Abstract
Background/Aim: The host's systemic inflammatory response is thought to affect the progression of cancer and the antitumor effects of chemotherapy. Meta-analyses have reported that the peripheral blood platelet-to-lymphocyte ratio (PLR) is a prognostic indicator of this effect. Therefore, we hypothesized that PLR may differ, depending on sentinel lymph node metastasis (SLNM) in patients diagnosed with cT1N0M0 breast cancer by preoperative imaging. This study investigated the ability of preoperative PLR to predict SLNM in patients diagnosed with cT1N0M0 breast cancer. Patients and Methods: This study included 475 patients with cT1N0M0 breast cancer diagnosed by preoperative imaging. Peripheral blood was obtained at diagnosis, i.e., before surgery. PLR was calculated from preoperative blood tests, by dividing the absolute platelet count by the absolute lymphocyte count. Results: The probability of SLNM was significantly higher (p=0.002) in cases where the tumor diameter was larger than 10 mm. The incidence of SLNM was significantly high in the high (preoperative) PLR group (p=0.031). Multivariate analysis revealed that high PLR [compared to low PLR, p=0.021, odds ratio (OR)=1.815, 95% confidence interval (CI)=1.093-3.090] and large tumor size (compared to small tumor size, p=0.001, OR=2.688, 95%CI=1.524-4.997) were independent factors influencing SLNM. Conclusion: PLR may act as a predictor of SLNM in cT1N0M0 breast cancer.
The frequency of axillary lymph node metastasis is high in breast cancer. Accurate assessment is essential for the treatment of breast cancer, because metastasis to axillary lymph nodes is a prognostic factor for early breast cancer (1). Sentinel lymph node biopsy (SLNB) for clinical N0 (cN0) breast cancer was established as a minimally invasive axillary staging method, based on the results of randomized controlled trials (2, 3). The rate of pathological metastasis detected by SLNB, which has been reported to be 21.7-39.1%, is not low even in patients diagnosed as cN0 by preoperative imaging (4-11). Therefore, various predictors of sentinel lymph node metastasis (SLNM) have been studied, and there have been several reports on the correlation between primary tumor size and SLNM (4-11). Since the probability of SLNM in breast cancers with small primary lesions is lower than the above-mentioned rate, even SLNB may be excessively invasive (12). A clinical trial that has omitted SLNB for patients diagnosed with cN0 by ultrasonography (US) is currently underway (13, 14).
The host's systemic inflammatory response is thought to affect the progression of cancer and the antitumor effects of chemotherapy (15-17). Platelets have been reported to promote tumor growth by releasing growth factors such as platelet-derived growth factor (PDGF) and transforming growth factor-β (TGF-β) (18-22). However, lymphocytes may also suppress cancer progression as a part of the host immune function (23). In support, meta-analyses have reported that the peripheral blood platelet-to-lymphocyte ratio (PLR) is one of the prognostic indicators of SLNM (24, 25). A correlation between PLR and lymph node metastasis has also been reported (24). It has been speculated that early breast cancer may have a small tumor volume and be susceptible to the host systemic inflammatory response.
Therefore, we hypothesized that PLR may differ, depending on SLNM in breast cancer diagnosed as cT1N0M0 by preoperative imaging. In this study, we investigated whether preoperative PLR in patients with cT1N0M0 breast cancer could be a predictor for SLNM.
Patients and Methods
Patient background. This study included 475 patients with cT1N0M0 breast cancer diagnosed by preoperative imaging from April 2007 to March 2018 at the Osaka City University Hospital. All patients were diagnosed with breast cancer after pathological examination following core needle biopsy (CNB) or vacuum-assisted biopsy (VAB). Immunohistological examination was used to assess the expression of estrogen receptor (ER), progesterone receptor (PgR), human epidermal growth factor receptor 2 (HER2), and Ki67. The patients were classified into the following subtypes (according to previous reports), based on the results of immunohistological staining: HER2-enriched breast cancer (HER2BC) (ER−, PgR−, and HER2+), triple-negative breast cancer (TNBC) (ER−, PgR−, and HER2−), and hormone receptor-positive breast cancer(HRBC) (ER+ and/or PgR+) (26). US, computed tomography (CT), and bone scintigraphy were used to determine the presence/absence of distant metastasis and axillary lymph node metastasis. Patients with multiple breast cancers were excluded from this study. All patients underwent mastectomy or breast-conserving surgery.
