|Year : 2015 | Volume
| Issue : 5 | Page : 6-11
A new perspective on the IIIC staging in Chinese patients with primary breast cancer: Single-center experiences
ZH Yu1, ZJ Yang1, Q Chen2, F Xing1, B Zhang1, XC Cao1
1 The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital; Key Laboratory of Cancer Prevention and Therapy; Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin, China
2 The Pneumology Department of Chest Hospital, Tianjin, China
|Date of Web Publication||3-Nov-2015|
X C Cao
The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital; Key Laboratory of Cancer Prevention and Therapy; Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer; Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin
Source of Support: None, Conflict of Interest: None
Purpose: The purpose of this retrospective study was to investigate whether Stage IIIC (TanyN3M0) breast cancer can be classified further into subgroups with different prognosis. Materials and Methods: One hundred and thirty-two patients with Stage IIIC breast cancer at Tianjin Medical University Cancer Institute and Hospital were analyzed. The disease-free survival (DFS) and overall survival (OS) were calculated by Kaplan–Meier method for lymph node ratio (LNR) and the number of positive lymph node (PLN). The receiver operating characteristic curve analysis was performed to determine the optimal cut-off value of the LNR and PLN. The univariate and multivariate analysis were applied to identify the prognostic factors. Results: The results showed that the optimal cut-off value of LNR value was 0.65, and the optimal cut-off value of PLN was 15. The Kaplan–Meier survival analysis showed the higher value of LNR or PLN was correlated with shortened DFS (P = 0.002, P = 0.008, respectively) and OS (P < 0.001, P = 0.001, respectively). In multivariate survival analysis, the value of LNR and PLN were still remained as independent prognostic factors for DFS (P = 0.014, P = 0.013, respectively) and OS (P = 0.004, P = 0.002, respectively). Conclusion: These results suggest that the value of LNR or PLN could be used as a new significant prognostic biomarker for Stage IIIC breast cancer patients. Stage IIIC breast cancer patients with lower value of LNR or PLN may be down staged.
Keywords: Breast cancer, lymph node ratio, positive lymph node, prognostic factors, Stage IIIC
|How to cite this article:|
Yu Z H, Yang Z J, Chen Q, Xing F, Zhang B, Cao X C. A new perspective on the IIIC staging in Chinese patients with primary breast cancer: Single-center experiences. Indian J Cancer 2015;52, Suppl S1:6-11
|How to cite this URL:|
Yu Z H, Yang Z J, Chen Q, Xing F, Zhang B, Cao X C. A new perspective on the IIIC staging in Chinese patients with primary breast cancer: Single-center experiences. Indian J Cancer [serial online] 2015 [cited 2021 Jul 31];52, Suppl S1:6-11. Available from: https://www.indianjcancer.com/text.asp?2015/52/5/6/168956
| » Introduction|| |
Breast cancer is one of the most commonly diagnosed cancers and a major cause of cancer-related death in women in China. Patients with Stage III breast cancer are accounted for about 6–7% of all invasive breast cancer cases annually in the world., The high chance of relapse and mortality rates are two characteristics of Stage III breast cancer. Over the past three decades in China, nationwide retrospective studies showed that the cases of breast cancer have been steadily increasing and has become the most common malignancy in large cities, such as Shanghai. Compared to developed countries, women in China suffered from breast cancer at a much younger age and tended to have a more advanced cancer at the time of preliminary diagnosis. So, it is necessary to define potential prognostic differences that could affect the staging system of breast cancer in developing countries.
The tumor-node-metastasis (TNM) system had been widely used for breast cancer to stratify patients into comparable groups and had provided valuable information for appropriate treatment options. The system could also predict a long-term outcome for the patients. However, there are many controversies on the TNM system; therefore, this staging system needs to be updated continuously and dynamically. In comparison of the 6/7th to 5th edition of the American Joint Committee on Cancer (AJCC) TNM classification, TanyN3M0 was spun off as a separate subgroup as Stage IIIC because TanyN3M0 were considered as the worst prognostic stage in Stage III. However, it had been reported that the prognostically different subgroups existed among Stage IIIC breast cancer.,
Axillary lymph node status was one of the most important prognostic factors , for breast cancer staging recommended by AJCC ever since 2002. The pN staging (the number of positive lymph nodes [PLNs]) is the standard criterion to classify breast cancer and has been incorporated into routine clinical decision making. However, the number of identified PLNs depends on the number of lymph nodes dissected and examined, which would vary based on the surgical and pathologic procedures used. In order to improve the prognostic scoring system, we should intuitively take into account not only the number of PLNs but also the number of nodes examined. Increasing evidence suggests that the lymph node ratio (LNR) (the ratio of the number of positive nodes to the total number of nodes excised) is a superior prognostic indicator as compared to the absolute number of nodes involved,,,, because it considers the fact that some lymph nodes has not been examined. Furthermore, Woodward et al. conducted a systematic review of 24 articles that had enrolled 32,299 patients in total and again confirmed the superiority of LNR. However, Wang et al. suggests that only in patients with pN3 could LNR have a prognostic advantage over pN.
In addition to axillary lymph node status, the prognosis is determined by a variety of factors, including age, tumor size, grade, receptors status, and treatment. To the best of our knowledge, there was sparse data assessing the addition of previously mentioned factors combining with LNR to predict overall survival (OS) and disease-free survival (DFS) in patients with pN3, in spite of the large number of studies that have addressed the prognostic value of LNR over the current pN staging. It was exciting to think that the combination of these prognostic factors with LNR could bring us closer to something that TNM currently does not provide in terms of precise prognosis for an individual cancer patient.
In this study, we aimed to retrospectively analyze clinicopathological characteristics and prognostic factors of the Stage IIIC breast cancer patients in China. What is more, we assessed the added prognostic value of LNR and PLN and set ideal cut-off value of them to distinguish between patient subgroups with significantly different prognosis so as to bring forward a new proposal on the current staging system of Stage IIIC. Based on our study, we could better evaluate the prognosis of Chinese breast cancer patients and deliver more precise protocol correspondently.
| » Materials and Methods|| |
From January 2001 to December 2005, a retrospective analysis was conducted in 2442 patients diagnosed with breast cancer, and a total of 144 patients with Stage IIIC breast cancer who underwent mastectomy at Tianjin Medical University Cancer Institute and Hospital in Tianjin, People's Republic of China. All of the patients included in the analysis met the following inclusion criteria: (1) Patients in Stage IIIC confirmed by histopathology, (2) all patients must have received breast surgery plus axillary dissection (Level I and Level II) and at least 15 lymph node examined for pathological diagnosis, (3) none of the patients had received either sentinel lymph node biopsy or neoadjuvant therapy, (4) all the patients had received radiotherapy. We excluded 3 patients with a prior history of cancer and 9 patients who had undergone neoadjuvant chemotherapy. Therefore, 132 patients remained and analyzed in this study. Informed consents were obtained from all the patients above, and research protocol for this study was approved by the Ethics Committees at the Tianjin Medical University Cancer Institute and Hospital.
The patient's clinicopathological characteristics were obtained retrospectively from their medical records and evaluated as prognostic factors. The LNR was calculated as the total number of PLNs divided by the total number of lymph nodes dissected, and the PLN was calculated as the total number of PLNs.
In our hospital, patients were followed up in our outpatient department every 6 months for the first 3 years after their surgery, then annually. Records of medical history, physical examination, ultrasound, and chest X-ray were collected and performed to observe regional recurrence or distant metastasis during the follow-ups. The last follow-up was until 28 July 2014, the mean follow-up was 69 (range 10–122) months, and OS data were obtained from medical records or by telephone calls or letter writing.
All statistical analysis were carried out using the package SPSS for windows 18.0 (Chicago, USA). OS was defined as a measurement to measure from the first surgery to the death of last follow-up or cancer-related death during follow-ups. DFS was defined as a duration of time between the date of the first surgery and the first regional recurrence or distant metastasis, or the last follow-up. In order to evaluate the sensitivity and specificity for the OS and DFS, the receiver operating characteristic (ROC) curve was calculated, and the Youden index was estimated to determine the optimal cut-off value for the LNR or PLN. In order to examine, if LNR or PLN was associated with DFS and OS, the Kaplan–Meier method and log-rank test were performed. For multivariable analysis, Cox proportional hazard model was applied. Multivariate survival analysis was performed using a stepwise forward procedure to derive a final model of the variables that had a significant independent relationship with DFS and OS. All tests were two-sided. P < 0.05 or a 95% confidence interval (CI) that did not include one was considered to be significant.
| » Results|| |
A total of 132 Stage IIIC breast cancer patients were analyzed in this study [Table 1]. The median age of the patients was 50 (range: 23–80) years old. After their surgery, a total of 128 patients (96.7%) received adjuvant chemotherapy.
We use the 5-year OS as an endpoint to get the optimal cut-off value of LNR or PLN. When the LNR was 0.65 or the PLN was 15, the Youden index is calculated as sensitivity - (1 - specificity) was maximal. Therefore, we set the cut-off value of LNR at 0.65, and the cut-off value of PLN was 15. Then, 73 patients (55.3%) with an LNR ≥ 0.65 and 84 patients (63.6%) with a PLN ≥ 15 were classified into LNR-high or PLN-high groups, respectively.
At the last time of follow-ups, 55 out of 132 (41.7%) patients were alive and disease-freed, 14 (10.6%) were alive with recurrent cancer, and 63 (47.7%) died of recurrent cancer. In the Kaplan–Meier analysis and log-rank tests, we found that the higher value of LNR or PLN was correlated with shortened DFS (P = 0.002, P = 0.008, respectively) and OS (P < 0.001, P = 0.001, respectively). As shown in [Figure 1], the 5-year DFS rate was 64.4% in the LNR-low group and 30.8% in the LNR-high group (P = 0.002). The 5-year OS rate was 77.6% in the LNR-low group and 45.9% in the LNR-high group (P < 0.001). As shown in [Figure 2], the 5-year DFS rate was 66.0% in the PLN-low group and 35.1% in the PLN-high group (P = 0.008). The 5-year OS rate was 78.3% in the PLN-low group and 50.1% in the PLN-high group (P = 0.001). When these variables were analyzed with Cox proportional hazard model [Table 2]a and [Table 2]b, LNR and PLN were still remained independent risk factors for both DFS (heart rate [HR] 1.85, 95% CI 1.13–3.02, P = 0.014 and HR 1.90, 95% CI 1.14–3.15, P = 0.013, respectively) and OS (HR 2.31, 95% CI 1.23–4.09, P = 0.004 and HR 2.68, 95% CI 1.42–5.05, P = 0.02, respectively).
|Figure 1: Kaplan–Meier disease-free survival and overall survival analysis of breast cancer|
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|Figure 2: Kaplan–Meier disease-free survival and overall survival analysis of breast cancer|
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| » Discussion|| |
The latest (2009) 7th version of the AJCC TNM classification for breast carcinoma did not make any modifications of pN staging compared with the former 6th edition in 2002. The classification of nodal status according to the number of lymph nodes with metastasis in the axilla still plays an important role in the staging of breast cancer patients. Moreover, pN3 disease group consists of patients with 10 or more metastatic axillary lymph nodes. In relation to this classification, patients in Stage IIIC, which comprises patients with TanyN3M0 disease, were considered as the second poorest prognostic stage after patients in Stage IV. Although this classification had been well accepted, the investigations had been carried out to test and verify whether the Stage IIIC breast cancer was a prognostically homogeneous group. It had been reported that the prognostically different subgroups existed among patients with IIIC breast cancer.,
Accurate evaluation is fundamental for personalized treatment. Axillary lymph nodes status is one of the three components of the TNM classification. However, the traditional breast cancer classification mainly determined by the basic PLNs is insufficient to reveal the “real” state of breast cancer, or to meet the needs of individualized care. Over the past few years, an increasing number of studies have been performed to evaluate the value of new breast cancer classification by LNR in breast cancer survival prediction. LNR classification showed superiority over Union for International Cancer Control/AJCC pN classification in predicting the prognosis of not merely breast cancer but also a colorectal and gastric cancer.,,,,, This superiority was true as compared to using total number of dissected lymph nodes as a prognostic factor. However, the appropriate cut-off point of LNR was still under depute in different studies for breast cancer based on different research objects. The cut-off point of LNR and follow-up time were not uniform in initial small-scale studies. Truong et al. chose the patients diagnosed with T1, 2N0, 1M0 breast cancer as the study subject and demonstrated 0.25 as an ideal cut-off point for LNR. Vinh-Hung et al., obtained optimal cut-off values of LNR (0.20 and 0.65) for breast cancer stratification in a large-scale, long-term, patient follow-up study. They came up with a more stable, reliable prognostic separation than traditional pN classification. Furthermore, there were other researchers who set the cut-off values at different levels (such as 0.50, 0.75, 0.85, etc.,),,,,,,, according to diverse conditions of breast cancer patients. In order to get the optimal cut-off value for the LNR in predicting the prognosis of patients with Stage IIIC breast cancer, we used an ROC curve analysis to get the optimal cut-off value. We found that the optimal cut-off value was determined to be 0.65. Based on the cut-off value, the patients were divided into LNR-low and LNR-high group.
