Recurrence In Early Breast Cancer Research Articles

Neoadjuvant letrozole and palbociclib in patients with HR-positive/HER2-negative early breast cancer and Oncotype DX Recurrence Score ≥18: DxCARTES study

The effect of the addition of cyclin-dependent kinases 4 and 6 inhibitors to endocrine therapy in terms of molecular downstaging remains undetermined. Switching from a high-risk to a low risk Recurrence Score (RS) group could provide useful information to identify patients who might not require chemotherapy. The purpose of this study was to assess the biological and clinical activity of letrozole plus palbociclib as neoadjuvant treatment for patients with hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative early breast cancer with an initial Oncotype DX RS ≥18. Participants were women aged ≥18 years with HR-positive/HER2-negative, Ki67 ≥ 20%, stage II-IIIB early breast cancer with a baseline RS ≥18. Eligible patients with a pretreatment RS 18-25 (cohort A) and 26-100 (cohort B) received six 28-day cycles of letrozole (2.5 mg per day; plus goserelin if pre- or perimenopausal) plus palbociclib (125 mg per day; 3/1 schedule) before surgery. The primary endpoint for both cohorts was the proportion of patients who achieved an RS ≤25 at surgery or a pathological complete response (pCR). A total of 67 patients were enrolled, among which 65 were assessable for the primary endpoint (32 patients in cohort A and 33 in cohort B). At surgery, 22 (68.8%) patients in cohort A and 18 (54.5%) patients in cohort B had an RS ≤25 or a pCR [only 1 (3.0%) patient in cohort B], meeting the primary endpoint in cohort B (P < 0.01), but not in cohort A (P= 0.98). No new safety signals were identified. The efficacy of neoadjuvant treatment with letrozole plus palbociclib does not seem to depend on pretreatment RS for patients with RS ≥18. However, around half of patients with HR-positive/HER2-negative early breast cancer with an RS 26-100 at baseline achieved molecular downstaging with this regimen.

234MO Explaining the relationships between age, endocrine therapy persistence and risk of recurrence in hormone-positive early breast cancer: A nationwide cohort study

234MO Explaining the relationships between age, endocrine therapy persistence and risk of recurrence in hormone-positive early breast cancer: A nationwide cohort study

Pattern of Recurrence in Early Breast Cancer at a Tertiary Center in Sub-Saharan Africa: A Retrospective Cohort Study

Pattern of Recurrence in Early Breast Cancer at a Tertiary Center in Sub-Saharan Africa: A Retrospective Cohort Study

Clinical and Genomic Risk for Late Breast Cancer Recurrence and Survival

BackgroundThe 21-gene recurrence score (RS) assay (Oncotype DX) is used to guide adjuvant chemotherapy use for patients with hormone receptor–positive, HER2 (human epidermal growth factor receptor 2)-negative, axillary node-negative breast cancer. Its role, however, in providing prognostic information for late distant recurrence when added to clinicopathologic prognostic factors is unknown.MethodsA patient-specific meta-analysis including 10,004 women enrolled in three trials was updated using extended follow-up data from TAILORx, integrating the RS with histologic grade, tumor size, and age at surgery for the RSClin tool. Cox models integrating clinicopathologic factors and the RS were compared by using likelihood ratio (LR) tests. External validation of prognosis for distant recurrence in years 0 to 10 and 5 to 10 was performed in an independent cohort of 1098 women in a real-world registry.ResultsRSClin provided significantly more prognostic information than either the clinicopathologic factors (ΔLR chi-square, 86.2; P<0.001) or RS alone (ΔLR chi-square, 131.0; P<0.001). The model was prognostic in an independent cohort for distant recurrence by 10 years after diagnosis (standardized hazard ratio, 1.56; 95% confidence interval, 1.25 to 1.94), was associated with late distant recurrence risk between 5 and 10 years after diagnosis (standardized hazard ratio, 1.78; 95% confidence interval, 1.25 to 2.55), and approximated the observed 10-year distant recurrence risk (Lin concordance, 0.87) and 5- to 10-year distant recurrence risk (Lin concordance, 0.92).ConclusionsThe 21-gene RS is prognostic for distant recurrence and overall survival in early breast cancer. A model integrating the 21-gene RS and clinicopathologic factors improved estimates of distant recurrence risk compared with either used individually and stratified late distant recurrence risk. (Funded by the National Cancer Institute, National Institutes of Health [U10CA180820, U10CA180794, UG1CA189859, U10CA180868, and U10CA180822] and others.)

