Small intestinal neuroendocrine tumors (SI-NETs) comprise the third largest subgroup of gastroenteropancreatic neuroendocrine tumors (NETs). A worldwide overall increase in SI-NETs has been reported in the last 30 years, in part because of the development of radiologic and endoscopic technology as well as a better knowledge of the biology of this tumor.[2,3] The clinical manifestations of SI-NETs range from no symptoms, localized lesions, to potentially fatal metastatic carcinoid syndrome. SI-NETs have distinct histopathologic characteristics according to their specific site of localization. According to the American Joint Committee on Cancer (AJCC) staging system, 8th edition, SI-NETs are divided into jejunoileal NETs and duodenal and ampulla of Vater NETs. Despite its relatively indolent nature, jejunoileal NETs frequently invade regional lymph nodes, leading to mesenteric fibrosis. The updated AJCC (8th edition) staging system of jejunoileal NETs proposes a new stage, N stage, in which N0 is defined as no regional lymph node involvement, N1 as involvement of 1 to 11 regional lymph nodes, and N2 as involvement of 12 or more regional lymph nodes. However, as Chen et al reported, this novel classification has no significant prognostic value for survival.
The ratio of metastatic lymph nodes to the total number of examined lymph nodes (ELNs) is defined as the lymph node ratio (LNR). The LNR is used as a supplement to the tumor lymph node metastasis (TNM) staging system. Chen et al combined ELNs with LNR and used Harrel concordance index (HCI) to assess the prognostic value of lymphatic metastasis in jejunoileal NETs. In their study, patients were divided into three groups (group 1: ELNs ≥12, any LNR; group 2: ELNs <12, LNR <0.35; group 3: ELNs <12, LNR ≥0.35). Their definition of lymphatic metastasis (HCI = 0.653) was better than the AJCC 8th edition stage classification system (HCI = 0.520). Recent studies show that the number of negative lymph nodes (NLNs) is a prognostic indicator in various cancers, including breast cancer, rectal cancer, head and neck squamous cell carcinoma, and ampulla of Vater carcinoma. However, it is unknown whether the NLN count is an independent prognostic factor in jejunoileal NETs. Therefore, in this study, we investigate the prognostic value of the NLN count in patients with jejunoileal NETs and compare it with the LNR and the classification system reported by Chen et al.
Subjects and methods
Patients were gathered from the Surveillance, Epidemiology and End Results (SEER) database (http://seer.cancer.gov/about), a national cancer registry managed by the United States National Cancer Institute, which collects information related to sociodemography and clinicopathology. All patients with jejunoileal NETs (site codes: C17.2 and C17.3; histologic codes: 8013, 8150 to 8156, 8240 to 8247, 8249 and 9091) diagnosed between 1988 and 2014 according to the International Classification of Disease for Oncology, 3rd edition (ICD-O-3), were selected in this study. Parameters included race, age, sex, tumor size and extension, primary tumor site, regional lymph node removed, regional lymph node involvement, distant metastasis, surgery, and survival status. Tumor size and extension were used to determine T categories according to the AJCC 8th edition stage classification system. Overall survival (OS) was the primary outcome measure. All included patients were over 18 years of age and had undergone surgical treatment. Exclusion criteria included the following: patients diagnosed at autopsy or on death certificate; patients with other cancers or distant metastasis; incomplete tumor size and extension information; incomplete lymph node information and survival time less than one month or unknown. Ethical approval was not needed because the data were obtained from the SEER database. The SEER Program of the National Cancer Institute is an authoritative and open source of information on cancer incidence and survival in the USA that is updated annually.
Descriptive statistics was used to report the basic clinicopathological characteristics of the patients. The cutoff point of the NLN count was determined with the X-tile program (https://x-tile.software.informer.com/) using the minimum P-values from log-rank chi-square analysis for the categorical NLNs in terms of OS. X-tile is a bioinformatics software for biomarker assessment and outcome-based cut-point optimization, first developed by Camp et al. Subgroups were set up according to the number of NLNs identified. Survival was examined between subgroups by using Kaplan–Meier analysis with the log-rank test. Univariate Cox proportional hazards regression was used to identify potential prognostic factors. All prognostic factors identified in the univariate analysis were included in the multivariate analysis. Multivariate analysis was carried out after adjusting for age, tumor size, tumor site and T classifications using the Cox proportional hazards model. Harrell concordance index (HCI) was used to compare the prognostic value of NLNs with LNR and the classification reported by Chen et al in 3 different datasets: jejunum, ileum, and jejunoileal NETs. A model with perfect predictive prognosis (sensitivity and specificity of 100%) would have a HCI of 1.00, while a HCI of 0.5 would indicate no predictive ability.
