. Lean body mass for each patient was calculated with using formulas of James [20]. For men, lean body mass was calculated as 1.1 × (body weight) − 128 × ((body weight) / (height))2, and for women, lean body mass was calculated as 1.07 × (body weight) − 148 × ((body weight) / (height))2. Maximum SUL of the primary cancer lesion (SULmax) was calculated by multiplying maximum SUV by the lean body mass divided by body weight. Afterwards, the volume and mean SUV of SAT and VAT were measured (Fig. 1). On three consecutive slices of CT images at the level of the L4 spine, the adipose tissue area was automatically computed using an attenuation range of −50 to −200 Hounsfield units (HU) [21–23]. SAT and VAT volumes were separately measured in cm3. SAT was defined as extra-peritoneal fat tissue between skin and muscle, and VAT was defined as intra-abdominal fat tissue [21]. The areas of SAT and VAT on CT images were exported to corresponding PET images, and the mean SUV of SAT and VAT were measured. For measuring FDG uptake of VAT, areas with FDG uptake of vessels, bowel and urine were manually removed.

2. Materials and methods 2.1. Patients This retrospective study was approved by the Institutional Review Board of our university and followed the principles of the Declaration of Helsinki. Because of the retrospective nature of the study, the requirement to obtained informed consent was waived. The electronic medical records of all patients with NSCLC who underwent a pre-treatment PET/CT scan as a part of their routine staging procedure from March 2012 to May 2015 were retrospectively reviewed. Among these patients, we recruited those with a primary tumor size > 1 cm on staging contrast-enhanced chest CT and who underwent curative surgical resection or definite chemoradiotherapy. Patients who had a distant metastasis on pre-treatment imaging studies or a history of another malignancy were excluded. A total of 171 patients met all inclusion criteria and were enrolled in the present study. They all underwent a pre-treatment work-up including a physical examination, blood tests including serum cholesterol and triglyceride levels, contrast-enhanced chest CT, brain magnetic resonance imaging, and FDG PET/CT. BMI was defined as weight divided by the square of height, and was calculated for each patient using weight and height measured at the time of PET/CT scan. According to the recommendation of the World Health Organization Expert Consultation for Asian populations, normal weight, overweight, and obesity were defined as BMI < 23.0 kg/m2, 23.0–24.9 kg/m2, and ≥25.0 kg/m2, respectively [17]. Based on the results of pre-treatment examinations, T and N stages of the patients were assessed according to the seventh edition of the American Joint Committee on Cancer Staging guidelines. Curative resection or chemoradiotherapy was performed according to the clinical stage and condition of the patient. The median interval between FDG PET/CT and initial treatment was 6 days (range, 1–30 days). In patients who received curative surgical resection, lobectomy, bilobectomy, or pneumonectomy with systematic lymph node dissection was performed and histopathological stage was assessed. In patients treated with chemoradiotherapy, stereotactic body radiotherapy with a total cumulative dose of 45–65 Gy was performed, and chemotherapy was performed concurrently with or sequentially after radiotherapy. The chemotherapy consisted of cisplatin or carboplatin with paclitaxel- or pemetrexed-based doublet therapy. After the initial treatment, followup examinations including blood tests, chest radiography, and contrastenhanced chest CT were performed every 3 months for the first 3 years and every 6 months thereafter. In cases with abnormal findings on follow-up studies, further diagnostic studies and/or histopathological confirmation were performed to confirm disease progression.

2.4. Statistical analyses For continuous variables, the Kolmogorov-Smirnov test was performed to assess the normalcy of the data distribution. Pearson's correlation coefficients were calculated to evaluate the relationship between variables. The prognostic values of the variables for progressionfree survival (PFS) and overall survival (OS) were assessed using a Cox proportional hazards regression test in univariate and multivariate analyses. Only variables that showed significance (p < 0.05) on univariate analysis were included in the multivariate analysis. All continuous variables in the survival analysis were grouped into two categories according to the optimal cut-off values determined by maximally selected chi-square statistics. Survival time was calculated from the time of initial treatment until disease progression (for PFS) or death (for OS) occurred. Disease progression was defined as the detection of newly developed metastatic lesion on follow-up imaging examinations, or a ≥20% increase in the size of a known malignant lesion. For estimation of survival curves of variables, the Kaplan-Meier method was used to calculated cumulative PFS and OS. Disease progression rates between groups were compared using chi-square test. Analyses were performed using R 2.13.0 software (The R Foundation for Statistical Computing, Vienna, Austria) and MedCalc Statistical Software version 17.4.4 (MedCalc Software, Ostend, Belgium). A P-value < 0.05 was considered significant.

