Breast Journal最新文献

Background: Although presurgical endocrine therapy has been used to enhance the rate of breast cancer conservation, its prognostic relevance is unknown. The search for a valid prognostic factor equivalent to pathological complete response in presurgical chemotherapy remains a challenge in presurgical endocrine therapy. This study investigated the efficacy of presurgical short-term endocrine therapy (preSTE) and assessed prognostic factors, including the preoperative endocrine prognostic index (PEPI) score.

Methods: From October 2012 to November 2021, 269 postmenopausal women diagnosed with hormone receptor-positive (HR+), human epidermal growth factor receptor 2 negative breast cancer underwent endocrine therapy with a nonsteroidal aromatase inhibitor during the presurgical waiting period. The primary endpoint was to assess the changes in tumor size using ultrasonography, and Ki67 expression levels before and after preSTE. The secondary endpoint was the prognosis of patients categorized using the PEPI score.

Results: The median age of patients was 68 years (range, 41–89 years). The median tumor size was 1.65 cm (range, 0.4–7.5 cm). The average pretreatment Ki67 expression level was 10% (range, 0%–90%). The median duration of endocrine therapy was 39 days (range, 2–88 days). Tumor diameter and Ki67 expression levels were significantly decreased to 1.43 cm (range, 0.45–5.83 cm) and 3.0% (range, 0%–85%) after preSTE, respectively. After the median observation period of 928 days, patients with PEPI scores ≥ 4 showed worse disease-free survival compared with those with lower PEPI scores. In terms of mortality, patients with PEPI score ≥ 4 had worse overall survival than did patients with lower PEPI scores.

Conclusions: Endocrine therapy during the waiting period for surgery might be effective in reducing tumor size, and the Ki67 expression level and PEPI score might be useful in predicting the prognosis of patients with postmenopausal HR+ breast cancer.

Neoadjuvant therapy before surgery offers varying benefits as a well-established treatment option for breast cancer. This study specifically evaluated the effectiveness of neoadjuvant endocrine therapy (NET), neoadjuvant chemotherapy (NCT), and neoadjuvant chemo-endocrine therapy (NCET) in patients with estrogen receptor (ER)–positive breast cancer. This meta-analysis was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Electronic searching was conducted to retrieve articles from databases including PubMed, Cochrane Library, EMBASE, CNKI, and Wanfang. The primary outcome measured by odds ratios (ORs) with 95% confidence intervals (CIs) focused on assessing pooled effect sizes. Random-effects or fixed-effect models were conducted according to the existence of statistical heterogeneity. A total of 15 eligible articles were included in the analysis. The results indicated clinical response (CR) (OR = 0.54; 95% CI = 0.41 to 0.73; I² = 39.6%) and clinical complete response (cCR) (OR = 0.31; 95% CI = 0.12 to 0.85; I² = 68.0%) after NET was significantly higher than NCT. However, no significant difference was shown in pathological complete response (pCR) (OR = 0.49; 95% CI = 0.23 to 1.04; I² = 0.0%) and breast-conserving surgery (BCS) (OR = 0.49; 95% CI = 0.23 to 1.04; I² = 0.0%). The combined paradigm of NCET presented no significant improvement compared with monotherapy of NET or NCT. Overall, both NET and NCT are effective neoadjuvant treatment options for patients with ER+ breast cancer. More explicit clinical decision indicators need to be further clarified. And NCET does not offer additional benefits over NET or NCT in patients with ER+ breast cancer.

Background and Objectives: We evaluated the prognostic value of pretreatment axillary nodal volume in breast cancer patients treated with neoadjuvant systemic therapy.

Methods: We retrospectively reviewed 302 breast cancer patients with biopsy-proven axillary LN involvement who received neoadjuvant systemic therapy. Axillary nodal volumes were obtained from pretreatment magnetic resonance imaging. Univariate and multivariate analyses for disease-free survival (DFS) and overall survival (OS) rates were conducted.

Results: The median follow-up period was 57.0 months, and 5-year DFS and OS rates were 81.6% and 91.9%, respectively. Pretreatment axillary nodal volume ranged from 0.2 mL to 134.2 mL, and the first tertile (2.6 mL) and fifth quintile (12.0 mL) were chosen as the optimal cutoff points for survival outcomes. In the multivariate analysis, nodal volume (< 2.6 mL vs. 2.6–12.0 mL vs. ≥ 12.0 mL) was a significant prognostic factor for DFS (5-year DFS, 90.1% vs. 79.6% vs. 72.2%) and OS (5-year OS, 97.9% vs. 90.9% vs. 84.2%), whereas the N stage was not.

