Neoadjuvant radiochemotherapy is safe and feasible for breast conserving surgery or immediate reconstruction.

This study aimed to evaluate the survival outcomes of neoadjuvant radiochemotherapy (NARCT) for early breast cancer. Female patients ≤ 80 years old with unilateral T1-T4 invasive ductal breast cancer treated with neoadjuvant chemotherapy (NAC) and radiation therapy (RT) between 2006 and 2015 were enrolled from SEER database. Baseline differences in clinical and pathological characteristics were evaluated using chi-square test. The survival outcomes were estimated by Kaplan-Meier analysis and compared using Cox hazards models. The effects of baseline differences on survival outcome in patients treated with neoadjuvant radiation therapy (NART) and post-operation radiation therapy (PORT) were circumvented by propensity score matching (PSM). Altogether 14,151 patients receiving NAC and RT were enrolled, among whom 386 underwent NART. Based on a 1:4 PSM cohort, NART was an independent unfavorable prognostic factor for breast cancer-specific survival (BCSS) and overall survival (OS) for the whole cohort. However, among patients receiving breast conserving surgery (BCS) (HR 1.029, P = 0.915 for BCSS; HR 1.003, P = 0.990 for OS) or implant-based immediate breast reconstruction (IBR) (HR 1.039, P = 0.921 for BCSS; HR 1.153, P = 0.697 for OS), those treated with NART had similar survival outcomes compared with patients treated with PORT. In conclusion, NARCT was a safe and feasible approach for patients undergoing BCS and IBR.

Chemotherapy is of prognostic significance to metaplastic breast cancer.

This study aimed to evaluate the significance of chemotherapy (CT) among metaplastic breast cancer (MpBC), and to compare the survival outcomes between triple negative MpBC (MpBC-TNBC) and triple negative invasive ductal carcinoma (IDC-TNBC). SEER database was indexed to identify female unilateral primary MpBC diagnosed from 2010 to 2017. Patients were classified into neoadjuvant chemotherapy (NAC) with response (NAC-response), NAC-no response, adjuvant chemotherapy, and no CT. Breast cancer-specific survival (BCSS) and overall survival (OS) was estimated using the Kaplan-Meier method and compared by log-rank test. Cox regression was used to evaluate the independent prognostic factors. A 1:4 propensity score matching method was adopted to balance baseline differences. Altogether 1186 MpBC patients were enrolled, among them 181 received NAC, 647 received adjuvant CT and 358 did not receive any CT. Chemotherapy was an independent favorable prognostic factor. NAC-response and adjuvant CT had a significant or an obvious trend of survival improvement compared with NAC-no response or no CT. MpBC-TNBC was an independent unfavorable prognostic factor compared with IDC-TNBC. Among them, there was significant or trend of survival improvement among all TNBCs receiving NAC or adjuvant CT compared with no CT. Chemotherapy was of important significance to MpBC prognosis and should be integrated in comprehensive treatment for MpBC.

The Added Prognostic Value of Oncotype Recurrence Score to AJCC Prognostic Staging System in Stage III ER+/HER2- Breast Cancer.

INTRODUCTION: Prognostic prediction based on prognostic stage (PS) with the Oncotype DX recurrence score (RS) has not been validated in stage III ER+/HER2- breast cancer. This study aimed to evaluate the added prognostic significance of RS incorporated with the PS system and to compare the prognostic prediction improvement with anatomic TNM stage (AS) using nomogram construction. METHODS: The SEER database was indexed to identify ER+/HER2- invasive ductal or lobular breast cancer in AS IIIA-IIIC with RS results diagnosed from 2004 to 2013. Patients with RS < 18, 18-30 and > 30 were categorized into low-, intermediate- and high-risk RS groups. Comparisons of the distribution of clinical-pathologic characteristics among RS risk groups were performed using Pearson's chi-square test. Breast cancer-specific survival (BCSS) was estimated using the Kaplan-Meier method and compared across RS or PS by log-rank test. Cox regression was used to evaluate the factors independently related to BCSS. A nomogram comprised of PS and RS was constructed with discrimination, calibration and clinical benefit evaluated. RESULTS: Altogether 629 patients who received RS were enrolled. There were 326 cases (51.8%) with low-risk RS, 237 (37.7%) with intermediate-risk RS and 66 (10.5%) with high-risk RS; 344 patients (54.7%) had PS IB, 84 (13.4%) had IIB, 150 (23.8%) had IIIA, 46 (7.3%) had IIIB, and only 5 had (0.8%) IIIC. Both PS and RS were independent prognostic factors for BCSS. There were significant or trends of differences in survival among RS within subtypes stratified by PS. There were significant differences in survival among PS only within intermediate-risk RS. A nomogram prediction 5-year BCSS was constructed with a c-index of 0.811. Lower histologic grade, positive PR and fewer positive lymph nodes were independently correlated with low-risk RS. CONCLUSION: PS incorporated with RS had improved prognostic significance for stage III ER+/HER 2- breast cancer.

