Pub Date : 2025-08-05DOI: 10.1016/j.clbc.2025.07.024
Congting Hu , Jia Liu , Suyan Liu , Pingping Peng , Jiaqin Cai , Xiaoxia Wei , Hong Sun
Background
Emerging evidence suggests that the gut microbiota (GM) may influence the progression of breast cancer by modulating immune responses. Given the vast diversity of GM and immune cell phenotypes, this study aimed to utilize the most advanced and comprehensive data to explore the causal relationships among the GM, immune cell phenotypes, and survival rates in hormone receptor-positive (HR+) breast cancer patients under different treatment regimens.
Methods
We investigated the causal relationships between the GM, immune cell phenotypes, and survival rates in HR+ breast cancer patients treated with 11 distinct therapeutic strategies using Mendelian randomization. Inverse variance weighted analysis served as the primary statistical method. Additionally, we explored whether immune cell phenotypes act as mediators in the pathway from the GM to HR+ breast cancer survival rates.
Results
In this comprehensive study, we identified 116 distinct GM species that established causal links with survival rates across 11 different subgroups of HR+ breast cancer patients. Furthermore, we discovered 13 potential pathways through which the GM might influence immune cell phenotypes, thereby affecting patient survival rates.
Conclusion
The GM is causally associated with survival rates in HR+ breast cancer patients treated with 11 different therapeutic strategies, and immune cell phenotypes serve as mediators in the pathway from the GM to HR+ breast cancer survival rates.
{"title":"Mendelian Randomization Study: The Impact of Gut Microbiota on Survival in HR+ Breast Cancer Patients Under Different Treatment Regimens Through the Modulation of Immune Cell Phenotypes","authors":"Congting Hu , Jia Liu , Suyan Liu , Pingping Peng , Jiaqin Cai , Xiaoxia Wei , Hong Sun","doi":"10.1016/j.clbc.2025.07.024","DOIUrl":"10.1016/j.clbc.2025.07.024","url":null,"abstract":"<div><h3>Background</h3><div>Emerging evidence suggests that the gut microbiota (GM) may influence the progression of breast cancer by modulating immune responses. Given the vast diversity of GM and immune cell phenotypes, this study aimed to utilize the most advanced and comprehensive data to explore the causal relationships among the GM, immune cell phenotypes, and survival rates in hormone receptor-positive (HR+) breast cancer patients under different treatment regimens.</div></div><div><h3>Methods</h3><div>We investigated the causal relationships between the GM, immune cell phenotypes, and survival rates in HR+ breast cancer patients treated with 11 distinct therapeutic strategies using Mendelian randomization. Inverse variance weighted analysis served as the primary statistical method. Additionally, we explored whether immune cell phenotypes act as mediators in the pathway from the GM to HR+ breast cancer survival rates.</div></div><div><h3>Results</h3><div>In this comprehensive study, we identified 116 distinct GM species that established causal links with survival rates across 11 different subgroups of HR+ breast cancer patients. Furthermore, we discovered 13 potential pathways through which the GM might influence immune cell phenotypes, thereby affecting patient survival rates.</div></div><div><h3>Conclusion</h3><div>The GM is causally associated with survival rates in HR+ breast cancer patients treated with 11 different therapeutic strategies, and immune cell phenotypes serve as mediators in the pathway from the GM to HR+ breast cancer survival rates.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 8","pages":"Pages 764-773"},"PeriodicalIF":2.5,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145014035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-05DOI: 10.1016/j.clbc.2025.07.029
Akshay Nagwani, Kanika Kapur, Pankaj Kumar Garg
{"title":"De-escalating Surgery, Escalating Radiation in Axillary Management of Breast Cancer: Progress or Lateral Shift?","authors":"Akshay Nagwani, Kanika Kapur, Pankaj Kumar Garg","doi":"10.1016/j.clbc.2025.07.029","DOIUrl":"10.1016/j.clbc.2025.07.029","url":null,"abstract":"","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 8","pages":"Pages e1026-e1027"},"PeriodicalIF":2.5,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144945073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-05DOI: 10.1016/j.clbc.2025.07.022
Amparo Garcia-Tejedor, Carla Julià, Julia Ciria, Rodrigo Guevara-Peralta, Carlos Ortega-Expósito, Raul Ortega, Agostina Stradella, Héctor Pérez-Montero, Gabriel Reyes-Juncan, Ana Benitez, Anna Guma, Juan Azcarate, Miriam Campos, Maria J Plà, Evelyn Martinez, Sonia Pernas, Jordi Ponce, Catalina Falo
Purpose: To compare survival outcomes between patients with invasive lobular carcinoma (ILC) and invasive ductal carcinoma non-special type (NST) presenting with sentinel lymph node biopsy (SLNB)-detected macrometastases in early-stage breast cancer.