Conclusions: In breast cancer patients treated with neoadjuvant systemic therapy, larger pretreatment axillary nodal volume was associated with poor survival outcomes.

Background: Florid lobular carcinoma in situ is an uncommon lobular neoplasia variant that is frequently associated with invasive carcinoma. However, there remains a paucity of information to guide management. The authors aimed to study imaging features associated with pathologic upgrade rates for patients with florid lobular carcinoma in situ identified on core biopsy undergoing surgical excision.

Methods: Patients with florid lobular carcinoma in situ on core biopsy were selected from an institutional pathology database. Patients were excluded if pleomorphic lobular carcinoma in situ was also present on core biopsy. Clinical, radiologic, and pathologic features for each case were reviewed focusing on imaging features which led to core biopsy and those associated with pathologic upgrade on surgical excision.

Results: Eighteen cases of florid lobular carcinoma in situ underwent surgical excision. Upgrade rates on surgical excision were higher in cases with suspicious calcifications (8/11, 73%, p = 0.049) compared to those without (1/7, 14.3%) and in cases with larger breast lesions (p = 0.011). The overall upgrade rate was 50% (9/18), 89% (8/9) with invasive lobular carcinoma and 11% (1/9) with ductal carcinoma in situ. Of the 8 cases with upgrade to invasive lobular carcinoma, 7/8 (87.5%) were Stage I cancers and only 1/8 (12.5%) had macroscopic lymph node involvement and was upgraded to Stage II.

Conclusion: Florid lobular carcinoma in situ on core biopsy had an upgrade rate on surgical excision of 50% overall, with 89% of these cases upgraded to invasive lobular carcinoma. Pathologic upgrade was seen more frequently with suspicious calcifications and larger breast lesions. These findings can help guide surgical management of this uncommon lobular neoplasia variant including planning extent of excision and consideration for lymph node evaluation.

Background: Breast carcinoma is divided into at least 21 separate histologies, according to the 2019 World Health Organization (WHO) classification. The present study is dedicated to a 5% or rarer group of all breast cancer cases.

Method: In this study, we retrospectively considered the data of 4550 patients operated on for breast carcinoma at the Ankara Oncology Training and Research Hospital of the University of Health Sciences between January 2018 and February 2024. Of those cases, 401 were discovered to have rare breast cancer types. We also explored the cases by clinicopathological features, overall survival (OS), and disease-free survival (DFS).

Results: Our findings revealed a total of 10 rare breast cancer types in patients explored: mucinous carcinoma, micropapillary carcinoma, papillary group carcinomas, metaplastic carcinoma, neuroendocrine carcinoma, tubular carcinoma, cribriform carcinoma, apocrine carcinoma, acinic cell carcinoma, and secretory carcinoma. While mucinous, tubular, cribriform, papillary group carcinomas, micropapillary, and secretory carcinomas are described as types associated with good prognosis, metaplastic, neuroendocrine, apocrine, and carcinomas are described as types associated with relatively poor prognosis.

Conclusion: Scrutinizing the clinicopathological features of rare breast cancer types altogether may be the distinct contribution of this paper to the relevant literature and future research.

Purpose: Meningeal carcinomatosis (MC) has a dismal prognosis in patients with breast cancer and requires invasive therapies. The aim of the present retrospective study was to determine a prognostic score for overall survival (OS) in patients with breast cancer and treated for MC.

Methods: The data of 109 patients with proven breast cancer MC treated with at least one intrathecal (IT) injection of methotrexate or thiotepa at Institut Curie were retrospectively recorded from 2011 to 2019. We developed prognostic clinical scores for OS and 24-week survival.

Results: The diagnosis and evaluation of MC were based on a combination of clinical, imaging, and laboratory studies. Three significant prognostic factors for OS were identified. Clinical response or stabilization after one month of IT therapy had a favorable independent prognostic value for both OS and 24-week survival. Additionally, a baseline CSF Cyfra 21-1 concentration lower than 79 ng/mL in the cerebrospinal fluid (CSF) and the absence of 1-month CSF malignant cells had borderline favorable independent prognostic value for OS and 24-week survival, respectively. We constructed 2-class and 3-class prognostic scores for each outcome, identifying a population with a very poor prognosis.

Conclusions: To our knowledge, this is the first study to develop a response-based prognosis score for patients with breast cancer-related MC. This one-month prognostic score may help to determine which patient could actually benefit from prolonged IT therapy.

Background: T regulatory cells (Tregs) are essential for preserving immune tolerance. They are present in large numbers in many tumors, hindering potentially beneficial antitumor responses. However, their predictive significance for breast cancer (BC) remains ambiguous. This study aimed to explore genes associated with Tregs and develop a prognostic signature associated with Tregs.

Methods: The gene expression and clinical data on BC were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The integration of CIBERSORT and weighted correlation network analysis (WGCNA) algorithms was utilized to identify modules associated with Tregs. The consensus cluster algorithm was utilized to create molecular subtypes determined by genes associated with Tregs. Then, a prognostic signature associated with Tregs was constructed and its relationship to tumor immunity and the prognosis was evaluated.

Results: The blue module genes exhibited the most significant correlation with Tregs, and 1080 genes related to Tregs were acquired. A total of 93 genes from the TCGA dataset were found to have a significant impact on patient prognosis. Samples from BC were categorized into two clusters by consensus cluster analysis. The overall survival, immune checkpoint genes, molecular subtype, and biological behaviors varied significantly between these two subtypes. A 10-gene signature developed from differentially expressed genes between two subtypes demonstrated consistent prognostic accuracy in both TCGA and GEO datasets. It functioned as a standalone prognostic marker for individuals with BC. In addition, patients with low risk are more inclined to exhibit increased immune cell infiltration, TME score, and tumor mutation burden (TMB). Meanwhile, Individuals classified within the low-risk group showed better responses to immunotherapies compared to their counterparts in the high-risk group.

Conclusions: The prognostic model derived from Tregs-related genes could aid in assessing the prognosis, guiding personalized treatment, and potentially enhancing the clinical outcomes for patients with BC.

Background: Limited data exist on complication rates in nipple-sparing mastectomy (NSM) in patients with large-volume breasts. Our aim was to evaluate the early complication rates of NSM with immediate reconstruction in a consecutive cohort of patients with large-volume breasts.

Methods: After IRB approval, patients treated with prophylactic or therapeutic NSM and immediate reconstruction from January 2020 to June 2022 at our health network were identified. Patients with breast weights > 600 g (the extreme NSM group) were compared to patients with breast weights of 600 g or less (the average-volume NSM group).

Results: A total of 184 patients underwent NSM with immediate reconstruction. Forty-three of 184 (23.37%) NSM patients had breast weights > 600 g. Of these, 30 patients had bilateral NSM, for a total of 73 breasts with volumes over 600 g, ranging from 603 to 1658 g. There were significantly more total complications in the extreme NSM compared to average-volume NSM groups (41.86% vs. 21.99%, p = 0.009852). When broken down into major and minor complications, the extreme NSM group had significantly more major complications than the average-volume NSM group (27.91% vs. 12.86%, p = 0.01072), but no difference in minor complications (13.95% vs. 9.29%, p = 0.2205). Overall, one (2.33%) patient in the extreme NSM group had a reconstruction failure, compared to three (2.14%) in the average-volume NSM group. Only two of 43 (4.65%) patients in the extreme NSM group lost their nipples due to total or partial nipple necrosis.

Conclusions: NSM with immediate reconstruction was successful in the majority of patients with large-volume breasts. The rate of nipple loss was acceptably low. Women with breast volumes larger than 600 g who are motivated to save their nipples at the time of mastectomy could be offered NSM.

Objective: To enhance the diagnostic accuracy of new nodules on the surgical side after breast cancer surgery using machine learning techniques and to explore the role of multifeature fusion.

Methods: Data from 137 breast cancer postoperative patients with new nodules from January 2016 to April 2024 were analyzed. Clinical, ultrasound, immunohistochemistry, and surgical features were combined. Multiple machine learning models, including support vector machine (SVM), random forest, gradient boosting, AdaBoost, and XGBoost, were trained and tested. Model performance was evaluated using stratified ten-fold cross-validation. Ablation experiments assessed the impact of different feature combinations on diagnostic performance.

Results: The SVM model performed best, with an AUC of 0.8664, an accuracy of 0.8099, a sensitivity of 0.565, and a specificity of 0.9267. Ablation experiments indicated that multifeature fusion significantly improved diagnostic performance, especially when combining clinical, ultrasound, immunohistochemistry, and surgical features. Gradient boosting and random forest models showed slightly inferior performance, while AdaBoost had balanced but lower effectiveness.

Conclusion: Machine learning, particularly the multifeature fusion SVM model, shows significant potential in diagnosing new nodules after breast cancer surgery. It can assist doctors in developing more effective treatment plans, improving patient outcomes. Future studies should expand sample sizes, include multicenter data, and explore advanced algorithms to further enhance diagnostic performance.