Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Peer-reviewed

Research Article

Increasing negative lymph node count predicts favorable OS and DSS in breast cancer with different lymph node-positive subgroups

  • Xin Zhao,

    Roles Data curation, Formal analysis, Investigation, Software, Validation, Writing – original draft

    Affiliation Department of General Surgery, Tianjin First Central Hospital,Tianjin,China

    ⨯
  • Jing Wei,

    Roles Formal analysis, Investigation, Methodology, Writing – original draft

    Affiliation Department of Thoracic Surgery, Xuzhou Central Hospital, The Affiliated Xuzhou Hospital of Medical College of Southeast University, Xuzhou, China

    ⨯
  • Xiaoxin Li,

    Roles Software, Supervision, Validation

    Affiliation Department of Pathology, Xuzhou Central Hospital, The Affiliated Xuzhou Hospital of Medical College of Southeast University, Xuzhou, China

    ⨯
  • Haochang Yang,

    Roles Investigation, Methodology, Software

    Affiliation College of Clinical Medicine, Binzhou Medical University, Yantai, China

    ⨯
  • Pei Wang ,

    Contributed equally to this work with: Pei Wang, Susheng Cao

    Roles Conceptualization, Project administration, Supervision, Validation, Writing – review & editing

    cssxzsy@126.com (SC); 13495333289@qq.com (PW)

    Affiliation Department of Breast Surgery, Xuzhou Central Hospital, The Affiliated Xuzhou Hospital of Medical College of Southeast University,Xuzhou, China

    ⨯
  • Susheng Cao

    Contributed equally to this work with: Pei Wang, Susheng Cao

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Writing – review & editing

    cssxzsy@126.com (SC); 13495333289@qq.com (PW)

    Affiliation Department of Breast Surgery, Xuzhou Central Hospital, The Affiliated Xuzhou Hospital of Medical College of Southeast University,Xuzhou, China

    ⨯

Abstract

Adequate lymph node evaluation is recommended for optimal staging in patients with malignant neoplasms including breast cancer. However, the role of negative lymph nodes (LNs) remains unclear in breast cancer according to N substage (N1, N2, and N3). In this study, for the first time, we analyzed the prognostic significance of negative LNs in breast cancer patients. A critical relationship was observed between negative LN count and survival, independent of patient characteristics and other related molecular variables including estrogen receptor (PR) status, progesterone receptor (ER) status, human epidermal growth factor receptor 2 (HER2) status, depth of tumor invasion and degree of differentiation. This research is of great importance in providing more information about the prognosis of breast cancer by statistical analysis of negative lymph nodes and can serve as a useful supplement to the current pathological system.

Citation: Zhao X, Wei J, Li X, Yang H, Wang P, Cao S (2018) Increasing negative lymph node count predicts favorable OS and DSS in breast cancer with different lymph node-positive subgroups. PLoS ONE 13(3): e0193784. https://doi.org/10.1371/journal.pone.0193784

Editor: William B. Coleman, University of North Carolina at Chapel Hill School of Medicine, UNITED STATES

Received: November 2, 2017; Accepted: February 16, 2018; Published: March 19, 2018

Copyright: © 2018 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Supporting Information from SEER are available in the Supporting Information files. SEER data can also be accessed by visiting the SEER website (https://seer.cancer.gov/data/) and submitting a data access request. You will receive an account and password, with which you can obtain all the clinical data for free. The authors did not have special access privileges to these data.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Breast cancer is one of the most common carcinomas worldwide, especially among females [1]. The prognosis of patients with early stage breast cancer is favorable, but patients with lymph node (LN) metastasis usually have a poor prognosis; the more metastatic lymph nodes identified, the worse the long-term survival [2]. In the American Joint Committee on Cancer (AJCC)/International Union Against Cancer (UICC) tumor-node-metastasis (TNM) classification [3], positive LNs are classified into 3 subgroups: N1 (1–3 LNs), N2 (4–9 LNs) and N3 (10 or more LNs). The staging system can discriminate prognostic groups very well. However, it is difficult to correctly assess a patient’s TNM classification. For example, one of the classic questions is the minimum number of LNs that should be dissected. Unfortunately, the number reported in the literature is inconsistent, ranging from 5 to 15 [4–8].

