Clinicopathological features and survival of early stage breast cancer in northwest China: A population-based retrospective study of 1287 patients

Clinicopathological and prognostic characteristic features of triple negative and nontriple negative breast cancer at a tertiary care hospital

Context

Carcinoma breast is a complex disease having diverse clinical, histopathological, and immunohistochemical features. Basing on estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor 2 receptor (HER2) status, these tumors are divided into triple-negative breast cancers (TNBC) where tumor cells are negative for all three receptors and nontriple negative breast cancer (non-TNBC) where tumor cells are positive for one or two or all. The clinicopathological and characteristic prognostic features are highlighted here.

Aim

The aim of this study is to evaluate the clinicopathological and prognostic features of TNBC and non-TNBC cases diagnosed in our hospital setting.

Settings and Design

Single institution, retrospective study conducted over 7 and half years.

Subjects and Methods

Histopathologically confirmed breast cancer cases with ER, PR, and HER2 receptor assessment were categorized into TNBC and non-TNBC. Detailed study on clinicopathological and prognostic features including pathological prognostic stage as per 8th AJCC was done in cases who underwent modified radical mastectomy.

Statistical Analysis Used

Data were analyzed in percentage and presented in tables and charts.

Results

The present study included 794 cases consisting of 253, 31.9% TNBC and 541, 68.1% non-TNBC cases. The mean age of TNBC and non-TNBC cases was 50.4 years and 51.7 years, respectively. Coagulative necrosis, lymphovascular invasion, lymph nodal metastasis, higher histopathological tumor grade, and NPI were observed in higher percentage of TNBC cases, i.e., 19 (10.9%), 21 (11.6%), 105 (57.7%), 127 (69.8%), and 149 (81.9%) cases, respectively, than non-TNBC seen in 18 (6.6%), 24 (8.8%), 135 (49.6%), 165 (60.7%), and 194 (71.3%) cases, respectively. Further, 25 (13.7%) TNBC and 1 (0.4%) non-TNBC case were upstaged, whereas 130 (47.8%) non-TNBC and 2 (1.1%) TNBC cases were downstaged by the pathological prognostic stage.

Conclusions

TNBC is more aggressive having a poor prognosis than non-TNBC.

Construction and validation of a prognostic nomogram in metastatic breast cancer patients of childbearing age: A study based on the SEER database and a Chinese cohort

Introduction

Cancer in patients of childbearing age continues to become increasingly common. The purpose of this study was to explore the impact of metastatic breast cancer (MBC) on overall survival (OS) and cancer-specifific survival (CSS) in patients of childbearing age and to construct prognostic nomograms to predict OS and CSS.

Methods

Data from MBC patients of childbearing age were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015, and the patients were randomly assigned into the training and validation cohorts. Univariate and multivariate Cox analyses were used to search for independent prognostic factors impacting OS and CSS, and these data were used to construct nomograms. The concordance index (C-index), area under the curve (AUC), and calibration curves were used to determine the predictive accuracy and discriminative ability of the nomograms. Additional data were obtained from patients at the Yunnan Cancer Hospital to further verify the accuracy of the nomograms.

Results

A total of 1,700 MBC patients of childbearing age were identifified from the SEER database, and an additional 92 eligible patients were enrolled at the Yunnan Cancer Hospital. Multivariate Cox analyses identifified 10 prognostic factors for OS and CSS that were used to construct the nomograms. The calibration curve for the probabilities of OS and CSS showed good agreement between nomogram prediction and clinical observations. The C-index of the nomogram for OS was 0.735 (95% CI = 0.725-0.744); the AUC at 3 years was 0.806 and 0.794 at 5 years.The nomogram predicted that the C-index of the CSS was 0.740 (95% CI = 0.730- 0.750); the AUC at 3 years was 0.811 and 0.789 at 5 years. The same results were observed in the validation cohort. Kaplan- Meier curves comparing the low-,medium-, and high-risk groups showed strong prediction results for the prognostic nomogram.

