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Body mass index as a prognostic factor in patients with extranodal natural killer/T-cell lymphoma, nasal type

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Oncotarget. 2016; 7:78159-78167. https://doi.org/10.18632/oncotarget.11373

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Jie Liu, Yao-Tiao Deng, Li Zhang, Na Li, Ming Jiang, Li-Qun Zou and Yu Jiang _

Abstract

Jie Liu1, Yao-Tiao Deng1, Li Zhang1, Na Li1, Ming Jiang1, Li-Qun Zou1 and Yu Jiang1

1 Department of Medical Oncology, Cancer Center, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China

Correspondence to:

Yu Jiang , email:

Li-qun Zou , email:

Keywords: extranodal natural killer/T-cell lymphoma, body mass index, prognosis, radiotherapy, chemotherapy

Received: May 10, 2016 Accepted: August 13, 2016 Published: August 18, 2016

Abstract

Epidemiological evidence has shown that body mass index (BMI) can predict survival in several types of cancer. However, the role of BMI in extranodal natural killer/T-cell lymphoma, nasal type (ENKTL) is still unclear. This retrospective single-center study included 251 newly diagnosed patients to determine the prognostic value of BMI in ENKTL. Of these, 203 patients received chemoradiotherapy, 37 received chemotherapy alone, 8 received radiotherapy alone, and 3 received only best supportive care. With a median follow-up of 28 months, the estimated 3-year overall survival (OS) and progression-free survival (PFS) rates were 64.4% and 60.9%, respectively. The receiver-operating characteristic curve showed that 20.8 kg/m2 was the optimal cut-off of BMI to predict survival. BMI < 20.8 kg/m2 was associated with lower 3-year OS (52.8% vs. 72.9%, P = 0.001) and PFS (48.8% vs. 69.8%, P < 0.001) rates. Multivariate analysis indicated that BMI, performance status, lactate dehydrogenase (LDH) levels, chemotherapy, and radiotherapy were independent prognostic factors for OS. Furthermore, BMI, number of extranodal sites, performance status, LDH, and radiotherapy were predictive of PFS. These results suggest that BMI at the cut-off of 20.8 kg/m2 might be a prognostic factor in patients with ENKTL.


Introduction

Extranodal natural killer/T-cell lymphoma, nasal type (ENKTL) is a rare subset of non-Hodgkin’s lymphoma (NHL). It is more frequent in Asia and Latin America, accounting for 7%-10% of all NHLs in these areas, but only 1% in western countries [1]. ENKTL can be dichotomized as nasal disease primarily localized to the upper aerodigestive tract (UAT), or extranasal disease occurring in non-UAT sites (e.g., skin, intestine, testicles) [2]. According to the data from the International Peripheral T-Cell Lymphoma Project, the median overall survival (OS) was only 0.36 and 1.6 years for extranasal and nasal disease, respectively [2]. In 2006, Lee et al. established a prognostic model for ENKTL, known as the Korean Prognostic Index, which contained four factors: B symptoms, serum lactate dehydrogenase (LDH) level, stage, and regional lymph node (RLN) involvement [3]. In this study, most patients (202/262) had received anthracycline-based chemotherapy [3]. Recently, the survival of ENKTL patients has improved owing to early radiotherapy and new chemotherapy regimens containing asparaginase and other non-anthracycline drugs [2, 4-10]. The prognostic index of natural killer lymphoma (PINK) model published in 2016 was developed for patients who received non-anthracycline-based chemotherapy with or without radiotherapy, based on their clinical characteristics including age, stage, distant lymph node (DLN) involvement, and non-nasal type disease [11].

Body mass index (BMI) is one of the common criteria to evaluate the degree of obesity. Increased BMI is associated with a higher risk of diabetes mellitus, cardiovascular diseases [12], as well as cancers [13]. Recent evidence has also shown that abnormal BMI can predict prognosis in many types of cancers [14-23], such as breast [14], colon [15] and liver [22] cancers, and diffuse large B-cell lymphoma (DLBCL) [17-19]. Although there is sufficient evidence in these cancers, the role of BMI in ENKTL is still unclear. Therefore, we carried out this retrospective study to determine the prognostic value of BMI in newly diagnosed patients with ENKTL.

