Relation Between Tumor Size and Lymph Node Metastasis According to Subtypes of Breast Cancer

New insights into acinic cell carcinoma of the breast: clinicopathology, origin of histology, molecular features, prognosis, and treatment

Acinic cell carcinoma (AciCC) of the breast is a rare malignant epithelial neoplasm, with approximately 60 cases reported in the literature. It predominantly affects women and exhibits significant histological heterogeneity. The diagnosis of breast AciCC is primarily based on the presence of eosinophilic and/or basophilic granular cytoplasm and markers of serous acinar differentiation. Despite being considered a low-grade variant of conventional triple-negative breast cancer (TNBC), over 25% of patients with breast AciCC have adverse clinical outcomes. Additionally, in early research, microglandular adenosis (MGA) and atypical MGA were considered potential precursors for various breast cancers, including intraductal carcinoma, invasive ductal carcinoma, adenoid cystic carcinoma, metaplastic carcinoma, and AciCC. Similarly, some studies have proposed that breast AciCC should be considered a type of carcinoma developing in MGA with acinic cell differentiation rather than a distinct entity. Therefore, the pathogenesis of breast AciCC has not yet been clarified. Moreover, to the best of our knowledge, the literature has not summarized the latest prognosis and treatment of breast AciCC. In this review, we synthesized the current literature and the latest developments, aiming at exploring the clinicopathology, histological origin, molecular features, prognosis, and treatment of breast AciCC from a novel perspective.

GAS5 lncRNA: A biomarker and therapeutic target in breast cancer

Breast cancer is one of the most common causes of cancer-related mortality globally, and its aggressive phenotype results in poor treatment outcomes. Growth Arrest-Specific 5 long non-coding RNA has attracted considerable attention due to its pivotal function in apoptosis regulation and tumor aggressiveness in breast cancer. Gas5 enhances apoptosis by regulating apoptotic proteins, such as caspases and BCL2 family proteins, and the sensitivity of BCCs to chemotherapeutic agents. At the same time, low levels of GAS5 increased invasion, metastasis, and overall tumor aggressiveness. GAS5 also regulates EMT markers, critical for cancer metastasis, and influences tumor cell proliferation by regulating various signaling components. As a result, GAS5 can be restored to suppress tumor development as a possible therapeutic strategy, which might present promising prospects for a patient's treatment. Its activity levels might also be a crucial indicator and diagnostic parameter for prediction. This review highlights the significant role of GAS5 in modulating apoptosis and tumor aggressiveness in breast cancer, emphasizing its potential as a therapeutic target for breast cancer treatment and management.

Factors Associated With Node-Positive Disease in Estrogen Receptor-Positive Breast Cancer Patients

INTRODUCTION

Larger tumor size and shorter tumor-to-nipple distance at diagnosis are associated with greater risk of lymph node involvement in breast cancer. However, the relationship between receptor subtype status and lymph node metastasis remains unclear. Our objective was to examine the association between primary tumor size, location, and nodal metastasis across estrogen receptor (ER)+/ progesterone receptor (PR)+/ human epidermal growth factor receptor 2 (HER2)-, ER+/PR-/HER2-, ER+/PR+/HER2+, and ER+/PR-/HER2+ tumors.

METHODS

A single-institution retrospective chart review was conducted of breast cancer patients diagnosed between 1998 and 2019 who underwent nodal evaluation during primary surgery. Neoadjuvant chemotherapy, pure ductal carcinoma in situ, inflammatory, recurrent, metastatic, bilateral, multicentric, and multifocal disease were excluded. Descriptive statistics (proportions and frequencies for categorical variables and medians [Q1-Q3] for continuous variables) were used to summarize patient characteristics. Kruskal-Wallis test was applied to test the association of outcome variables and continuous variables. Chi-square test or Fisher exact test was applied to test the association of outcome variables and categorical variables.

RESULTS

Six hundred eighteen ER + patients had a median tumor size of 1.7 cm (1.1-2.5 cm). Two hundred ninety six out of 618 (47.9%) were node-positive and 188/618 (30.4%) had axillary dissection. Eighty four point three percent of patients were ER+/PR+/HER2-, 6.31% were ER+/PR-/HER2-, 6.96% were ER+/PR+/HER2+, and 1.13% were ER+/PR-/HER2+. Median tumor size was significantly larger in node-positive cases compared to node-negative cases in ER+/PR+/HER2-, ER+/PR+/HER2+, and ER+/PR-/HER2- subgroups. In ER+/PR+/HER2-patients, median tumor-nipple distance was significantly shorter in node-positive patients compared to node-negative patients. Upper outer quadrant location was significantly associated with nodal positivity in ER+/PR-/HER2- patients.