The sentinel lymph node was identified using the combined radioisotope and dye methods, during surgery for breast cancer, according to the method described in previous reports (27, 28). The histopathological diagnosis of SLNM was made by slicing the entire sentinel lymph node into 2-mm-thick sections (29, 30). SLNM was classified according to the method described in previous reports: (macrometastasis: tumor diameter >2 mm; micrometastasis: tumor diameter >0.2 mm, ≤2 mm or <200 tumor cells; and isolated tumor cells: tumor diameter <0.2 mm or <200 tumor cells) (31).
Blood sample analysis. Peripheral blood was obtained at diagnosis, i.e., before surgery. Preoperative PLR was calculated by dividing the absolute platelet count by the absolute lymphocyte count. First, the blood cell count was measured with a hemocytometer. Subsequently, the absolute platelet count and absolute lymphocyte count were determined using the Coulter LH 750 Hematology Analyzer (Beckman Coulter, Brea, CA, USA). The PLR cut-off value for predicting SLNM was defined as 112.5 [area under the curve (AUC): 0.544, sensitivity: 0.412, and specificity: 0.724], based on receiver operating characteristic curve analysis (Figure 1).
Consort diagram. There were 608 patients with cT1N0M0 breast cancer preoperatively. Twenty-one patients were transferred to another hospital before surgery, while another 13 patients did not undergo SLNB during breast cancer surgery. In addition, 5 patients did not undergo surgery for the treatment of other diseases, and 27 patients received preoperative chemotherapy. Preoperative PLR could not be calculated in 52 patients. We considered that other cancers and their treatment might affect PLR. Thus, we excluded 15 patients with a history of cancer (irrespective of breast cancer). In other words, 93 patients were excluded from this study, and 475 cases were examined (Figure 2).
Statistical analysis. All statistical analyses were performed using the JMP software package (SAS, Tokyo, Japan). Each correlation was examined using the Pearson's chi-square test. The odds ratio (OR) and 95% confidence intervals (CI) were calculated using logistic analysis. Multivariable analysis was performed using the multivariable logistic regression model. Differences were considered statistically significant if the p-value was <0.05.
Results
Clinicopathological features. Table I shows the clinicopathological features of the 475 patients with cT1N0M0 breast cancer included in this study. The median age was 58 years (range=29-79 years). The median tumor diameter was 13 mm (range=4.0-20.0 mm) and 388 patients (81.7%) were positive for ER, 254 patients (53.5%) were positive for PgR, and 43 patients (9.1%) were positive for HER2. Therefore, 394 patients (82.9%) were classified as HRBC, 25 patients (5.3%) were classified as HER2BC, and 56 (11.8%) were classified as TNBC. The expression of Ki67 was higher than 14% in 235 patients (49.5%). The median number of excised sentinel lymph nodes was 2 (range, 1-8) and pathological evaluation was performed. SLNM was observed in 87 patients (18.3%) (macrometastasis: 57 patients, micrometastasis: 26 patients, isolated tumor cells: 4 patients). The mean preoperative PLR was 122.7 (range=20.7-347.5). The cut-off value determined by the analysis, classified 290 patients (61.1%) into the high PLR group.
Correlations between clinicopathological features and SLNM. The correlations between the clinicopathological features and SLNM are listed in Table II. The probability of SLNM was significantly higher (p=0.002) if the tumor diameter was larger than 10 mm. ER-positive or PgR-positive cancers demonstrated a proclivity for SLNM (ER; p=0.069, PgR; p=0.075, respectively). Thus, SLNM was significantly associated with HRBC (p=0.031).