The previously studies have reported that LNR has an impact on the outcomes of patients in several malignant cancers.,,, In line with these studies, we also demonstrated that the LNR could predict the outcomes of patients with Stage IIIC breast cancer, and we found that patients in LNR-low group had better outcomes than those patients in LNR-high group. The 5-year DFS and 5-year OS rates were 64.4% and 77.6% in the LNR-low group and 30.8% and 45.9% in the LNR-high group, respectively.
In the following multivariate Cox regression analysis, the result of our study reflected that LNR was an independent prognostic factor for predicting DFS and OS in patients with Stage IIIC breast cancer patients [Table 2]a. We then further validated this cut-off point by making sure that it could separate the IIIC patients into significantly different prognostic subgroups.
In the same method, we get the optimal cut-off value of PLN; we found that the optimal cut-off value was determined to be 15. Based on the cut-off value, the patients were divided into PLN-low and PLN-high group. In our present study, the results showed that patients with higher value of PLN had poor outcomes compared with lower value of PLN [Table 2]b. The 5-year DFS and OS rates were 66.0% and 78.3% in the PLN-low group and 35.1% and 50.1% in the PLN-high groups, respectively. Patients with a higher level of PNI had a worse DFS (HR: 1.90, 95% CI 1.14–3.15, P = 0.013) and OS (HR: 2.68, 95% CI 1.42–5.05, P = 0.02). These results suggest that patients a high level of PLN will lead to a high risk of aggressive potential of Stage IIIC breast cancer patients, and that is associated with a poor DFS and OS.
To the best of our knowledge, the LNR or PLN is a better predictor for patient survival. However, our study is the first to evaluate the value of LNR and PLN classification system by specifically targeting the Chinese breast cancer population with pN3 stage which usually yields a worse outcome. Treatment strategies for patients with N3 disease as a homogenous group have not been able to provide a significant improvement for survival in patients who had a potential worse prognosis. Meanwhile, under China's current medical conditions, the patient would be considered as advanced-stage cancer patients by the time they were diagnosed of IIIC breast cancer. By then, these patients might give up their systemic therapies due to their financial burden. What is more, clinicians would also take expectant treatments to alleviate these patients' sufferings as well as to relieve their economic burden. Therefore, if prognostically different subgroups can be identified within this patient group, and the IIIC breast cancer with better prognosis may be downstage, different treatment modalities for these patients may be more beneficial. We could take more effective treatments to those patients with downstage IIIC breast cancer to obtain a better prognosis. Furthermore, the comparison of the various studies' findings would be more reliable after our study's finding.
The limitations of this study should be taken into account. First, the result came from a retrospective and single-centered study, which lessens the power of these findings and fails to reflect the complete epidemiology of the Chinese patients with pN3 breast cancer. Second, we made mortality as our endpoint regardless of different causes of death, because we do not have clear data of all causes of death in those patients. Third, there were additional information such as human epidermal growth factor receptor 2 status, socioeconomic status, and comorbidity that we were unable to gather, which could lead to a deeper statistical biases in the selection of patients. Therefore, the cut-off value of LNR or PLN in pN3 staging patients' needs further studies to better reflect Chinese population.
| » Conclusion|| |
Our present study demonstrated that LNR or PLN, which could be easily measured and served as an independent prognostic factor for predicting the outcomes for Stage IIIC breast cancer patients after surgery. Patients with a higher level of LNR or PLN are associated with a poor DFS and OS than those patients with a lower value of LNR or PLN. Therefore, we suggest that the LNR or PLN should be included in the routine assessment of patients with Stage IIIC breast cancer patients.
| » Acknowledgments|| |
This research was funded by the National Natural Science Foundation of China (Grant No. 81372843) and the Tianjin Municipal Nature Science Foundation (Grant No. 13JCYBJC21800).
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]