CONCLUSIONS

Across ER + patients, the significance between tumor size, location, and lymph node positivity varied significantly when differentiating by PR and HER2 status.

Patient-derived scaffolds representing breast cancer microenvironments influence chemotherapy responses in adapted cancer cells consistent with clinical features

BACKGROUND

The tumor microenvironment clearly influences cancer progressing properties but less is known about how individual cancer microenvironments potentially moderate cancer treatment effects. By cultivating and treating cancer cell lines in patient-derived scaffolds (PDS), the impact of specific characteristics of individual cancer microenvironments can be incorporated in human-like growth modelling and cancer drug treatment testing.

METHODS

PDSs from 78 biobanked primary breast cancer samples with known patient outcomes, were prepared and repopulated with donor breast cancer cell lines, followed by treatment with 5-fluorouracil or doxorubicin after cellular adaption to the various microenvironments. Cancer cell responses to the treatments were monitored by RNA-analyses, highlighting changes in gene sets representative for crucial tumor biological processes such as proliferation, cancer stem cell features, differentiation and epithelial-to-mesenchymal transition.

RESULTS

The chemotherapy treatments induced distinct gene expression patterns in adapted cancer cells with clusters of similar treatment responses depending on the patient-derived cancer microenvironment used as growth substrate. The doxorubicin treatment displayed a favorable gene signature among surviving cancer cells with low proliferation (MKI67) and pluripotency features (NANOG, POU5F1), in comparison to 5-fluorouracil showing low proliferation but increased pluripotency. Specific gene changes monitored post-treatment were also significantly correlated with clinical data, including histological grade (NANOG), lymph node metastasis (SLUG) and disease-free patient survival (CD44).

CONCLUSIONS

This laboratory-based treatment study using patient-derived scaffolds repopulated with cancer cell lines, clearly illustrates that the human cancer microenvironment influences chemotherapy responses. The differences in treatment responses defined by scaffold-cultures have potential prognostic and treatment predictive values.

Incidence and risk factors of lymph node metastasis in breast cancer patients without preoperative chemoradiotherapy and neoadjuvant therapy: analysis of SEER data

Background

Breast cancer (BC) is the leading cause of death in the female reproductive system, often linked to lymph node involvement, indicating poor prognosis. This study investigated lymph node metastasis incidence and risk factors in M0 stage BC patients who hadn't received preoperative chemoradiotherapy or neoadjuvant therapy. We explored the influence of various factors on lymph node metastasis.

Methods

We conducted a retrospective analysis using Surveillance, Epidemiology, and End Results data from BC patients diagnosed between 2010 and 2015. Binary logistic regression and propensity score matching (PSM) assessed significant factors in BC patients without preoperative treatment. We developed predictive nomograms and evaluated model performance using the concordance index, calibration curve, area under the curve, and decision curve analysis.

Results

Among 256,504 eligible BC patients, 25.57% had lymph node metastasis. Multivariate logistic regression revealed associations between lymph node metastasis and younger age, African-American ethnicity, central/nipple location, lobular carcinoma, human epidermal growth factor receptor 2 (HER2)-positive status, grade III classification, and T3 stage. PSM confirmed these findings. Interactions were identified between age, race, primary site, histology, breast subtype, grade, and T stage, all influencing lymph node metastasis.

Conclusions

This retrospective study identified lymph node metastasis in female BC patients with distinct clinicopathological characteristics who received no preoperative treatment. We constructed valuable nomograms, revealing that: (I) young age (<35 years), African-American race, central/nipple location, infiltrating duct carcinoma, HER2 positivity, high histological grade (grade III), and larger tumor size are risk factors for regional lymph node metastasis; (II) lymph node metastasis may not solely represent the invasive nature of triple-negative BC; (III) patients with different BC subtypes in T1c-T2 stages may benefit from individualized neoadjuvant treatment strategies.

Novel model based on ultrasound predict axillary lymph node metastasis in breast cancer

BACKGROUND

Whether there is axillary lymph node metastasis is crucial for formulating the treatment plan for breast cancer. Currently, invasive methods are still used for preoperative evaluation of lymph nodes. If non-invasive preoperative evaluation can be achieved, it will effectively improve the treatment plan.

OBJECTIVE

Constructed a predict model based on ultrasound examination, which forest axillary lymph node metastasis in breast cancer, and validated this model.

