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J Thorac Cardiovasc Surg 2006;132:1374-1381
© 2006 The American Association for Thoracic Surgery

General Thoracic Surgery

The prognostic importance of the number of involved lymph nodes in esophageal cancer: Implications for revisions of the American Joint Committee on Cancer staging system

^a Thoracic Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY
^b The Biostatistics Service, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.

Received for publication December 19, 2005; revisions received March 28, 2006; accepted for publication July 12, 2006.

^_* Address for reprints: Nabil Rizk, MD, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10021 (Email: rizkn{at}mskcc.org).

	Abstract

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OBJECTIVE: The American Joint Committee on Cancer (AJCC) staging system for esophageal cancer is controversial because it relies on arbitrary definitions of the anatomic location of lymph nodes to establish N and M status. It has been proposed that the number of involved lymph nodes may better predict survival. We reviewed our experience to determine the prognostic impact of the number of involved nodes and the extent of lymphadenectomy on the current staging system.

METHODS: Records of all patients who underwent resection of previously untreated adenocarcinoma and squamous cell carcinoma of the esophagus and gastroesophageal junction were reviewed. Overall survival according to the AJCC staging system and the number of involved lymph nodes was analyzed by the method of Kaplan and Meier and by recursive partitioning methods.

RESULTS: Data were available on 336 patients operated on between January 1996 and September 2003. Recursive partitioning analysis using AJCC staging variables reproduced the AJCC staging system. When the number of involved lymph nodes is added, patients with more than 4 involved lymph nodes have survival similar to that of patients with M1 disease, and patients with no involved lymph nodes have the best prognosis. Recursive partitioning analysis identified 18 lymph nodes as the minimal number required for accurate staging. In patients who have 18 or more lymph nodes removed, survival is only predicted by the presence of nodal involvement and M1 disease.

CONCLUSION: Our analysis suggests that revisions of the current AJCC staging system for esophageal cancer should include N staging based on the number of involved lymph nodes and minimal requirements for the extent of lymphadenectomy.

	Introduction

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The current version of the American Joint Committee on Cancer (AJCC) staging system¹ for esophageal cancer has not changed significantly from previous ones, and it remains controversial. A major concern is that the current descriptors for N staging are based on arbitrary definitions of the anatomic locations of lymph nodes, which may not correlate accurately with overall survival. Previous reports from our group and others^2-8 suggest that the number of involved lymph nodes predicts survival more reliably. In addition, the current staging system does not fully address the issue of what constitutes an adequate lymphadenectomy for staging. Both of these features have already been incorporated into the staging of gastric cancer, which now includes three nodal groupings (N0, N1, and N2) based on the number of involved lymph nodes, and there is a minimal requirement for the number of lymph nodes to be removed below which staging is considered unreliable.¹

The purpose of this study is to analyze our recent experience with a large group of patients with esophageal cancer treated exclusively by surgical resection, using recursive partitioning methods as a robust statistical approach to evaluate the issue of lymph node involvement in esophageal cancer staging. Specifically, we address whether the number of involved lymph nodes should be part of a staging system and what constitutes an adequate lymphadenectomy for staging purposes. In addition, we investigate the significance of M1a nodes relative to N1 nodes. Of note, we do not address in this study separate but important issue within the staging system, namely whether the T1 descriptor should be dichotomized into two separate categories as has been advocated by some.³ Similarly, we do not address other factors that might contribute to a future staging system, such as tumor differentiation, vascular and neural invasion, and extracapsular nodal invasion. Although these are important considerations, we do not have a sufficient number of patients to answer these questions.

	Methods

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Acquisition of Clinical Data
We undertook a retrospective review of all esophagectomies performed for cancer at Memorial Sloan-Kettering Cancer Center between January 1996 and September 2003. January 1996 is the time point at which an institutional electronic medical record system was instituted, and it is therefore a date from which highly reliable data can be obtained. Patients who did not have survival information available were excluded from this analysis. We also excluded patients who received induction chemotherapy or radiation before surgery. We included patients who had adenocarcinoma or squamous cell carcinoma of the thoracic esophagus with or without involvement of the gastroesophageal junction and gastric cardia.

The data collected included patient demographics, the tumor histologic type and location, the depth of tumor invasion, and the number and location of all malignant and benign lymph nodes. Overall survival, as calculated from the time of operation, was confirmed from the Social Security Death Index. January 2004 was the censoring date for survival.

TNM Classification
The T, N, and M descriptors and staging classification used for this analysis were those defined in the sixth edition of the AJCC Cancer Staging Manual,¹ the version in use at the time this analysis was performed. Because of some variations in the nomenclature used by surgeons and pathologists in identifying the exact location of lymph nodes within a resected specimen, lymph nodes were consistently identified as "celiac axis" if they were labeled as left gastric, splenic, celiac, or hepatic. Within the chest, lymph nodes were identified as subcarinal lymph nodes if they were labeled as level 7, left main stem, or right main stem. M1a nodes were labeled according to the primary tumor location. "Celiac axis" nodes were M1a for distal esophageal, gastroesophageal junction, and gastric cardia tumors that involved the gastroesophageal junction. Cervical lymph nodes were M1a for tumors of the proximal one third of the esophagus. The total number of involved lymph nodes included any positive lymph node found excluding remote nodes that would be assigned as M1b. The overall number of lymph nodes included the sum of all involved lymph nodes plus all benign lymph nodes found. Disease was considered M1b if nodes were positive outside the regional basin or if visceral metastases were identified. Within the various analyses, we include two M categories, namely M1b and M1. M1 combines the M1a and M1b descriptors. These two M categories are used in an attempt to establish whether M1b and M1a are distinct groups. Because M1a nodes and the number of involved lymph nodes are so closely associated, M1a could not be analyzed in a similar manner. Therefore, analyses that did not distinguish between M1b and M1 nodes were used as indirect evidence of the relevance of M1a nodes. The T stage was based on the depth of tumor invasion into the esophageal wall as described in the AJCC staging manual.

Statistical Analysis
Patient characteristics are described with categorical variables and medians and range are used for continuous variables. Survival time was measured from the date of surgery to the date of death or last follow-up. Survival curves were estimated by the Kaplan-Meier method.⁹ Maximum log-rank analysis¹⁰ was used to determine the optimal cutoffs for lymph node numbers. Recursive partitioning¹¹ was used to develop a scheme to classify patients into stage categories, because the goal of a staging system is to group the patients into homogenous categories with respect to their prognosis (in this case overall survival). Because several clinical characteristics (T, N, M, lymph node numbers) affect the prognosis of a patient, traditional multivariable modeling such as Cox proportional hazards regression to account for these covariates does not provide a simple way to group the patients by prognostic categories. Recursive partitioning, on the other hand, partitions the patients recursively at each step into two groups on the basis of the covariate that gives the maximal separation with respect to their prognosis. In addition to providing an algorithm to group the patients into categories, it accounts for interactions between factors and, therefore, was considered the most appropriate statistical method for this study. Recursive partitioning was done using the RPART routines of Therneau and Atkinson.¹² This algorithm partitions patients after scaling the survival times so as to fit an exponential model. The hazard rates in the "exponential-scaled" times of terminal nodes are reported. Also reported in the analyses is the number of patient who died relative to the overall number of patients within the subset.

	Results

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Clinical Data
During the study period, 710 esophagectomies were performed, and 336 of these were appropriate for this analysis. A total of 284 patients received chemotherapy and radiation and 60 patients received chemotherapy alone before surgery and were therefore excluded. Additional patients were excluded because of lack of follow-up (n = 10), histologic classification other than squamous or adenocarcinoma (n = 10), inadequate pathologic data (n = 5), and prior esophageal resection (n = 5). The median age of the 234 (69.6%) men and 102 (30.4%) women was 66.8 years. Patient demographics, tumor location and histologic type, and the numbers of involved lymph nodes are shown in Tables 1 and 2. According to the 2002 AJCC staging system, 30 patients had stage 0 disease, 84 stage I, 67 stage IIa, 31 stage IIb, 70 stage III, 27 stage IVa, and 27 patients had stage IVb disease.

View larger version (10K): [in this window] [in a new window]   Figure 1. Kaplan-Meier analysis of overall survival showed poor discrimination between stages IIa and IIb (P = .71), as well as between stages IVa and IVb (P = .81).

View larger version (10K): [in this window] [in a new window]   Figure 2. Recursive partitioning analysis using the variables T, N, and M (M1b and M1) essentially recreates the AJCC staging system with the exception of the M descriptor. AJCC, American Joint Committee on Cancer.

View larger version (15K): [in this window] [in a new window]   Figure E1. Recursive partitioning analysis using T, N, M as variables.

View larger version (9K): [in this window] [in a new window]   Figure 3. Recursive partitioning analysis that includes the number of involved lymph nodes as a variable in addition to T, N, and M (M1b and M1) identified the presence of more than 4 involved lymph nodes as the single most important discriminator of survival, irrespective of T stage.