SLNM was significantly observed in the high (preoperative) PLR group (p=0.031). The evaluation of the correlation between PLR and other clinicopathological features revealed that PLR was significantly lower in elderly patients aged over 60 years than in those aged below 60 years (p=0.004) (Table III). There was no correlation between PLR and the other clinicopathological features. Multivariate analysis revealed that high PLR (versus low PLR, p=0.031, OR=1.740, 95%CI=1.049-2.888), HRBC (versus non-HRBC, p=0.031, OR=2.288, 95%CI=1.059-4.945), and larger tumor size (versus small tumor size, p=0.002, OR=2.450, 95%CI=1.370-4.379) were predictors of SLNM (Table IV). Moreover, multivariate analysis revealed that high PLR (versus low PLR, p=0.021, OR=1.815, 95%CI=1.093-3.090) and large tumor size (versus small tumor size, p=0.001, OR=2.688, 95%CI=1.524-4.997) were independent factors predicting SLNM.
Discussion
Several reports have focused on the predictors of SLNM. Numerous studies have revealed a correlation between tumor size and SLNM (4-11). Therefore, the rate of SLNM in patients with cT1 breast cancer was further reduced to 18.8-29.6% (4-8). The rate of SLNM was 18.3% in this study, which is not significantly different from that reported by previous studies. Furthermore, there was a significant difference in tumor size, even in the case of tumors measuring 20 mm or less only, as reported previously (4, 5, 10). Other predictors of SLNM have also been found for various breast cancer subtypes.
Qiu et al. have reported that ER-positive or PgR-positive breast cancer exhibited significant metastases to sentinel lymph nodes (11). Reyal et al. have also reported that SLNM was common in ER-positive breast cancer (6). Klar et al. have reported that SLNM was significantly observed in HER2-positive breast cancers, but there was no correlation with expression of ER or PgR (10). Some studies have reported no correlation of ER, PgR, and HER2 with metastasis (4, 5, 7-9). These differences may be attributed to differences in tumor size, race, or preoperative imaging examination. SLNB may be widely used in clinical practice, because the clinical features of ER-positive breast cancer are associated with good prognosis.
The analysis of lymph node metastasis and the clinicopathological features of T1 breast cancer (irrespective of SLNB) using the Surveillance, Epidemiology, and End Results Program has shown that the lymph node metastasis rate varied, depending on the race and the expression of ER, PgR, and HER2 (32). The similarity of the results of this study that was conducted in Japan with that of Qiu et al. (11), supports the above-mentioned assumption. That study showed that PLR is a predictor of SLNM.
Our study found a correlation between PLR and age. Other studies have shown that PLR decreases with age (33, 34. These studies also examined the neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR), which are indicators of systemic inflammatory responses in hosts, and showed a relationship with age (33, 34). Some studies have reported that the SLNM rate decreased significantly with age (4-6, 8). This may be attributed to the changes in the host systemic inflammatory response with age. In other words, systemic inflammatory responses may be diminished due to immune aging (35).
This study has some limitations. The accuracy of this study may be low, because the cutoff value of PLR was determined by receiver operating characteristic curve analysis of SLNM and the AUC was low. The PLR is also easily affected by other causes of inflammation and liver diseases. However, a high therapeutic effect may be expected if PLR is low. Thus, it is highly likely that the prognosis was unaffected by appropriate adjuvant treatment even if SLNB is not performed in patients with SLNM.
Conclusion
In conclusion, our findings suggested that PLR may be a predictor of SLNM in cT1N0M0 breast cancer.
Acknowledgements
The Authors thank Yayoi Matsukiyo and Tomomi Okawa (Department of Breast and Endocrine Surgery, Osaka City University Graduate School of Medicine) for the helpful advice regarding data management.
Sources of support: This study was funded by grants from the Japan Society for the Promotion of Science (KAKENHI, Nos. 19K18067, 26461957, and 17K10559) to Shinichiro Kashiwagi.
Footnotes
Authors' Contributions
All Authors were involved in the preparation of this manuscript. KT collected the data and wrote the manuscript. SK, YA, WG, RK, AY, TM, and TT performed the operation and designed the study. KT, SK, HF, and MS summarized the data and revised the manuscript. KH and MO provided a substantial contribution to the study design, performed the operation, and revised the manuscript. All Authors read and approved the final manuscript.
Conflicts of Interest
All of the Authors have no conflicts of interest to disclose regarding this study.
- Received February 17, 2020.
- Revision received February 20, 2020.
- Accepted February 21, 2020.
- Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved