Abstract
Aim: The aim of this study was to assess the prognostic value of lymph node ratio (LNR) in premenopausal patients with luminal breast carcinoma. Materials and Methods: A total of 885 female patients who presented with axillary lymph node-positive luminal breast cancer between 2000 and 2009 were investigated. Using X-tile, we classified patients into low-, intermediate- and high-risk groups based on LNR. The Kaplan–Meier method was used to determine cumulative survival curves. Cox proportional hazards analyses were used to identify the factors that contributed to disease-free (DFS) and overall (OS) survival. Results: The median age of patients was 42 years (range=21-58 years). A training set of 295 patients and a validation set of 590 patients were used to determine the optimal LNR cut-off points (0.20 and 0.63). DFS was 87.7%, 77.4% and 53.9% (p<0.001) and OS was 91.5%, 76.7% and 50.9% (p<0.0001) for the low- (≤0.20), intermediate- (0.21-0.63) and high-risk (>0.63) groups, respectively. The 10-year DFS and OS rates were significantly longer in the low-risk group than in the high-risk group. Nomogram analysis demonstrated that LNR contributed more compared to nodal stage in predicting both DFS and OS. Conclusion: We conclude that LNR strongly predicts prognosis in premenopausal patients with lymph node-positive luminal breast cancer.
Breast cancer is currently the leading cause of tumor-related deaths in China (1) and the second leading cause of tumor-related deaths in females worldwide (2). Multidisciplinary approaches that include surgery, chemotherapy, radiotherapy and endocrine therapy are effective in reducing tumor recurrence and cancer-related death in selected patients. However, such patients have markedly different survival outcomes given the heterogeneity observed in their molecular expression profiles (3, 4). Age, which is closely associated with menopausal status, has been shown in analyses of large sample databases to be an important factor correlated with prognosis (5, 6). In addition, the proportion of patients with luminal A-like subtype has gradually declined and that of those with luminal B-like human epidermal growth factor receptor-2 (HER2-negative) disease has increased (7). Therefore, various studies have attempted to identify molecular biomarkers that can be used to predict breast cancer recurrence, and numerous promising biomarkers have been evaluated as potential prognostic predictors of breast cancer.
Endocrine therapy is a primary component of treatment regimens aimed at managing estrogen receptor (ER)-positive or progesterone receptor (PR)-positive breast cancer (8, 9). The Early Breast Cancer Trialists' Collaborative Group meta-analysis of 2000 demonstrated that women with hormone receptor-positive breast cancer had a 50% reduction in the annual rate of recurrence and a 31% reduction in breast cancer-related mortality after 5 years of adjuvant tamoxifen treatment (10). Currently, the standard endocrine therapy used to treat premenopausal women is a selective ER modulator, such as tamoxifen (11, 12). Recently, two phase III studies both indicated that the addition of ovarian function-suppressing drugs significantly improves disease-free survival (DFS) (13, 14). In addition, other trials have confirmed that 10 years of treatment with tamoxifen was more effective than 5 years of treatment with tamoxifen in treating early breast cancer (15). Few studies have examined which patients most benefit from longer-term tamoxifen treatment; hence, this evidence should be further explored to distinguish its effects on patients with luminal breast cancer.
Recurrence patterns are different among patients with luminal, HER2-enriched or triple-negative breast cancer (16). Recurrence tests, such as Adjuvant! Online and Oncotype DX, can be used to determine an individual's risk of developing recurrent cancer (17). The St. Gallen consensus, conducted from 2009 to 2013, suggested that age, tumor size, lymph node stage, ER/PR status, HER2 expression and molecular subtype were prognostic factors in early-stage breast cancer (18, 19). Recently, the results of several prognostic models for breast cancer were compared, including the Breast Cancer Index, Oncotype DX recurrence scores (20), IHC4 scores (21) and the HOXB13/IL17BR (H/I) index (22), to produce a model that can predict the risk of disease recurrence. In addition, a study from the CALGB9741 trial that used body mass index (BMI) and PAM50 analyses determined that baseline BMI and molecular subtype affected patient prognosis (23). Given the biological heterogeneity of cancer, the present staging system, even when used in combination with molecular subtype information, remains inadequate in predicting breast cancer prognosis. Therefore, we hypothesized that additional biomarkers could complement nodal staging. These additional biomarkers could be used in combined sets to improve the prognostic stratification of patients with breast cancer.