In addition to the total number of LNs excised, many other parameters have been developed and validated for various malignancies, such as number of negative lymph nodes [9,10], ratio of involved to removed nodes (lymph node ratio, LNR) [11,12], and log odds of positive lymph nodes (LODDS) [13,14], to aid the TNM system in predicting the outcome more accurately. However, few studies have focused on the relationship between the number of negative LNs and prognosis of breast cancer. Kuru [9] compared the roles of total number of nodes removed, negative nodes removed, and ratio of positive nodes to removed nodes in breast cancer using small samples from a single institute. Vinh-Hung et al [15] investigated the effect of number of negative nodes on survival in early breast cancer using the Surveillance Epidemiology and End Results (SEER) database. To the best of our knowledge, this study is the first to evaluate the role of negative LN count in breast cancer according to N substage (N1, N2, and N3) using a population-based database.

Materials and methods

Patients

Patients were collected from the SEER database (2004–2013), which is a population-based cancer registry in the United States. The National Cancer Institute’s SEER*Stat software (Version 8.2.0) was applied to identify patients with breast cancer. Included in the study were patients more than 18 years old, who had received surgical treatment and a pathologically confirmed diagnosis of breast cancer. The exclusion criteria were as follows: (1) patients for whom the number of examined or positive regional lymph nodes was 0 or unknown; (2) patients with distant metastasis (M1); (3) patients with a history of prior malignancy; and (4) patients with chemotherapy or radiotherapy before surgery. We retrieved baseline and clinical characteristics, including sex, age, race, tumor grade, T stage according to the 6th and 7th edition of AJCC criteria, estrogen receptor (ER) status, progesterone receptor (PR) status and human epidermal growth factor receptor 2 (HER2) status. All methods were carried out in accordance with relevant guidelines and regulations. All experimental protocols were approved by the Bioethics Committee of the Affiliated XuZhou Hospital of Medical College of Southeast University, China. Informed consent was obtained from all subjects in the SEER database.

Statistical analysis

Data about baseline and clinical characteristics were presented as count and percent values. The selection of the subgroups in the negative number of lymph nodes was determined by X-tile software (Yale University, Version 3.6.1). Overall survival (OS) and disease-specific survival (DSS) were evaluated by the Kaplan-Meier method. OS was calculated from the time of initial diagnosis to last follow-up or death, and DSS was defined as the interval from diagnosis until death due to breast cancer. Multivariate analyses for OS and DSS of breast cancer were performed by Cox regression models with adjusted hazard ratios (HRs). P values < 0.05 were considered statistically significant. All analyses were conducted utilizing PASW Statistics 18 software.

Results

A total of 125981 patients with breast cancer and positive LNs were selected from the SEER database, including 87523 cases with N1 substage, 26350 cases with N2 substage, and 12108 cases with N3 substage. Baseline and clinical characteristics are shown in Table 1. Most patients were female (99.1%), and the median age was 56 years old. The majority of patients had early T stage (T1 accounting for 37.7%, T2 accounting for 44.7%). The number of negative LNs for the cohort ranged from 0 to 77, and the median number was 8.

thumbnail
Download:
Table 1. Demographic and tumor characteristics for breast cancer patients with positive lymph nodes.

https://doi.org/10.1371/journal.pone.0193784.t001

During the follow-up period, 21679 (17.2%) patients in the entire cohort died. Overall, 14729 patients died from breast cancer, accounting for 67.9% (14729/21679) of total deaths. Taking into consideration the optimal cutoff number of negative LNs acquired by X-tile software in N1, N2 and N3 substage and the number of negative LNs in each subgroup, four negative LNs were categorized as an interval. The N1, N2 and N3 substage were divided into 4 subgroups: 0–3, 4–7, 8–11 and more than 11. OS and DSS for N1, N2 and N3 substage stratified by 4 subgroups are presented in Fig 1A, 1B, 1C, 1D, 1E and 1F. For all three N substages, the differences in both OS and DSS were statistically significant (P < 0.001). It should be noted that there was no difference between N1 patients with 4–7 negative LNs and those with 8–11 for OS (P > 0.05). No significant differences were observed among N1 patients with subgroups 4–7, 8–11 and more than 11 for DSS (P > 0.05). All the survival curves indicated that patients with more negative LNs had better outcomes, especially for N2 and N3 substage.

thumbnail
Download:
Fig 1.

The OS of substage N1, N2 and N3 for breast cancer is shown in A, C and E, respectively. The DSS of substage N1, N2 and N3 for breast cancer is shown in B, D and F, respectively.

https://doi.org/10.1371/journal.pone.0193784.g001

The effect of negative LNs on prognosis was evaluated by multivariate analyses (Tables 2 and 3). The number of negative LNs was an independent prognostic factor for OS and CSS in each N substage. A larger number of negative LNs had a more positive effect on the prognosis of breast cancer. N2 disease was most influenced; patients with more than 11 negative LNs compared with patients with 0–3 negative LNs had 48.9% of the death risk for OS (95% CI, 0.455 to 0.526, respectively) and 43.9% for DSS (95% CI, 0.403 to 0.478, respectively). Additionally, T stage, ER status (positive vs. negative), PR status (positive vs. negative), HER2 status (positive vs. negative), grade (well or moderately differentiated vs. poorly differentiated or undifferentiated), age (≤55 years vs. >55 years) and race (white vs. black) were independent prognostic factors for all patients. Sex did not always influence mortality independently. For example, sex had no effect on either OS or DSS for N3 substage (P = 0.360, P = 0.495, respectively).

thumbnail
Download:
Table 2. Multivariate analyses for OS in breast cancer patients with positive lymph nodes.

https://doi.org/10.1371/journal.pone.0193784.t002

thumbnail
Download:
Table 3. Multivariate analyses for DSS in breast cancer patients with positive lymph nodes.

https://doi.org/10.1371/journal.pone.0193784.t003

Discussion

The TNM classification system attempts to account for most basic parameters of cancer, to provide guidance for treatment planning and to predict the outcome. The number of positive LNs has been the focus on for a long time. In the present study, for the first time, we analyzed the prognostic significance of negative LNs in breast cancer patients. We observed a critical relationship between negative lymph node count and survival, independent of patient characteristics and other related molecular variables including PR status, ER status, HER2 ststus, depth of tumor invasion and degree of differentiation.

Although the number of negative LNs has an apparent effect on survival in each N stage, the mechanism underlying the relationship between negative LNs and survival remains unconfirmed. It has been reported that stage migration probably occurs due to under-evaluation of total lymph nodes, which has an intimate connection with the number of positive and negative LNs, thus influencing on pathological stage. Examining more lymph nodes can more accurately identify metastasis, thus avoiding misclassification of pathological stage [16].

Another possible hypothesis is that the number of negative LNs reflects the host lymphocytic reaction to tumor. The interaction between host and tumor contributes to the size or count of lymph nodes, and the increase of negative LNs indicates that the host takes a predominant position when competing with a tumor, and consequently obtains longer survival. A similar hypothesis has been associated with longer survival in colorectal cancer [17,18].

The number of lymph nodes informs the surgical approach, classification of pathological stage and institutional care. It has been reported that the number of lymph nodes may have a connection with better care overall and may not affect outcome directly [19–22]. There are also studies showing that the removal of more lymph nodes leads to a better prognosis [11]. Negative lymph nodes, clinically, imply that cancer cells were not observed using microscopy, instead of absolute no-tumor-metastasis, which means that there may be micro-metastasis of cancer cells. In other words, positive lymph nodes examined on routine pathological analysis do not necessarily reflect lymph node metastasis. For approximately 9%-30% of breast cancer patients, there are micro-metastases in their axillary lymph nodes that are undetectable by routine pathological examination [23]. Lymph node micro-metastasis is a strong risk factor for tumor-free survival and metastatic recurrence [24]. Therefore, the increase of the negative lymph node count, to a certain extent, can avoid the adverse effects of lymph node micro-metastasis and improve the prognosis of patients [25,26].