Results

Patient characteristics

In total, 301 patients met the inclusion criteria. Fifty cases were excluded. Of these, 28 patients had primary extranasal diseases, 9 were younger than 18 years, 6 were complicated by other types of cancer, and the staging was unclear in 7 patients. The median age of the remaining 251 eligible patients was 42 years (range, 18-86 years), and 170 (67.7%) patients were male. At diagnosis, 40 patients (15.9%) were classified as underweight, 130 (51.8%) as normal weight, 49 (19.6%) as overweight, and 32 (12.7%) as obese according to the Asian criteria of BMI classification. Most (n = 203, 80.9%) patients received chemoradiotherapy, 37 (14.7%) received chemotherapy alone, 8 (3.2%) received radiotherapy alone, and 3 (1.2%) received only best supportive care. The chemotherapy regimens included VDLP (etoposide, dexamethasone, L-asparaginase, and cisplatin: 184 patients), LVP (L-asparaginase, vincristine, and prednisone: 36 patients), asparaginase combined with non-anthracycline drugs (e.g., gemcitabine, irinotecan, or dexamethasone: 8 patients), CHOP (doxorubicin, cyclophosphamide, vincristine, and prednisone: 8 patients), and other regimens in 4 patients. Of patients treated with radiotherapy, 205 (97.2%) completed the planned dose (50-56 Gy). By December 2015, 79 patients had died. The median follow-up time was 28 months (range, 8-86 months) for patients who were alive. The estimated 3-year OS and PFS rates were 64.4% and 60.9%, respectively. Patient characteristics are listed in Table 1.

Table 1: Patient characteristics

Characteristic

No. of patients

%

Characteristic

No. of patients

%

Gender

Ann Arbor Stage

Female

81

32.3%

I–II

213

84.9%

Male

170

67.7%

III–IV

38

15.1%

Age

Local invasiveness

≤60

219

87.3%

No

178

70.9%

>60

32

12.7%

Yes

73

29.1%

B symptoms

RLN involvement

No

122

48.6%

No

164

65.3%

Yes

129

51.4%

Yes

87

34.7%

Performance status

DLN involvement

0-1

223

88.8%

No

236

94.0%

2-4

28

11.2%

Yes

15

6.0%

LDH

No. of extranodal sites

Normal

151

60.2%

1 site

216

86.1%

Elevated

100

39.8%

>1 site

35

13.9%

BMI

Radiotherapy

<18.5

40

15.9%

No

40

15.9%

18.5-22.9

130

51.8%

Yes

211

84.1%

23-24.9

49

19.6%

Chemotherapy

≥25

32

12.7%

With asparaginase

228

90.8%

Without asparaginase

12

4.8%

No

11

4.4%

The prognostic value of BMI in patients with ENKTL

It was found that the estimated 3-year OS rates were 54.5%, 64.3%, 66.8%, and 75.2%, and the 3-year PFS rates were 48.3%, 60.5%, 66.8%, and 69.0% for underweight, normal weight, overweight, and obese patients, respectively. Survival curves showed that the significant difference of OS was only between underweight and obese patients (P = 0.045, Figure 1A). The PFS of the underweight group was shorter than that of other groups (all P < 0.05), and similar PFS curves were observed in normal weight, overweight and obese patients (Figure 1B). Therefore, patients were dichotomized into the following groups: BMI < 18.5 kg/m2 and BMI ≥ 18.5 kg/m2. Patients with BMI < 18.5kg/m2 had inferior 3-year OS (54.5% vs. 66.3%, P = 0.035) and PFS (48.3% vs. 63.4%, P = 0.017) rates than those with BMI ≥ 18.5 kg/m2. However, BMI at the cut-off of 18.5 kg/m2 was not an independent prognostic factor for either OS [(hazard ratio (HR) = 1.555, 95% confidence interval (CI) = 0.903-2.681, P = 0.111)] or PFS (HR = 1.600, 95% CI = 0.955-2.681, P = 0.074).

Survival curves of 251 patients diagnosed with ENKTL.

Figure 1: Survival curves of 251 patients diagnosed with ENKTL. A. and B. Patients were stratified into BMI groups according to the Asian criteria: underweight ( < 18.5 kg/m2), normal weight (18.5-22.9 kg/m2), overweight (23.0-24.9 kg/m2) and obese ( ≥ 25.0 kg/m2). C. and D. Patients were divided by the optimal cut-off of BMI (20.8 kg/m2).

The receiver operating characteristic (ROC) curve analysis indicated that 20.8 kg/m2 was the optimal cut-off value of BMI to predict survival (area under the curve = 0.592, P = 0.020). Patients with BMI < 20.8 kg/m2 had lower 3-year OS (52.8% vs. 72.9%, P = 0.001, Figure 1C) and PFS (48.8% vs. 69.8%, P < 0.001, Figure 1D) rates than patients with BMI ≥ 20.8 kg/m2. Multivariate analysis indicated that BMI at this cut-off was an independent prognostic factor for both OS and PFS (Table 2). Patients were further stratified to perform subgroup analyses to identify those who might be compromised by a low BMI (BMI < 20.8 kg/m2) according to the stage (early stage vs. advanced stage), use of radiotherapy (yes vs. no), and the regimen of chemotherapy (asparaginase-containing vs. non-asparaginase-containing). It was found that in patients with early stage (n = 213), receiving radiotherapy (n = 211), and undergoing asparaginase-containing chemotherapy (n = 228), BMI < 20.8 kg/m2 was associated with poor survival outcomes (all P < 0.050).

Table 2: Multivariate analysis in 251 patients with ENKTL

Overall survival

Progression-free survival

Characteristic

HR (95% CI)

P value

HR (95% CI)

P value

Gender (male vs. female)

1.708 (0.997-2.927)

0.051

1.338 (0.821-2.182)

0.243

Ann Arbor Stage (III–IV vs. I–II)

0.000 (0.000- 6.493×1048)

0.887

3.114 (0.772- 12.565)

0.111

Local invasiveness (yes vs. no)

1.367 (0.790- 2.366)

0.264

1.251 (0.761- 2.057)

0.377

RLN involvement (yes vs. no)

1.491 (0.886- 2.510)

0.132

1.514 (0.937- 2.444)

0.090

DLN involvement (yes vs. no)

0.970 (0.375- 2.505)

0.949

1.130 (0.457- 2.792)

0.791

No. of extranodal sites (>1 vs. 1)

4534.994 (0.000- 1.913×1056)

0.892

6.623 (1.667-26.316)

0.007

B symptoms (yes vs. no)

0.832 (0.486-1.426)

0.504

0.841 (0.508- 1.393)

0.501

Performance status (2–4 vs. 0–1)

4.172 (2.086- 8.346)

<0.001

2.723 (1.385- 5.354)

0.004

LDH (elevated vs. normal)

2.349 (1.390- 3.970)

0.001

1.725 (1.063- 2.797)

0.027

Chemotherapy (per 1-degree increase) a

0.612 (0.407-0.922)

0.019

0.717 (0.490- 1.048)

0.086

Radiotherapy (yes vs. no)

0.283 (0.149-0.538)

<0.001

0.156 (0.077- 0.316)

<0.001

BMI (<20.8 vs. ≥20.8)

1.689 (1.049-2.717)

0.031

1.656 (1.059-2.591)

0.027

Note: a Patients treated without chemotherapy, with non-asparaginase-based chemotherapy, and with asparaginase-containing chemotherapy were assigned the values 1, 2, and 3, respectively.

Association between BMI and other characteristics

A greater proportion of patients with BMI < 20.8 kg/m2 were female (39.6% vs. 26.9%, P = 0.033), presented with advanced stage disease (21.7% vs. 10.3%, P = 0.013), RLN involvement (42.5% vs. 29.0%, P = 0.027), DLN involvement (11.3% vs. 2.1%, P = 0.002), and extranodal sites > 1 (19.8% vs. 9.7%, P = 0.022), and were treated without radiotherapy in first-line treatment (24.5% vs. 9.7%, P = 0.001) than those with BMI ≥ 20.8 kg/m2 (Table 3). In patients receiving antitumor treatment, patients with BMI < 20.8 kg/m2 were more likely to receive radiotherapy doses of less than 50 Gy (6.3% vs. 0.8%, P = 0.030) and chemotherapy of less than 3 cycles (32.0% vs. 16.4%, P = 0.005) than those with BMI ≥ 20.8 kg/m2 (Table 3).