METHOD

Patients admitted to Xiamen First Hospital from April 2018 to August 2021 with complete case data were included in this study. Patients who had undergone breast cancer resection and axillary lymph node dissection or sentinel lymph node biopsy were divided into a training and validation cohort in a 7:3 ratio. In the training cohort, patients were divided into metastatic and non-metastatic groups based on whether axillary lymph nodes had metastasis. The parameters of the two groups were compared, and statistically significant parameters were included in multivariate analysis. Then, a Nomogram model was constructed, named Lymph metastasis predict model (LMPM). Calibration curves, receiver operating curve (ROC), and decision curve analysis (DCA) were plotted between the training and validation cohort, calculate the risk score of each patient, identify the optimal cutoff value, and test the predictive efficacy of LMPM.

RESULT

Two hundred seventy-three patients were enrolled in final study, the average age 49.7 ± 8.7, training cohort included 191 patients, the diameter of breast cancer, the lymph node peak systolic flow velocity (LNPS) and the cortex area hilum ratio (CH) of lymph node were exist significant difference in metastatic and non-metastatic group. Multivariate analysis showed cancer diameter, LNPS and CH included in LMPM, the cutoff value was 95, the calibration curve, ROC, DCA in training and validation cohort show satisfactory result.

CONCLUSION

The predict model-LMPM, can predict axillary lymph node metastasis in breast cancer, which is useful for developing personalized treatment plans. However, further validation of the model is required by incorporating a larger number of patients.

NIR diagnostic imaging of triple-negative breast cancer and its lymph node metastasis for high-efficiency hypoxia-activated multimodal therapy

BACKGROUND

Triple-negative breast cancer (TNBC) possesses special biological behavior and clinicopathological characteristics, which is highly invasive and propensity to metastasize to lymph nodes, leading to a worse prognosis than other types of breast cancer. Thus, the development of an effective therapeutic method is significant to improve the survival rate of TNBC patients.

RESULTS

In this work, a liposome-based theranostic nanosystem (ILA@Lip) was successfully prepared by simultaneously encapsulating IR 780 as the photosensitizer and lenvatinib as an anti-angiogenic agent, together with banoxantrone (AQ4N) molecule as the hypoxia-activated prodrug. The ILA@Lip can be applied for the near-infrared (NIR) fluorescence diagnostic imaging of TNBC and its lymph node metastasis for multimodal therapy. Lenvatinib in ILA@Lip can inhibit angiogenesis by cutting oxygen supply, thereby leading to enhanced hypoxia levels. Meanwhile, large amounts of reactive oxygen species (ROS) were produced while IR 780 was irradiated by an 808 nm laser, which also rapidly exhausted oxygen in tumor cells to worsen tumor hypoxia. Through creating an extremely hypoxic in TNBC, the conversion of non-toxic AQ4N to toxic AQ4 was much more efficiency for hypoxia-activated chemotherapy. Cytotoxicity assay of ILA@Lip indicated excellent biocompatibility with normal cells and tissues, but showed high toxicity in hypoxic breast cancer cells. Also, the in vivo tumors treated by the ILA@Lip with laser irradiation were admirably suppressed in both subcutaneous tumor model and orthotopic tumor models.

CONCLUSION

Utilizing ILA@Lip is a profound strategy to create an extremely hypoxic tumor microenvironment for higher therapeutic efficacy of hypoxia-activated chemotherapy, which realized collective suppression of tumor growth and has promising potential for clinical translation.

Prediction of Axillary Lymph Node Metastasis in Early-stage Triple-Negative Breast Cancer Using Multiparametric and Radiomic Features of Breast MRI

RATIONALE AND OBJECTIVES

To investigate whether machine learning (ML) approaches using breast magnetic resonance imaging (MRI)-derived multiparametric and radiomic features could predict axillary lymph node metastasis (ALNM) in stage I-II triple-negative breast cancer (TNBC).

MATERIALS AND METHODS

Between 2013 and 2019, 86 consecutive patients with TNBC who underwent preoperative MRI and surgery were enrolled and divided into ALNM (N = 27) and non-ALNM (n = 59) groups according to histopathologic results. For multiparametric features, kinetic features using computer-aided diagnosis (CAD), morphologic features, and apparent diffusion coefficient (ADC) values at diffusion-weighted images were evaluated. For extracting radiomic features, three-dimensional segmentation of tumors using T2-weighted images (T2WI) and T1-weighted subtraction images were respectively performed by two radiologists. Each predictive model using three ML algorithms was built using multiparametric features or radiomic features, or both. The diagnostic performances of models were compared using the DeLong method.

RESULTS

Among multiparametric features, non-circumscribed margin, peritumoral edema, larger tumor size, and larger angio-volume at CAD were associated with ALNM in univariate analysis. In multivariate analysis, larger angio-volume was the sole statistically significant predictor for ALNM (odds ratio = 1.33, P = 0.008). Regarding ADC values, there were no significant differences according to ALNM status. The area under the receiver operating characteristic curve for predicting ALNM was 0.74 using multiparametric features, 0.77 using radiomic features from T1-weighted subtraction images, 0.80 using radiomic features from T2WI, and 0.82 using all features.

CONCLUSION

A predictive model incorporating breast MRI-derived multiparametric and radiomic features may be valuable in predicting ALNM preoperatively in patients with TNBC.

Predictors of nodal metastases in early stage HER2+ breast cancer: Deciding on treatment approach with neoadjuvant chemotherapy vs. upfront surgery

BACKGROUND

The purpose of this study is to evaluate preoperative predictors of nodal metastases in patients with early-stage, HER2-positive (HER2+) breast cancer.

METHODS

The SEER Database was queried to identify women with a first diagnosis of stage I-II (T1-T2) HER2-positive breast cancer treated with upfront surgery in 2018. Multivariable logistic regression was used to identify clinical characteristics independently associated with nodal involvement.

RESULTS

Overall, 3333 women with stage I-II HER2+ breast cancer met inclusion criteria and were included in the study. The median age at diagnosis was 59 years (IQR, 51-69 years). Most patients underwent breast-conserving surgery (60.9%), with a median of 3 (IQR 2-4) axillary lymph nodes removed. On final pathology, 762 (22.9%) of T1-T2 HER2+ patients were node positive; 2.7% pN0[i+], 3.7% pN1mi, 15.1% pN1, and 1.4% pN2. Women less than 40 years and those between 40 and 49 years showed the highest proportion of axillary lymph node metastasis, in 33.7% and 30.7% respectively, and declining with age (p < 0.001). Patients with triple-positive breast cancer had the highest rates of nodal involvement (24.8%), compared to 20.7% ER+/PR-/HER2+ and 19.6% of HER2-enriched patients (p = 0.006). On adjusted analysis, age, biologic subtype, tumour size, and type of surgery remained independent predictors of nodal involvement. On subgroup analysis, women under age 50 with T1c HER2-enriched or triple-positive breast cancer had a 33% and 35% incidence of nodal involvement, which declined with age.

CONCLUSIONS

The likelihood of pathologic nodal involvement in early-stage HER2+ breast cancer is contingent on age, ER/PR status, and tumour size.

Individualized Clinical Target Volume for Irradiation of the Supraclavicular Region in Breast Cancer Based on Mapping of the Involved Ipsilateral Supraclavicular Lymph Nodes

PURPOSE

To map supraclavicular fossa-involved lymph nodes (SCF-LNs) in patients with nonmetastatic breast cancer, evaluate the coverage of widely adopted atlases, and propose modified borders for individualized regional irradiation.

METHODS AND MATERIALS

M0 patients with biopsy-proven SCF-LNs who were SCF treatment-naïve were included. The SCF was spatially divided into subregions, with each node mapped on the original images. The geographic misses after the borders of multiple atlases were evaluated and factors affecting SCF-LNs' spread pattern were analyzed.

RESULTS

From 1998 to 2022, 209 patients with 1242 SCF-LNs were eligible. Patients had a median of 4 nodes. At least 537 nodes (43.2%) in 147 patients (70.3%) were lateral to the sternocleidomastoid muscle (SCM), and 403 nodes (32.4%) in 127 patients (60.8%) were dorsal to the anterior scalene muscle (ASM). In the 88 patients with ≤3 SCF-LNs, at least 66 nodes (39.1%) in 40 patients (45.5%) were lateral to the SCM, and 34 nodes (20.1%) in 29 patients (33.0%) were dorsal to the ASM. These nodes were not covered by the Radiation Therapy Oncology Group (RTOG) atlas and partly within the Radiotherapy Comparative Effectiveness atlas. One hundred four patients (49.8%) had 432 SCF-LNs (34.8%) beyond the upper border of the European Society for Radiotherapy and Oncology (ESTRO) atlas. In multivariate regression, nodal sizes were associated with wider spread in the primary group. Being triple-negative (TN) subtype was associated with less spread in the recurrent group. Situation-based clinical target volumes (CTVs) were theorized, in which for a sequential spread, the posterior border could be the posterior scalene muscle or even be more constringent; otherwise, it should touch the anterior trapezius surface.