An automatic recognition method of nematode survival rate based on bright field and dark field experimental images.

BACKGROUND: The survival rate of experimental animals is a very important index in chemical toxicity evaluation experiments. The calculation of nematode survival rate is used in many experiments. OBJECTIVE: Traditional survival rate quantification methods require manual counting. This is a time-consuming and laborious work when using 384-well plate for high-throughput chemical toxicity assessment experiments. At present, there is a great need for an automatic method to identify the survival rate of nematodes in the experiment of chemical toxicity evaluation. METHODS: We designed an automatic nematode survival rate recognition method by combining the bright field experimental image of nematodes and the dark field image of nematodes which is captured after adding Propidium Iodide dye, and used it to calculate the nematode survival rate in different chemical environments. Experiment results show that the survival rate obtained by our automatic counting method is very similar to the survival rate obtained by manual counting. RESULTS: Through several different chemical experiments, we can see that chemicals with different toxicity have different effects on the survival rate of nematodes. And the survival rate of nematodes under different chemical concentrations has an obvious gradient trend from high concentration to low concentration. In addition, our method can quantify the motility of nematodes. There are also significant differences in the motility of nematodes cultured in different chemical environments. Moreover, the nematode motility under different chemical concentrations showed an obvious gradient change trend from high concentration to low concentration. CONCLUSION: Our study provides an accurate and efficient nematode survival rate recognition method for chemical toxicology research.

CASP9 As a Prognostic Biomarker and Promising Drug Target Plays a Pivotal Role in Inflammatory Breast Cancer.

Background: Inflammatory breast cancer (IBC) is one of the most rare and aggressive subtypes of primary breast cancer (BC). Our study aimed to explore hub genes related to the pathogenesis of IBC, which could be considered as novel molecular biomarkers for IBC diagnosis and prognosis. Material and Methods. Two datasets from gene expression omnibus database (GEO) were selected. Enrichment analysis and protein-protein interaction (PPI) network for the DEGs were performed. We analyzed the prognostic values of hub genes in the Kaplan-Meier Plotter. Connectivity Map (CMap) and Comparative Toxicogenomics Database (CTD) was used to find candidate small molecules capable to reverse the gene status of IBC. Results: 157 DEGs were selected in total. We constructed the PPI network with 154 nodes interconnected by 128 interactions. The KEGG pathway analysis indicated that the DEGs were enriched in apoptosis, pathways in cancer and insulin signaling pathway. PTEN, PSMF1, PSMC6, AURKB, FZR1, CASP9, CASP6, CASP8, BAD, AKR7A2, ZNF24, SSX2IP, SIGLEC1, MS4A4A, and VSIG4 were selected as hub genes based on the high degree of connectivity. Six hub genes (PSMC6, AURKB, CASP9, BAD, ZNF24, and SSX2IP) that were significantly associated with the prognosis of breast cancer. The expression of CASP9 protein was associated with prognosis and immune cells infiltration of breast cancer. CASP9- naringenin (NGE) is expected to be the most promising candidate gene-compound interaction for the treatment of IBC. Conclusion: Taken together, CASP9 can be used as a prognostic biomarker and a novel therapeutic target in IBC.

Identification of Cancer-Associated Fibroblast Subtype of Triple-Negative Breast Cancer.