View larger version (14K): [in this window] [in a new window]   Figure E2. Recursive partitioning analysis using T, N, M and number of positive lymph nodes as variables. LN, Lymph nodes.

View larger version (8K): [in this window] [in a new window]   Figure 4. In T2-3 tumors, patients with no positive lymph nodes have the best prognosis, and patients with 4 or more positive lymph nodes have the worst prognosis.

View larger version (14K): [in this window] [in a new window]   Figure E3. Recursive partitioning analysis using T, N, M, number of positive lymph nodes, and total number of lymph nodes as variables. LN, Lymph nodes.

View larger version (10K): [in this window] [in a new window]   Figure 5. Among of T2-3 tumors with 0 to 4 involved lymph nodes, survival was significantly better if more than 18 lymph nodes were removed.

View larger version (13K): [in this window] [in a new window]   Figure E4. Recursive partitioning analysis using T, N, M and total number of lymph nodes as variables in patients with more than 18 lymph nodes removed. LN, Lymph nodes.

View larger version (8K): [in this window] [in a new window]   Figure 6. In patients with an adequate lymphadenectomy (>18 lymph nodes removed), depth of invasion is no longer a significant predictor of survival.

	Discussion

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The current AJCC staging system for esophageal cancer emphasizes the importance of depth of invasion (T) and the involvement of lymph nodes based on anatomic location (N1, M1a). This is different from the current staging systems for other gastrointestinal tract cancers, including gastric and colorectal cancer, in which N stage is based on the number of involved lymph nodes and minimal requirements for lymphadenectomy exist. For example, in patients with adequately staged gastric cancer, the number of involved lymph nodes has been shown to reflect the true burden of disease and, therefore, to predict outcome.^13-15

Similar findings regarding the importance of lymph node numbers have been reported in esophageal cancer,^2-8,15,16 but with varying recommendations as to the number and exact cutoffs for lymph node groupings. In our previous study, based on a smaller, more heterogeneous, and earlier patient cohort, we suggested separating tumors according to whether they were N0 or had 1 to 3 or 4 or more lymph nodes involved.² Most studies have also recommended 3 nodal groupings,^3-7 while some recommend 4^15,16 and others 2 groupings.⁸ The basis for selecting these various cutoffs is not specified in most of these studies, however, and often it is not evident how the interactions between the various staging variables were accounted for. For instance, although Baba and associates⁷ propose 3 nodal groupings (N0-1, N2-5, N > 5), it is not stated how these numbers were chosen, nor were these groupings subjected to a multivariate analysis. Similarly, while Igaki and associates⁸ restrict their evaluation to T1 and T2 lesions, they do not specify how their lymph node groupings were selected. In our current study, we use recursive partitioning analysis as a nonbiased means to identify appropriate lymph node cutoffs, with the additional advantage that this type of analysis accounts for interactions with other variables. Furthermore, the recursive partitioning algorithm uses a cross-validation approach to prevent the overfitting of data. Thus, we have confidence in the reproducibility of the inferences drawn even though the size of the data used is limited. This resulted in the identification of 3 nodal groups in patients with adequately staged disease.

The extent of lymphadenectomy and its impact on staging, on the other hand, has not been directly addressed in studies of the staging of esophageal cancer. There is, however, indirect evidence of the impact of a lymphadenectomy on staging. In publications that report more extensive lymphadenectomies, reported survival is typically better stage for stage than would be expected.^4,17 Although proponents of the more extensive operations attribute this survival advantage to surgical technique,^18,19 this finding could be at least partially attributed to "stage migration" owing to better identification of involved lymph nodes.²⁰ Indeed, patients who undergo cervical node dissection (3-field) frequently have occult positive lymph nodes detected,^17,18,21 possibly as a result of skip metastases.²² Further evidence that a more extensive lymphadenectomy leads to potential stage migration was shown by Nigro and associates,²³ wherein they demonstrate that in T1 tumors, patients who undergo an en bloc esophagectomy are significantly more likely to have positive lymph nodes identified than patients who have a transhiatal esophagectomy. In our current study, we show that stage for stage, survival is worse if a lesser lymphadenectomy is done. Moreover, we show that this survival difference is likely to the result of stage migration because the probability of identifying positive lymph nodes is directly correlated to the adequacy of the lymphadenectomy. As a consequence, when only including patients with an adequate lymphadenectomy, depth of invasion no longer is prognostic of outcome, and a 3-tiered staging system is created based primarily on the number of involved lymph nodes. Because of the close association between the depth of invasion and the likelihood of lymph node involvement,^17,24 it is not surprising that when nodal status is adequately assessed, depth of invasion would no longer provide surrogate information regarding the nodal status and T status would no longer independently predict survival. Supporting evidence for this includes data from Hsu and coworkers,²⁵ who found that, once there was nodal involvement, T status no longer predicted survival. Likewise, Altorki and colleagues¹⁷ showed that the survival of patients with AJCC stage I is similar to that of patients with stage IIa disease, indicating little influence of depth of invasion on survival in patients with adequately staged node-negative disease. This is in contrast to Orringer, Marshall, and Iannettoni’s experience²⁶ with transhiatal esophagectomy, wherein the 5-year survival of stage I is significantly better than in stage IIa.

