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Original Research: Lung Cancer |

A Proposal for Combination of Total Number and Anatomical Location of Involved Lymph Nodes for Nodal Classification in Non-small Cell Lung CancerNew Lymph Node Classification FREE TO VIEW

Hisashi Saji, MD, PhD; Masahiro Tsuboi, MD, PhD; Yoshihisa Shimada, MD, PhD; Yasufumi Kato, MD, PhD; Koichi Yoshida, MD, PhD; Masaharu Nomura, MD, PhD; Jun Matsubayashi, MD, PhD; Toshitaka Nagao, MD, PhD; Masatoshi Kakihana, MD, PhD; Jitsuo Usuda, MD, PhD; Naohiro Kajiwara, MD, PhD; Tatsuo Ohira, MD, PhD; Norihiko Ikeda, MD, PhD
Author and Funding Information

From the Division of Thoracic Surgery, Department of Surgery (Drs Saji, Tsuboi, Shimada, Kato, Yoshida, Kakihana, Usuda, Kajiwara, Ohira, and Ikeda), and Department of Anatomic Pathology (Drs Nomura, Matsubayashi, and Nagao), Tokyo Medical University, Tokyo, Japan.

Correspondence to: Hisashi Saji, MD, PhD, Division of Thoracic Surgery, Department of Surgery, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo 160-0023, Japan; e-mail: saji-q@ya2.so-net.ne.jp


Funding/Support: This study was supported by grants from the Ministry of Education, Culture, Sports, Science and Technology [21791332] and the Ministry of Health, Labour and Welfare [22101601].

For editorial comment see page 1527

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2013;143(6):1618-1625. doi:10.1378/chest.12-0750
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Background:  We previously reported the prognostic impact of the number of involved lymph nodes (LNs) on survival in non-small cell lung cancer (NSCLC). However, it remains unknown whether the total number or anatomic location of involved LNs is a superior prognostic factor.

Methods:  A total of 689 patients with NSCLC who underwent complete resection involving dissection of the hilar and mediastinal LNs with curative intent of ≥ 10 LNs were enrolled. The association between the total number of LNs (nN) involved and survival was assessed by comparison with the anatomic location of LN involvement (pathologic lymph node [pN]), the present nodal category.

Results:  We classified the patients into five categories according to the combined pN and nN status as follows: pN0-nN0, pN1-nN1-3, pN1-nN4−, pN2-nN1-3, and pN2-nN4. Although there was no statistically significant difference between the pN1-nN4− and pN2-nN1-3 categories, pN2-nN1-3 had better prognoses than pN1-nN4−. On multivariate analysis, the nN category was an independent prognostic factor for overall survival and disease-free survival (vs nN4−; the hazard ratios of nN0 and nN1-3 for overall survival were 0.223 and 0.369, respectively, P < .0001 for all), similar to the pN category. We propose a new classification based on a combination of the pN and nN categories: namely, N0 becomes pN0-nN0, the N1 category becomes pN1-nN1-3, the N2a category becomes pN2-nN1-3 + pN1-nN4−, and the N2b category becomes pN2-nN4. Each survival curve was proportional and was well distributed among the curves.

Conclusions:  A combined anatomically based pN stage classification and numerically based nN stage classification is a more accurate prognostic determinant in patients with NSCLC, especially in the prognostically heterogeneous pN1 and pN2 cases. Further large-scale international cohort validation analyses are warranted.

Figures in this Article

Various pathologic and molecular markers have been assessed regarding their usefulness in identifying patients at high risk for recurrence. However, the TNM system remains the most important determinant of staging. Because the prognosis of lung cancer is directly proportional to the presence of lymph node (LN) metastasis, accurate LN assessment is crucial in determining treatment. Accurate staging of non-small cell lung cancer (NSCLC) requires assessment of the hilar and mediastinal LNs with pathologic evaluation. However, the present nodal classification still contains some limitations particularly concerning heterogeneous pN1 and pN2 disease and the lack of a clear biologic definition of the distinguishing of N1 and N2.14

The seventh edition of the TNM classification for NSCLC5 has been updated, with some modifications from the sixth edition.6 However, the LN descriptor in the new classification remains the same as in the previous edition, and depends solely on the anatomic extent of LN involvement, despite the changes in the nodal map. In some other solid tumors, such as breast, gastric, and colorectal tumors, the number of metastatic lymph nodes has been included in the TNM staging system.