Statistical analyses were performed using SPSS statistical software package, version 20.0 (SPSS Inc., Armonk, NY, USA) and R project version 3.5.2 (http://www.r-project.org/). All P-values were two-sided. A value of P < 0.05 was considered statistically significant.
We collected information for 2395 patients with jejunoileal NETs diagnosed between 1988 and 2014. The program selection details for the SEER database queries are shown in Additional Figure 1, http://links.lww.com/JR9/A7. The median age at diagnosis was 59.0 years (range, 18–100 years). The median follow-up time was 57.0 months (range, 1–318 months), and the 10-year OS was 74.0%. Among the patients, 2089 (87.2%) were white, and the ratio of men to women was approximately 1:1 (1172 men and 1223 women). Overall, 91.4% of jejunoileal NETs were located in the ileum and 8.6% in the jejunum. According to the AJCC 8th edition staging criteria, patients with T3 disease (47.6%) were the most numerous, followed by patients with T1/T2 disease (32.8%) and T4 disease (19.6%). A total of 468 (19.5%) patients had node-negative diseases, and lymphatic metastasis was found in 80.3% of patients, among whom 1878 (78.4%) had a positive lymph node (PLN) count <12 and 49 (2.0%) had a PLN count ≥12. The median number of NLNs was 8 (range, 0–77). The detailed clinicopathological characteristics are presented in Table 1.
The optimal cutoff value for NLNs identified with the X-tile program
The NLN count was first treated as a continuous variable. X-tile software was used to perform log-rank chi-square analysis for the categorical NLNs in terms of OS to estimate the cutoff value of NLNs with the minimum P values. The X-tile analysis was performed using patient data from the SEER registry, which was equally divided into training and validation sets. The X-tile plots of training sets are shown in Figure 1A. The green color of the plot illustrates that patients with higher NLN counts did better. The optimal cut-point is shown on a histogram of the entire cohort. Patients were divided into high (NLN count ≤8) and low (NLN count >8) risk subgroups with the optimal cutoff point of 8 (Fig. 1B). Kaplan–Meier plots were created based on the cutoff value (χ2 = 30.116, P < 0.001; Fig. 1C).
Impact of PLN count on OS
Survival curves based on PLN categories, according to the AJCC 8th edition classification system are shown in Figure 2. The PLN count did not have a statistically significant impact on OS among the patients with jejunoileal NETs (P = 0.508; Fig. 2A). Patients with T1 and T2 stage tumors had overlap of survival in cases with PLN count <12 and PLN count ≥12 (P = 0.820; Fig. 2B), as well as in patients with T3 (P = 0.447; Fig. 2C) and T4 (P = 0.637; Fig. 2D) tumors.
Impact of NLN count on OS stratified by T stage
Kaplan–Meier curves stratified by NLN count are shown in Figure 3A. The 10-year OS rate was lower in patients with an NLN count ≤8 (70.1%; 95% confidence interval (CI): 66.8–73.4%) than in patients with an NLN count >8 (80.7%; 95% CI: 76.8–84.6%). Next, we further examined the prognostic significance of NLN count on OS in each subgroup of T1, T2, T3 and T4 disease patients. Regardless of T status, patients with 8 or fewer NLNs had lower OS than patients with 9 or more NLNs. For T1 and T2 jejunoileal NETs, the 10-year OS rate was 83.7% (95% CI: 78.4–89.0%) and 91.9% (95% CI: 87.0–96.8%) in patients with 8 or fewer NLNs and 9 or more NLNs, respectively (P = 0.004; Fig. 3B). Similarly, for T3 jejunoileal NETs, the 10-year OS was lower in patients with 8 or fewer NLNs (65.3%; 95% CI: 60.4–70.2%) than in patients with 9 or more NLNs (74.3%; 95% CI: 67.8–80.8%; P = 0.002; Fig. 3C). For T4 jejunoileal NETs, patients with 8 or fewer NLNs had a worse 10-year OS rate (64.0%; 95% CI: 56.0–72.0%) compared with those with 9 or more NLNs (74.1%; 95% CI: 63.9–84.3%; P = 0.012; Fig. 3D).
Impact of NLN count on OS stratified by N status
The prognostic value of the NLN count was assessed according to lymph node status. For patients with node-positive disease, the number of NLNs was highly significantly associated with OS. Patients with 9 or more negative nodes had better 10-year OS than those with 8 or fewer negative nodes (79.6% [95% CI: 75.1–84.1%] vs 68.1% [95% CI: 64.2–72.0%]; P < 0.001; Fig. 4A). In contrast, the statistical interaction between the high number and low number of NLNs was attenuated in patients with node-negative disease (10-year OS rate: 85.7% [95% CI: 78.1–93.3%] vs 76.3% [95% CI: 70.0–82.5%]; P = 0.081; Fig. 4B).
Prognostic value of NLN count in patients with jejunoileal NETs
Univariate Cox survival analysis indicated that the number of NLNs was an important prognostic factor for OS (hazards ratio (HR): 0.555 [95% CI: 0.449–0.685]; P < 0.001). The PLN count did not have a statistically significant impact on OS (P = 0.513). Other significant prognostic factors included age (P < 0.001), tumor site (P = 0.029), tumor size (P < 0.001) and T classification (P < 0.001; Table 2). Multivariate Cox analysis adjusted by univariate analysis was used to assess the independent prognosis of the number of NLNs and PLNs separately. A higher number of NLNs was related to a better OS (HR: 0.641 [95% CI: 0.519–0.793]; P < 0.001), but the number of PLNs was not prognostic for OS (PLNs = 0 as the reference; PLNs <12: HR: 0.962, 95% CI: 0.751–1.231, P
= 0.756; PLNs ≥12: HR: 0.417, 95% CI: 0.152–1.144, P = 0.089; Additional Table 1, http://links.lww.com/JR9/A7). Other significant independent prognostic parameters included age (P < 0.001), tumor size (P = 0.001) and T classification (P < 0.001; Table 3).
Comparison of prognostic values of the 3 different classification systems
As shown in Table 4, when all patients were included, the HCI values indicated that the NLN classification method had similar significance compared with the LNR and the classification reported by Chen et al (HCI = 0.758, 0.753 and 0.762, respectively; P = 0.076). Similar results were also observed for jejunal NETs (HCI = 0.793, 0.793 and 0.792, respectively; P = 0.454) and ileal NETs (HCI = 0.754, 0.749 and 0.758, respectively; P = 0.063).
Jejunoileal NETs are a heterogeneous group of tumors with different prognoses. The recent establishment of the AJCC staging system has greatly assisted treatment decisions. However, this classification system has not been thoroughly verified, especially for lymph nodes. Lymphatic metastasis is quite common in jejunoileal NETs. In this study, over 80% of patients had lymphatic metastasis. Therefore, it is important to better estimate the prognostic value of lymphatic metastasis. In this study, we used population-based data to assess the effect of the number of NLNs on prognosis in patients with jejunoileal NETs. By X-tile analysis, the optimal cut-point of NLNs was 8. A higher number of NLNs was associated with longer OS. Subgroups analysis showed that NLN count was a prognostic factor for patients with different T classification and node-positive diseases. Furthermore, the NLN classification reported in this study had a similar prognostic value to the LNR and the classification scheme reported by Chen et al, suggesting it may provide accurate prognostic information for patients with jejunoileal NETs.
We also studied the prognostic value of the pathologic lymph node (pN) classification in jejunoileal NETs. Our results showed that the pN classification did not have a significant predictive value for prognosis, as a previous study reported. Admittedly, large mesenteric mass was also defined as N2 classification in jejunoileal NETs. In view of these data being unavailable in the SEER database, they were not considered in this study. However, our study revealed that the use of PLNs to define the pN classification is questionable. Many factors, such as the number of ELNs and neoadjuvant therapy, may influence the detection of PLNs and subsequently underestimate the lymph node status of patients. Moreover, one problem of employing node counts in the jejunoileal NETs is the frequent occurrence of large mesenteric masses, which often implies aggregation of lymph nodes and cannot be enumerated exactly.
Several recent studies showed that the NLN count influences the prognosis of breast cancer, esophageal cancer, colorectal cancer and cervical cancer. Although the mechanisms underlying the survival advantage conferred by a higher NLN count remain unknown, several hypotheses have been proposed. The first hypothesis simply attributes the association to stage migration, meaning that some patients diagnosed as N0 disease may actually suffer from cancer already disseminated to regional lymph nodes. As the number of ELNs increases, the probability of missing PLNs and misclassification to an early stage decreases.[22,23] This stage migration hypothesis may account for the beneficial effect of high NLN count in patients with early stage tumors, but it cannot fully explain the beneficial effect observed in patients with advanced stage tumors. Thus, the stage migration hypothesis does not seem to be a reasonable explanation in our study because the effect was more evident among patients with node-positive jejunoileal NETs. This finding may be attributed to the survival mechanisms of the different tumor stages. Another possibility is that an increased number of NLNs is associated with a stronger immune response to the tumor. Previous studies suggest that the NLN count is related to the molecular biology of colorectal cancer cells and the host immune response to cancer.[26,27] For breast cancer, NLN counts might reflect the balance between host cells and cancer cells, and to some extent, affect the presence of circulating cancer cells. Various tumor factors may stimulate lymph nodes to enlarge, making them easier to be surgically and pathologically detected, thereby increasing the detected number of lymph nodes. If this concept is correct, the number of NLNs may possibly affect the presence and function of circulating cancer cells, and serve as a potential marker of tumor–host interactions, which may have an independent effect on survival. Another alternative explanation is lymph node micrometastasis, a main cause of recurrence and metastasis after jejunoileal NET resection. Lymph node micrometastases, usually found in 0.2 to 2.0 mm nodes, are positive for cytokeratin immunohistochemical staining but negative in hematoxylin-eosin staining.[30,31] Because it is difficult to detect lymphatic micrometastasis during surgery, we can retrieve more NLNs to identify micrometastasis and reduce the possibility of potential residual lesions. This may also explain why patients with a higher number of NLNs have better survival.
There are several limitations to the current study. First, this is a retrospective study that lacked information on therapy options, such as chemotherapy, targeted therapy and immunotherapy, which might directly affect the prognosis of patients. However, our findings are credible and widely applicable because the SEER database is based on the United States population and clinical practice. Second, the information on mesenteric mass, which was also defined as N2 disease in jejunoileal NETs, was unavailable in the SEER database. However, the main purpose of this study was to investigate the prognostic value of lymph node metastasis, rather than mesenteric mass. Third, the tumor grade information was missing in our study. Tumor grade is a prognostic indicator in a variety of malignant tumors. However, SI-NETs generally tend to be of low pathological grade. Thus, tumor grade may provide less information in this patient population.
Lymphatic metastasis is very common in jejunoileal NETs. Although based on the AJCC 8th edition staging system, the pN classification method lacked the ability to predict the prognosis of patients with jejunoileal NETs. The threshold PLN counts for N2 disease require further study. Our newly proposed classification of NLN count had a better prognostic value than the pN classification system in jejunoileal NET patients. Of course, additional studies are required to investigate the mechanisms underlying the prognostic effect of NLN count in patients with jejunoileal NETs.
The authors would like to thank SEER for providing open access to the database.
WH and YD contributed to the concept and design of the study. SJ, RZ, ZL, and XH performed the experiments. DD, XY, HL, and WH analyzed the data and prepared the figures. WH, SJ, LR wrote the paper. All authors reviewed and approved the manuscript.
This work was supported by the National Natural Science Foundation of China (No. 81573007 to YD, 81572361 to WH), the Ten Thousand Plan Youth Talent Support Program of Zhejiang Province, China (to WH), the Zhejiang Natural Sciences Foundation of China (No. LQ18H160008 to HL), the Zhejiang Medical Science and Technology Project, China (No. 2016KYB290 to XY), the Zhejiang Province Preeminence Youth Fund, China (No. LR16H160001 to WH), and the Zhejiang Medical Innovative Discipline Construction Project-2016, China (to WH).
Institutional review board statement
The ethics is not needed because we used data from the SEER database The SEER Program of the National Cancer Institute is an authoritative and open source of information on cancer incidence and survival in the USA that is updated annually.
Conflicts of interest
The authors declare that they have no conflicts of interest.
1. Niederle MB, Hackl M, Kaserer K, et al. Gastroenteropancreatic neuroendocrine tumours: the current incidence and staging based on the WHO and European Neuroendocrine Tumour Society classification: an analysis based on prospectively collected parameters. Endocr Relat Cancer
2. Yao JC, Hassan M, Phan A, et al. One hundred years after “carcinoid”: epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J Clin Oncol
3. Fraenkel M, Kim MK, Faggiano A, et al. Epidemiology of gastroenteropancreatic neuroendocrine tumours. Best Pract Res Clin Gastroenterol
4. Landry CS, Brock G, Scoggins CR, et al. A proposed staging system for small bowel carcinoid tumors based on an analysis of 6,380 patients. Am J Surg
2008; 196:896–903. discussion 903.