Evaluation of the significance of M1a nodes in this group of patients showed that there is a strong correlation between M1a status and a large nodal burden. In addition, while a univariate comparison of survival between patients with M1a nodes compared with those with N1 nodes does indeed show the former to have a worse survival (10.6 months vs 20.8 months, P = .006, respectively), in none of our analyses did M1a independently predict survival when analyzed in conjunction with lymph node number. This result is at odds with some reports,²⁷ whereas others have supported this finding.^3,28 Our previous study supported both lymph node numbers and location as prognostic variables.² That study, however, included significantly fewer patients (n = 216), 15% of whom received preoperative therapy. Furthermore, the analysis of lymph node location in our earlier study was done independently of lymph node number, with the only supporting evidence for the importance of M1a nodes being the lack of correlation between lymph node number and lymph node location.

There are several drawbacks in our current study. Although the median number of nodes removed is relatively high compared with most studies, it clearly is also less than what some others have reported. In addition, by performing only the equivalent of a 2-field lymphadenectomy, we are not assessing cervical lymph nodes. These issues might contribute to understaging. A separate concern, which we do not address in this study because of the number of patients, is the potential difference in staging between squamous cell carcinoma and adenocarcinoma, an issue raised by Siewert and associates,²⁴ among others. Similarly, the question of whether T1 lesions should be stratified into T1a and T1b³ can only be addressed if both depth of invasion and nodal involvement are addressed. Unfortunately, this cohort of patients is too small to yield a valid answer, with only 26 T1a lesions and 69 T1b lesions, only 13 including lymph node involvement. Last, a significant number of patients with advanced-stage disease were excluded from this analysis (n = 344). At our institution, we at present commonly use preoperative chemoradiotherapy in patients whose clinical stage is IIa or greater, reflecting a change in practice compared with the earlier periods in this study. As such, the majority of patients in this analysis who have an advanced pathologic stage represent patients from earlier time points in this series. For instance, in 1996, 82% of the patients in this analysis were in AJCC stage II or higher, whereas in 2003 the stage distribution included 65% of patients with AJCC stages 0 or I. Furthermore, as a group, the patients in this series were older than patients in our institution who received preoperative therapy (66.8 vs 59.8, P < .001, respectively), reflecting a bias to not offer multimodality treatment in older patients. While excluding patients who received preoperative therapy is necessary for proper interpretation of the staging characteristics, the impact of the consequent selection bias is unclear.

In summary, the analyses presented in this study suggest that several modifications could improve the current esophageal cancer staging system, including a recommendation that a minimum of 18 lymph nodes be removed for reliable staging and that the N stage be separated into 3 categories, namely N0, 1 to 4 positive nodes, and more than 4 positive nodes. Although not definitive, our results suggest that these groupings for lymph node involvement could supplant the M1a and M1b descriptors in the current staging system. Thus, a revised staging system could include M0 and M1 descriptors only with M1 designating distant visceral metastases, as is common in the AJCC staging systems for other malignant diseases. A study with a larger number of patients would be necessary to incorporate these proposed lymph node groupings (in the context of an adequate lymphadenectomy) into a formal staging system. Furthermore, future studies with larger numbers of patients will be necessary to incorporate additional prognostic variables such as lymph node size, evidence of extracapsular nodal invasion, and other histologic and perhaps molecular characteristics of the tumor.

In conclusion, we would recommend that any future staging system for esophageal cancer include the number of involved lymph nodes rather than just whether lymph nodes are involved. Furthermore, for the staging system to reliably represent the true tumor burden, we would also recommend that a minimum number of lymph nodes be removed.²⁹

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This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Personal Folders Download to citation manager Author home page(s): Nabil Rizk Bernard Park Raja Flores Manjit S. Bains Valerie Rusch Permission Requests Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Rizk, N. Articles by Rusch, V. Search for Related Content PubMed PubMed Citation Articles by Rizk, N. Articles by Rusch, V.