In our previous report,7 we demonstrated that resection of ≥ 10 LNs influenced survival and that the number of involved LNs (four and more) is a strong independent prognostic factor in NSCLC. This may provide new information for determining the N category in the next TNM classification. However, it remains unknown whether the total number or anatomic location of involved LNs is a superior prognostic factor in NSCLC. Therefore, we retrospectively compared or combined the number of metastatic LNs (nN) category and the classic pathologic LNs (pN) category on survival in patients with completely resected NSCLC in whom ≥ 10 LNs had been harvested.

Patient Eligibility

A total of 1,311 consecutive patients who underwent surgical resection for primary lung cancer at our institution from 2000 to 2007 were examined retrospectively. The patients with clinical stages IA to IIIA, including patients with stage cN2 with single-station nodal metastasis, underwent surgery. Cases of induction therapy, incomplete resection, and limited resection were excluded from this study. Patients with tumors classified histologically as small-cell lung cancer or low-grade malignancies were also excluded. In addition, those in whom nine or fewer LNs were harvested were also excluded in the present analysis because our previous study suggested that resection of at least 10 LNs was necessary to maintain the optimal quality of surgery and accurate staging.7 Finally, a total of 689 patients with NSCLC who underwent complete resection involving dissection of ≥ 10 hilar and mediastinal lymph nodes with curative intent, consisting of lobectomy or more extensive resection, were eligible.

Data Collection

The patient charts, including the pathologic diagnosis and operative reports, were reviewed. Staging was determined according to the sixth edition of the TNM staging system.8 The histologic tumor type was determined according to the World Health Organization classification (third edition).9 LNs were dissected with the adipose connective tissue of the corresponding anatomic regions, as designated by the surgeon intraoperatively. All dissected LNs were examined pathologically and classified on the basis of anatomic location by the numbering system described in the Naruke map.10 The number of resected and involved LNs from each defined anatomic location was confirmed on the basis of the pathologic report provided by Drs Nomura, Matsubayashi, and Nagao. We performed two different stratifications of LN status assessment: the absence or presence and anatomic extent of nodal metastases (pN categories), and the number of regional LNs with metastases (nN categories). Based on our previous results, four or more involved LNs is the best benchmark of prognostic variables.7 Therefore, we classified involved LNs into the three nN categories as follows: nN0, no LN metastasis; nN1-3, metastasis in one to three nodes; and nN4−, metastasis in four or more LNs. The pathologists were blinded to the clinical outcome.

We chose overall survival (OS) and disease-free survival (DFS) as end points and investigated the associations between the nN categories and these endpoints compared with standard pN categories. OS was calculated from the date of surgery to the time of death. Observations were censored at final follow-up if the patient was alive. DFS was defined as the time from surgery to locoregional relapse or distant metastasis of lung cancer, and in cases without relapse, any deaths due to causes other than lung cancer were censored. Patients were examined at intervals of 3 months for the first 2 years and at intervals of 6 months for the next 3 years or thereafter on an outpatient basis. The follow-up evaluation involved the following procedures: physical examination, chest radiography, CT scan of the chest and abdomen, and blood examination, including that of pertinent tumor markers. Further evaluations, including brain MRI or CT scan, bone scintigraphy, and integrated PET scan, were performed on the first appearance of any symptoms or signs of recurrence. The median follow-up time was 3.5 years.

Statistical Analysis

Survival curves were plotted using the Kaplan-Meier method. Differences in survival among the groups were examined using the log-rank test. A two-category comparison was performed using the Student t test for quantitative data. Multivariate analysis was performed using the Cox proportional hazards model to examine any possible association between the total number of involved LNs and survival, with adjustment for the effects of other potential prognostic factors, including age, sex, histology, tumor factor, and type of surgery performed. All tests were two-sided, and P values of < .05 were considered to indicate statistically significant differences. StatView 5.0 software (SAS Institute Inc) was used for statistical analysis.

Ethical Considerations

The approval of the institutional review board of Tokyo Medical University was obtained (project approval no. 965). But, as this was a retrospective study, the need to obtain written informed consent from either the patients or their representatives was waived, in accordance with the American Medical Association.

Patient Characteristics

The characteristics of patients were as follows: median age: 64.5 years; sex: 417 men (60.5%) and 272 women (39.5%); histopathologic diagnosis: 497 adenocarcinomas (72.1%), 140 squamous cell carcinomas (20.3%), 42 large cell carcinomas (6.1%), and 10 others (1.5%); pathologic stages: 480 stage I (69.7%), 94 stage II (13.6%), and 115 stage III (14.1%); pN factors: 510 pN0 (74.0%), 93 pN1 (13.5%), and 86 pN2 (12.5%); nN factors: 510 nN0 (74.0%), 101 nN1-3 (14.5%), and 78 nN4− (11.4%). The mean number of resected LNs was 18.1 (right side, 18.5; left side, 17.6). The mean number of involved LNs was 4.5 (range, 1-22) in LN-positive cases (Table 1).