Background: There is limited knowledge about the role of cancer-associated fibroblasts (CAF) in the tumor microenvironment of triple-negative breast cancer (TNBC). Methods: Three hundred and thirty-five TNBC samples from four datasets were retrieved and analyzed. In order to determine the CAF subtype by combining gene expression profiles, an unsupervised clustering analysis was adopted. The prognosis, enriched pathways, immune cells, immune scores, and tumor purity were compared between CAF subtypes. The genes with the highest importance were selected by bioinformatics analysis. The machine learning model was built to predict the TNBC CAF subtype by these selected genes. Results: TNBC samples were classified into two CAF subtypes (CAF+ and CAF-). The CAF- subtype of TNBC was linked to the longer overall survival and more immune cells than the CAF+ subtype. CAF- and CAF+ were enriched in immune-related pathways and extracellular matrix pathways, respectively. Bioinformatics analysis identified 9 CAF subtype-related markers (ADAMTS12, AEBP1, COL10A1, COL11A1, CXCL11, CXCR6, EDNRA, EPPK1, and WNT7B). We constructed a robust random forest model using these 9 genes, and the area under the curve (AUC) value of the model was 0.921. Conclusion: The current study identified CAF subtypes based on gene expression profiles and found that CAF subtypes have significantly different overall survival, immune cells, and immunotherapy response rates.

An Innovative Breast-Conserving Oncoplastic Technique for Treating Small to Medium Volume Breasts With a Tumor in the Lower Quadrant: The Folding Flap Technique.

Background: Here, we describe an innovative oncoplastic technique for small to medium volume breasts with a tumor in the lower quadrant and this technique could provide sufficient tissue to avoid visible defects after tumor removal and help reshape the natural shape of the breast. Methods: A detailed procedure for the folding flap technique is described step by step. Then, the results of a retrospective analysis of patients treated using this technique, including complications and disease recurrence rate, between January 2017 and November 2021 are reported. Aesthetic outcomes were evaluated on a 5-point scale proposed by the Paris Breast Center. Results: A total of 52 patients underwent surgery with the folding flap technique, The average operation time was 98.4 min (range, 75-120 min), and the mean bleeding volume was 56.5 mL (range, 20-100 mL). A margin-positive result was confirmed in 1 patient who underwent re-excision. Short-term postoperative complications were observed in 7 patients, including 4 with fat liquefaction, 2 with seroma, and 1 with skin redness and swelling. No flap necrosis was observed. The median follow-up time was 28.6 months (range, 9-58 months), and 2 patients experienced local recurrence. The mean aesthetic score was 4.7 points, with 36 patients scoring 5 points and 26 patients scoring 4 points, respectively. Conclusions: The folding flap technique, as an innovative and favorable oncoplastic technique for treating small- to medium-volume breasts with a tumor in the lower quadrant, could retain sufficient tissue to fill the residual cavity after the operation while improving the aesthetic outcome of the breast.

Input to state stabilization of networked systems under a specified packet dropout rate.

This paper studies an input to state stabilizing control of networked control systems (NCSs) under a specified packet dropout rate. By considering packet dropouts in the NCSs, the transmission intervals are categorized by small delay intervals (packet-dropout-free case) and large delay intervals (packet-dropout case). Based on such classifications, we establish the concept of average packet dropout rate (ADR) to characterize the quality of service (QoS) for networks. Then, a switched systems approach is used to derive the ISS (input to state stability) conditions by exploiting Lyapunov theory and input delay approach for a specified ADR. In what follows, the controller design method for the NCSs under a specified ADR is reached by solving linear matrix inequalities (LMIs). According to the proposed results, a control and communication co-design method is developed such that one can design the controller gain according to QoS. Finally, simulations on self-steering control of autonomous vehicles are presented to verify the effectiveness of the proposed co-design method.

HTRPCA: Hypergraph Regularized Tensor Robust Principal Component Analysis for Sample Clustering in Tumor Omics Data.