Materials and methods: A retrospective cohort study was conducted including 364 cN0 breast cancer patients with SLNB-detected macrometastases who underwent surgical treatment between July 2011 and December 2023. Patients were categorized as NST (n = 250) or ILC (n = 108). SLNB was the primary axillary staging procedure, with axillary lymph node dissection (ALND) performed according to predefined clinical criteria. Univariate and multivariate Cox regression analyses were used to identify predictors of pN2-pN3. Survival outcomes were assessed using Kaplan-Meier curves and compared with log-rank tests.
Results: ILC patients presented with larger tumors, higher rates of multifocality, and greater axillary nodal involvement compared to NST. Surgery was more frequently mastectomy and ALND. pN2-N3 was identified in 12% of cases, with pT3 stage, ILC histology, and lymphovascular invasion as independent predictors. After a median follow-up of 7.6 years, the ILC group exhibited higher overall mortality (19.4% vs. 9.6%) and deaths attributed to systemic progression (57% vs. 29%). Ten-year distant disease-free survival and breast cancer-specific survival were significantly lower in the ILC cohort (63% vs. 87% and 65% vs. 93%, respectively; P < .05). Although 10-year overall survival was lower in ILC (54% vs. 79%), statistical significance was only observed in patients with advanced nodal disease (pN2-N3).
Conclusions: ILC is associated with more advanced axillary burden and significantly worse long-term oncologic outcomes compared to NST carcinoma when macrometastases are present at SLNB.
{"title":"Prognostic Outcomes by Axillary Approach in Lobular and Ductal Breast Cancer With Sentinel Node Macrometastases: A Retrospective Cohort Study.","authors":"Amparo Garcia-Tejedor, Carla Julià, Julia Ciria, Rodrigo Guevara-Peralta, Carlos Ortega-Expósito, Raul Ortega, Agostina Stradella, Héctor Pérez-Montero, Gabriel Reyes-Juncan, Ana Benitez, Anna Guma, Juan Azcarate, Miriam Campos, Maria J Plà, Evelyn Martinez, Sonia Pernas, Jordi Ponce, Catalina Falo","doi":"10.1016/j.clbc.2025.07.022","DOIUrl":"https://doi.org/10.1016/j.clbc.2025.07.022","url":null,"abstract":"<p><strong>Purpose: </strong>To compare survival outcomes between patients with invasive lobular carcinoma (ILC) and invasive ductal carcinoma non-special type (NST) presenting with sentinel lymph node biopsy (SLNB)-detected macrometastases in early-stage breast cancer.</p><p><strong>Materials and methods: </strong>A retrospective cohort study was conducted including 364 cN0 breast cancer patients with SLNB-detected macrometastases who underwent surgical treatment between July 2011 and December 2023. Patients were categorized as NST (n = 250) or ILC (n = 108). SLNB was the primary axillary staging procedure, with axillary lymph node dissection (ALND) performed according to predefined clinical criteria. Univariate and multivariate Cox regression analyses were used to identify predictors of pN2-pN3. Survival outcomes were assessed using Kaplan-Meier curves and compared with log-rank tests.</p><p><strong>Results: </strong>ILC patients presented with larger tumors, higher rates of multifocality, and greater axillary nodal involvement compared to NST. Surgery was more frequently mastectomy and ALND. pN2-N3 was identified in 12% of cases, with pT3 stage, ILC histology, and lymphovascular invasion as independent predictors. After a median follow-up of 7.6 years, the ILC group exhibited higher overall mortality (19.4% vs. 9.6%) and deaths attributed to systemic progression (57% vs. 29%). Ten-year distant disease-free survival and breast cancer-specific survival were significantly lower in the ILC cohort (63% vs. 87% and 65% vs. 93%, respectively; P < .05). Although 10-year overall survival was lower in ILC (54% vs. 79%), statistical significance was only observed in patients with advanced nodal disease (pN2-N3).</p><p><strong>Conclusions: </strong>ILC is associated with more advanced axillary burden and significantly worse long-term oncologic outcomes compared to NST carcinoma when macrometastases are present at SLNB.</p>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-08-05DOI: 10.1016/j.clbc.2025.07.021
Britt A M Jansen, Claudia A Bargon, Danny A Young-Afat, Annemiek Doeksen, Teun Teunis
Background: The smallest clinically relevant change (ie, minimal clinically important difference, MCID) for several valuable PROMs for women undergoing breast cancer surgery is unknown. Therefore, this study evaluated the smallest clinically relevant change for decision uncertainty, distress after traumatic events, body image, and health status in women diagnosed with breast cancer considering surgery.
Patients and methods: Between August 2020 and October 2022, we included 123 women with breast cancer considering surgical treatment. Women completed the decisional conflict scale (DCS), impact of event scale (IES), body image scale (BIS), and 36-Item Short Form (SF-36) after their first visit, and 4-6 weeks and 6 months after surgery. The MCID was calculated using the anchor-based method. For the MCID to be reliable, it needs to be greater than the minimum detectable change (MDC).
Results: The MCID for decision uncertainty (8.6) was smaller than the MDC (22). MCID values were 11 and 12 (MDC 8.4) for improvement in cancer-specific distress (IES), 2.5 and 6.5 (MDC 2.6) for deterioration in body image (BIS) and 27 and 14 (MDC 12) for deterioration in health status (SF-36) at 4 to 6 weeks and 6 months after surgery, respectively.
Conclusion: This study successfully determined MCIDs for several PROMs. For IES, BIS, and SF-36 the MCID seems reliable, while the DCS cannot reliably capture a clinically relevant change. The MCID values may be useful when assessing clinically relevant changes over time, interpreting treatment effects, and trial sample size determination.
{"title":"Minimal Clinically Important Differences in Scales Measuring Decision Uncertainty, Distress After a Traumatic Event, Body Image and Health Status Among Women With Breast Cancer Having Surgery.","authors":"Britt A M Jansen, Claudia A Bargon, Danny A Young-Afat, Annemiek Doeksen, Teun Teunis","doi":"10.1016/j.clbc.2025.07.021","DOIUrl":"https://doi.org/10.1016/j.clbc.2025.07.021","url":null,"abstract":"<p><strong>Background: </strong>The smallest clinically relevant change (ie, minimal clinically important difference, MCID) for several valuable PROMs for women undergoing breast cancer surgery is unknown. Therefore, this study evaluated the smallest clinically relevant change for decision uncertainty, distress after traumatic events, body image, and health status in women diagnosed with breast cancer considering surgery.</p><p><strong>Patients and methods: </strong>Between August 2020 and October 2022, we included 123 women with breast cancer considering surgical treatment. Women completed the decisional conflict scale (DCS), impact of event scale (IES), body image scale (BIS), and 36-Item Short Form (SF-36) after their first visit, and 4-6 weeks and 6 months after surgery. The MCID was calculated using the anchor-based method. For the MCID to be reliable, it needs to be greater than the minimum detectable change (MDC).</p><p><strong>Results: </strong>The MCID for decision uncertainty (8.6) was smaller than the MDC (22). MCID values were 11 and 12 (MDC 8.4) for improvement in cancer-specific distress (IES), 2.5 and 6.5 (MDC 2.6) for deterioration in body image (BIS) and 27 and 14 (MDC 12) for deterioration in health status (SF-36) at 4 to 6 weeks and 6 months after surgery, respectively.</p><p><strong>Conclusion: </strong>This study successfully determined MCIDs for several PROMs. For IES, BIS, and SF-36 the MCID seems reliable, while the DCS cannot reliably capture a clinically relevant change. The MCID values may be useful when assessing clinically relevant changes over time, interpreting treatment effects, and trial sample size determination.</p>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144945038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-30DOI: 10.1016/j.clbc.2025.07.023
Marcelo Antonini, André Mattar, Marcelo Madeira, Letícia Xavier Félix, Julio Antonio Pereira de Araújo, Francisco Pimentel Cavalcante, Felipe Zerwes, Fabricio Palermo Brenelli, Antonio Luis Frasson, Eduardo Camargo Millen, Marina Diógenes Teixeira, Larissa Chrispim de Oliveira, Marcellus do Nascimento Moreira Ramos, Gil Facina, Rogério Fenile, Henrique Lima Couto, Sabrina Monteiro Rondelo, Leonardo Ribeiro Soares, Ruffo de Freitas, Renata Arakelian, Vitoria Rassi Mahamed Rocha, Renata Montarroyos Leite, Luiz Henrique Gebrim
Purpose: To evaluate the rate and types of immunohistochemical (IHC) changes after neoadjuvant chemotherapy (NAC) and their influence on disease-free survival (DFS) and overall survival (OS) in breast cancer patients, with a focus on conversions such as HR+/HER-2+ to HR-/HER-2- and their implications for treatment adjustments.
Methods: This retrospective cohort study included 369 female patients aged 18 years or older with nonmetastatic breast cancer treated with NAC between January 2011 and January 2023. Patients who did not achieve complete pathological response were evaluated for changes in IHC profiles, including hormone receptor (HR) status, HER-2 expression, and Ki-67 index. Prognostic outcomes were assessed using Kaplan-Meier survival analysis and multivariate Cox regression models.
Results: IHC changes were observed in 41.7% of patients. Among those initially classified as HR-/HER-2-, 50.9% gained HR expression, and 14.1% acquired HER-2 expression. In HR+/HER-2+ cases, 70.8% experienced a loss of HER-2 expression. Patients with HER-2+ tumors exhibited more frequent IHC changes compared to HER-2- cases (P < .0001). After a median follow-up of 47.7 months, local recurrences occurred in 10.3% of patients, distant metastases in 29.5%, and 25.5% had died. Patients with IHC changes demonstrated significantly worse DFS and OS (P = .002), with the poorest outcomes associated with conversion to HR-/HER-2- (P < .001).
Conclusion: Post-NAC IHC changes are common and associated with poor prognosis, especially in patients losing HR and HER-2 expression. Monitoring IHC shifts is critical for guiding personalized treatment and improving prognostic evaluation.