Conclusion

We identifified several independent prognostic factors and constructed nomograms to predict the OS and CSS for MBC patients of childbearing age.These prognostic models should be considered in clinical practice to individualize treatments for this group of patients.

Predictive value of chest computed tomography for axillary lymph node metastasis in patients with breast cancer: A retrospective cohort study

Purpose: This study aimed to evaluate the predictive value of preoperative chest computed tomography (CT) for axillary lymph node (ALN) metastasis in patients with breast cancer.Methods: CT features of ALNs were retrospectively reviewed in 212 patients with breast cancer who underwent preoperative chest CT examination and ALN dissection. Primary tumor size and CT characteristics of ALNs (cortical thickness, cortical shape, the presence or absence of contrast enhancement of ALNs, and the presence or absence of perinodal infiltration) were recorded and analyzed. A nomogram was developed to visualize the associations between the predictors and each ALN status endpoint.Results: Of 212 patients, 95 (44.8%) had ALN metastasis. Primary tumor size and CT characteristics of ALNs were identified as predictors of ALN metastasis. The nomogram comprising primary tumor size and cortical shape was a good validation model for predicting ALN metastasis. The sensitivity, specificity, and accuracy of the nomogram for predicting ALN metastasis were 88.4%, 79.5%, and 83.5%, respectively.Conclusion: Using preoperative chest CT scans, a nomogram combining the cortical shape of ALNs with the primary tumor size showed good performance in predicting ALN metastasis.

Nab-paclitaxel-based regimens with docetaxel-based regimens as neoadjuvant treatment for early breast cancer

Background Nanoparticle albumin-bound paclitaxel (nab-PTX) and docetaxel (DOC) both demonstrated favorable efficacy as neoadjuvant therapy in breast cancer. We retrospectively evaluated the efficacy and safety of nab-PTX-based chemotherapy (nPBC) and DOC-based chemotherapy (DBC) as neoadjuvant therapy in patients with breast cancer. Methods Breast cancer patients who received neoadjuvant nPBC or DBC and underwent surgery from January 2018 to June 2020 were consecutively analyzed. Pathologic complete response (pCR) was defined as no residual invasive cells in the breast and axillary nodes (ypT0/is ypN0) after surgery. The pCR, clinical complete response (cCR), and safety profiles were assessed in the two groups. Results A total of 104 breast cancer patients were included in this study. Fourty one patients received nPBC, and 63 patients received DBC The pCR was 34.1% in the nPBC group and 12.7% in the DBC group. Additionally, the cCR was 36.6% in the nPBC group and 15.9% in the DBC group. Peripheral sensory neuropathy was more common in the nPBC group, while hematologic toxicity was observed more frequently in the DBC group. Conclusions This study presented antitumor activity of nPBC and DBC in patients with early breast cancer receiving neoadjuvant treatment in a real-world setting. Further prospective research is warranted to confirm the results and to develop biomarkers for better patient selection.

Construction of Nomograms for Predicting Pathological Complete Response and Tumor Shrinkage Size in Breast Cancer

Purpose

Pathological complete response (pCR) is the goal of neoadjuvant chemotherapy (NAC) for the HER2-positive and triple-negative subtypes of breast cancer and is related to survival benefit; however, luminal breast cancer is not sensitive to NAC, and the size of tumor shrinkage is a more meaningful clinical indicator for the luminal breast cancer subtype. We wanted to use a nomogram or formula to develop and implement a series of prediction models for pCR or tumor shrinkage size.

Patients and Methods

We developed a prediction model in a primary cohort consisting of 498 patients with invasive breast cancer, and the data were gathered from July 2016 to September 2018. The endpoint was pCR and tumor shrinkage size. In the primary cohort, the HER2-positive cohort, and the triple-negative cohort, multivariate logistic regression analysis was used to screen the significant clinical features and clinicopathological features to develop nomograms. In the luminal group, multivariate linear regression analysis was used to test the risk factors that affect tumor shrinkage size. The area under the receiver operating characteristic curve (AUC) and calibration curves were adopted to evaluate and analyze the discrimination and calibration ability of nomograms. Furthermore, we also performed internal validation and independent validation in the primary cohort.

Results

ER status, KI67 status, HER2 status, number of NAC cycles, and tumor size were independent predictive factors of pCR in the primary cohort. These indicators had good discrimination and calibration in the primary and validation cohorts (AUC: 0.873, 0.820). The nomogram for HER2-positive and triple-negative breast cancer (TNBC) had an AUC of 0.820 and 0.785, respectively. Both the HER2 positive and TNBC nomogram calibration curves indicated significant agreement. Moreover, the luminal subtype prediction model was Y (tumor shrinkage size) = -0.576 × (age at diagnosis) + 2.158 × (number of NAC cycles) + 0.233 × (pre-NAC tumor size) + 51.662.

Conclusion

Utilizing this predictive model will enable us to identify patients at high probability for pCR after NAC. Clinicians can stratify these patients and make individualized and personalized recommendations for therapy.

Reliability, validity, and sensitivity of the Chinese Short-Form 36 Health Survey version 2 (SF-36v2) in women with breast cancer

RATIONALE, AIMS, AND OBJECTIVES

The psychometrics of the Short-Form 36 Health Survey version 2 (SF-36v2) in female breast cancer patients remains unknown. This study aimed to test the reliability, validity, and sensitivity of the Chinese SF-36v2 in women with breast cancer.

METHODS

The sample included 326 eligible participants. The reliability and the item convergent and discriminant validity were estimated using Cronbach α (≥0.70) and the multi-trait multi-item matrix analysis, respectively. The structural validity was tested using confirmatory factor analysis. Sensitivity was determined via an analysis of variance and the relative efficiency for initially diagnosed cases (yes vs no) as well as the time since diagnosis (years) before and after stratifying by initially diagnosed cases.

RESULTS

The overall Cronbach α was 0.91 (eight scales range: 0.72-0.92). All hypothesized item-scale correlations were greater than the alternatives (r ≥ 0.40). With acceptable model fit indices, the physical functioning, role-physical, bodily pain, and general health subscales had stronger contributions to the physical component summary (goodness-of-fit index [GFI]: 0.92, parsimony goodness-of-fit index [PGFI]: 0.60, comparative fit index [CFI]: 0.91, Tucker-Lewis index [TLI]: 0.93, adjusted goodness-of-fit index [AGFI]: 0.91, root mean square error of approximation [RMSEA]: 0.06, normed chi-squared [NC]: 2.65), while the vitality, social functioning, role-emotional, and mental health subscales contributed more to the mental component summary (GFI: 0.91, PGFI: 0.62, CFI: 0.91, TLI: 0.92, AGFI: 0.91, RMSEA: 0.07, NC: 2.76). The relative efficiencies with significant F-statistics were found for mental health (relative efficiency: 34.28; initially diagnosed cases), physical functioning (12.88; time since diagnosis), and physical functioning (5.80), role-physical (5.15), bodily pain (7.70), social functioning (4.62), role-emotional (4.72), mental health (4.75), and physical component summary (6.96; initially diagnosed cases with time since diagnosis; P < 0.05 for all variables).

CONCLUSIONS

Chinese SF-36v2 has acceptable psychometric properties and is suitable for women with breast cancer.

Prognostic factors influencing prognosis in early breast cancer patients

Aim of the study

The present study showed the clinicopathological characteristics and survival of early breast cancer (BC) patients.

Material and methods

A total of 236 patients were included in the study. The mean follow-up time was 59.5 months (range: 12-204 months). The inclusion criteria consisted of female patients aged > 20 years and early BC patients (stages I and IIA).

Results

The mean age at diagnosis was 51.2 years (range, 23-83 years), and 55.9% of patients were aged ≥ 50 years. Most patients (92.8%) did not have lymph node metastasis, and luminal B had the highest prevalence (54.2%) in patients. The eight-year overall survival (OS) and disease-free survival (DFS) rates were 98.3% and 92.3%, respectively. Stage IIA and Ki67 index ≥ 14% were more prevalent in the patients with tumour size of 2 ≤ T ≤ 5 cm compared to another tumour size group and Ki67 index.

Conclusions

The mean age at diagnosis in this study was in agreement with other studies reported in various areas, but with a higher percentage for elderly patients compared to some previous studies. In addition, the survival rate in the present study was higher than the results of previous studies. Future studies need to investigate these factors in a higher number of patients and in different areas and should select similar stages for early BC.

Overexpression and mutation of ZNF384 is associated with favorable prognosis in breast cancer patients

Background

To search for genes with high sensitivity and to explore its application value related to clinical prognostic prediction, so as to provide important foundation for the preventive intervention, early diagnosis, treatment and prognosis evaluation for breast cancer.

Methods

Tissue samples from ten clinical breast cancer patients were collected to search for the common mutant genes among various samples, and to explore the enrichment degree of mutant genes at both disease and signaling pathway levels using the whole exome sequencing (WES). Subsequently, targets genes with changes in expression levels that showed high correlations with mutation were screened from the above common genes using The Cancer Genome Atlas (TCGA) database. On this basis, differences in the mutation and expression levels of the screened target genes between breast cancer tissues and para-carcinoma tissues, as well as their correlations with patient survival were analyzed using the gene expression and mutation data in TCGA database, together with the clinical information. Finally, the potential regulatory pathways and potential downstream targets of the target genes were predicted through gene set enrichment analysis (GSEA) using Multi-Experiment Matrix (MEM) software.

Results

A total of 23 common mutant genes were discovered from the tissue samples from ten breast cancer patients, which were mostly enriched in the cancer, PI3K/Akt and cAMP signaling pathways. Among these 23 genes, only the changes in the expression levels of ZNF384 and PDE4DIP had displayed over 15% consistency with mutation. Besides, it was discovered through TCGA database analysis that, the expression level of ZNF384 gene in breast cancer tissues with ZNF384 mutation was far higher than that in those with no ZNF384 mutation. Moreover, such gene mutation and high expression had shown significantly positive correlation with the patient survival (P<0.05). In addition, GSEA indicated that, tissues with high ZNF384 expression were associated with enrichments related to cell cycle signaling pathway and mitosis metaphase pathway, while this series of effects might be correlated with its regulation on the level and activity of its downstream gene CXCL14.

Conclusions

ZNF384 mutation and up-regulated ZNF384 expression level in breast cancer tissues is significantly positively correlated with patient survival. Therefore, ZNF384 can serve as a molecular marker for the diagnosis and prognostic prediction of breast cancer as well as a potential therapeutic target.

Axillary lymph node metastasis detection by magnetic resonance imaging in patients with breast cancer: A meta-analysis

BACKGROUND

The study was conducted to evaluate the diagnostic performance of magnetic resonance imaging (MRI) for the detection of axillary lymph node metastasis in patients with breast cancer.

METHODS

PubMed, Medline, Web of Science, Cochrane Embase, Chinese Biomedical Literature, and China National Knowledge Infrastructure databases were searched for open published studies relevant to the use of MRI for the detection of axillary lymph node metastasis in breast cancer patients. The pooled diagnostic sensitivity, specificity, and the symmetric receiver operating characteristic (SROC) curve was calculated by combining the individual data extracted from 26 included studies.

RESULTS

The pooled diagnostic sensitivity and specificity of MRI to detect axillary lymph node metastasis in patients with breast cancer were 0.77 (95% confidence interval [CI] 0.75-0.80) and 0.90 (95% CI 0.89-0.91), respectively. The pooled positive and negative likelihood ratios were 7.67 (95% CI 5.09-11.53) and 0.23 (95% CI 0.17-0.32), respectively, by random effect method. The area under the SROC curve was 0.93 for MRI to detect axillary lymph node metastasis in breast cancer patients.

CONCLUSION

With high sensitivity, specificity, and area under the curve, MRI is an effective method to differentiate metastatic axillary lymph node in breast cancer patients, which can provide useful information for surgical procedure selection.