Table Graphic Jump Location
Table 1 —Patient Characteristics (N = 689)

LN = lymph node, nN = number of lymph nodes; pN = pathologic lymph node; pT = pathologic tumor.

Survival Analysis

First, we classified the patients into three nN categories: nN0, no LN metastasis; nN1-3, metastasis in one to three nodes; and nN4−, metastasis in four or more LNs. We then assessed the OS and DFS in each pN stage classification and nN category (Fig 1). The survival curves showed clear differences in the OS and DFS of each subgroup of both the pN and nN classifications. There was also a significant difference in OS and DFS for each of the nN categories (the 5-year OS rates for nN0, nN1-3, and nN4− were 79.2%, 64.8%, and 39.2%, respectively, P = .0426 and P < .0001 for nN0 vs nN1-3 and nN1-3 vs nN4−, respectively; the 5-year DFS rates were 83.0%, 71.6%, and 32.9%, respectively, P = .0024 and P = .0002 for nN0 vs nN1-3 and nN1-3 vs nN4−, respectively).

Figure Jump LinkFigure 1. DFS and OS according to pN status and nN status. A, DFS curve according to pN status. The 5-year DFS rates for pN0, pN1, and pN2 were 83.0%, 75.3%, and 31.1%, respectively. a, pN0 vs pN1, P = .0464; b, pN1 vs pN2, P < .0001. B, OS curve according to pN status. The 5-year OS rates for pN0, pN1, and pN2 were 79.2%, 65.9%, and 35.4%, respectively. c, pN0 vs pN1, P = .0181; d, pN1 vs pN2, P < .0001. C, DFS curve according to nN status. The 5-year DFS rates for nN0, nN1, and nN2-3 were 83.0%, 71.6%, and 39.2%, respectively. e, nN0 vs nN1, P = .0024; f, nN1 vs nN2-3, P = .0002. D, OS curve according to nN status. The 5-year DFS rates for nN0, nN1, and nN2-3 were 79.2%, 64.8%, and 32.9%, respectively. g, nN0 vs nN1, P = .0426; h, nN1 vs nN2-3, P < .0001. DFS = disease-free survival; nN = number of lymph nodes; OS = overall survival; pN = pathologic lymph node.Grahic Jump Location

Second, we performed validation of the nN category in terms of OS for each pathologic tumor (pT) category (Fig 2). Although the differences between each pair of nN categories were not always significant, there was a tendency toward the deterioration of OS from the nN0 to the nN4− subgroup. Similar results were found in terms of DFS (data not shown).

Figure Jump LinkFigure 2. OS curves according to nN status across each pT category. A, OS curve according to nN status in pT1 patients. The 5-year OS rates for nN0, nN1, and nN2-3 were 88.5%, 81.4%, and 52.1%, respectively. a, nN0 vs nN1-3, P = .6757; b, nN1-3 vs nN4−, P = .0024. B, OS curve according to nN status in pT2 patients. The 5-year OS rates for nN0, nN1-3, and nN4− were 71.2%, 58.7%, and 16.7%, respectively. c, nN0 vs nN1-3 P = .6083; d, nN1-3 vs nN4− P < .0001. C, OS curve according to nN status in pT3 patients. The 5-year OS rates for nN0, nN1-3, and nN4− were 37.3%, 50.0%, and 0%, respectively. e, nN0 vs nN1-3, P = .2537; f, nN1-3 vs nN4−, P = .0046. D, OS curve according to nN status in pT4 patients. The 5-year OS rates for nN0, nN1-3, and nN4− were 50.0%, 62.5%, and 58.3%, respectively. g, nN0 vs nN1-3 P = .4305; h, nN1-3 vs nN4−, P = .8623. pT = pathologic tumor. See Figure 1 legend for expansion of other abbreviations.Grahic Jump Location

Third, we classified the patients into five categories of combinations of the pN and nN status to compare the prognostic significance of the pN and nN status. The five N categories were as follows: pN0-nN0, pN1-nN1-3, pN1-nN4−, pN2-nN1-3, and pN2-nN4. As shown in Figure 3, patients with pN2-nN1-3 (n = 22) had better prognoses than patients with pN1-nN4− (n = 13). However, there was no statistically significant difference between these two groups due to the small populations. The survival curve of pN2-nN1-3 patients was similar to that of pN1-nN1-3 patients, which is an operable population, while the survival curves of pN1-nN4− patients were similar, but still superior to that of pN2-nN4− patients.

Figure Jump LinkFigure 3. OS curves according to combinations between nN status and pN status. Patients with pN2-nN1-3 (n = 22) had better prognoses than patients with pN1-nN4− (n = 13). However, there was no statistically significant difference between the two groups due to the small populations. The survival curve of pN2-nN1-3 was similar to that of pN1-nN1-3, while the survival curves of pN1-nN4− were similar to that of pN2-nN4, a population with worse prognoses. a, pN0-nN0 vs pN1-nN1-3, P = .2908; b, pN1-nN1-3 vs pN2-nN1-3, P = .1102; c, pN2-nN1-3 vs pN1-nN4, P = .1292; d, pN1-nN4− vs pN2-nN4, P = .7810. See Figure 1 legend for expansion of abbreviations.Grahic Jump Location

Because of the strong correlation between the pN and nN categories, we performed multivariate analysis for each category to confirm each prognostic impact for OS and DFS.11 On multivariate analysis, the nN category was an independent prognostic factor for OS and DFS (vs nN4−; the hazard ratios of nN0 and nN1-3 for OS were 0.223 and 0.369, respectively, P < .0001 for all categories) as was the case for the pN category (Tables 2, 3). Therefore, both the pN and nN categories were identified as strong prognostic factors for OS and DFS in NSCLC. Moreover, the populations of the pN1-nN1-3 and pN2-nN1-3 categories were small, and the OS of patients within these two groups did not statistically differ. And, there were significant differences between pN1 and pN2 (Figs 1A, 1B) and between nN1-3 and nN4− (Figs 2A, 2B), which mean by a still subcategory exist. We propose a new classification for testing, based on combined pN and nN categories: namely, the new N0 category becomes pN0-nN0, the new N1 category becomes pN1-nN1-3, the new N2a category becomes pN2-nN1-3 + pN1-nN4−, and the new N2b category becomes pN2-nN4. Figure 4 shows the survival curves of the new classifications, which were proportional and well distributed among the curves.

Table Graphic Jump Location
Table 2 —Multivariate Analysis of OS and DFS Including pN Classification

DFS = disease-free survival; HR = hazard ratio; OS = overall survival. See Table 1 for expansion of other abbreviations.

a 

Statistically significant.

Table Graphic Jump Location
Table 3 —Multivariate Analysis of OS and DFS Including nN Classification

See Table 1 and 2 legends for expansion of abbreviations.

a 

Statistically significant.

Figure Jump LinkFigure 4. OS curves according to combinations of nN status and pN status. We propose a new classification based on combined pN and nN categories: namely, N0 becomes pN0-nN0, N1 becomes pN1-nN1-3, N2a becomes pN2-nN1-3 + pN1-nN4− and N2b becomes pN2-nN4. Each survival curve was proportional and well distributed. a, New N0 vs new N1a, P = .2908; b, new N1a vs new N2a, P = .0028; c, new N2a vs new N2b, P = .0726. See Figure 1 legend for expansion of abbreviations.Grahic Jump Location

The TNM stage classification was developed to provide high specificity for patients with similar prognoses and treatment options. Nodal status is a major determinant of stage and survival of patients with NCSLC after surgery. The seventh TNM staging system included notable changes in the T and M descriptors and in the nodal map, while the N descriptor remained the same as in the previous version and depended solely on the anatomic extent of involved LNs. The anatomically based pN classification has some unsatisfactory aspects. Of these, the heterogeneity of pN1 and pN2 with regard to prognosis is the most notable. Therefore, some subclassifications have been proposed.14,1217 In addition, differences among surgeons in the labeling of LN stations intraoperatively will occur regardless of the use of a new nodal map. This indicates that it is necessary to refine the currently used pN stage classification and has justified attempts to identify alternative nodal classification methods. In some other solid tumors, such as breast, gastric, and colorectal tumors, the number of metastatic lymph nodes has been included in the TNM staging system. The number of metastatic LNs, when classified into several categories, has been shown to be a prognostic factor for resected NSCLC.11,15,18 Wei and colleagues11 evaluated this issue and suggested that the nN category is a better prognostic determinant than the location-based pN stage classification. However, to date, it has remained unknown whether the nN category or the pN stage classification is a better prognostic factor in lung cancer.