2.2. FDG PET/CT scan FDG PET/CT scans were performed using a dedicated PET/CT scanner (Biograph mCT 128 scanner, Siemens Healthcare, Knoxville, TN, USA). All patients were instructed to fast at least 6 h and had a

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Fig. 1. Example of measurement of volume and mean SUV of SAT. On three consecutive transaxial CT images at L4 spine level, the area of SAT, defined as fat tissue between skin and muscle, was automatically computed using an attenuation range between −50 to −200 HU (A). With the area of SAT on three consecutive images, the volume of SAT was computed (B). Afterwards, the area of SAT on CT images were exported to corresponding PET (C) and fused PET/CT (D) images, and mean SUV of the area was measured. Table 1 Patient characteristics (n = 171). Characteristics Age (years) Sex BMI (kg/m2) Diabetes mellitus Histopathology

Serum cholesterol (mg/dL) Serum triglyceride (mg/dL) T stage

N stage TNM stage

SULmax SAT volume (cm3) VAT volume (cm3) Mean SUV of SAT Mean SUV of VAT

Number (%)

Median (range) 69 (38–87)

Men Women

130 (76.0%) 41 (24.0%) 21.8 (16.3–37.2)

Adenocarcinoma Squamous cell carcinoma Others

59 (34.5%) 81 (47.4%) 80 (46.8%) 10 (5.9%) 164 (70–384) 110 (36–429)

T1 T2 T3 T4 N0–1 N2–3 Stage I Stage II Stage III

40 (23.4%) 77 (45.0%) 26 (15.2%) 28 (16.4%) 123 (72.0%) 48 (28.0%) 59 (34.5%) 45 (26.3%) 67 (39.2%)

Fig. 2. Scatter plot showing the relationship between SAT volume and SULmax on FDG PET/CT with logarithmic transformation.

3. Results

7.34 (1.35–20.93) 55.8 (2.4–217.0) 42.4 (2.7–159.4) 0.32 (0.17–0.65) 0.49 (0.21–0.91)

3.1. Characteristics of the patients The characteristics of the 171 enrolled patients are presented in Table 1. Thirty six (21.1%) patients were overweight and another 36 were obese. Supraclavicular and/or mediastinal lymph node metastases were found in 48 patients (28.0%). On FDG PET/CT, mean SUV of VAT was significantly higher than the SAT for all patients (p < 0.001). Of the 171 patients, 88 patients (51.5%) underwent curative surgical resection and 83 patients (48.5%) received chemoradiotherapy. The

BMI, Body mass index; SULmax, maximum standardized uptake value of lung cancer normalized body lean body mass; SAT, subcutaneous adipose tissue; VAT, visceral adipose tissue; SUV, standardized uptake value.

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Table 2 Univariate and multivariate analyses for disease progression-free survival. Variable

Univariate analysis

Multivariate analysis

Hazard ratio P-value (95% CI)

Hazard ratio (95% CI)

Table 3 Disease progression rates according to the combination of SULmax and SAT volume SULmax

Age (≤60 vs. > 60)

1.04 (0.61–1.78) 1.87 (1.09–3.39) 0.38 (0.19–0.76)

Sex (female vs. male) BMI (≤25 vs. > 25) Histopathology Adenocarcinoma Squamous cell carcinoma

1.00 0.85 (0.53–1.37) 1.64 (0.73–3.70) 2.49 (1.58–3.93) 2.19 (1.38–3.48)