{"title":"Prognostic Impact of Real-World Immunohistochemical Changes in Breast Cancer Treated with Neoadjuvant Chemotherapy.","authors":"Marcelo Antonini, André Mattar, Marcelo Madeira, Letícia Xavier Félix, Julio Antonio Pereira de Araújo, Francisco Pimentel Cavalcante, Felipe Zerwes, Fabricio Palermo Brenelli, Antonio Luis Frasson, Eduardo Camargo Millen, Marina Diógenes Teixeira, Larissa Chrispim de Oliveira, Marcellus do Nascimento Moreira Ramos, Gil Facina, Rogério Fenile, Henrique Lima Couto, Sabrina Monteiro Rondelo, Leonardo Ribeiro Soares, Ruffo de Freitas, Renata Arakelian, Vitoria Rassi Mahamed Rocha, Renata Montarroyos Leite, Luiz Henrique Gebrim","doi":"10.1016/j.clbc.2025.07.023","DOIUrl":"https://doi.org/10.1016/j.clbc.2025.07.023","url":null,"abstract":"<p><strong>Purpose: </strong>To evaluate the rate and types of immunohistochemical (IHC) changes after neoadjuvant chemotherapy (NAC) and their influence on disease-free survival (DFS) and overall survival (OS) in breast cancer patients, with a focus on conversions such as HR+/HER-2+ to HR-/HER-2- and their implications for treatment adjustments.</p><p><strong>Methods: </strong>This retrospective cohort study included 369 female patients aged 18 years or older with nonmetastatic breast cancer treated with NAC between January 2011 and January 2023. Patients who did not achieve complete pathological response were evaluated for changes in IHC profiles, including hormone receptor (HR) status, HER-2 expression, and Ki-67 index. Prognostic outcomes were assessed using Kaplan-Meier survival analysis and multivariate Cox regression models.</p><p><strong>Results: </strong>IHC changes were observed in 41.7% of patients. Among those initially classified as HR-/HER-2-, 50.9% gained HR expression, and 14.1% acquired HER-2 expression. In HR+/HER-2+ cases, 70.8% experienced a loss of HER-2 expression. Patients with HER-2+ tumors exhibited more frequent IHC changes compared to HER-2- cases (P < .0001). After a median follow-up of 47.7 months, local recurrences occurred in 10.3% of patients, distant metastases in 29.5%, and 25.5% had died. Patients with IHC changes demonstrated significantly worse DFS and OS (P = .002), with the poorest outcomes associated with conversion to HR-/HER-2- (P < .001).</p><p><strong>Conclusion: </strong>Post-NAC IHC changes are common and associated with poor prognosis, especially in patients losing HR and HER-2 expression. Monitoring IHC shifts is critical for guiding personalized treatment and improving prognostic evaluation.</p>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-30DOI: 10.1016/j.clbc.2025.07.028
M Judy Lubas, Jill Hasler, Jordan Fredette, Ana Sandoval-Leon, Richard Bleicher, Austin Williams, Lindsay Taylor, Joshua Meyer, Rebecca Shulman
Background: Older patients with hormone receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative early-stage breast cancer (HPEsBC) typically undergo breast-conserving surgery (BCS) followed by adjuvant radiation therapy (RT) and/or endocrine therapy (ET). Our study aimed to identify predictors of low ET adherence and evaluate the role of RT in modifying survival among patients with low ET adherence.
Methods: A retrospective analysis was performed using a US-based, electronic health record-derived, de-identified database. Patients aged ≥65 years with HPEsBC treated with BCS from 2011 to 2018 were included. Four adjuvant treatment groups were identified. Low ET adherence was defined as ET use for <80% of the 5-year post surgery follow-up period. Multinomial logistic regression was used to identify predictors of low adherence. Survival outcomes were assessed using hazard ratios (HRs) adjusted for covariates.
Results: A total of 1,488 patients were included in the study. Among patients receiving ET, 23% demonstrated low adherence. After adjustment for covariates, mortality was higher for RT alone (HR = 1.79, p = .011) and no adjuvant therapy (HR = 2.65, p < .001) compared with ET + RT. Predictors of low ET adherence included increasing age (odds ratio [OR] = 1.06, p < .010) and treatment at an academic practice (OR = 2.58, p < .001). A 10% decline in ET adherence was associated with increased mortality (HR = 1.17, p < .001). An interaction analysis revealed no differential effect of RT in the context of ET adherence.
Conclusion: Low ET adherence occurred in approximately one-quarter of patients and was associated with advancing age and treatment at academic centers. Reduced ET adherence was linked to significantly increased mortality. Further investigation into the role of RT in patients with low ET adherence is warranted.
背景：激素受体阳性，人表皮生长因子受体2 （HER2）阴性的早期乳腺癌（HPEsBC）的老年患者通常接受保乳手术（BCS），然后进行辅助放射治疗（RT）和/或内分泌治疗（ET）。我们的研究旨在确定低ET依从性的预测因素，并评估RT在改善低ET依从性患者生存中的作用。方法：使用基于美国的电子健康记录衍生的去识别数据库进行回顾性分析。纳入2011年至2018年接受BCS治疗的年龄≥65岁的HPEsBC患者。确定了四个辅助治疗组。低ET依从性被定义为ET使用的结果：共有1488名患者纳入研究。在接受ET治疗的患者中，23%表现出低依从性。调整协变量后，与ET + RT相比，单独RT组（HR = 1.79, p = 0.011）和无辅助治疗组（HR = 2.65, p < 0.001）的死亡率更高。低ET依从性的预测因素包括年龄增加（优势比[OR] = 1.06, p < 0.010）和学术实践治疗（OR = 2.58, p < 0.001）。ET依从性下降10%与死亡率增加相关（HR = 1.17, p < 0.001）。相互作用分析显示，在ET依从性的背景下，RT没有差异效应。结论：低ET依从性发生在大约四分之一的患者中，并且与年龄的增长和学术中心的治疗有关。降低ET依从性与死亡率显著增加有关。进一步研究RT在低ET依从性患者中的作用是必要的。
{"title":"The Role of Adjuvant Radiation Therapy in Treating Older Breast Cancer Patients With Low Adherence to Endocrine Therapy.","authors":"M Judy Lubas, Jill Hasler, Jordan Fredette, Ana Sandoval-Leon, Richard Bleicher, Austin Williams, Lindsay Taylor, Joshua Meyer, Rebecca Shulman","doi":"10.1016/j.clbc.2025.07.028","DOIUrl":"https://doi.org/10.1016/j.clbc.2025.07.028","url":null,"abstract":"<p><strong>Background: </strong>Older patients with hormone receptor-positive, human epidermal growth factor receptor 2 (HER2)-negative early-stage breast cancer (HPEsBC) typically undergo breast-conserving surgery (BCS) followed by adjuvant radiation therapy (RT) and/or endocrine therapy (ET). Our study aimed to identify predictors of low ET adherence and evaluate the role of RT in modifying survival among patients with low ET adherence.</p><p><strong>Methods: </strong>A retrospective analysis was performed using a US-based, electronic health record-derived, de-identified database. Patients aged ≥65 years with HPEsBC treated with BCS from 2011 to 2018 were included. Four adjuvant treatment groups were identified. Low ET adherence was defined as ET use for <80% of the 5-year post surgery follow-up period. Multinomial logistic regression was used to identify predictors of low adherence. Survival outcomes were assessed using hazard ratios (HRs) adjusted for covariates.</p><p><strong>Results: </strong>A total of 1,488 patients were included in the study. Among patients receiving ET, 23% demonstrated low adherence. After adjustment for covariates, mortality was higher for RT alone (HR = 1.79, p = .011) and no adjuvant therapy (HR = 2.65, p < .001) compared with ET + RT. Predictors of low ET adherence included increasing age (odds ratio [OR] = 1.06, p < .010) and treatment at an academic practice (OR = 2.58, p < .001). A 10% decline in ET adherence was associated with increased mortality (HR = 1.17, p < .001). An interaction analysis revealed no differential effect of RT in the context of ET adherence.</p><p><strong>Conclusion: </strong>Low ET adherence occurred in approximately one-quarter of patients and was associated with advancing age and treatment at academic centers. Reduced ET adherence was linked to significantly increased mortality. Further investigation into the role of RT in patients with low ET adherence is warranted.</p>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-30DOI: 10.1016/j.clbc.2025.07.020
Karlijn E.P.E. Hermans , Sandra M.E. Geurts , Franchette Van den Berkmortel , Jolien Tol , Joan B. Heijns , Marcus W. Dercksen , Birgit E.P.J. Vriens , Kirsten N.A. Aaldering , Manon J.A.E. Pepels , Natascha A.J.B. Peters , Linda van de Winkel , Eline Boon , Nathalie Teeuwen , Maartje A.C.E. van Kats , Vivianne C.G. Tjan-Heijnen
Purpose
The aim was to evaluate factors associated with taking 2 biopsies during the disease course of metastatic breast cancer (mBC) and to assess discordance rates for the oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2).
Methods
Patients diagnosed with mBC in ten Dutch hospitals between 2007 and 2020 were retrieved from the SONABRE Registry (NCT-03577197). Patients were identified if they had at least 2 biopsies at different time points during their mBC disease course. Last follow-up was collected in September 2023. Frequencies and factors related to a second biopsy were studied using competing risk analysis with subdistribution hazard ratios (sHR). Discordance rates and factors associated with receptor subtype discordance were analysed using logistic regression using odds ratios (OR).
Results
Of 4,470 patients with mBC, 65% had 1 and 10% 2 biopsies during the course of mBC. Having 2 biopsies for mBC was related to age (sHR: 0.61), comorbidity (sHR: 0.76), WHO performance score (sHR: 0.30 for ≥2), initial TN subtype (sHR: 0.67), and initial metastatic site (sHR: 3.68 for soft tissue only), compared with the reference categories. Patients had an overall receptor subtype discordance of 23% compared to the second biopsy. Only HR+/HER2+ status was related to receptor subtype discordance (OR: 6.45).
Conclusion
Only the minority of patients with mBC underwent a second biopsy during their mBC disease course. Receptor subtype heterogeneity is however frequent, particularly in patients with initially HR+/HER2+ mBC. Future studies are needed to guide treatment decisions as heterogeneity may play a role.
{"title":"Receptor Discordance During the Treatment Course of Patients With Metastatic Breast Cancer: Results From the SONABRE Registry","authors":"Karlijn E.P.E. Hermans , Sandra M.E. Geurts , Franchette Van den Berkmortel , Jolien Tol , Joan B. Heijns , Marcus W. Dercksen , Birgit E.P.J. Vriens , Kirsten N.A. Aaldering , Manon J.A.E. Pepels , Natascha A.J.B. Peters , Linda van de Winkel , Eline Boon , Nathalie Teeuwen , Maartje A.C.E. van Kats , Vivianne C.G. Tjan-Heijnen","doi":"10.1016/j.clbc.2025.07.020","DOIUrl":"10.1016/j.clbc.2025.07.020","url":null,"abstract":"<div><h3>Purpose</h3><div>The aim was to evaluate factors associated with taking 2 biopsies during the disease course of metastatic breast cancer (mBC) and to assess discordance rates for the oestrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2).</div></div><div><h3>Methods</h3><div>Patients diagnosed with mBC in ten Dutch hospitals between 2007 and 2020 were retrieved from the SONABRE Registry (NCT-03577197). Patients were identified if they had at least 2 biopsies at different time points during their mBC disease course. Last follow-up was collected in September 2023. Frequencies and factors related to a second biopsy were studied using competing risk analysis with subdistribution hazard ratios (sHR). Discordance rates and factors associated with receptor subtype discordance were analysed using logistic regression using odds ratios (OR).</div></div><div><h3>Results</h3><div>Of 4,470 patients with mBC, 65% had 1 and 10% 2 biopsies during the course of mBC. Having 2 biopsies for mBC was related to age (sHR: 0.61), comorbidity (sHR: 0.76), WHO performance score (sHR: 0.30 for ≥2), initial TN subtype (sHR: 0.67), and initial metastatic site (sHR: 3.68 for soft tissue only), compared with the reference categories. Patients had an overall receptor subtype discordance of 23% compared to the second biopsy. Only HR+/HER2+ status was related to receptor subtype discordance (OR: 6.45).</div></div><div><h3>Conclusion</h3><div>Only the minority of patients with mBC underwent a second biopsy during their mBC disease course. Receptor subtype heterogeneity is however frequent, particularly in patients with initially HR+/HER2+ mBC. Future studies are needed to guide treatment decisions as heterogeneity may play a role.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 7","pages":"Pages 704-713.e3"},"PeriodicalIF":2.5,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-29DOI: 10.1016/j.clbc.2025.07.025
Ofer Feinstein , Dan Ofer , Eitan Bachmat , Sivan Gazit , Michal Linial , Tehillah S. Menes
Background
Despite progress in breast cancer screening many women are diagnosed with advanced stage. We sought to develop a short-term (one year) prediction model for breast cancer risk, based on readily available data from electronic medical records (EMRs), to support decision-making.
Methods
A retrospective cohort study using data of 1,039,212 members of a large healthcare organization between the years 1985 and 2021. During the study years, 18,959 people were diagnosed with breast cancer. Longitudinal personal medical information such as demographics, cancer-related family history, smoking habits, medical history, fertility treatments, surgeries, biopsies, medications, BMI, blood pressure and lab tests was used to predict the outcome: breast cancer diagnosis one year from the recorded data.
Prediction models were trained using the CatBoost decision tree methodology. SHapley Additive exPlanations (SHAP) values were used to estimate the marginal impact of a feature on the model performance, considering the other features.
Results
The model includes numerous features not utilized in existing breast cancer risk models (e.g., medications, systolic blood pressure, TSH levels and more), available from the EMR. The informative features, ranked by SHAP values, include age, the number of surgical consultations and the number of breast biopsies. The model achieved high performance with an area under the ROC curve (AUC-ROC) of 0.85.
Conclusions
Use of data readily available from the EMR, can assist clinicians when assessing the short-term breast cancer risk.
{"title":"Short-Term Prediction Model for Breast Cancer Risk Based on One Million Medical Records","authors":"Ofer Feinstein , Dan Ofer , Eitan Bachmat , Sivan Gazit , Michal Linial , Tehillah S. Menes","doi":"10.1016/j.clbc.2025.07.025","DOIUrl":"10.1016/j.clbc.2025.07.025","url":null,"abstract":"<div><h3>Background</h3><div>Despite progress in breast cancer screening many women are diagnosed with advanced stage. We sought to develop a short-term (one year) prediction model for breast cancer risk, based on readily available data from electronic medical records (EMRs), to support decision-making.</div></div><div><h3>Methods</h3><div>A retrospective cohort study using data of 1,039,212 members of a large healthcare organization between the years 1985 and 2021. During the study years, 18,959 people were diagnosed with breast cancer. Longitudinal personal medical information such as demographics, cancer-related family history, smoking habits, medical history, fertility treatments, surgeries, biopsies, medications, BMI, blood pressure and lab tests was used to predict the outcome: breast cancer diagnosis one year from the recorded data.</div><div>Prediction models were trained using the CatBoost decision tree methodology. SHapley Additive exPlanations (SHAP) values were used to estimate the marginal impact of a feature on the model performance, considering the other features.</div></div><div><h3>Results</h3><div>The model includes numerous features not utilized in existing breast cancer risk models (e.g., medications, systolic blood pressure, TSH levels and more), available from the EMR. The informative features, ranked by SHAP values, include age, the number of surgical consultations and the number of breast biopsies. The model achieved high performance with an area under the ROC curve (AUC-ROC) of 0.85.</div></div><div><h3>Conclusions</h3><div>Use of data readily available from the EMR, can assist clinicians when assessing the short-term breast cancer risk.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 8","pages":"Pages 774-781.e4"},"PeriodicalIF":2.5,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-29DOI: 10.1016/j.clbc.2025.07.027
Juan Pablo Alzate-Granados , Luis Fernando Niño
Introduction
Triple-negative breast cancer (TNBC) accounts for 15% to 20% of breast cancer cases and is characterized by its aggressiveness and high relapse rate. Due to the absence of hormonal receptors and HER2, standard treatment relies on chemotherapy, yielding limited outcomes in overall survival (OS) and relapse-free survival (RFS). The molecular heterogeneity of TNBC complicates risk stratification and personalized treatment approaches. In this context, unsupervised machine learning could improve the identification of clinically homogeneous subgroups and facilitate prognostic predictions.
Objective
To develop predictive models for OS and RFS in TNBC patients using machine learning algorithms, specifically k-prototypes for subgroup identification and random forest for outcome prediction.
Methods
A retrospective cohort study was conducted on 4808 TNBC patients diagnosed between 2012 and 2024. Clinical, demographic, and biomolecular variables were analyzed from anonymized clinical records. The k-prototypes algorithm was applied to cluster patients into groups based on shared characteristics. Subsequently, predictive models using random forest were trained and evaluated through stratified cross-validation and metrics such as AUC, sensitivity, and specificity. Cox regression was used to identify risk factors associated with mortality and relapse.
Results
Four clusters with distinct risk profiles were identified. Overall mortality was 28.8%, and relapse occurred in 40.9%, with a median follow-up time of 8.46 years. The highest-risk group exhibited a mortality rate of 42.3% and a relapse rate of 54.2%, associated with poorer functional status (ECOG ≥3) and a high prevalence of BRCA1/2 mutations (71%). The random forest model achieved 80% accuracy in mortality prediction (AUC = 0.78) and 75% accuracy in relapse prediction (AUC = 0.76). Factors such as the Charlson Comorbidity Index, ECOG, BRCA1/2 status, and PD-L1 expression were key determinants in outcome prediction.
Discussion
The findings confirm the relevance of machine learning in TNBC stratification. A clinically meaningful classification was achieved, outperforming traditional models based solely on clinical or genomic variables. Comorbid burden and tumor biomarkers played crucial roles in outcome prediction. Despite its strengths, the study has limitations, including its retrospective nature and the absence of transcriptomic data. Prospective validation of these models could enhance their applicability in clinical practice.
{"title":"Prediction of Overall and Relapse-Free Survival in Triple-Negative Breast Cancer Patients Through Machine Learning-Based Clustering on Clinical Data","authors":"Juan Pablo Alzate-Granados , Luis Fernando Niño","doi":"10.1016/j.clbc.2025.07.027","DOIUrl":"10.1016/j.clbc.2025.07.027","url":null,"abstract":"<div><h3>Introduction</h3><div>Triple-negative breast cancer (TNBC) accounts for 15% to 20% of breast cancer cases and is characterized by its aggressiveness and high relapse rate. Due to the absence of hormonal receptors and HER2, standard treatment relies on chemotherapy, yielding limited outcomes in overall survival (OS) and relapse-free survival (RFS). The molecular heterogeneity of TNBC complicates risk stratification and personalized treatment approaches. In this context, unsupervised machine learning could improve the identification of clinically homogeneous subgroups and facilitate prognostic predictions.</div></div><div><h3>Objective</h3><div>To develop predictive models for OS and RFS in TNBC patients using machine learning algorithms, specifically k-prototypes for subgroup identification and random forest for outcome prediction.