CONCLUSIONS

SCF-LNs tend to spread laterally and dorsally beyond the RTOG borders, even in M0 stages with ≤3 SCF-LNs. The ESTRO upper border does not guarantee coverage with multiple SCF-LNs. Nodal burden and non-TN types are predictive of wider dissemination. A situation-based CTV is possibly feasible. Deciphering the SCF-LN spread route is needed.

Interactive effects of molecular subtypes with tumor size and extracranial metastatic pattern on risk of brain metastasis in breast cancer patients: A population-based study

BACKGROUND

Early detection of brain metastasis (BM) is essential for prognostic improvement in breast cancer (BC) patients. The aim was to identify predictors of BCBM in different molecular subtypes on a population-based level.

METHODS

The Surveillance, Epidemiology, and End Results database was used to select BC patients diagnosed from 2010 to 2018. We evaluated the incidence and risk factors of BCBM and tested the interaction effects between molecular subtypes and other risk factors.

RESULTS

Among the 527,525 selected patients, molecular subtypes significantly interacted with T stage and extracranial metastasis (ECM) patterns on the risk of BM in the whole BC population (interaction p = 0.002, <0.001, respectively) and after excluding patients with unknown states of key factors. BM development was independent of the T stage only in HR-/HER2- patients (trend p = 0.126). We selected BC patients with single-organ ECM and found a significant interaction between molecular subtypes and ECM patterns (interaction p = 0.013). The impact of ECM patterns on the risk of BM was limited to HR-/HER2- patients (trend p < 0.001), for whom using bone metastasis as a reference, lung metastasis increased the risk of BM (OR = 1.936, 95% CI: 1.300-2.882, p = 0.001).

CONCLUSION

T stage and ECM patterns had different associations with BM in different molecular subtypes. HR-/HER2- BC had distinct features on BM development, manifested as a lack of tumor size effect and is associated with lung metastasis. Close surveillance for BM should be considered for HR-/HER2- BC patients.

Ultrasonography and clinicopathological features of breast cancer in predicting axillary lymph node metastases

Background

Early identification of axillary lymph node metastasis (ALNM) in breast cancer (BC) is still a clinical difficulty. There is still no good method to replace sentinel lymph node biopsy (SLNB). The purpose of our study was to develop and validate a nomogram to predict the probability of ALNM preoperatively based on ultrasonography (US) and clinicopathological features of primary tumors.

Methods

From September 2019 to April 2022, the preoperative US) and clinicopathological data of 1076 T1-T2 BC patients underwent surgical treatment were collected. Patients were divided into a training set (875 patients from September 2019 to October 2021) and a validation set (201 patients from November 2021 to April 2022). Patients were divided into positive and negative axillary lymph node (ALN) group according pathology of axillary surgery. Compared the US and clinicopathological features between the two groups. The risk factors for ALNM were determined using multivariate logistic regression analysis, and a nomogram was constructed. AUC and calibration were used to assess its performance.

Results

By univariate and multivariate logistic regression analysis, age (p = 0.009), histologic grades (p = 0.000), molecular subtypes (p = 0.000), tumor location (p = 0.000), maximum diameter (p = 0.000), spiculated margin (p = 0.000) and distance from the skin (p = 0.000) were independent risk factors of ALNM. Then a nomogram was developed. The model was good discriminating with an AUC of 0.705 and 0.745 for the training and validation set, respectively. And the calibration curves demonstrated high agreement. However, in further predicting a heavy nodal disease burden (> 2 nodes), none of the variables were significant.

Conclusion

This nomogram based on the US and clinicopathological data can predict the presence of ALNM good in T1-T2 BC patients. But it cannot effectively predict a heavy nodal disease burden (> 2 nodes).

Axillary management for early invasive breast cancer patients: Who will truly benefit?

Background

The implementation of sentinel lymph node biopsy (SLNB) and further completion axillary lymph node dissection (cALND) after positive sentinel lymph nodes (SLNs) on early invasive breast cancer patients should be cautiously tailored. Identifying predictors for SLN and non-sentinel lymph node (nSLN) metastases can help surgeons make better surgical decisions.