Lymph node ratio (LNR) is considered an attractive potential biomarker that complements TNM classification in breast cancer. In addition, the LNR has been reported in breast cancer and identified as an important factor in many different types of cancer, such as head and neck cancer, esophageal cancer, melanoma, oral cavity squamous cell carcinoma and non-small cell lung cancer (24-28). The LNR plays an important role in predicting locoregional recurrence, early distant metastasis and it can function as an alternative to pN staging in lymph node-positive breast cancer (29-31). However, patients presenting with different molecular subtypes and stages may benefit from different treatment strategies. A commercial panel of 21 genes was used to distinguish genotypes with a favorable prognosis from those with an unfavorable prognosis in luminal-A subtype patients, as recommended by the National Comprehensive Cancer Network (NCCN) guidelines (32). Scores on this panel were shown to affect the decisions that physicians made regarding patient treatment options (33). However, this panel is unavailable in many countries and it is expensive (34, 35). Therefore, the present study compared prognoses in patients with different LNRs and stage II premenopausal luminal breast cancer to provide information that might be useful in personalized therapies.
Materials and Methods
This retrospective analysis included patients with histologically proven unilateral invasive ductal breast cancer who were treated between January 2000 and December 2009 at Sun Yat-Sen University Cancer Center. No tissues, blood samples or private information was obtained from patients in this study. Therefore, this study was not required to be approved by the Ethics Committee of Sun Yat-Sen University Cancer Center.
All patients were staged according to the American Joint Committee on Cancer (AJCC 2010, seventh edition) TNM Staging System for Breast Cancer (36) evaluation was performed prior to neo-adjuvant therapy or surgery, depending on which procedure came first. Patients with distant metastases at the initial diagnosis who were also node-negative were excluded. The following information was collected, assessed and retrospectively reviewed: demographic features; tumor characteristics (pathological subtype, size, grade, lymphovascular invasion, hormone receptor status, and HER2 expression); treatment protocols (surgery, adjuvant chemotherapy, radiotherapy, hormonal therapy, and trastuzumab) and clinical outcomes.
We selected women with primary breast cancer who underwent axillary lymph node dissection. For each of these women, the total number of nodes examined was noted in the pathology report, and they were found to have presented with one or more involved (i.e. positive) lymph nodes. In addition, the selected patients were required to have the following criteria: undergone mastectomy, breast-conserving surgical treatment, or treatment with an adjuvant-selective ER modulator after chemotherapy and radiotherapy (if indicated); a known tumor size and premenopausal status, which was defined as regularly occurring menses or plasma follicle-stimulating hormone and estradiol level not in the postmenopausal range at diagnosis. Chemotherapy regimens were performed as recommended by NCCN guidelines for adjuvant chemotherapy.
Patients were excluded if they were peri-menopausal, which was defined as older than 45 years with a decrease in ovarian estrogen synthesis and chemotherapy-related amenorrhea, or postmenopausal and presented with the following: hormone receptor-negative breast cancer; evidence of metastasis or cancer in the contralateral breast; a prior history of malignancy including breast cancer; node-negativity; or pathologically confirmed in situ ductal carcinoma or in situ lobular carcinoma, or inflammatory breast cancer. Patients were also excluded if their medical records did not include the total number of nodes, only contained sentinel node information, or were incomplete and lacking information such as hormone receptor status and follow-up assessments. Tumor grades and histological classifications were based on WHO criteria (37). The ER and PR status of the primary tumor were determined using immunohistochemistry, and staining of >10% of cells was defined as positive. Patients were considered HER2-positive if HER2 protein expression measured 3+ intensity when examined using immunohistochemistry or they head amplification of the HER2/neu gene using fluorescence in situ hybridization.