The rate of LNR was not used in this study to assess the prognosis of patients. LNR refers to the ratio of the number of metastatic lymph nodes to the total number of lymph nodes cleared. In recent years, many studies have indicated that LNR is superior to pN staging in reflecting axillary lymph node status and predicting prognosis [11, 27–31]. PN staging depends on the number of positive lymph nodes and the total number of lymph nodes cleared. Different from pN staging, LNR balances the potential influencing factors. It can better reflect axillary lymph node stage, as well as prognosis [32,33]. In a meta-analysis study, Woodward also suggested that LNR is better as a prognostic index than the number of metastatic lymph nodes [34].

In addition, we only selected patients from the SEER database to analyze survival and prognostic factors. It is necessary for us to obtain more detailed information to confirm the relationship between negative LNs and survival.

In conclusion, we confirmed, for the first time, the relationship between negative lymph node count and prognosis of breast cancer in substage N2 and N3. The analysis is consistent with the presentation of colorectal cancer: more negative LNs imply longer survival [35–38]. It is of great importance to provide more information about the prognosis of breast cancer by statistical analysis of negative lymph nodes, which can serve as a useful supplement to the current pathological system.

Supporting information

S1 File. Detailed data of all the patients from SEER.

https://doi.org/10.1371/journal.pone.0193784.s001

(XLSX)

References

  1. 1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A. Global cancer statistics, 2012. CA Cancer J Clin. 2015; 65: 87–108. pmid:25651787
  2. 2. Fisher B, Bauer M, Wickerham DL, Redmond CK, Fisher ER, Cruz AB, et al: Relation of number of positive axillary nodes to the prognosis of patients with primary breast cancer. An NSABP update. Cancer. 1983; 52: 1551–1557. pmid:6352003
  3. 3. Edge SB, Compton CC. The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM. Ann Surg Oncol. 2010; 17: 1471–1474. pmid:20180029
  4. 4. Rosen PP, Lesser ML, Kinne DW, Beattie EJ. Discontinuous or "skip" metastases in breast carcinoma. Analysis of 1228 axillary dissections. Ann Surg. 1983; 197: 276–283. pmid:6830335
  5. 5. Van Lancker M, Goor C, Sacre R, Lamote J, Van Belle S, De Coene N, et al. Patterns of axillary lymph node metastasis in breast cancer. Am J Clin Oncol. 1995; 18: 267–272. pmid:7747717
  6. 6. Axelsson CK, Mouridsen HT, Zedeler K. Axillary dissection of level I and II lymph nodes is important in breast cancer classification. The Danish Breast Cancer Cooperative Group (DBCG). Eur J Cancer. 1992; 28: 1415–1418.
  7. 7. Graversen HP, Blichert-Toft M, Andersen JA, Zedeler K. Breast cancer: risk of axillary recurrence in node-negative patients following partial dissection of the axilla. Eur J Surg Oncol. 1988; 14: 407–412. pmid:3181444
  8. 8. Somner JE, Dixon JM, Thomas JS. Node retrieval in axillary lymph node dissections: recommendations for minimum numbers to be confident about node negative status. J Clin Pathol. 2004; 57: 845–848. pmid:15280406
  9. 9. 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. 2006; 32: 1082–1088. pmid:16887320
  10. 10. Karlsson P, Cole BF, Price KN, Coates AS, Castiglione-Gertsch M, Gusterson BA, et al. The role of the number of uninvolved lymph nodes in predicting locoregional recurrence in breast cancer. J Clin Oncol. 2007; 25: 2019–2026. pmid:17420511
  11. 11. Tausch C, Taucher S, Dubsky P, Seifert M, Reitsamer R, Kwasny W, et al. Prognostic value of number of removed lymph nodes, number of involved lymph nodes, and lymph node ratio in 7502 breast cancer patients enrolled onto trials of the Austrian Breast and Colorectal Cancer Study Group (ABCSG). Ann Surg Oncol. 2012; 19: 1808–1817. pmid:22207051
  12. 12. Vinh-Hung V, Verschraegen C, Promish DI, Cserni G, Van de Steene J, Tai P, et al. Ratios of involved nodes in early breast cancer. Breast Cancer Res. 2004; 6: 680–688. pmid:15535850
  13. 13. La Torre M, Nigri G, Petrucciani N, Cavallini M, Aurello P, Cosenza G, et al. Prognostic assessment of different lymph node staging methods for pancreatic cancer with R0 resection: pN staging, lymph node ratio, log odds of positive lymph nodes. Pancreatology. 2014; 14: 289–294. pmid:25062879
  14. 14. Arslan NC, Sokmen S, Canda AE, Terzi C, Sarioglu S. The prognostic impact of the log odds of positive lymph nodes in colon cancer. Colorectal Dis. 2014; 16: 386–392. pmid:24980876
  15. 15. Vinh-Hung V, Cserni G, Burzykowski T, van de Steene J, Voordeckers M, Storme G. Effect of the number of uninvolved nodes on survival in early breast cancer. Oncol Rep, 2003; 10: 363–368. pmid:12579273
  16. 16. Aurello P, D'Angelo F, Rossi S, Bellagamba R, Cicchini C, Nigri G, et al. Classification of lymph node metastases from gastric cancer: comparison between N-site and N-number systems. Our experience and review of the literature. Am Surg. 2007; 73: 359–366. pmid:17439029
  17. 17. Pagès F, Galon J, Fridman WH. The essential role of the in situ immune reaction in human colorectal cancer. J Leukoc Biol. 2008; 84: 981–987. pmid:18559950
  18. 18. Morris M, Platell C, Iacopetta B. Tumor-infiltrating lymphocytes and perforation in colon cancer predict positive response to 5-fluorouracil chemotherapy. Clin Cancer Res. 2008; 14: 1413–1417. pmid:18316563
  19. 19. Schrag D, Panageas KS, Riedel E, Hsieh L, Bach PB, Guillem JG, et al. Surgeon volume compared to hospital volume as a predictor of outcome following primary colon cancer resection. J Surg Oncol. 2003; 83: 68–78. pmid:12772198
  20. 20. Kaiser AM, Nunoo-Mensah JW, Wasserberg N. Re: Surgical volume and long-term survival following surgery for colorectal cancer in the Veterans Affairs Health-Care System. Am J Gastroenterol. 2005; 100: 250. pmid:15654811
  21. 21. Aslam MI, Venkatesh J, Jameson JS, West K, Pringle JH, Singh B. Identification of high-risk Dukes B colorectal cancer by microRNA expression profiling: a preliminary study. Colorectal Dis. 2015; 17: 578–588. pmid:25557290
  22. 22. Goldstein NS. Lymph node recoveries from 2427 pT3 colorectal resection specimens spanning 45 years: recommendations for a minimum number of recovered lymph nodes based on predictive probabilities. Am J Surg Pathol. 2002; 26: 179–189. pmid:11812939
  23. 23. Al-Shibli KI, Mohammed HA, Mikalsen KS. Sentinel lymph nodes and breast carcinoma: analysis of 70 cases by frozen section. Ann Saudi Med. 2005; 25: 111–114. pmid:15977687
  24. 24. Querzoli P, Pedriali M, Rinaldi R, Lombardi AR, Biganzoli E, Boracchi P et al. Axillary lymph node nanometastases are prognostic factors for disease-free survival and metastatic relapse in breast cancer patients. Clin Cancer Res. 2006; 12: 6696–6701. pmid:17121888
  25. 25. Gyorki DE, Henderson MA. Significance of sentinel lymph node micrometastases in patients with breast cancer. J Clin Oncol. 2010; 28: e139. pmid:20159811
  26. 26. de Boer M, van Deurzen CH, van Dijck JA, Borm GF, van Diest PJ, Adang EM, et al. Micrometastases or isolated tumor cells and the outcome of breast cancer. N Engl J Med. 2009; 361: 653–663. pmid:19675329
  27. 27. Dings PJ, Elferink MA, Strobbe LJ, de Wilt JH. The prognostic value of lymph node ratio in node-positive breast cancer: a Dutch nationwide population-based study. Ann Surg Oncol. 2013; 20: 2607–2614. pmid:23536053
  28. 28. Schiffman SC, McMasters KM, Scoggins CR, Martin RC, Chagpar AB. Lymph node ratio: a proposed refinement of current axillary staging in breast cancer patients. J Am Coll Surg. 2011; 213:45–52. pmid:21601490
  29. 29. Vinh-Hung V, Verkooijen HM, Fioretta G, Neyroud-Caspar I, Rapiti E, Vlastos G, et al. Lymph node ratio as an alternative to pN staging in node-positive breast cancer. J Clin Oncol. 2009; 27: 1062–1068. pmid:19164210
  30. 30. Vinh-Hung V, Nguyen NP, Cserni G, Truong P, Woodward W, Verkooijen HM, et al. Prognostic value of nodal ratios in node-positive breast cancer: a compiled update. Future Oncol. 2009; 5: 1585–1603. pmid:20001797
  31. 31. Voordeckers M, Vinh-Hung V, Van de Steene J, Lamote J, Storme G. The lymph node ratio as prognostic factor in node-positive breast cancer. Radiother Oncol. 2004; 70: 225–230. pmid:15064006
  32. 32. Martin FT , O'Fearraigh C, Hanley C, Curran C, Sweeney KJ, Kerin MJ. The prognostic significance of nodal ratio on breast cancer recurrence and its potential for incorporation in a new prognostic index. Breast J. 2013; 19: 388–393. pmid:23721403
  33. 33. Ahn SH, Kim HJ, Lee JW, Gong GY, Noh DY, Yang JH, et al. Lymph node ratio and pN staging in patients with node-positive breast cancer: a report from the Korean breast cancer society. Breast Cancer Res Treat, 2011; 130: 507–515. pmid:21858659
  34. 34. Woodward WA, Vinh-Hung V, Ueno NT, Cheng YC, Royce M, Tai P, et al. Prognostic value of nodal ratios in node-positive breast cancer. J Clin Oncol. 2006; 24: 2910–2916. pmid:16782931
  35. 35. Jestin P, Påhlman L, Glimelius B, Gunnarsson U. Cancer staging and survival in colon cancer is dependent on the quality of the pathologists' specimen examination. Eur J Cancer. 2005; 41: 2071–2078. pmid:16125926
  36. 36. Chang GJ, Rodriguez-Bigas MA, Skibber JM, Moyer VA. Lymph node evaluation and survival after curative resection of colon cancer: systematic review. J Natl Cancer Inst. 2007; 99: 433–441. pmid:17374833
  37. 37. George S, Primrose J, Talbot R, Smith J, Mullee M, Bailey D, et al. Wessex Colorectal Cancer Audit Working Group. Will Rogers revisited: prospective observational study of survival of 3592 patients with colorectal cancer according to number of nodes examined by pathologists. Br J Cancer. 2006; 95: 841–847. pmid:16969342
  38. 38. Iachetta F, Reggiani Bonetti L, Marcheselli L, Di Gregorio C, Cirilli C, Messinese S, et al. Lymph node evaluation in stage IIA colorectal cancer and its impact on patient prognosis: a population-based study. Acta Oncol. 2013; 52: 1682–1690. pmid:23786176