Methods

A retrospective case-control study was designed and a total of 560 eligible patients were enrolled consecutively. They were all diagnosed in our center and received appropriate medical care. According to the metastasis of SLN and nSLN, they were divided into metastatic and non-metastatic groups on two successive occasions to investigate the relationship between clinical factors, pathological factors, hematological factors and lymph node metastasis.

Results

In total, 101 (18.04%) patients developed SLN metastases, including 98 patients with macro-metastases and 3 patients with micro-metastases. Out of 97 patients receiving further cALND, 20 patients (20.62%) developed nSLN metastases. Multivariate analysis revealed that “high expression of Ki-67” and “lymphatic invasion” predicted a higher risk of SLN metastasis; and “increased number of positive SLNs” and “increased systemic inflammation index (SII)” predicted a higher risk of nSLN metastasis.

Conclusion

Surgery for early invasive breast cancer patients should be more customized and precise. Appropriate axillary management is necessary for patients with the associated predictors.

Accurate Evaluation of Feature Contributions for Sentinel Lymph Node Status Classification in Breast Cancer

The current guidelines recommend the sentinel lymph node biopsy to evaluate the lymph node involvement for breast cancer patients with clinically negative lymph nodes on clinical or radiological examination. Machine learning (ML) models have significantly improved the prediction of lymph nodes status based on clinical features, thus avoiding expensive, time-consuming and invasive procedures. However, the classification of sentinel lymph node status represents a typical example of an unbalanced classification problem. In this work, we developed a ML framework to explore the effects of unbalanced populations on the performance and stability of feature ranking for sentinel lymph node status classification in breast cancer. Our results indicate state-of-the-art AUC (Area under the Receiver Operating Characteristic curve) values on a hold-out set (67%) while providing particularly stable features related to tumor size, histological subtype and estrogen receptor expression, which should therefore be considered as potential biomarkers.

Predictive Value of Ultrasound Characteristics for Disease-Free Survival in Breast Cancer

The main objective of this study was to determine the predictive value of US characteristics for disease-free survival (DFS) in BC patients. We retrospectively analyzed the ultrasonic images and clinical data of BC patients who had previously undergone breast surgery at least 10 years before study enrollment and divided them into a case group and a control group according to the cutoff value of 120 months for DFS. Correlation analysis was performed to identify US characteristics as independent predictors for DFS by multivariable logistic regression and Kaplan−Meier survival analysis. A total of 374 patients were collected, including 174 patients in the case group with short-DFS and 200 patients in the control group with long-DFS. Three US characteristics (size on US, mass shape, mass growth orientation) and two clinical factors (axillary lymph node (ALN), molecular subtypes) were identified as independent predictors for DFS (p < 0.05). The ROC curve showed good performance of the multivariate linear regression model with the area under the curve being 0.777. The US characteristics of large size, irregular shape, and nonparallel orientation were significantly associated with short-DFS, which is a promising supplementary for clinicians to optimize clinical decisions and improve prognosis in BC patients.

Neutrophil to Lymphocyte Ratio after Treatment Completion as a Potential Predictor of Survival in Patients with Triple-Negative Breast Cancer

Purpose

Triple-negative breast cancer (TNBC) has been associated with worse prognosis, and biomarkers are needed to identify high-risk patients who may benefit from clinical trials or escalated treatment after completion of standard treatment. We aimed to assess whether the post-treatment neutrophil-to-lymphocyte ratio (NLR) can reflect patient prognosis and determine the follow-up period that can provide the most feasible data.

Methods

In this retrospective analysis involving patients with TNBC, clinicopathological data, including those on peripheral complete blood cell count, were collected. The prognostic powers of serial NLRs obtained at baseline and after treatment completion were compared. Kaplan-Meier curves were generated to compare the overall survival (OS) and distant disease-free survival (DDFS).

Results

In total, 210 patients were enrolled. Forty-three (20.5%) events were detected. Two-thirds of the events (29/43) were related to breast cancer. Most recurrent breast cancer-related diseases (27/29) were detected within 5 years of the initial diagnosis. In contrast, half of the events due to secondary malignancies or non-breast-related diseases (7/14) occurred 5 years after the initial diagnosis. Comparison of the prognostic performance of NLRs at baseline and at 6, 12, and 24 months after treatment completion revealed the strongest prognostic performance at 6 months after treatment completion (area under the curve = 0.745). The high NLR group (NLR >2.47) showed worse OS (p = 0.006) and DDFS (p < 0.001) than low NLR group.

Conclusion

Elevated post-treatment NLR was significantly associated with worse survival in patients with TNBC. We believe that it can be a useful surrogate marker for identifying high-risk patients with TNBC.