5. Rindi G, Falconi M, Klersy C, et al. TNM staging of neoplasms of the endocrine pancreas: results from a large international cohort study. J Natl Cancer Inst
6. Nakakura EK. Challenges staging neuroendocrine tumors of the pancreas, jejunum and ileum, and appendix. Ann Surg Oncol
7. Chen L, Song Y, Zhang Y, et al. Exploration of the exact prognostic significance of lymphatic metastasis in jejunoileal neuroendocrine tumors. Ann Surg Oncol
8. Landry CS, Lin HY, Phan A, et al. Resection of at-risk mesenteric lymph nodes is associated with improved survival in patients with small bowel neuroendocrine tumors. World J Surg
9. van der Wal BC, Butzelaar RM, van der Meij S, et al. Axillary lymph node ratio and total number of removed lymph nodes: predictors of survival in stage I and II breast cancer. Eur J Surg Oncol
10. Li X, Lu H, Xu K, et al. Negative lymph node count is an independent prognostic factor for patients with rectal cancer who received preoperative radiotherapy. BMC Cancer
11. Xing Y, Zhang J, Lin H, et al. Relation between the level of lymph node metastasis
and survival in locally advanced head and neck squamous cell carcinoma. Cancer
12. Falconi M, Crippa S, Dominguez I, et al. Prognostic relevance of lymph node ratio and number of resected nodes after curative resection of ampulla of Vater carcinoma. Ann Surg Oncol
13. Fritz A, Percy C, Jack A, et al. International classification of diseases for oncology. Geneva:World Health Organization; 2000.
14. Egner JR. AJCC Cancer Staging Manual. JAMA
15. Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin Cancer Res
16. Jin S, Wang B, Zhu Y, et al. Log odds could better predict survival in muscle-invasive bladder cancer patients compared with pN and lymph node ratio. J Cancer
17. Howe JR, Cardona K, Fraker DL, et al. The surgical management of small bowel neuroendocrine tumors: consensus guidelines of the north american neuroendocrine tumor society. Pancreas
18. Kuru B. Prognostic significance of total number of nodes removed, negative nodes removed, and ratio of positive nodes to removed nodes in node positive breast carcinoma. Eur J Surg Oncol
19. Wu SG, Wang Y, Zhou J, et al. Number of negative lymph nodes
should be considered for incorporation into staging for breast cancer. Am J Cancer Res
20. Chen Y, Zhang L, Tian J, et al. Combining the negative lymph nodes
count with the ratio of positive and removed lymph nodes can better predict the postoperative survival in cervical cancer patients. Cancer Cell Int
21. Altorki NK, Zhou XK, Stiles B, et al. Total number of resected lymph nodes predicts survival in esophageal cancer. Ann Surg
22. Greenstein AJ, Litle VR, Swanson SJ, et al. Effect of the number of lymph nodes sampled on postoperative survival of lymph node-negative esophageal cancer. Cancer
23. Karlsson P, Cole BF, Price KN, et al. The role of the number of uninvolved lymph nodes in predicting locoregional recurrence in breast cancer. J Clin Oncol
24. Baba Y, Watanabe M, Shigaki H, et al. Negative lymph-node count is associated with survival in patients with resected esophageal squamous cell carcinoma. Surgery
25. Ogino S, Nosho K, Irahara N, et al. Negative lymph node count is associated with survival of colorectal cancer patients, independent of tumoral molecular alterations and lymphocytic reaction. Am J Gastroenterol
26. Johnson PM, Porter GA, Ricciardi R, et al. Increasing negative lymph node count is independently associated with improved long-term survival in stage IIIB and IIIC colon cancer. J Clin Oncol
27. Pagès F, Berger A, Camus M, et al. Effector memory T cells, early metastasis, and survival in colorectal cancer. N Engl J Med
28. Vinh-Hung V, Burzykowski T, Cserni G, et al. Functional form of the effect of the numbers of axillary nodes on survival in early breast cancer. Int J Oncol
29. Zeng YJ, Zhang CD, Dai DQ. Impact of lymph node micrometastasis on gastric carcinoma prognosis
: a meta-analysis. World J Gastroenterol
30. Hayashi N, Ito I, Yanagisawa A, et al. Genetic diagnosis of lymph-node metastasis in colorectal cancer. Lancet
31. Jeuck TL, Wittekind C. Gastric carcinoma: stage migration by immunohistochemically detected lymph node micrometastases. Gastric Cancer
32. Arbache A, Kara M, El Mouhadi S, et al. Neuroendocrine tumor of the small intestine. Clin Res Hepatol Gastroenterol
33. Jann H, Roll S, Couvelard A, et al. Neuroendocrine tumors of midgut and hindgut origin: tumor-node-metastasis classification determines clinical outcome. Cancer
jejunoileal neuroendocrine tumor; lymph node metastasis; lymph node staging; negative lymph nodes; prognosis
Supplemental Digital Content
Copyright © 2019 The Chinese Medical Association. Published by Wolters Kluwer Health, Inc.