Others T stage (T1T2 vs. T3T4) N stage (N0N1 vs. N2N3) TNM stage Stage I Stage II Stage III SULmax (≤4.6 vs. > 4.6) SAT volume (≤75.0 vs. > 75.0) VAT volume (≤45.0 vs. > 45.0) Mean SUV of SAT (≤0.40 vs. > 0.40) Mean SUV of VAT (≤0.37 vs. > 0.37)

1.00 2.83 (1.46–5.46) 4.26 (2.34–7.75) 3.25 (1.71–6.16) 0.46 (0.29–0.82) 1.10 (0.71–1.71) 1.26 (0.74–2.14) 0.65 (0.37–1.13)

P-value

0.891 0.040 0.006

SAT volume 1.29 (0.68–2.44) 0.48 (0.23–1.01)

0.436

> 75.0 cm

0.051

P-value

1.00 2.20 (1.11–4.35) < 0.001 2.90 (1.09–7.70) < 0.001 2.22 (1.11–4.42) 0.009 0.54 (0.30–0.90) 0.680

P-value

7/28 (25.0%) 4/19 (21.1%) 0.756

58/94 (61.7%) 10/30 (33.3%) 0.007

< 0.001 0.359

correlation with SAT volume (p = 0.002, r = −0.257; Fig. 2), but not with VAT volume (p = 0.102) or BMI (p = 0.385). SULmax in both most common pathological types, adenocarcinoma and squamous cell carcinoma, showed significant correlation with SAT volume (p = 0.023, r = −0.221 for squamous cell carcinoma and p = 0.001, r = −0.262 for adenocarcinoma). Mean SUV of SAT had a significant negative correlation with SAT volume (p < 0.001, r = −0.420), serum cholesterol (p = 0.034, r = −0.162), and triglyceride level (p = 0.002, r = −0.237). Likewise, mean SUV of VAT also showed significant negative correlations with VAT volume (p < 0.001, r = −0.578) and serum triglyceride level (p = 0.002, r = −0.237), but not with cholesterol level (p = 0.126).

0.234

0.002

3

> 4.6

SULmax, maximum standardized uptake value of lung cancer normalized body lean body mass; SAT, subcutaneous adipose tissue.

0.508

< 0.001 1.06 (0.57–1.97) < 0.001 1.15 (0.56–2.37)

≤75.0 cm3

≤4.6

0.855 0.704

0.023 0.032 0.024 0.033

3.3. Disease progression-free survival

0.395

The optimal cut-off values determined by maximally selected chisquare analysis for age, SULmax, SAT volume, VAT volume, mean SUV of SAT, and mean SUV of VAT were 60 years, 4.6, 75 cm3, 45 cm3, 0.40, and 0.37, respectively. On univariate analysis, sex, BMI, T stage, N stage, TNM stage, SULmax, and SAT volume showed significant association with PFS (p < 0.050; Table 2). VAT volume and FDG uptake of SAT and VAT were not significant factors (p > 0.050). PFS was significantly improved in patients with high SAT volume (Fig. 3A) as well as those with obesity. On multivariate analysis, TNM stage (p = 0.023 for stage II and p = 0.032 for stage III), SULmax (p = 0.024), and SAT volume (p = 0.033) were independent prognostic factors for PFS, while BMI showed marginal significance (p = 0.051; Table 2). Patients who had high SULmax (> 4.6) and low SAT volume (≤75.0 cm3) showed the highest disease progression rate of 61.7%, whereas other patients subgroups showed disease progression rates between 21.1 and 33.3% (Table 3).

0.126

BMI, Body mass index; SULmax, maximum standardized uptake value of lung cancer normalized body lean body mass; SAT, subcutaneous adipose tissue; VAT, visceral adipose tissue; SUV, standardized uptake value.

median duration of clinical follow-up was 23.9 months (range, 2.0–61.7 months). During follow-up, 79 patients (46.2%) experienced disease progression and 61 patients (35.7%) died. 3.2. Relationship between fat tissue volume and FDG uptake of fat tissue and lung cancer Correlation analysis with logarithmic transformation revealed no significant correlation of SULmax with mean SUV of SAT (p = 0.469) and VAT (p = 0.720). SULmax did display a significant negative

Fig. 3. Cumulative disease progression-free survival (A) and overall survival (B) based on SAT volume. 311

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BMI [27]. Hence, in the present study, we measured the volume of SAT and VAT separately and evaluated their prognostic values to elucidate the protective effect of obesity in NSCLC. A significant negative correlation was found between SAT volume and FDG uptake of tumor, suggesting that tumors in patients with high fat tissue mass might have different biological characteristics from tumors in other patients, which is consistent with previous studies [8,9]. Furthermore, high SAT was independently associated with longer PFS. This significant relationship between SAT volume and survival has been demonstrated in previous studies of renal cell carcinoma, diffuse large B-cell lymphoma, and prostate cancer [28–30]. The mechanism of the protective effect of fat tissue is not precisely known. It has been speculated that high SAT could prevent cancer cachexia and could be related with a lower level of lipolysis of less progressive cancer [24,28,30]. Because patients with high FDG uptake of cancer and low SAT volume have highest risk of disease progression, close follow-up would be needed in those patients. Presently, VAT did not display significant correlation with survival. A previous study with prostate cancer also showed similar discrepancy between VAT and SAT in predicting prognosis [30]. Only a few studies have evaluated the differences between role of SAT and VAT, and further studies are needed to elucidate the mechanism of these differences and interaction between tumor cells and fat tissue [31,32]. However, a previous study showed an even worse survival in lung cancer patients with large waist circumference, which represents visceral fat mass, whereas patients with high BMI still showed improved survival [33]. Therefore, VAT is unlikely to have a favorable effect on the prognosis of NSCLC patients. Contrary to the PFS analysis, SAT volume failed to show a significant association with OS in multivariate analysis. Only TNM stage was an independent prognostic factor for OS. This could reflect the superior prognostic value of TNM stage to other covariates in NSCLC [34]. In addition, co-morbidities in patients with high fat tissue volume might affect non-cancerous death during long-term follow-up [6,30]. In a previous study, obese NSCLC patients initially showed better outcome followed by worse overall survival after 16 months, suggesting a timedependency of the protective effect of obesity [5]. In normal healthy subjects, FDG uptake of SAT and VAT has significant negative relationships with fat tissue volume and biochemical factors including cholesterol, triglyceride, and serum insulin level [23,35]. For patients with malignant diseases, previous studies have demonstrated contradictory results regarding relationship between FDG uptake of adipose tissue and primary tumor and survival [14,16]. A study with pancreatic cancer showed inverse correlation between FDG uptake of SAT and primary tumor and lower FDG uptake of SAT in patients with early stage, suggesting that these results could be indirect evidence that tumor cells inhibit fatty acid uptake and lipoprotein catabolism of adipose tissue to use fatty acids for their growth [14]. In contrast, in a recent study with colon cancer, FDG uptake of VAT showed a significant positive correlation with FDG uptake of primary tumor and patients with high FDG uptake of VAT had worse prognosis than those with low uptake, suggesting that FDG uptake of VAT could reflect inflammatory response of adipose tissue, which is correlation with tumor aggressiveness and clinical outcomes [15,16]. Unlike the results of the previous studies, there was presently no significant correlation of FDG uptake of adipose tissue with FDG uptake of lung cancer and survival. Only negative correlation of FDG uptake of adipose tissue with fat tissue volume and serum triglyceride level was shown similar to the previous studies with normal healthy subjects [23,35]. Further studies are needed to assess the clinical implication of FDG uptake of adipose tissue. There are several limitations in the study. Because of the retrospective nature of the study, selection bias is inevitable. Second, because there is still no established method for measuring volume and FDG uptake of adipose tissue, further studies are needed to devise proper measuring method and to determine proper cut-off value for classifying low and high adipose tissue volume. Third, gene expression