In recent years, clustering analysis of cancer genomics data has gained widespread attention. However, limited by the dimensions of the matrix, the traditional methods cannot fully mine the underlying geometric structure information in the data. Besides, noise and outliers inevitably exist in the data. To solve the above two problems, we come up with a new method which uses tensor to represent cancer omics data and applies hypergraph to save the geometric structure information in original data. This model is called hypergraph regularized tensor robust principal component analysis (HTRPCA). The data processed by HTRPCA becomes two parts, one of which is a low-rank component that contains pure underlying structure information between samples, and the other is some sparse interference points. So we can use the low-rank component for clustering. This model can retain complex geometric information between more sample points due to the addition of the hypergraph regularization. Through clustering, we can demonstrate the effectiveness of HTRPCA, and the experimental results on TCGA datasets demonstrate that HTRPCA precedes other advanced methods. This paper proposes a new method of using tensors to represent cancer omics data and introduces hypergraph items to save the geometric structure information of the original data. At the same time, the model decomposes the original tensor into low-order tensors and sparse tensors. The low-rank tensor was used to cluster cancer samples to verify the effectiveness of the method.

A Machine Learning Model to Predict the Triple Negative Breast Cancer Immune Subtype.

Background: Immune checkpoint blockade (ICB) has been approved for the treatment of triple-negative breast cancer (TNBC), since it significantly improved the progression-free survival (PFS). However, only about 10% of TNBC patients could achieve the complete response (CR) to ICB because of the low response rate and potential adverse reactions to ICB. Methods: Open datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were downloaded to perform an unsupervised clustering analysis to identify the immune subtype according to the expression profiles. The prognosis, enriched pathways, and the ICB indicators were compared between immune subtypes. Afterward, samples from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset were used to validate the correlation of immune subtype with prognosis. Data from patients who received ICB were selected to validate the correlation of the immune subtype with ICB response. Machine learning models were used to build a visual web server to predict the immune subtype of TNBC patients requiring ICB. Results: A total of eight open datasets including 931 TNBC samples were used for the unsupervised clustering. Two novel immune subtypes (referred to as S1 and S2) were identified among TNBC patients. Compared with S2, S1 was associated with higher immune scores, higher levels of immune cells, and a better prognosis for immunotherapy. In the validation dataset, subtype 1 samples had a better prognosis than sub type 2 samples, no matter in overall survival (OS) (p = 0.00036) or relapse-free survival (RFS) (p = 0.0022). Bioinformatics analysis identified 11 hub genes (LCK, IL2RG, CD3G, STAT1, CD247, IL2RB, CD3D, IRF1, OAS2, IRF4, and IFNG) related to the immune subtype. A robust machine learning model based on random forest algorithm was established by 11 hub genes, and it performed reasonably well with area Under the Curve of the receiver operating characteristic (AUC) values = 0.76. An open and free web server based on the random forest model, named as triple-negative breast cancer immune subtype (TNBCIS), was developed and is available from https://immunotypes.shinyapps.io/TNBCIS/. Conclusion: TNBC open datasets allowed us to stratify samples into distinct immunotherapy response subgroups according to gene expression profiles. Based on two novel subtypes, candidates for ICB with a higher response rate and better prognosis could be selected by using the free visual online web server that we designed.

Breast-Conserving Surgery is Oncologically Safe for Well-Selected, Centrally Located Breast Cancer.

OBJECTIVE: The aim of this study was to evaluate the long-term survival outcomes of breast-conserving surgery (BCS) in centrally located breast cancer (CLBC) compared with mastectomy in CLBC and BCS in non-CLBC, based on the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: Female patients aged < 80 years with unilateral T1-T2 invasive ductal or lobular breast cancer undergoing BCS or mastectomy were enrolled. The differences in clinical-pathological characteristics were evaluated using Chi square tests. Multivariate logistic regression was used to measure the relationship between predictive variables and performing BCS in CLBC. Survival outcomes were estimated using the Kaplan-Meier method and compared using Cox proportional hazards models. To overcome the effects of baseline differences on survival outcome in patients treated with BCS in the central and upper-outer locations, a 1:1 ratio propensity score matching method was performed. RESULTS: Overall, among 16,522 CLBC patients, 7982 cases (48.3%) underwent BCS between 1998 and 2015. Factors such as older age, Black race, invasive ductal carcinoma (IDC), grade I, small tumor size, none or limited lymph node metastasis, positive progesterone receptor status, and receiving chemotherapy were independently correlated with BCS. BCS was an independent favorable prognostic factor among CLBC patients, based on multivariate Cox analysis. It was also shown that CLBC had similar survival outcomes compared with tumors in the upper-outer quadrant, and had a better breast cancer-specific survival compared with tumors in the lower quadrants, based on multivariate Cox analysis. CONCLUSIONS: BCS should be an acceptable and preferable alternative to mastectomy for well-selected, early-stage T1 or T2 CLBC.