It is important to consider how many or to what extent LNs should be harvested for the accurate assessment of nodal status and to maintain the optimal quality of surgery in NSCLC before evaluating the effectiveness of prognostic determinants among the pN and nN categories. The number of resected LNs in early NSCLC has been proven to be a prognostic factor which has influenced survival, similar to that in colorectal, breast, and bladder cancer.1924 Some reports have suggested that the optimal number of removed LNs is 11 to 16 in order to accurately assess stage I lung cancer.24,25 In another study, the removal of 11 LNs was set as a threshold for inclusion.18 The Staging Manual in Thoracic Oncology of the International Association for the Study of Lung Cancer (IASLC) recommends that at least six LNs/stations be removed or sampled and histologically confirmed to be free of disease in order to define pN0 status.5 We previously demonstrated that the resection of 10 or more LNs influenced survival while maintaining the quality of surgery.7 Therefore, in the present analysis, we excluded those for whom < 10 LNs were harvested. In the present series, 617 of 689 cases (89.6%) met this criterion. In the TNM classification for some other tumors, the number of positive LNs has been included in the definition of pN categories.26 The number of metastatic LNs, when classified into several categories, has been shown to be a prognostic factor for resected NSCLC.11,15,18 There was a significant difference in OS and DFS among each nN category as well as the pN categories. The OS and DFS survival curves of each nN category are well distributed and proportional (Fig 1). Moreover, as Figure 2 shows, a clear tendency toward the deterioration of OS from nN0 to nN4− in the same pT category was observed when we attempted to validate the results for each pT category. The curves were evenly distributed over pT1, pT2, and pT3. However, the curves were closer in the higher pT stage of pT4, perhaps due to the small population size. Another reason may be that the prognosis of the higher pT category was already poor, regardless of the presence of metastatic LNs. On multivariate analysis, not only the pN status, but also the nN status, was demonstrated to be a major independent prognostic factor for both OS and DFS in the current series, which is consistent with a previous report.11 These results showed that both pN and nN categories have a powerful discriminative ability concerning the prognosis of NSCLC.

In general, patients with NSCLC with pN1 or pN2 disease are known to exhibit prognostic heterogeneity.14,1217 The OS and DFS curves of pN1 and pN2 were widely distributed in the current series, indicating that there are some subclassifications required to distinguish the two curves. To evaluate these subgroups and demonstrate which is the most accurate prognostic factor, the anatomic location of involved LNs, or the total number of involved LNs, we classified the patients into five categories combining the pN and nN status as follows: pN0-nN0, pN1-nN1-3, pN1-nN4−, pN2-nN1-3, and pN2-nN4−. Patients with pN2-nN1-3 (n = 22) had better prognoses than patients with pN1-nN4− (n = 13). However, there was no statistically significant difference between the two groups due to the small numbers of patients. This result indicates that the nN category might be used to further subdivide the pN category into two prognostically distinct subgroups. Finally, we propose combining patients with pN2-nN1-3 with those who have a better prognosis into the pN2 category and patients in the pN1-nN4− category with those who have a worse prognosis into a single pN category. Therefore, we reclassified the patients in the current series into four categories as shown in Figure 4. Each OS survival curve of the new classification appears to be proportional with a significant tendency to differ between the new N1 and new N2a and between the new N2a and new N2b categories (P = .0028 and P = .0726, respectively).

When we subdivided the pN1 and pN2 categories into two subgroups according to the nN category, there was no statistically significant difference between the two groups, but patients with pN2-nN1-3 had better prognoses than patients with pN1-nN4−. This result indicates a possible limitation of the present pN classification for nodal status. The overall disease burden, rather than the anatomic location of LN involvement, has the most relevance in prognosis.11,27 However, the present pN classification is a major independent prognostic factor in operative NSCLC, as was the nN classification on multivariate analysis in the present series. Therefore, we propose a new nodal classification combination of the pN (anatomic location) and nN (total number) status of LN involvement, which may reflect the survival of operable NSCLC cases more accurately than any single category.

There are some limitations in this study, despite the benefits of the addition of the nN category for predicting survival. First, this was a retrospective and single-institution analysis. Second, it is difficult to accurately estimate the number of LN sites involved both preoperatively and in inoperable patients by CT scan or any other diagnostic imaging methods. The scope of this study involved only the definition of prognosis based on the p stage and not on the c stage, which is a limitation of this investigation. Technical improvements in preoperative evaluation to accurately identify all metastatic LN sites are necessary. Although there are various clinical markers to evaluate potential malignant lesions, there is as yet no reliable method or evidence suggesting that PET scans or tumor markers can definitively indicate malignancy. Therefore, this is the reason why we decided to concentrate on the p stage as a step toward establishing preoperative clinical evaluation. Third, the definition of the optimal category in terms of the number of metastatic lymph nodes needs to be further explored; because the definitions, and, therefore, the data, differ according to the institution, it is difficult to determine the optimal category definition. Further multiinstitution studies using identical protocols are needed.