A total of 885 female patients diagnosed with invasive breast carcinoma were included in the study. A flow chart describing the selection process is shown in Figure 1. The follow-up schedule was every 3-4 months within the first 3 years of treatment and 4-6 months after that if adjuvant endocrine therapy was regularly prescribed. All patients regardless of DFS events were followed-up until 31 Aug 2014 via out-patients clinic or via telephone.
Statistical analysis. Descriptive analyses were performed for demographic and clinical patient characteristics. The cut-off LNR value was determined using X-tile software (38). DFS was defined as the time from surgery to locoregional recurrence, distant metastasis, or death from any cause. Overall survival (OS) was defined as the time from surgery to death from any causes. Kaplan–Meier analysis was performed to examine the influence of predefined factors on survival, and log-rank tests were used to compare strata. Cox regression analysis was used to conduct a multivariate analysis of factors associated with OS or DFS. The first endpoint was DFS, and the second endpoint was OS. The statistical analysis was performed using SPSS software version 19.0 (IBM Corp., Armonk, NY, USA), MedCalcsoftware version 12.7 (MedCalc Software,Ostend, Belgium) and R software version 3.2.2 (The R Foundation for Statistical Computing, Vanderbilt University, Nashville, TN). Statistical significance was set at a value of p<0.05.
Results
Characteristics of patients with luminal breast cancer. The median follow-up duration was 92.98 months (range=6.93 to 176.16 months). A total of 885 female patients with breast cancer were enrolled in the study, with a median age of 42 years (range=21 to 58 years). A large majority of the patients (87%) had at least 10 or more lymph nodes removed. The mean tumor size was 3.30 cm (range=1.0 to 11.0 cm). The median positive number of lymph nodes and the total number of dissected axillary lymph nodes were 3.329 (range 1 to 51) and 16.198 (range 1 to 63), respectively. In addition, HER2 expression was positive in 180 of the tumors. Fifty-five patients who received neo-adjuvant chemotherapy were also included in this study. All of the patients included in the study received radiotherapy, chemotherapy, or hormone therapy either alone or in combination. The clinicopathological characteristics of the patients are shown in Table I.
Determining the cut-off point for LNR and its association with prognosis. In the first stage of multivariate analyses, clinical prognostic factors containing patient age at diagnosis, tumor size, grade, nodal stage, TNM stage, ER status, PR status, HER2 status, Ki67 index and LNR were included. The results indicated LNR was an independent prognostic factor for DFS (Table II).
Next, X-tile software was used to determine the lower and upper LNR values in these patients. X-Tile divided the cohort at a 1:2 ratio into two independent data sets, a test set and a validation set, determined the optimal cut-off points for LNR for the test set, and applied this value to the validation set. The results, shown in Figure 2 as distribution histograms, demonstrate a sharply defined lower LNR cut-off point of 0.20 and an upper LNR cut-off point of 0.63. Thereafter, we used this pair of cut-off points to classify patients with an LNR <0.20 as low risk, with an LNR between 0.21 and 0.63 as intermediate risk, and an LNR greater than 0.63 as high risk in predicting breast cancer recurrence. According to two cut-off points, the number of patients overlapping between LNR and pN3, pN2, pN1 in high-risk, intermediate-risk and low-risk groups were 109, 196 and 407, respectively (Figure 3).
For the whole patient cohort, univariate Kaplan–Meier survival estimates of DFS and OS were determined according to risk groups that were defined using upper and lower values of LNR of 0.20 and 0.63 (Figure 4A and B). We also determined Kaplan–Meier survival estimates for DFS and OS according to the risk groups that were defined by the LNR cut-off values of 0.20 and 0.65 (39). The results showed that patients in the high-risk group had significantly worse DFS and OS than patients in the other two groups (Figure 4C and D). The 10-year DFS rate for patients in the low-, intermediate-, and high-risk LNR groups were 87.7%, 77.4%, and 53.9%, respectively (log-rank chi-squared= 84.032, p<0.001). The 10-year OS rates for patients in the low-, intermediate-, and high-risk LNR groups were 91.5%, 76.7%, and 50.9%, respectively (log-rank chi-squared= 121.043, p<0.001).
LNR in predicting DFS and OS. Univariate analyses indicated that pN staging was significantly able to predict DFS (Tables II and III). Moreover, univariate analyses also showed that LNR was a significant factor for both DFS and OS (Tables II and III). Furthermore, in order to compare the accuracy of LNR to that achieved using pN staging in predicting DFS and OS, we confirmed that the area under the curve (AUC) for LNR was larger than that for pN staging (Figure 5A).
Multivariate analyses showed that patient age at diagnosis, tumor size, grade, nodal stage, TNM stage, ER status, HER2 status, Ki67 index and LNR were independent factors for DFS (Table II). In addition, we performed multivariate analyses of OS in which patient age at diagnosis, tumor grade, Ki67 index and LNR were also independent prognostic factors for OS (Table III). The above results indicate that LNR may predict DFS and OS.
Nomogram analysis included the factors age, tumor size, grade, nodal stage, TNM stage, ER status, PR status, HER2 status, Ki67 index and LNR. The results showed that LNR was the greatest contributor in predicting both DFS and OS (Figure 6).
Discussion
In this study, we demonstrated that patients in high- and intermediate-risk groups were at significantly higher risk for breast cancer recurrence than the patients in the low-risk group. The 10-year survival rate in the low-risk group was significantly higher than the rates in patients in the intermediate-risk and high-risk groups. We determined that LNR was the most important prognostic factor for both disease recurrence and mortality in premenopausal patients with node-positive luminal breast cancer.
Approximately 70% of human breast tumors express hormone receptors, such as the ER and PR. These receptors are the primary transcription factors that drive oncogenesis in hormone receptor-positive breast cancer (40). By contrast, invasive lobular carcinoma (ILC) represents the second most common breast cancer histological subtype, accounting for 10-15% of all breast cancer, and the vast majority of these tumors express hormone receptors (41). ILC differs from invasive ductal carcinomas in its epidemiology, clinicopathological features, and natural history, based on varied molecular subtypes (42). Histological classification is important for selecting drugs to treat hormone receptor-positive breast cancer. Therefore, we selected invasive ductal breast cancer for this study to avoid potential biases from other types of breast cancer. In this study, we found that 84% of patients were ER-positive and that more than 90% of patients were PR-positive.
Tumor characteristics and molecular subtype were the two most important factors for selecting adjuvant treatment (19, 43). The pathological staging system categorizes tumors according to the number of lymph nodes involved: 1-3, 4-9 and 10 or more as N1, N2 and N3, respectively. Some studies have indicated that adding LNR classification to pN staging is more effective at distinguishing prognoses between low-risk and high-risk groups. Our results showed that patients in the low-risk group had significantly better survival than patients in the intermediate and high-risk groups. Therefore, studies focused on LNR have considered treatments involving the total resection of the LNs in an attempt to provide more information relating to tumor recurrence, which was in agreement with the primary hypothesis.
Among the highly proliferative/high- ER-sensitive tumors, relapses occurring after 5 years of adjuvant tamoxifen treatment are the most common, although risk of recurrence is modest during the first 5 years of tamoxifen treatment (44). Although several predictive markers have been identified, no factor that precisely predicts long-term survival in breast cancer patients has been reported. In a recent study in Lancet Oncology, patients with luminal-A subtype tumors were recommended to receive 10 years of endocrine therapy (45). All of the patients enrolled in these studies were recommended to receive 5 years of endocrine therapy rather than 10 years. Thus, we could not determine the effect of LNR in patients who received long-term endocrine therapy. However, our results here showed that LNR as a continuous variable gave a high adjusted HR in both DFS and OS in patients who were administered selective ER modulators. Specifically, patients in the high- and intermediate-risk groups were more than 5- and 2-fold more likely, respectively, to experience disease recurrence than patients in the low-risk group.
LNR is an alternative prognostic factor to pN staging for lymph node-positive breast cancer (39, 46). Accumulating evidence has supported the prognostic value of LNR in breast cancer (39, 46-49). Receiver operating-characteristic curve analysis showed that the AUC of LNR was slightly higher than the AUC of pN staging. In addition, nomogram analysis showed that LNR contributed more than any other factor to predicting both breast cancer recurrence and mortality. However, the optimal cut-off value remains unclear. In early studies, LNR cut-off values to evaluate risk for breast cancer was not definite (48, 50-52). The high-risk group had a significantly increased risk of breast cancer recurrence and metastases in patients with lymph node-positive breast cancer. Several studies subsequently indicated that patients can be categorized into low- (≤0.20), intermediate- (>0.20 and ≤0.65), and high-risk (>0.65) groups by LNR. These results demonstrated that patients in the high-risk group had significantly lower DFS than patients in the intermediate- and low-risk groups (53-55). However, there were also some studies that used 0.25 and 0.55 (54) or 0.10 and 0.65 (57) for the high- and low-risk groups, respectively. In our study, we used X-tile to categorize patients into low-, intermediate- and high-risk groups by using lower cut-off values for the LNR lower (0.20) and upper (0.63) cut-offs. Patients in the high-risk group had significantly worse prognoses than patients in the intermediate- and low-risk groups.
LNR was used to assist in determining whether adjuvant radiotherapy should be used in N1-3 patients. Although the tumor recurrence rate was reduced in patients using endocrine therapy, patients inevitably acquired resistance to these therapies (58, 59). Several effective drugs, including fulvestrant, aromatase inhibitors, and the CDK4/6 inhibitor palbociclib, have been approved to treat luminal subtype breast cancer that selective estrogen receptor modulators have failed to treat effectively (60-63). Therefore, screening for biomarkers that can be used to predict breast cancer recurrence after breast surgery is important. Significant progress has been made in understanding the molecular biomarkers of breast cancer, and axillary lymph node status remains one of the fundamental prognostic factors that guides the decision to undergo post-mastectomy radiation therapy.
There are some limitations to this study. Its conclusions are based on a single-center study that incorporated a large breast cancer sample size. Secondly, information was not available for all of the patients regarding early tumor grade and Ki-67 index scores because not all tumor samples had been tested. Thirdly, the drugs used included toremifene, which is not commonly used in premenopausal patients with breast cancer as an endocrine therapy. However, we have confirmed that there was no difference in DFS between patients receiving toremifene and tamoxifen treatment for premenopausal breast cancer (64).
In conclusion, we determined that LNR is significantly associated with poor prognosis in lumina-subtype premenopausal breast cancer. Further research is required to determine whether a particular cut-off value for LNR can be used to predict tumor recurrence or breast cancer survival.
Acknowledgements
This study was supported by a grants from the Science and Technology Planning Project of Guangdong Province China (2014A020212384), the National Natural Science Foundation of China (81502302), the Medical Scientific Research Foundation of Guangdong Province, China (A2017092). The Authors acknowledge the China Scholarship Council.
Footnotes
↵* These Authors contributed equally to this study.
Conflicts of Interest
The Authors declare no conflicts of interest in regard to this study.
- Received May 12, 2017.
- Revision received June 9, 2017.
- Accepted June 16, 2017.
- Copyright© 2017, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved