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Increased number of negative lymph nodes is associated with improved survival outcome in node positive gastric cancer following radical gastrectomy

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Oncotarget. 2016; 7:35084-35091. https://doi.org/10.18632/oncotarget.9041

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Rong-liang Shi, Qian Chen, Jun Bing Ding, Zhen Yang, Gaofeng Pan, Daowen Jiang _ and Weiyan Liu

Abstract

Rong-liang Shi1,2,3,*, Qian Chen1,*, Jun Bing Ding1, Zhen Yang1, Gaofeng Pan1, Daowen Jiang1,4, Weiyan Liu1

1Department of General Surgery, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China

2Department of Head and Neck Surgery, Fudan University Shanghai Cancer Center, Shanghai, People’s Republic of China

3Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, People’s Republic of China

4Department of Thoracic Surgery, Minhang Hospital, Fudan University, Shanghai, People’s Republic of China

*These authors have contributed equally to this work

Correspondence to:

Daowen Jiang, e-mail: daowenjiangfudan@163.com

Weiyan Liu, e-mail: weiyanliufudan@163.com

Keywords: gastric cancer, negative lymph node, SEER

Received: February 06, 2016     Accepted: April 15, 2016     Published: April 27, 2016

ABSTRACT

The concept of negative lymph node (NLN) counts has recently attracted attention as a prognostic indicator in various cancer. However, the correlation between NLN counts and patient prognosis in the setting of gastric cancer is not fully studied. Surveillance, Epidemiology, and End Results Program (SEER)-registered gastric cancer patients were used for analysis in this study. Clinicopathological characteristics, including race, age, gender, and tumor stage, grade, and cause specific survival were collected. Univariate and multivariate Cox proportional hazards model were used to assess the risk factors for survival. As results, X-tile plots identified 3 and 9 as the optimal cutoff value to divide the patients into high, middle and low risk subsets in terms of cause specific survival, and NLN was validated as independently prognostic factor in mulivariate Cox analysis (P < 0.001). Further analysis showed that NLN was a prognosis factor in each N stage. Collectively, our study results firmly demonstrated that the number of NLNs was an independent prognostic factor for gastric cancer patients, and together with the N stage, it could provide more accurate prognostic information than the N stage alone.


Increased number of negative lymph nodes is associated with improved survival outcome in node positive gastric cancer following radical gastrectomy | Shi | Oncotarget

INTRODUCTION

Gastric cancer (GC) is one of major cause of cancer related death worldwide because of its poor prognosis [1]. Surgical resection is the primary therapy option that offers the only curative chance for GC and lymph node status was a strong predictor for patients with GC after surgical resection. Although it has been shown that a 15-node minimum has been endorsed as a consensus standard for proper tumor stage and associated with a good survival outcome in patients treated with gastrectomy for GC [2]; However, a subgroup of them die of recurrence and metastases. In fact, the node-positive patients with GC are heterogeneous and the prognosis of these patients cannot be stratified by the node-stage only [3-5]. In view of these, pinpoint of prognostic factors, especially a common clinicopathological factor, for recurrence and metastasis would allow to find patients at high risk that may benefit from adjuvant chemotherapy or intensive care, usually proposed to node-positive GC patient only [6]. The concept of negative lymph node (NLN) counts has recently attracted attention as a prognostic indicator in colon [7, 8], gastric [9], esophageal [10], and cervical [11]. However, the correlation between NLN counts and patient prognosis in the setting of GC is not fully studied. Therefore, the aims of this retrospective study is to explore the effect of NLN counts on the long-term survival outcome in patients with GC after surgical resection. GC.

In the present article, the Surveillance, Epidemiology, and End Results (SEER)-registered database for GC is analyzed, aimed to investigate role of NLN count on node-positive GC patients’ survival outcomes after surgical treatment.

RESULTS

SEER database patient characteristics

In our 9-year study period, a total of 6,177 eligible GC patients were enrolled in the current study. Figure S1 depicts the flow chart of the study. The median follow up time was 27 months (0-127 months). The median age at diagnosis was 67 years (range, 21–99 years). Median survival time was 27 months with the 5-year GC-cause specific survival rate (GCSS) was 36.0%. Data from 3,124 (50.6%) patients were death. The mean number of LNs examined was 17.72 (range, 1–89), the median positive LN (PLN) count was 5.72 (range, 1–68), and the median NLN was 11.99(0-86). Patient demographics and baseline are listed in Table 1. In this setting, N stage was correlated with the number of dissected LN count, but had a significant reversely impact on NLNs (P < 0.001). A significant relationship was also found between NLNs proportion and retrieved nodes (P < 0.001). Meanwhile, Correlations between the number of NLNs and positive lymph node were weak or negligible (r = −0.108) [12].

Table 1: Demographic and tumor characteristics of patients with node positive gastric cancer

 

Subgroup

χ2 Value

P Value

N1

N2

N3

n=2221

n=2059

n=1897

Characteristic

No.

%

No.

%

No.

%

 

 

Sex

 

 

 

 

 

 

2.308

0.315

 male

1408

63.4%

1346

65.4%

1238

65.3%

 

 

 female

813

36.6%

713

34.6%

659

34.7%

 

 

Age

 

 

 

 

 

 

17.244

<0.001

 ≤60

662

29.8%

718

34.9%

666

35.1%

 

 

 >60

1559

70.2%

1341

65.1%

1231

64.9%

 

 

Race

 

 

 

 

 

 

35.363

<0.001

 Caucasian

1491

67.1%

1377

66.9%

1194

62.9%

 

 

 Black

297

13.4%

305

14.8%

243

12.8%

 

 

 Other*

433

19.5%

377

18.3%

460

24.3%

 

 

Pathological grading

 

 

 

 

 

 

98.763

<0.001

 High/Moderate

740

33.3%

528

25.6%

380

20.0%

 

 

 Poor/Anaplastic

1412

63.6%

1483

72.0%

1462

77.1%

 

 

 Unknown

69

3.1%

48

2.3%

55

2.9%

 

 

Histotype

 

 

 

 

 

 

16.938

<0.001

 Adenocarcinoma

1720

77.4%

1505

73.1%

1483

78.2%

 

 

 Mucinous/Signet ring cell

501

22.6%

554

26.9%

414

21.8%

 

 

T stage

 

 

 

 

 

 

434.932

<0.001

 T1

338

15.2%

152

7.4%

44

2.3%

 

 

 T2

372

16.7%

212

10.3%

118

6.2%

 

 

 T3

961

43.3%

1002

48.7%

883

46.5%

 

 

 T4

550

24.8%

693

33.7%

852

44.9%

 

 

No. of LNs dissected

14.72(1-87)

16.57(3-89)

22.47(7-88)

 

<0.001**

No. of positive LNs

1.43(1-2)

4.23(3-6)

12.35(7-68)

 

<0.001**

No. of negative LNs

13.29(0-86)

12.34(0-84)

10.09(0-76)

 

<0.001**

* Other includes American Indian/Alaska native, Asian/Pacific Islander, and unknown.

**One-way ANOVA analysis

Identification of cutoff points for the NLN retrieved in lymph node positive patients in the SEER database

We first treated NLN count as a continuous variable, and it was validated as a significant prognostic factor by univariate Cox analysis (χ2 = 363.387, P < 0.001). Next, X-tile plots were constructed and the maximum χ2 log-rank value of 490.428 (P < 0.001) was produced, applying 3 and 9 as the optimal cutoff value to divide the cohort into high, middle and low risk subsets in terms of GCSS. (Figure 1). There was an absolute 29.7% improvement in 5-year GCSS if ≥9 NLNs were analyzed compared with those who had <3.

X-tile analysis of survival data from the SEER registry.

Figure 1: X-tile analysis of survival data from the SEER registry. X-tile analysis was performed using data from SEER database, which were equally divided into training and validation sets. X-tile plots of the training sets are shown in the left panels, with plots of matched validation sets shown in the smaller inset. The optimal cut-point highlighted by the black circle in the left panels is shown on a histogram of the entire cohort (middle panels), and a Kaplan-Meier plot (right panels). P values were determined using the cutoff point defined in the training set and applying it to the validation set. Figure 1 shows the optimal cutoff point for the lymph node positive patients (number 3 and 9, χ2=490.428, P < 0.001).

Impact of the number of NLNs on GCSS in the SEER database

The number of NLNs and other clinicopathological factors, including age (P < 0.001), race (P < 0.001), poor and undifferentiated tumor grade (P < 0.001), advanced T stage (P < 0.001), and higher N stage (P < 0.001) were significant correlated with poor survival outcome on univariate analysis (Table 2). A reduced model was used in the multivariate Cox analysis as previous described [13]. Multivariate Cox regression analysis demonstrated that age, race, grade, T stage, N stage, and NLN group were independent predictors of GCSS and a higher number of NLNs were found to have a reduced risk of death on survival (NLN number 3-8, hazard ratio [HR] 0.680; 95% confidence interval [CI] 0.617-0.750; ≥9, HR 0.452; 95% CI 0.411-0.496. Table 2).

Table 2: Univariate and multivariate survival analyses for evaluating the influence of the number of NLNs retrieved on GCSS in node positive gastric cancer

Variable

5-year RCCS

Univariate analysis

Multivariate analysis

Log rank χ2 test

P

HR(95%CI)

P

Sex

 

0.372

0.542

 

NI

 Male

36.2%

 

 

 

 

 Female

36.2%

 

 

 

 

Age

 

69.746

<0.001

 

<0.001

 ≤60

41.7%

 

 

Reference

 

 >60

33.4%

 

 

1.486(1.375-1.605)

 

Race

 

44.286

<0.001

 

<0.001

 Caucasian

34.2%

 

 

Reference

 

 Black

33.2%

 

 

1.035(0.934-1.147)

0.508

 Others

44.7%

 

 

0.712(0.648-0.783)

<0.001

Grade

 

39.699

<0.001

 

0.002

 High/Moderate

42.7%

 

 

Reference

 

 Poor/Anaplastic

33.9%

 

 

1.165(1.071-1.268)

<0.001

 Unknown

33.3%

 

 

1.127(0.908-1.398)

0.278

Histotype

 

0.032

0.859

 

NI

 Adenocarcinoma

36.4%

 

 

 

 

 Mucinous/signet ring cell

35.5%

 

 

 

 

T Stage

 

64.721

<0.001

 

<0.001

 T1

64.2%

 

 

Reference

 

 T2

55.7%

 

 

1.083(0.882-1.331)

0.448

 T3

36.4%

 

 

1.805(1.523-2.139)

<0.001

 T4

22.6%

 

 

2.425(2.042-2.881)

<0.001

No. of NLNs

 

490.428

<0.001

 

<0.001

 0-2

16.4%

 

 

Reference

 

 3-8

29.0%

 

 

0.680(0.617-0.750)

<0.001

 ≥9

46.1%

 

 

0.452(0.411-0.496)

<0.001

N stage

 

315.020

<0.001

 

<0.001

 N1

48.8%

 

 

Reference

 

 N2

35.9%

 

 

1.282(1.171-1.403)

<0.001

 N3

21.6%

 

 

1.745(1.593-1.912)

<0.001

NI: not included in the multivariate survival analysis.

Subgroup analysis for evaluating the effect of NLN counts according to N stage in the SEER database

We then made further analysis of the effects of NLN on survival in each N stage. After stratifying patients by N stage, NLN counts were validated as independently prognostic factor in each N stage on both univariate and multivariate analysis (P < 0.001); For GC patients with N1 stage, there was an absolute 30.2% improvement in 5-year GCSS if ≥9 NLNs were analyzed compared with to those who had <3 (P < 0.001). Similarly, in patients with N2 and N3 stage cancer, there were absolute 24.8% improvement in 5-year GCSS if ≥9 NLN were analyzed compared with to those who had <3 (P < 0.001). (Table 3, Figure 2). Of particular importance, the 5-year GCSS for N3 patients with ≥9 NLN was better than N1 and N2 patients with 0-2 NLN counts (Table 3).

Log-rank tests of cause specific comparing those who had &#x2265;9, 3-8, and &#x003C;3 negative lymph nodes for

Figure 2: Log-rank tests of cause specific comparing those who had ≥9, 3-8, and <3 negative lymph nodes for a. all stage: χ2 = 490.428, P < 0.001; b. N1 stage: χ2 = 121.351, P < 0.001; c. N2 stage: χ2 = 118.978, P < 0.001; d. N3 stage: χ2 = 163.051, P < 0.001.

Table 3: Univariate and multivariate analyses of NLN count on GCSS based on different cancer stage

Variable

5-year RCCS

Univariate analysis

Multivariate analysis

Log rank χ2 test

P

HR(95%CI)

P

N Stage

 

 

 

 

 

N1 stage

 

 

 

 

 

No. of NLNs

 

121.351

<0.001

 

<0.001

 0-2

25.7%

 

 

Reference

 

 3-8

43.1%

 

 

0.640(0.526-0.779)

<0.001

 ≥9

55.9%

 

 

0.440(0.367-0.528)

<0.001

N2 stage

 

 

 

 

 

No. of NLNs

 

118.978

<0.001

 

<0.001

 0-2

19.1%

 

 

Reference

 

 3-8

29.2%

 

 

0.697(0.584-0.831)

<0.001

 ≥9

43.9%

 

 

0.471(0.397-0.558)

<0.001

N3 stage

 

 

 

 

 

No. of NLNs

 

163.051

<0.001

 

<0.001

 0-2

8.5%

 

 

Reference

 

 3-8

15.0%

 

 

0.684(0.591-0.791)

<0.001

 ≥9

33.3%

 

 

0.436(0.376-0.505)

<0.001

P-values refer to comparisons between two groups and were adjusted for age, race, pathological grading, and tumor stage as covariates.

DISCUSSION

Despite advances in early diagnosis, operative technique, and adjuvant therapies, radical gastrectomy remains the only potentially curative treatment for GC. However, even after surgical management, the 5-year overall survival rate is only about 20% in series from the United States [14]. It is generally accepted that gastrectomy with dissection of the regional lymph nodes would improve the 5-year survival of patients with GC cancer [15, 16]. At least of 15 lymph nodes should be retrieval from surgical specimens for accurate postoperative stage according to the 7th edition tumor-node-metastasis (TNM) staging system for GC [5, 17, 18]. The N category is defined by the number of positive nodes is one of the most important predictors of survival outcomes in patients with GC and has been included as a staging parameter in the 7th edition UICC/AJCC TNM staging system for GC [5, 18]. However, the node-positive patients GC are heterogeneous and the prognosis of these patients cannot be accurately stratified by the node-stage system alone [5]. The number of NLNs has been confirmed as an independent prognosis factor in colon [7, 8], gastric [9], esophageal [10], et al. Taking account of these considerations, the aim of present study was to investigate the prognostic value of NLN count in the patients with node-positive GC. In this large population based study, our results demonstrated that the NLNs count was an independent prognosis factor for GC, and even in subgroup analysis of N1, N2, and N3 stage patients, increased numbers of NLNs were associated with improved GCSS. The number of NLNs had a weak or negligible correlation with PLN counts, which means that it was a predictor independent of current metastatic LNs count-based staging.

Several hypotheses have been proposed to explain the underlying mechanism for the relationship between the number of NLNs and survival. The first hypothesis involves stage-migration. The extent of lymphadenectomy for curative GC gastrectomy has been debated for several decades; however it is generally accepted that more radical surgery is associated with better lymph node examination [9, 19]. Our study indicated that there was a significant relationship between the number of total LN and NLN counts; the more LN examined, the more likely that it reflects the true stage, and lower nodal counts may increase the risk of under-staging, and a higher number of LNs examined was linked with more accurate N stage classification. Second, the surgeon is a technician. Theoretically, a great number of retrieved NLNs indicate an authoritative surgical curability and quality of surgical care or pathology. The isolated tumor cellsin NLN are though as the main source that could lead to poor survival outcomes of GC patients [20-22]. Third, NLN may simply reflect a host lymphocytic reaction to the tumor [23], and lymphocytic reaction to tumor cells has been associated with longer survival in cancer patients [24, 25].