Table 4 Univariate and multivariate analyses for overall survival. Variable

Age (≤60 vs. > 60) Sex (female vs. male) BMI (≤25 vs. > 25) Histopathology Adenocarcinoma Squamous cell carcinoma Others T stage (T1T2 vs. T3T4) N stage (N0N1 vs. N2N3) TNM stage Stage I Stage II Stage III SULmax (≤4.6 vs. > 4.6) SAT volume (≤75.0 vs. > 75.0) VAT volume (≤45.0 vs. > 45.0) Mean SUV of SAT (≤0.40 vs. > 0.40) Mean SUV of VAT (≤0.37 vs. > 0.37)

Univariate analysis

Multivariate analysis

Hazard ratio (95% CI)

P-value

Hazard ratio (95% CI)

P-value

1.81 (0.89–3.67) 1.85 (0.94–3.65) 0.46 (0.21–0.97)

0.102

0.66 (0.30–1.48)

0.319

< 0.001 1.11 (0.58–2.12) 0.001 1.23 (0.54–2.84)

0.752

1.00 1.85 (0.61–3.71) 0.86 (0.31–2.42) 2.67 (1.60–4.44) 2.31 (1.39–3.86) 1.00 6.14 (2.48–15.25) 7.57 (3.17–18.14) 3.12 (1.48–6.58) 0.49 (0.26–0.95) 0.79 (0.47–1.31) 0.71 (0.40–1.29) 0.80 (0.41–1.54)

0.085 0.045

0.491 0.779

1.00 4.61 (1.80–11.77) < 0.001 4.43 (1.29–15.25) 0.003 2.03 (0.87–4.73) 0.035 0.81 (0.44–1.49) 0.362 0.001

0.620

0.001 0.014 0.100 0.492

0.265 0.499

BMI, Body mass index; SULmax, maximum standardized uptake value of lung cancer normalized body lean body mass; SAT, subcutaneous adipose tissue; VAT, visceral adipose tissue; SUV, standardized uptake value.

3.4. Overall survival On univariate analysis, BMI, T stage, N stage, TNM stage, SULmax, and SAT volume were significantly associated with OS (p < 0.050; Table 4). Similar to the survival analysis for PFS, patients with obesity and high SAT volume showed better OS than those with normal weight/ overweight and low SAT volume (Fig. 3B). However, on multivariate analysis, only TNM (p = 0.001 for stage II and p = 0.014 for stage III) was determined to be an independent prognostic factor. 4. Discussion Obesity is associated with adverse health conditions. Thus, it seems paradoxical that BMI is inversely correlated with survival. Yet, during the last decade, numerous studies have documented longer survival for obese patients in various diseases including NSCLC [24]. Obese patients with NSCLC display significantly prolonged PFS and OS compared to normal/underweight patients in both early and advanced stages, for both ever and never smokers [5,25,26]. A recent study with stage I NSCLC patients reported that normal weight patients with high FDG uptake of lung cancer had worse disease-free survival than overweight/ obese patients with high FDG uptake, suggesting a significant interaction between host energy balance status and tumor glucose metabolism [9]. In previous studies regarding obesity paradox in NSCLC, BMI has been consistently used to define obese patients. Nevertheless, BMI cannot represent total body fat amount or abnormal fat accumulation, because mass of SAT and VAT, as well as muscle mass, contributes to 312

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analysis and laboratory analysis to explain the mechanism of protective effect of SAT could not be performed. Lastly, because all patients in the study were East-Asian, further studies are necessary to confirm our results in other ethnic groups.

[14]

5. Conclusions

[15]

NSCLC patients with high SAT volume had a significant beneficial effect in PFS. SAT volume measured on FDG PET/CT was an independent prognostic factor for PFS. VAT volume and FDG uptake of SAT and VAT showed no significant association with survival. The mechanism of the protective effect of SAT and differences of role between SAT and VAT in NSCLC should be further investigated.

[16]

[17] [18]

[19]

Funding [20]

This work was supported in part by the Soonchunhyang University Research Fund and by research fund of Catholic Kwandong University International St. Mary's Hospital.

[21]

[22]

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