Noniterative Sparse LS-SVM Based on Globally Representative Point Selection.

A least squares support vector machine (LS-SVM) offers performance comparable to that of SVMs for classification and regression. The main limitation of LS-SVM is that it lacks sparsity compared with SVMs, making LS-SVM unsuitable for handling large-scale data due to computation and memory costs. To obtain sparse LS-SVM, several pruning methods based on an iterative strategy were recently proposed but did not consider the quantity constraint on the number of reserved support vectors, as widely used in real-life applications. In this article, a noniterative algorithm is proposed based on the selection of globally representative points (global-representation-based sparse least squares support vector machine, GRS-LSSVM) to improve the performance of sparse LS-SVM. For the first time, we present a model of sparse LS-SVM with a quantity constraint. In solving the optimal solution of the model, we find that using globally representative points to construct the reserved support vector set produces a better solution than other methods. We design an indicator based on point density and point dispersion to evaluate the global representation of points in feature space. Using the indicator, the top globally representative points are selected in one step from all points to construct the reserved support vector set of sparse LS-SVM. After obtaining the set, the decision hyperplane of sparse LS-SVM is directly computed using an algebraic formula. This algorithm only consumes O(N2) in computational complexity and O(N) in memory cost which makes it suitable for large-scale data sets. The experimental results show that the proposed algorithm has higher sparsity, greater stability, and lower computational complexity than the traditional iterative algorithms.

Bioinformatics analysis of prognostic significance of COL10A1 in breast cancer.

BACKGROUND: Collagen type X alpha 1 (COL10A1) is overexpressed in diverse tumors and displays vital roles in tumorigenesis. However, the prognostic value of COL10A1 in breast cancer remains unclear. METHODS: The expression of COL10A1 was analyzed by the Oncomine database and UALCAN cancer database. The relationship between COL10A1 expression level and clinical indicators including prognostic data in breast cancer were analyzed by the Kaplan-Meier Plotter, PrognoScan, and Breast Cancer Gene-Expression Miner (bc-GenExMiner) databases. RESULTS: COL10A1 was up-regulated in different subtypes of breast cancer. Estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor-2 (HER-2) status and nodal status were positively correlated with COL10A1 expression. Conversely, age, the Scarff-Bloom-Richardson (SBR) grade, basal-like status, and triple-negative status were negatively related to COL10A1 level in breast cancer samples compared with normal tissues. Patients with increased COL10A1 expression level showed worse overall survival (OS), relapse-free survival (RFS), distant metastasis-free survival (DMFS) and disease-free survival (DFS). COL10A1 was positively correlated with metastatic relapse-free survival. GSEA analysis revealed that enrichment of TGF-ß signaling pathway. 15-leucine-rich repeat containing membrane protein (LRRC15) is a correlated gene of COL10A1. CONCLUSION: Bioinformatics analysis revealed that COL10A1 might be considered as a predictive biomarker for prognosis of breast cancer. Further experiments and clinical trials are essential to elucidate the value of COL10A1 in breast cancer treatment.

The prognostic significance of co-existence ductal carcinoma in situ in invasive ductal breast cancer: a large population-based study and a matched case-control analysis.

BACKGROUND: To evaluate the prognostic significance of co-existence ductal carcinoma in situ (DCIS) in invasive ductal breast cancer (IDC) compared with pure IDC. METHODS: The Surveillance, Epidemiology, and End Results (SEER) database was searched to identify unilateral IDC cases between 2004 and 2015, which were grouped into pure IDC and IDC with DCIS component (IDC-DCIS). Comparisons of the distribution of clinical-pathological characteristics the two groups were performed using Pearson's chi-square. Breast cancer-specific survival (BCSS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared across RS groups using the log-rank statistic. Cox models were fitted to assess the factors independently associated with survival. A 1:1 matched case-control analysis was conducted with each clinical-pathological characteristic matched completely. RESULTS: A total of 98,097 pure IDC cases (39.6%) and 149,477 IDC-DCIS cases (60.4%) were enrolled. IDC-DCIS patients were presented with less aggressive characteristics such as lower proportion of histologic grade III (34.2% vs. 42.2%, P<0.001), ER negative (16.8% vs. 26.1%, P<0.001) and PR negative (26.5% vs. 35.7%, P<0.001) disease and higher proportion of T1 cases (68.7% vs. 58.2%, P<0.001) compared with pure IDC patients. Co-existence DCIS was an independent prognostic factor for BCSS and OS in the whole cohort. According to the multivariate analysis, it was an independent favorable prognostic factor among ER positive cases, but an independent negative prognostic factor among ER negative cases based on the matched cohort. CONCLUSIONS: Co-existence DCIS showed quite different prognostic significance among ER positive and negative disease.

Injectable hydrogels for the sustained delivery of a HER2-targeted antibody for preventing local relapse of HER2+ breast cancer after breast-conserving surgery.

A high risk of local relapse is the main challenge of HER2+ breast cancer after breast-conserving surgery. We aimed to develop a long-acting delivery system for Herceptin, a HER2-targeting antibody, using injectable and thermosensitive hydrogels as the carrier to prevent the local relapse of HER2+ breast tumors while minimizing systemic side effects, especially cardiotoxicity. Methods: Two poly(lactic acid-co-glycolic acid)-b-poly(ethylene glycol)-b-poly(lactic acid-co-glycolic acid) (PLGA-PEG-PLGA) triblock copolymers with different PEG/PLGA proportions were synthesized. Their mixtures with rational mix proportions displayed sol-gel transitions in water with rising of temperature and the Herceptin-loaded hydrogel systems were then prepared. Both the in vivo antitumor and anti-relapse efficacies were evaluated after hypodermic injection of the Herceptin-loaded hydrogel, and the cardiotoxicity was also detected. Results: The gel performance, degradation rate and drug release kinetics of hydrogels were easily adjustable by simply varying the mix proportion. The hydrogel matrix with a specific mix proportion not only avoided initial burst release but also achieved sustained release of Herceptin in vitro for up to 80 days, which is the longest period of Herceptin delivery that has ever been reported. In vivo biodistribution studies performed in SK-BR-3 tumor-bearing mice revealed that a single hypodermic administration of the Herceptin-loaded hydrogel adjacent to the tumor tissue promoted the intratumoral antibody accumulation. This resulted in a better antitumor efficacy compared to weekly hypodermic injections of Herceptin solution for 28 days. A tumor relapse model was also established by imitative breast-conserving surgery on tumor-bearing mice, and both the single injection of the Herceptin-loaded hydrogel and the weekly injection of the Herceptin solution achieved superior anti-relapse efficacy. Furthermore, both antitumor and anti-relapse experiments demonstrated that the weekly pulsed administration of the Herceptin solution caused cardiotoxicity; however, the sustained release of Herceptin from the hydrogel effectively prevented this side effect. Conclusion: The Herceptin-loaded hydrogel has great potential for preventing the relapse of HER2+ breast tumors after breast-conserving surgery with enhanced therapeutic efficacy, improved patient compliance and significantly reduced side effects.

Post-mastectomy immediate breast reconstruction is oncologically safe in well-selected T4 locally advanced breast cancer: a large population-based study and matched case-control analysis.

PURPOSE: Although it is well accepted that the survival outcome is most probably unaffected by immediate breast reconstruction (IBR) for T1-T3 tumors, the safety of IBR in T4 locally advanced breast cancer (LABC) remains unclear. METHODS: By using data from the Surveillance, Epidemiology, and End Results (SEER) database, the trend of IBR for female T4 LABC patients undergoing mastectomy, chemotherapy and radiotherapy was explored. The predictors of IBR in T4 LABC were evaluated by multivariate logistic regression. The survival outcomes were compared by means of Cox hazards models adjusting for known clinicopathological variables and stratifying on the T stage and contralateral prophylactic mastectomy (CPM). RESULTS: Altogether 714 cases underwent IBR between 1998 and 2015. The IBR cohort had a lower percentage of cases with T4d disease whereas higher percentage with CPM. The IBR rate was 10.1% and increased from 4.1% in 1998 to 17.7% in 2015. Since 2009, the rate of implant-based IBR exceeded that of the autologous tissue method. An age less than 45 years (OR 2.930, 95% CI 2.299-3.735) and CPM (OR 2.758, 95% CI 2.306-3.299) were the strongest predictors of IBR. In the 1:2 matched case-control analysis, IBR was not an independent prognostic factor for breast cancer specific-survival (BCSS) (HR 0.893, p = 0.236, 95% CI 0.741-1.077) and overall survival (OS) (HR 0.886, p = 0.183, 95% CI 0.741-1.059). BCSS and OS were similar among patients undergoing IBR whether they underwent CPM or not and whether they were inflammatory breast cancer (IBC) or not. CONCLUSIONS: IBR is oncologically safe in well-selected T4 LABC.

Growing Trends of Contralateral Prophylactic Mastectomy and Reconstruction in Young Breast Cancer.

BACKGROUND: The aim of this study was to evaluate the trends of surgical treatments among young patients in T1N0-1M0 stage based on the Surveillance, Epidemiology, and End Results database. MATERIALS AND METHODS: Patients aged less than 40 y diagnosed between 1998 and 2015 were enrolled, with tumors in T1N0-1M0 stage and not located in the central area. Differences in clinical-pathological characteristics were evaluated using chi-square tests. Multivariate logistic regression was used to measure the various factors associated with contralateral prophylactic mastectomy (CPM). Independent prognostic factors were evaluated by Cox model. RESULTS: The total rate of breast-conserving surgery (BCS) was 51.6%, which declined from 64.5% in 1998 to 39.6% in 2015. The total rate of CPM was 22.7%, which increased from 3.7% in 1998 to 38.7% in 2014 despite a decline to 32.7% in 2015. Meanwhile, the rate of reconstruction increased in line with that of CPM, from 9.4% in 1998 to 35.0% in 2015. There was a trend of increasing use of implant-based reconstruction. Significant higher odds of CPM were found in recent year of diagnosis between 2010 and 2015 and in implant-based reconstruction. Patients undergoing CPM had similar survival outcomes compared with those undergoing BCS and unilateral mastectomy, whereas those undergoing BCS had better survival outcomes compared with those undergoing unilateral mastectomy. CONCLUSIONS: A trend of growing preference for CPM and reconstruction was observed among young patients in early stage in recent years without survival benefits. Efforts should be made to promote efficient communication and evidence-based decision-making.

The Prognostic Significance of the Oncotype DX Recurrence Score in T1-2N1M0 Estrogen Receptor-Positive HER2-Negative Breast Cancer Based on the Prognostic Stage in the Updated AJCC 8th Edition.

BACKGROUND: This study aimed to evaluate the prognostic significance of the Oncotype DX recurrence score (RS) in T1-2N1M0 estrogen receptor (ER)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer based on the prognostic stage in the updated American Joint Commission on Cancer, 8th edition. METHODS: The Surveillance, Epidemiology, and End Results database was searched to identify ER-positive invasive ductal breast cancer in T1-2N1M0 with RS results diagnosed between 2004 and 2012. Patients with RS were categorized into low-risk (RS < 11), intermediate-risk (RS 11-25), and high-risk (RS > 25) groups. The distributions of clinical-pathological characteristics were compared among the RS risk groups using Pearson's Chi square. Breast cancer-specific survival (BCSS) and overall survival (OS) were estimated using the Kaplan-Meier method and compared across RS groups using the log-rank statistic. Cox models were fitted to assess the factors independently associated with survival. RESULTS: The study enrolled 4059 cases categorized into prognostic stages IA to IIB. The RS risk groups were positively correlated with pathological prognostic stages (P < 0.001). The RS risk groups differed significantly in terms of BCSS and OS (P < 0.001). According to the multivariate analysis, RS risk group was an independent prognostic factor for BCSS and OS together with the pathological prognostic stage. The subgroup analysis showed similar survival rates across pathological prognostic stages in the RS low-risk group but significant differences in survival rates among pathological prognostic stages in the RS intermediate-risk group. The survival rates among the RS risk groups also differed significantly in pathological prognostic stage IA. CONCLUSIONS: Oncotype DX RS provided independent prognostic significance to complement the prognostic staging system.