</div></div><div><h3>Methods</h3><div>A retrospective cohort study was conducted on 4808 TNBC patients diagnosed between 2012 and 2024. Clinical, demographic, and biomolecular variables were analyzed from anonymized clinical records. The k-prototypes algorithm was applied to cluster patients into groups based on shared characteristics. Subsequently, predictive models using random forest were trained and evaluated through stratified cross-validation and metrics such as AUC, sensitivity, and specificity. Cox regression was used to identify risk factors associated with mortality and relapse.</div></div><div><h3>Results</h3><div>Four clusters with distinct risk profiles were identified. Overall mortality was 28.8%, and relapse occurred in 40.9%, with a median follow-up time of 8.46 years. The highest-risk group exhibited a mortality rate of 42.3% and a relapse rate of 54.2%, associated with poorer functional status (ECOG ≥3) and a high prevalence of BRCA1/2 mutations (71%). The random forest model achieved 80% accuracy in mortality prediction (AUC = 0.78) and 75% accuracy in relapse prediction (AUC = 0.76). Factors such as the Charlson Comorbidity Index, ECOG, BRCA1/2 status, and PD-L1 expression were key determinants in outcome prediction.</div></div><div><h3>Discussion</h3><div>The findings confirm the relevance of machine learning in TNBC stratification. A clinically meaningful classification was achieved, outperforming traditional models based solely on clinical or genomic variables. Comorbid burden and tumor biomarkers played crucial roles in outcome prediction. Despite its strengths, the study has limitations, including its retrospective nature and the absence of transcriptomic data. Prospective validation of these models could enhance their applicability in clinical practice.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"25 7","pages":"Pages 714-719"},"PeriodicalIF":2.5,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144944987","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-24DOI: 10.1016/j.clbc.2025.07.019
Lisa Anderson, Oindrila Bhattacharyya, Akia Clark, Sharnell Smith, Michael Grimm, Elizabeth Fox, Annie Trance, Bridget A Oppong
Purpose: With advancements in breast cancer treatment, survivorship has increased, leading to 3.8 million survivors in the US. These women have diverse supportive care needs, often addressed through survivorship programs (SPs), which provide clinical and nonclinical support services. SPs aim to deliver a holistic approach to comprehensive breast cancer treatment and recurrence prevention. Historically, disparities in SP utilization exist among minority and elderly women. This study aims to explore trends varying in SP participation by age and race within a single institution.
Methods: A retrospective analysis of breast cancer patients' survivorship needs at a tertiary referral academic cancer center program was conducted. Data were collected from programs between 2019 and 2022, including demographics and referrals to clinical resources such as Adolescent/Young Adult care, Fertility preservation, Palliative care, Psychosocial support, and Survivorship. Participation in nonclinical areas, including Art, Education, Exercise, Mind-Body-Spirit, and Nutrition, was also evaluated. Descriptive statistics summarized patterns based on age, race, and ethnicity.
Results: From 2019 to 2022, 2198 patients attended SPs, with Nutrition and Exercise being the most popular. Most attendees were 60-69 years old and White. Black attendees declined from 9.9% (2019) to 5.7% (2022). Clinical resources showed the highest referral rate to survivorship clinics. Black patients saw an increase in palliative care referrals, rising from 11% to 21%.
Conclusion: Data reveal differences in clinical referrals by age and race, with fewer referrals for older women and more for Black patients. Participation in nonclinical SPs was similar across groups. Future program development will focus on inclusivity and equitable access.
{"title":"Preferences for Breast Cancer Survivorship Programs Among Multiracial and Ethnic Women.","authors":"Lisa Anderson, Oindrila Bhattacharyya, Akia Clark, Sharnell Smith, Michael Grimm, Elizabeth Fox, Annie Trance, Bridget A Oppong","doi":"10.1016/j.clbc.2025.07.019","DOIUrl":"10.1016/j.clbc.2025.07.019","url":null,"abstract":"<p><strong>Purpose: </strong>With advancements in breast cancer treatment, survivorship has increased, leading to 3.8 million survivors in the US. These women have diverse supportive care needs, often addressed through survivorship programs (SPs), which provide clinical and nonclinical support services. SPs aim to deliver a holistic approach to comprehensive breast cancer treatment and recurrence prevention. Historically, disparities in SP utilization exist among minority and elderly women. This study aims to explore trends varying in SP participation by age and race within a single institution.</p><p><strong>Methods: </strong>A retrospective analysis of breast cancer patients' survivorship needs at a tertiary referral academic cancer center program was conducted. Data were collected from programs between 2019 and 2022, including demographics and referrals to clinical resources such as Adolescent/Young Adult care, Fertility preservation, Palliative care, Psychosocial support, and Survivorship. Participation in nonclinical areas, including Art, Education, Exercise, Mind-Body-Spirit, and Nutrition, was also evaluated. Descriptive statistics summarized patterns based on age, race, and ethnicity.</p><p><strong>Results: </strong>From 2019 to 2022, 2198 patients attended SPs, with Nutrition and Exercise being the most popular. Most attendees were 60-69 years old and White. Black attendees declined from 9.9% (2019) to 5.7% (2022). Clinical resources showed the highest referral rate to survivorship clinics. Black patients saw an increase in palliative care referrals, rising from 11% to 21%.</p><p><strong>Conclusion: </strong>Data reveal differences in clinical referrals by age and race, with fewer referrals for older women and more for Black patients. Participation in nonclinical SPs was similar across groups. Future program development will focus on inclusivity and equitable access.</p>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":" ","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144945006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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