Breast最新文献

{"title":"P096: The value of ultrasound in patients with T1-T2 breast cancer with no palpable lymph nodes enrolled in the EORTC 10981–22023 AMAROS trial","authors":"T. Snellen, A. Beerthuizen, S. Bartels, A. Kuijer, F van Duijnhoven","doi":"10.1016/j.breast.2025.103963","DOIUrl":"10.1016/j.breast.2025.103963","url":null,"abstract":"","PeriodicalId":9093,"journal":{"name":"Breast","volume":"80 ","pages":"Article 103963"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"P117: Assessment of Histopathological Correlation between Two Synchronous, Ipsilateral Groups of Calcifications in light of Imaging Features","authors":"A. Marneri, C. Theodoropoulos, A. Triantafyllou, M. Roma, C. Dimitriou, N Michalopoulos","doi":"10.1016/j.breast.2025.103983","DOIUrl":"10.1016/j.breast.2025.103983","url":null,"abstract":"","PeriodicalId":9093,"journal":{"name":"Breast","volume":"80 ","pages":"Article 103983"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"P116: HER2 Destiny: Visual scoring using ASCO/CAP guidelines or precise quantification using A.I?","authors":"X.X. Lim, D.F. Sanchez, T.W. Ramsing, A.B. Jensen, J. Thagaard, A. Cramer, P Oliveira","doi":"10.1016/j.breast.2025.103982","DOIUrl":"10.1016/j.breast.2025.103982","url":null,"abstract":"","PeriodicalId":9093,"journal":{"name":"Breast","volume":"80 ","pages":"Article 103982"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"P001: Prognostic variables for risk of recurrence in patients (pts) with HR+/HER2–early breast cancer (EBC) using data from the NATALEE trial: a machine learning (ML) model–based analysis","authors":"P.A. Fasching, C.H. Barrios, E. Lim, S.L. Graff, S. Chia, J.-S. Frenel, S.-A. Im, C.-S. Huang, A. Ring, Z. Nowecki, Q. Liu, M. Akdere, J.P. Zarate, H. Hu, K. Pantoja, J.A O'Shaughnessy","doi":"10.1016/j.breast.2025.103895","DOIUrl":"10.1016/j.breast.2025.103895","url":null,"abstract":"","PeriodicalId":9093,"journal":{"name":"Breast","volume":"80 ","pages":"Article 103895"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143578237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Describing quality of life trajectories in young Hispanic women with breast cancer: 5-year results from a large prospective cohort","authors":"Bryan F. Vaca-Cartagena ,&nbsp;Ana S. Ferrigno Guajardo ,&nbsp;Hatem A. Azim Jr ,&nbsp;Federico Rotolo ,&nbsp;Antonio Olivas-Martinez ,&nbsp;Alejandra Platas ,&nbsp;Alan Fonseca ,&nbsp;Fernanda Mesa-Chavez ,&nbsp;Marlid Cruz-Ramos ,&nbsp;Ana Rodriguez ,&nbsp;Alejandro Mohar ,&nbsp;Cynthia Villarreal-Garza","doi":"10.1016/j.breast.2024.103866","DOIUrl":"10.1016/j.breast.2024.103866","url":null,"abstract":"<div><h3>Introduction</h3><div>Cancer treatments have a detrimental impact on the quality of life (QoL) of young women with breast cancer (YWBC). Research exploring QoL trajectories has been mostly centered on postmenopausal women. Here we report longitudinal changes across all QoL domains and associated factors in YWBC.</div></div><div><h3>Methods</h3><div>In this prospective longitudinal cohort study, women aged ≤40 with stage I-III BC completed the European Organization for the Research and Treatment of Cancer Core QoL questionnaire at diagnosis and during 4 follow-up visits over 5 years, alongside demographic and clinical data collection. Group-based multivariate trajectory modeling was used to identify patient groups based on their functional and symptom scores, finding 3 groups (best, good, and poor). Factors associated with each trajectory pattern were identified with multinomial logistic models.</div></div><div><h3>Results</h3><div>A total of 477 women (median age: 36; IQR: 32–38) were clustered into the best (n = 259, 54 %), good (n = 79, 17 %), or poor trajectory groups (n = 139, 29 %). Throughout the disease, patients with a poor QoL experienced clinically significant impairment in emotional functioning, nausea and vomiting, and pain. They also had significant cognitive impairment, dyspnea, and diarrhea. Patients with a good QoL had clinically meaningful diarrhea for the first 7 months, while those with the best QoL had clinically important nausea and vomiting during the first 2 months since diagnosis. Noteworthy, all groups experienced significant financial difficulties throughout their follow-up. Regular alcohol consumption at diagnosis (aOR [adjusted odds ratio] 1.64; 95 % CI [confidence interval] 1.02–2.65) and HER2-positive BC (aOR 2.53; 95 % CI 1.35–4.73) were independent factors associated with classification to the poor and good groups, respectively.</div></div><div><h3>Conclusion</h3><div>This study underscores the variability in QoL among YWBC and the importance of ongoing monitoring. Strategies to improve access to economic resources, manage treatment-related adverse effects, and support patients in discontinuing modifiable risk factors are needed.</div></div>","PeriodicalId":9093,"journal":{"name":"Breast","volume":"79 ","pages":"Article 103866"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11755074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142926641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Novel models based on machine learning to predict the prognosis of metaplastic breast cancer","authors":"Yinghui Zhang ,&nbsp;Wenxin An ,&nbsp;Cong Wang ,&nbsp;Xiaolei Liu ,&nbsp;Qihong Zhang ,&nbsp;Yue Zhang ,&nbsp;Shaoqiang Cheng","doi":"10.1016/j.breast.2024.103858","DOIUrl":"10.1016/j.breast.2024.103858","url":null,"abstract":"<div><h3>Background</h3><div>Metaplastic breast cancer (MBC) is a rare and highly aggressive histological subtype of breast cancer. There remains a significant lack of precise predictive models available for use in clinical practice.</div></div><div><h3>Methods</h3><div>This study utilized patient data from the SEER database (2010–2018) for data analysis. We utilized prognostic factors to develop a novel machine learning model (CatBoost) for predicting patient survival rates. Simultaneously, our hospital's cohort of MBC patients was utilized to validate our model. We compared the benefits of radiotherapy among the three groups of patients.</div></div><div><h3>Results</h3><div>The CatBoost model we developed exhibits high accuracy and correctness, making it the best-performing model for predicting survival outcomes in patients with MBC (1-year AUC = 0.833, 3-year AUC = 0.806; 5-year AUC = 0.810). Furthermore, the CatBoost model maintains strong performance in an external independent dataset, with AUC values of 0.937 for 1-year survival, 0.907 for 3-year survival, and 0.890 for 5-year survival, respectively. Radiotherapy is more suitable for patients undergoing breast-conserving surgery with M0 stage [group1: (OS:HR = 0.499, 95%CI 0.320–0.777 <em>p</em> &lt; 0.001; BCSS: HR = 0.519, 95%CI 0.290–0.929 <em>p</em> = 0.008)] and those with T3-4/N2-3M0 stage undergoing mastectomy [group2: (OS:HR = 0.595, 95%CI 0.437–0.810 <em>p</em> &lt; 0.001; BCSS: HR = 0.607, 95%CI 0.427–0.862 <em>p</em> = 0.003)], compared to patients with stage T1-2/N0-1M0 undergoing mastectomy [group3: (OS:HR = 1.090, 95%CI 0.673–1.750 <em>p</em> = 0.730; BCSS: HR = 1.909, 95%CI 1.036–3.515 <em>p</em> = 0.038)].</div></div><div><h3>Conclusion</h3><div>We developed three machine learning prognostic models to predict survival rates in patients with MBC. Radiotherapy is considered more appropriate for patients who have undergone breast-conserving surgery with M0 stage as well as those in stage T3-4/N2-3M0 undergoing mastectomy.</div></div>","PeriodicalId":9093,"journal":{"name":"Breast","volume":"79 ","pages":"Article 103858"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11699302/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142827447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in breast cancer among elderly women: Development in estrogen and HER2 subtypes in the last ten years","authors":"Frederik K. Palshof ,&nbsp;Lina S. Mørch ,&nbsp;Maj-Britt R. Jensen ,&nbsp;Hans H. Storm ,&nbsp;Niels Kroman ,&nbsp;Tove H.F. Tvedskov","doi":"10.1016/j.breast.2024.103860","DOIUrl":"10.1016/j.breast.2024.103860","url":null,"abstract":"<div><h3>Background</h3><div>Increasing life expectancy increases breast cancer (BC) rates in elderly, where better health allows for improved tolerance of treatments. We assessed trends in BC incidence of tumor subtypes for women with focus on the elderly.</div></div><div><h3>Methods</h3><div>Changes in BC incidence in women by age from 2012 to 2021 were assessed using data from the Nordic countries. We calculated the incidence of BC subtypes by age group using data from the Danish Breast Cancer Group (DBCG) database. We used generalized linear models assuming a Poisson distribution.</div></div><div><h3>Results</h3><div>In the Nordic countries, 205 305 women were diagnosed with BC between 2012 and 2021. In Denmark, 50 858 BC patients were diagnosed between 2012 and 2022, identified with tumor characteristics. Incidence of BC among women aged 80+ increased significantly across the Nordic Countries, with 1.24 % per year (95 % CI: 0.07 %: 2.41 %). In Denmark, in the 80+ group, the ER+/HER2- subtype had the highest increase, with 1.98 % per year (95 % CI: 1.10 %: 2.87 %).</div></div><div><h3>Conclusion</h3><div>Across the Nordic countries, incidence of BC in women aged 80+ increased. In Denmark, rising incidence of BC is driven by the ER+/HER2- subtype in the 80+ group, which has the best prognosis and gentle treatments. More elderly BC patients will require treatment and follow-up in the future.</div></div>","PeriodicalId":9093,"journal":{"name":"Breast","volume":"79 ","pages":"Article 103860"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11722930/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142852708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical treatment score Post-5 Years (CTS5) predicts the benefit of postmastectomy radiotherapy in patients with T1-2N1 luminal breast cancer","authors":"Ke Liu ,&nbsp;Guan-Qiao Li ,&nbsp;Si-Qi Li ,&nbsp;Xue-Qin Chen ,&nbsp;San-Gang Wu","doi":"10.1016/j.breast.2025.103873","DOIUrl":"10.1016/j.breast.2025.103873","url":null,"abstract":"<div><h3>Purpose</h3><div>To investigate the clinical value of Clinical Treatment Score Post-5 Years (CTS5) to predict the survival benefits of postmastectomy radiotherapy (PMRT) of patients with T1-2N1 luminal breast cancer (BC).</div></div><div><h3>Methods</h3><div>Patients who were diagnosed with T1-2N1 luminal BC between 2010 and 2015 were included in the Surveillance, Epidemiology, and End Results database. The chi-square test, binomial logistic regression, Kaplan-Meier analysis, and multivariable Cox proportional hazard model were used for statistical analyses.</div></div><div><h3>Results</h3><div>A total of 11190 patients were included with a median follow-up time of 76 months. Regarding the CTS5 classification, 1641 (14.7 %), 3915 (35.0 %), and 5633 (50.3 %) patients had low-risk, intermediate-risk, and high-risk diseases, respectively. Patients with younger age, T2 stage, higher tumor grade, a higher number of positive lymph nodes, infiltrating lobular carcinoma subtype, and receipt of chemotherapy were associated with the receipt of PMRT (all P &lt; 0.05). The multivariate analysis showed that the receipt of PMRT was the independent prognostic factor associated with better BCSS (P = 0.005) and OS (P &lt; 0.001). The sensitivity analysis showed that PMRT did not improve BCSS (low-risk, P = 0.932; intermediate-risk, P = 0.952) and OS (low-risk, P = 0.637; intermediate-risk, P = 0.825) compared to those without PMRT in the low-risk and intermediate-risk groups. However, PMRT improved BCSS (P = 0.003) and OS (P &lt; 0.001) in those with high-risk groups compared to those without PMRT.</div></div><div><h3>Conclusions</h3><div>CTS5 is an innovative model that could predict the survival benefit of PMRT for T1-2N1 luminal BC patients.</div></div>","PeriodicalId":9093,"journal":{"name":"Breast","volume":"79 ","pages":"Article 103873"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11758395/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142926644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of model-informed precision dosing for tamoxifen therapy in patients with breast cancer: A prospective intervention study","authors":"Ruben Y.M. van Nijnatten ,&nbsp;Sanne M. Buijs ,&nbsp;Bram C. Agema ,&nbsp;Raphaël M.J. Fischer ,&nbsp;Inge Ghobadi Moghaddam-Helmantel ,&nbsp;Caroline M.E. Contant ,&nbsp;Felix E. de Jongh ,&nbsp;Auke M.T. Huijben ,&nbsp;Manon Kop ,&nbsp;Annemieke van der Padt-Pruijsten ,&nbsp;Hanneke J.M. Zuetenhorst ,&nbsp;Ron H.N. van Schaik ,&nbsp;Birgit C.P. Koch ,&nbsp;A. Jager ,&nbsp;Stijn L.W. Koolen ,&nbsp;Ron H.J. Mathijssen","doi":"10.1016/j.breast.2025.103880","DOIUrl":"10.1016/j.breast.2025.103880","url":null,"abstract":"<div><div>Tamoxifen is an estrogen-receptor (ER) antagonist, used as adjuvant treatment of ER-positive breast cancer. It is converted by CYP2D6 into endoxifen, its most active metabolite. Patients with endoxifen plasma concentrations &lt;16 nM face a higher risk of recurrence. The use of <em>a priori</em> model-informed precision dosing (MIPD) may lead to faster target attainment and thus potentially improve patient outcomes.</div><div>In total, 106 evaluable patients were prospectively included in this single-arm MIPD-intervention study. Patients received a model-predicted tamoxifen dose when starting tamoxifen-treatment (65.1 % of patients received 20 mg, 16.0 % received 30 mg and 18.9 % received 40 mg). Seventy-five percent of the 40 mg group was predicted to be unable to reach the threshold of 16 nM despite receiving the highest registered dose. After attaining steady-state, 84.0 % of patients reached endoxifen levels ≥16 nM, which was not significantly higher compared to a historical control cohort (77.9 %, <em>p</em> = 0.17). The model showed adequate performance and correctly identified patients requiring 40 mg tamoxifen. Endoxifen samples that were acquired 4–6 weeks after treatment initiation, are informative of steady-state endoxifen levels and can be used to inform MIPD and adjust tamoxifen dosing prior to steady-state attainment.</div><div>In this first MIPD implementation study for patients treated with tamoxifen, MIPD did lead to more patients achieving endoxifen levels ≥16 nM as compared to the one-dose-fits-all strategy, albeit insignificant. This may partly be explained by a larger proportion of patients who were recommended to switch to an aromatase inhibitor (AI) in the intervention cohort. In conclusion, MIPD seems beneficial compared to one-size-fits-all-dosing, but TDM still remains an important addition.</div></div>","PeriodicalId":9093,"journal":{"name":"Breast","volume":"79 ","pages":"Article 103880"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11783121/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143000001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"P085: Comparison between classic immunohistochemistry and Mammmaprint/Blueprintmolecular reclassification in Luminal breast cancer: Our clinical experience","authors":"D. Rompoti,&nbsp;E. Papachatzopoulou,&nbsp;S. Koura,&nbsp;I. Papapanagiwtou,&nbsp;A.-G. Giannakaki,&nbsp;K. Goula,&nbsp;S. Marinopoulos,&nbsp;C Dimitrakakis","doi":"10.1016/j.breast.2025.103955","DOIUrl":"10.1016/j.breast.2025.103955","url":null,"abstract":"","PeriodicalId":9093,"journal":{"name":"Breast","volume":"80 ","pages":"Article 103955"},"PeriodicalIF":5.7,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143576781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}