The current results demonstrate that combined anatomically based pN and numerically based nN stage classification as proposed in this study is a better prognostic determinant in pN1 and pN2 prognostically heterogeneous patients with NSCLC. Further large-scale cohort studies, including global prospective validation analyses and multiinstitution studies, are warranted to demonstrate the validity of this proposal for the next TNM classification.

Author contributions: Dr Saji is guarantor of the article.

Dr Saji: contributed to the design and coordination of the study, statistical analysis, preparing the manuscript, and revising the article for important intellectual content and read and approved the final manuscript.

Dr Tsuboi: contributed to preparing the manuscript and read and approved the final manuscript.

Dr Shimada: contributed to data collection and analysis and read and approved the final manuscript.

Dr Kato: contributed to data collection and analysis and read and approved the final manuscript.

Dr Yoshida: contributed to data collection and analysis and read and approved the final manuscript.

Dr Nomura: contributed to pathologic analysis and read and approved the final manuscript.

Dr Matsubayashi: contributed to pathologic analysis and read and approved the final manuscript.

Dr Nagao: contributed to pathologic analysis and read and approved the final manuscript.

Dr Kakihana: contributed to data collection and analysis and read and approved the final manuscript.

Dr Usuda: contributed to preparing the manuscript and read and approved the final manuscript.

Dr Kajiwara: contributed to preparing the manuscript and read and approved the final manuscript.

Dr Ohira: contributed to preparing the manuscript and read and approved the final manuscript.

Dr Ikeda: contributed to preparing the manuscript and read and approved the final manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Role of sponsors: The sponsors had no role in the design of the study, the collection and analysis of the data, or in the preparation of the manuscript.

Other contributions: We are indebted to Roderick J. Turner, BS (Associate Professor); Edward F. Barroga, PhD; and J. Patrick Barron, BA (Professor and Chairman, Department of International Medical Communications, Tokyo Medical University) for their editorial review of the English manuscript.

DFS

disease-free survival

LN

lymph node

nN

number of lymph nodes

NSCLC

non-small cell lung cancer

OS

overall survival

pN

pathologic lymph node

pT

pathologic tumor

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Fukui T, Mori S, Yokoi K, Mitsudomi T. Significance of the number of positive lymph nodes in resected non-small cell lung cancer. J Thorac Oncol. 2006;1(2):120-125. [CrossRef] [PubMed]
 
Misthos P, Sepsas E, Athanassiadi K, Kakaris S, Skottis I. Skip metastases: analysis of their clinical significance and prognosis in the IIIA stage of non-small cell lung cancer. Eur J Cardiothorac Surg. 2004;25(4):502-508. [CrossRef] [PubMed]
 
Rusch VW, Crowley J, Giroux DJ, et al. The IASLC Lung Cancer Staging Project: proposals for the revision of the N descriptors in the forthcoming seventh edition of the TNM classification for lung cancer. J Thorac Oncol. 2007;2(7):603-612. [CrossRef] [PubMed]
 
Lee JG, Lee CY, Park IK, et al. Number of metastatic lymph nodes in resected non-small cell lung cancer predicts patient survival. Ann Thorac Surg. 2008;85(1):211-215. [CrossRef] [PubMed]
 
Bria E, Milella M, Sperduti I, et al. A novel clinical prognostic score incorporating the number of resected lymph-nodes to predict recurrence and survival in non-small-cell lung cancer. Lung Cancer. 2009;66(3):365-371. [CrossRef] [PubMed]
 
Tepper JE, O’Connell MJ, Niedzwiecki D, et al. Impact of number of nodes retrieved on outcome in patients with rectal cancer. J Clin Oncol. 2001;19(1):157-163. [PubMed]
 
Weir L, Speers C, D’yachkova Y, Olivotto IA. Prognostic significance of the number of axillary lymph nodes removed in patients with node-negative breast cancer. J Clin Oncol. 2002;20(7):1793-1799. [CrossRef] [PubMed]
 
Herr HW, Bochner BH, Dalbagni G, Donat SM, Reuter VE, Bajorin DF. Impact of the number of lymph nodes retrieved on outcome in patients with muscle invasive bladder cancer. J Urol. 2002;167(3):1295-1298. [CrossRef] [PubMed]
 
Darling GE, Allen MS, Decker PA, et al. Number of lymph nodes harvested from a mediastinal lymphadenectomy: results of the randomized, prospective American College of Surgeons Oncology Group Z0030 trial. Chest. 2011;139(5):1124-1129. [CrossRef] [PubMed]
 
Varlotto JM, Recht A, Nikolov M, Flickinger JC, Decamp MM. Extent of lymphadenectomy and outcome for patients with stage I nonsmall cell lung cancer. Cancer. 2009;115(4):851-858. [CrossRef] [PubMed]
 
Ludwig MS, Goodman M, Miller DL, Johnstone PA. Postoperative survival and the number of lymph nodes sampled during resection of node-negative non-small cell lung cancer. Chest. 2005;128(3):1545-1550. [CrossRef] [PubMed]
 
Sobin LH, Gospodarowicz MK, Wittekind C. TNM Classification of Malignant Tumours.. 7th ed. Hoboken, NJ: Wiley-Blackwell; 2009;
 
Rusch VW, Asamura H, Watanabe H, et al. The IASLC lung cancer staging project: a proposal for a new international lymph node map in the forthcoming seventh edition of the TNM classification for lung cancer. J Thorac Oncol. 2009;4(5):568-:577. [CrossRef] [PubMed]
 

Figures

Figure Jump LinkFigure 1. DFS and OS according to pN status and nN status. A, DFS curve according to pN status. The 5-year DFS rates for pN0, pN1, and pN2 were 83.0%, 75.3%, and 31.1%, respectively. a, pN0 vs pN1, P = .0464; b, pN1 vs pN2, P < .0001. B, OS curve according to pN status. The 5-year OS rates for pN0, pN1, and pN2 were 79.2%, 65.9%, and 35.4%, respectively. c, pN0 vs pN1, P = .0181; d, pN1 vs pN2, P < .0001. C, DFS curve according to nN status. The 5-year DFS rates for nN0, nN1, and nN2-3 were 83.0%, 71.6%, and 39.2%, respectively. e, nN0 vs nN1, P = .0024; f, nN1 vs nN2-3, P = .0002. D, OS curve according to nN status. The 5-year DFS rates for nN0, nN1, and nN2-3 were 79.2%, 64.8%, and 32.9%, respectively. g, nN0 vs nN1, P = .0426; h, nN1 vs nN2-3, P < .0001. DFS = disease-free survival; nN = number of lymph nodes; OS = overall survival; pN = pathologic lymph node.Grahic Jump Location
Figure Jump LinkFigure 2. OS curves according to nN status across each pT category. A, OS curve according to nN status in pT1 patients. The 5-year OS rates for nN0, nN1, and nN2-3 were 88.5%, 81.4%, and 52.1%, respectively. a, nN0 vs nN1-3, P = .6757; b, nN1-3 vs nN4−, P = .0024. B, OS curve according to nN status in pT2 patients. The 5-year OS rates for nN0, nN1-3, and nN4− were 71.2%, 58.7%, and 16.7%, respectively. c, nN0 vs nN1-3 P = .6083; d, nN1-3 vs nN4− P < .0001. C, OS curve according to nN status in pT3 patients. The 5-year OS rates for nN0, nN1-3, and nN4− were 37.3%, 50.0%, and 0%, respectively. e, nN0 vs nN1-3, P = .2537; f, nN1-3 vs nN4−, P = .0046. D, OS curve according to nN status in pT4 patients. The 5-year OS rates for nN0, nN1-3, and nN4− were 50.0%, 62.5%, and 58.3%, respectively. g, nN0 vs nN1-3 P = .4305; h, nN1-3 vs nN4−, P = .8623. pT = pathologic tumor. See Figure 1 legend for expansion of other abbreviations.Grahic Jump Location
Figure Jump LinkFigure 3. OS curves according to combinations between nN status and pN status. Patients with pN2-nN1-3 (n = 22) had better prognoses than patients with pN1-nN4− (n = 13). However, there was no statistically significant difference between the two groups due to the small populations. The survival curve of pN2-nN1-3 was similar to that of pN1-nN1-3, while the survival curves of pN1-nN4− were similar to that of pN2-nN4, a population with worse prognoses. a, pN0-nN0 vs pN1-nN1-3, P = .2908; b, pN1-nN1-3 vs pN2-nN1-3, P = .1102; c, pN2-nN1-3 vs pN1-nN4, P = .1292; d, pN1-nN4− vs pN2-nN4, P = .7810. See Figure 1 legend for expansion of abbreviations.Grahic Jump Location
Figure Jump LinkFigure 4. OS curves according to combinations of nN status and pN status. We propose a new classification based on combined pN and nN categories: namely, N0 becomes pN0-nN0, N1 becomes pN1-nN1-3, N2a becomes pN2-nN1-3 + pN1-nN4− and N2b becomes pN2-nN4. Each survival curve was proportional and well distributed. a, New N0 vs new N1a, P = .2908; b, new N1a vs new N2a, P = .0028; c, new N2a vs new N2b, P = .0726. See Figure 1 legend for expansion of abbreviations.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Patient Characteristics (N = 689)

LN = lymph node, nN = number of lymph nodes; pN = pathologic lymph node; pT = pathologic tumor.

Table Graphic Jump Location
Table 2 —Multivariate Analysis of OS and DFS Including pN Classification

DFS = disease-free survival; HR = hazard ratio; OS = overall survival. See Table 1 for expansion of other abbreviations.

a 

Statistically significant.

Table Graphic Jump Location
Table 3 —Multivariate Analysis of OS and DFS Including nN Classification

See Table 1 and 2 legends for expansion of abbreviations.

a 

Statistically significant.

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Misthos P, Sepsas E, Kokotsakis J, Skottis I, Lioulias A. The significance of one-station N2 disease in the prognosis of patients with nonsmall-cell lung cancer. Ann Thorac Surg. 2008;86(5):1626-1630. [CrossRef] [PubMed]
 
Fukui T, Mori S, Yokoi K, Mitsudomi T. Significance of the number of positive lymph nodes in resected non-small cell lung cancer. J Thorac Oncol. 2006;1(2):120-125. [CrossRef] [PubMed]
 
Misthos P, Sepsas E, Athanassiadi K, Kakaris S, Skottis I. Skip metastases: analysis of their clinical significance and prognosis in the IIIA stage of non-small cell lung cancer. Eur J Cardiothorac Surg. 2004;25(4):502-508. [CrossRef] [PubMed]
 
Rusch VW, Crowley J, Giroux DJ, et al. The IASLC Lung Cancer Staging Project: proposals for the revision of the N descriptors in the forthcoming seventh edition of the TNM classification for lung cancer. J Thorac Oncol. 2007;2(7):603-612. [CrossRef] [PubMed]
 
Lee JG, Lee CY, Park IK, et al. Number of metastatic lymph nodes in resected non-small cell lung cancer predicts patient survival. Ann Thorac Surg. 2008;85(1):211-215. [CrossRef] [PubMed]
 
Bria E, Milella M, Sperduti I, et al. A novel clinical prognostic score incorporating the number of resected lymph-nodes to predict recurrence and survival in non-small-cell lung cancer. Lung Cancer. 2009;66(3):365-371. [CrossRef] [PubMed]
 
Tepper JE, O’Connell MJ, Niedzwiecki D, et al. Impact of number of nodes retrieved on outcome in patients with rectal cancer. J Clin Oncol. 2001;19(1):157-163. [PubMed]
 
Weir L, Speers C, D’yachkova Y, Olivotto IA. Prognostic significance of the number of axillary lymph nodes removed in patients with node-negative breast cancer. J Clin Oncol. 2002;20(7):1793-1799. [CrossRef] [PubMed]
 
Herr HW, Bochner BH, Dalbagni G, Donat SM, Reuter VE, Bajorin DF. Impact of the number of lymph nodes retrieved on outcome in patients with muscle invasive bladder cancer. J Urol. 2002;167(3):1295-1298. [CrossRef] [PubMed]
 
Darling GE, Allen MS, Decker PA, et al. Number of lymph nodes harvested from a mediastinal lymphadenectomy: results of the randomized, prospective American College of Surgeons Oncology Group Z0030 trial. Chest. 2011;139(5):1124-1129. [CrossRef] [PubMed]
 
Varlotto JM, Recht A, Nikolov M, Flickinger JC, Decamp MM. Extent of lymphadenectomy and outcome for patients with stage I nonsmall cell lung cancer. Cancer. 2009;115(4):851-858. [CrossRef] [PubMed]
 
Ludwig MS, Goodman M, Miller DL, Johnstone PA. Postoperative survival and the number of lymph nodes sampled during resection of node-negative non-small cell lung cancer. Chest. 2005;128(3):1545-1550. [CrossRef] [PubMed]
 
Sobin LH, Gospodarowicz MK, Wittekind C. TNM Classification of Malignant Tumours.. 7th ed. Hoboken, NJ: Wiley-Blackwell; 2009;
 
Rusch VW, Asamura H, Watanabe H, et al. The IASLC lung cancer staging project: a proposal for a new international lymph node map in the forthcoming seventh edition of the TNM classification for lung cancer. J Thorac Oncol. 2009;4(5):568-:577. [CrossRef] [PubMed]
 
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