Table 3: Association between BMI and other characteristics

Characteristic

BMI <20.8

BMI≥20.8

P value

Gender

0.033

Female

42

39

Male

64

106

Age

0.844

≤60

93

126

>60

13

19

Ann Arbor

0.013

I–II

83

130

III–IV

23

15

Local invasiveness

0.742

No

74

104

Yes

32

41

RLN involvement

0.027

No

61

103

Yes

45

42

DLN involvement

0.002

No

94

142

Yes

12

3

Extranodal involvement

0.022

1 site

85

131

>1 site

21

14

B symptoms

0.519

No

49

73

Yes

57

72

Performance status

0.090

0-1

90

133

2-4

16

12

LDH

0.077

Normal

57

94

Elevated

49

51

Chemotherapy

0.535a

No

6

5

Yes

100

140

Chemotherapy cycles

0.005

<3

32

23

≥3

68

117

Radiotherapy

0.001

No

26

14

Yes

80

131

Radiotherapy dosage

0.030a

<50Gy

5

1

≥50Gy

75

130

Note: a Fisher's exact test.

Treatment-related adverse events based on BMI

Among 248 patients receiving antitumor treatment, grade 3-4 hematological and hepatic toxicities occurred in 86 (34.7%) and 12 (4.8%) patients, respectively. There was no grade 3-4 nephritic toxicity. Treatment-related mortality rate was 2.4%. Grade 3-4 neutropenia (33.3% vs. 19.6%, P = 0.014) and treatment interruption (9.5% vs. 2.1%, P = 0.010) were more likely to occur in patients with BMI < 20.8 kg/m2 than in those with BMI ≥ 20.8 kg/m2 (Table 4).

Table 4: Treatment-related adverse events based on BMI

Adverse event

BMI <20.8

BMI ≥20.8

P value

Anemia

0.095

Grade 0-2

93

135

Grade 3-4

12

8

Leukopenia

0.055

Grade 0-2

70

111

Grade 3-4

35

32

Neutropenia

0.014

Grade 0-2

70

115

Grade 3-4

35

28

Thrombopenia

0.154

Grade 0-2

95

136

Grade 3-4

10

7

Elevated transaminase

0.289a

Grade 0-2

100

140

Grade 3-4

5

3

Elevated bilirubin

0.999a

Grade 0-2

101

138

Grade 3-4

4

5

Elevated creatinine

0.999a

Grade 0

103

139

Grade 1-2

2

4

Treatment interruption

0.010

No

95

140

Yes

10

3

Treatment-related death

0.245a

No

101

141

Yes

4

2

Note: a Fisher's exact test.

Discussion

In this study, we found that BMI at diagnosis was an independent prognostic factor in newly diagnosed ENKTL patients, after being adjusted for other theoretical confounding factors. To the best of our knowledge, our study represents the first large cohort to evaluate the prognostic value of BMI in patients with ENKTL.

The survival rates of ENKTL patients seemed greater with higher BMI, but a statistically significant difference did not exist between normal weight and overweight/obese patients (Figure 1A and 1B). In fact, the prognostic value of overweight/obese status in cancer remains controversial. Obesity, rather than overweight, was associated with higher mortality in breast and colorectal cancers [14, 24], but being overweight or obese improved clinical outcomes of liver, and head and neck cancers [16, 22]. In DLBCL, overweight/obesity was a favorable prognostic factor in two studies conducted in America and Austria [17, 18], but the OS did not seem different among normal weight, overweight, and obese patients in another study by a Korean group [19], which seemed consistent with our findings in ENKTL (Figure 1A).

As similar prognosis were observed in normal weight and overweight/obese patients (Figure 1A and 1B), we adopted a dichotomized classification of BMI with a cut-off of 18.5 kg/m2. The survival of patients with BMI < 18.5 kg/m2 was poorer than that of patients with BMI ≥ 18.5 kg/m2 in ENKTL. It was consistent with previous findings in breast, colon, and head and neck cancers [14, 15, 20, 23]. However, multivariate analysis suggested that BMI at the cut-off of 18.5 kg/m2 was not an independent prognostic factor in ENKTL. Therefore, an ROC curve analysis was conducted, which suggested that 20.8 kg/m2 was the optimal cut-off value. BMI < 20.8 kg/m2 was associated with lower 3-year OS (Figure 1C) and PFS (Figure 1D) rates. Multivariate analysis also indicated that BMI at this cut-off was an independent prognostic factor (Table 2).

A series of studies support that patients with ENKTL can benefit from asparaginase-containing chemotherapy [7-10, 25]. Early or upfront radiotherapy is also an effective treatment to improve clinical outcome of localized disease [2, 4-6]. We confirmed these findings in the present study (Table 2). Moreover, based on the results of multivariate analysis and subgroup analysis, our findings further suggested that BMI could predict the clinical outcome of ENKTL patients who received the current mainstream treatment strategies.

The reason for poor prognosis among low-weight cancer patients is not well known. One explanation is that underweight patients may be more likely to suffer from comorbidities that increase mortality risk, such as higher rate of second malignancies [15]. In our study, 6 patients who were complicated by other types of cancer were excluded. Therefore, it might not be the reason in ENKTL. Another explanation is that low-weight patients might experience chronic undernutrition, which could weaken the immune system [14, 26]. In our study, BMI < 20.8 kg/m2 was associated with other adverse prognostic factors and the absence of early radiotherapy (Table 3). Moreover, patients with lower BMI were more likely to receive less radiotherapy doses and chemotherapy cycles in first-line treatment (Table 3) and experience severe neutropenia and adverse event-related treatment interruption (Table 4). These associations might be the reason for poor prognosis among low-weight patients with ENKTL.

There are several potential limitations in this single-institution retrospective study. Firstly, we excluded patients with primarily extranasal disease. Secondly, most patients (184 of 251) were treated with the chemotherapy regimen of VDLP. These factors limit the ability to extrapolate our findings to the entire ENKTL patient population, especially considering that a standardized chemotherapy regimen for ENKTL is not well established. Thirdly, BMI has limitations in evaluating the patients with sarcopenic or non-sarcopenic obesity [27]. Sarcopenia and visceral obesity were associated with poor survival in some malignant tumors [28-30]. Finally, we could not rule out the possibility of other confounding factors, such as socioeconomic status that might influence the BMI of patients.

In summary, our results indicated that BMI was a prognostic factor for patients with ENKTL in the context of current treatment strategy. Prospective multicentric studies are needed to further confirm this finding in the entire ENKTL patient population.

materials and Methods

Patient population and data collection

The study was approved by the Ethics Committee of West China Hospital of Sichuan University. We retrospectively analyzed the data of patients diagnosed with ENKTL between July 2008 and April 2015 in our center. Patients were included if: (1) they were newly diagnosed with ENKTL, and (2) their BMI data were available. Patients were excluded if: (1) their diseases primarily occurred in extranasal sites, (2) they were younger than 18 years, (3) they were athletes, (4) they were pregnant or lactating women, (5) they had other types of cancer, and (6) their staging was unclear. Patient characteristics including age, sex, weight, height, Ann Arbor stage, local invasiveness [31], RLN involvement [3], DLN involvement [11], number of extranodal sites, B symptoms, Eastern Cooperative Oncology Group performance status, serum LDH level, first-line treatment regimens, and survival status were recorded. BMI was calculated as weight in kilograms divided by height in meters squared (kg/m2). Patients were stratified into BMI groups according to the Asian criteria: underweight ( < 18.5 kg/m2), normal weight (18.5-22.9 kg/m2), overweight (23.0-24.9 kg/m2) and obese ( ≥ 25.0 kg/m2) [19]. Progression-free survival was defined as the time interval from diagnosis to disease progression, relapse or death as a result of any cause. Overall survival was defined as the time from diagnosis to death as a result of any cause.

Statistical analysis

Categorical variables were summarized as frequency counts and were analyzed using the Chi-squared test. If appropriate, Fisher’s exact test was performed. The optimal cut-off value of BMI to predict prognosis was calculated using an ROC curve analysis referring to death of patients. Both OS and PFS were estimated using the Kaplan-Meier method, and survival curves were compared using the log-rank test. Only those factors that were statistically associated with survival at the 0.1 level (P ≤ 0.100) in the log-rank test were included in the multivariate analysis of Cox proportional hazard model. All statistical tests were performed using SPSS v17.0 (SPSS, Inc., Chicago, IL), and two-sided P ≤ 0.05 was considered statistically significant.

Acknowledgments

The authors would like to thank Dr. Bo-Yan Huang and Di Luo for providing language guidance.

conflicts of interest

We declare that no conflict of interest exists in this manuscript.

Funding

This study was supported by the National Natural Science Foundation of China (81572853).

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