The results of this study must be interpreted in the light of certain limitations. First, the quality of surgical care or pathological technique may affect LN harvest, we cannot adjust these in our analysis. Second, distant lymph node metastases always classified as distant metastases and therefore the surgery were regarded as palliative resection, and should be excluded from this study. But for SEER data lacks such information, we cannot adjust for this. Third. SEER database lacks information of therapy options (radical resection or palliative therapy), subsequent therapy, co-morbidities and recurrence, which may also impact patients’ survival outcome.

Despite these potential limitations, our study results firmly demonstrated that NLNs counts was an independent prognostic predictor for patients with GC after gastrectomy, and together with the N stage, it provides more accurate prognostic information than the N stage alone.

MATERIALS AND METHODS

Patient selection in the SEER database

Data were obtained from the publicly available version of the SEER database, which consisted of 18 population-based cancer registries covering approximately 28% of the population of the United States. The National Cancer Institute's SEER*Stat software (Surveillance Research Program, National Cancer Institute SEER*Stat software, www.seer.cancer.gov/seerstat; Version 8.1.5) was used to access the database.

We searched for patients diagnosed between 2004 and 2012 with single primary GC. Histological types were limited to adenocarcinoma, mucinous adenocarcinoma, and signet ring cell carcinoma. Patients were excluded if age at diagnosis was less than 18 years, had more than one primary cancer but the gastric wasn’t the first one, had no surgical resection or palliative resection (patients with distant metastasis), had undefined TNM stage, had unknown cause of death or unknown survival months.

Patients’ demographic and clinicopathological variables, including age, sex, race, tumor grade, histologic type, T or N stage, primary site, tumor metastatic status, treatment type, reginal lymph node retrieval, reginal lymph node metastasis, et al, were retrieved from the SEER database. The primary endpoint in this study was GC cause specific survival (GCSS), defined as the period from diagnosis to death due to GC. Data of patients who died from other causes or who were alive on the date of their last follow-up were censored.

Statistical analyses

The LNs cutoff points were analyzed using the X-tile program (http://www.tissuearray.org/rimmlab/), which identified the cutoff with the minimum P values from log-rank χ2 statistics for the categorical LNs in terms of survival [26, 27]. A comparison of the categorical variables between N stage subgroups was conducted using Pearson's χ2 test. Continuous variables were compared using the Mann-Whitney U test. The Kaplan-Meier method was used to calculate the actual survival rate and to plot survival curves, followed by the log-rank test for clinical and histological variables. The Cox proportional hazard regression model was used to identify the variables that could independently influence survival in GC. Hazard ratios (HRs) and 95% confidence intervals were calculated, with an HR of <1.0 indicating survival benefit. All statistical analyses were performed using SPSS ver.19.0 (SPSS Inc., Chicago, IL), and a value of P < 0.05 indicated statistical significance. All tests were 2 sided with p < 0.05 defined as statistically significant.

ACKNOWLEDGMENTS AND FUNDING

The authors acknowledge the efforts of the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER database. The interpretation and reporting of these data are the sole responsibility of the authors.

This study was partially supported by grants from Shanghai Minhang District natural science research project (NO. 2013, mhz019; 2014, mhz026 and 2015, mhz001).

CONFLICTS OF INTEREST

None of the authors have any conflicts of interest to declare.

Author contributions

RLS, QC, DWJ and WYL conceived of and designed the study. JBD, YZ and GFP performed the analyses. RLS, QC and WYL prepared all figures and tables. RLS, QC, DWJ and WYL wrote the main manuscript. All authors reviewed the manuscript.

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