The impact of extensive intraductal component (EIC) on the genomic risk of recurrence in early hormone receptor positive breast cancer

BackgroundEarly invasive ductal carcinoma (IDC) breast cancer often presents with a coexisting ductal carcinoma in situ (DCIS) component, while about 5 % of cases present with an extensive (>25 %) intraductal component (EIC). The impact of EIC on the genomic risk of recurrence is unclear. MethodsPatients with early hormone receptor-positive HER2neu-negative (HR + HER2-) IDC breast cancer and a known OncotypeDX Breast Recurrence Score® (RS) who underwent breast surgery at our institute were included. Using a rule-based text-analysis algorithm, we analyzed pathological reports and categorized patients into three groups: EIC, non-extensive DCIS (DCIS-L), and pure-IDC (NO-DCIS). Genomic risk was determined using OncotypeDX RS. ResultsA total of 33 (4.6 %) EIC cases, 377 (57.2 %) DCIS-L cases and 307 (42.8 %) NO-DCIS cases were identified. Patients in the EIC group were younger and had lower tumor grades than other groups. The distribution of genomic risk varied between the groups, with EIC tumors significantly less likely to have a high RS (>25) compared to DCIS-L and No-DCIS tumors (3 % vs 20 % and 20 %, respectively; p = 0.03). When adjusted to age, tumor size, grade and LNs involvement, both DCIS-L and NO-DCIS groups were significantly correlated with a higher probability of high RS compared to the EIC group (OR 12.3 and OR 13.1, respectively; p < 0.02). Moreover, patients with EIC had a lower likelihood for adjuvant chemotherapy recommendation. ConclusionsIn early HR + HER2- IDC, an EIC correlates with a reduced genomic recurrence risk. The impact on genomic risk seems to be influenced by the extent, not merely the presence, of DCIS.

The correlation between Ki 67 and Oncotype Dx on HR+, HER2- early breast cancer management: Insights of molecular testing.

e12546 Background: Elevated Ki-67 expression serves as an indicator of tumoral proliferation in breast cancer (BC) and is used in Ecuador for survival estimation, recurrence risk assessment, and guiding chemotherapy decisions. The Oncotype DX Breast Recurrence Score (ODX RS) is a validated 21-gene assay for hormone receptor-positive, HER2-negative invasive BC. It predicts chemotherapy benefits and the risk of distant recurrence over 10 years and is a mortality indicator. ODX RS has the potential to reduce the need for chemotherapy, alleviate financial burdens, and enhance clinical outcomes. Despite conflicting evidence on the significance of Ki-67 in the ODX RS, there is a lack of exploration within Latin populations. This study aims to compare the correlation of immunohistochemical (IHC) measured Ki-67 to the ODX RS in the Ecuadorian population. Methods: A retrospective analysis included women with early BC who underwent ODX RS testing in Ecuador from May 2020 to January 2023. Inclusion criteria: early BC (T1-T3/N0-N1a); IHC estrogen receptor (ER) positive; HER2 negative; and availability of tumor size, grade, lymph node status, and Ki67 proliferation index data. Exclusion criteria: patients with recurrent BC, incomplete pathology, or lacking IHC data. Patients were categorized into low (≤5%), intermediate (6%–29%), and high Ki67 expression groups (≥30%). Using the statistical software SPSS, the correlation between ODX scores and Ki-67 expression was analyzed using Pearson’s correlation coefficient. For risk stratification groups, Spearman's correlation was employed. Results: Among 77 patients undergoing Oncotype DX testing, 64 (with a mean age of 55) met the inclusion criteria. Eighty-six percent of cases were invasive ductal carcinomas (IDC). Seventeen percent exhibited low Ki-67 expression, 61% intermediate, and 20% high. No statistically significant correlation was found between IHC Ki-67 expression and ODX RS (r=0.051; p=0.69), neither when stratified by categories (r=0.086; p=0.50). A subanalysis based on risk categories showed 82% correspondence in the low Ki-67 group, 18% in the intermediate group, and 31% in the high Ki-67 group. No significant correlation was observed when stratified by histological types (invasive ductal carcinoma and invasive lobular carcinoma), nor by sample origin (core biopsy, excisional biopsy). Conclusions: There was no correlation between IHC Ki-67 expression and ODX risk scores in this study involving Ecuadorian patients. Our findings emphasize that IHC Ki-67 expression should not be the sole determinant for guiding therapeutic decisions and predicting recurrence in early breast cancer.[Table: see text]

Artificial intelligence algorithms for recurrence risk score prediction in early-stage breast cancer: A multicenter study of 437 cases.

545 Background: In non-developed and developing countries, the 21 gene assay (Oncotype DX) test is expensive and not covered by private and social health insurance, which limits its use. However, clinicians need this test for treatment prediction in early stage breast cancer. Therefore, we aimed to predict the risk of recurrence in patients using artificial intelligence (AI) algorithms. Methods: This study was conducted with 437 early-stage breast cancer patients whose recurrence risk scores were determined by 21 Oncotype DX and were followed in 14 oncology centers in Turkey between 2012 and 2022. The optimum cut-off for the 21 gene assay risk score (RS) was found by ROC analysis using the patients' recurrence information (scale of RS ≥17: high risk, &lt;17: low risk). In artificial intelligence prediction models, patients with a 21 gene assay risk score ≥17 were considered high risk. Additionally, algorithm predictions were made within other cut-offs recommended in the literature (&lt;10, 11-25, &gt;25). Python programming language was used in the analyses. The Random Forest (RF), Logistic regression (LG) and K-Nearest Neighbors (KNN) were used as AI prediction algorithms. Results: The study analyzed 437 women with an average age of 49.49±10.30. During the follow-up period from 2012 to 2022, 7.1% of the patients experienced a recurrence. AI prediction algorithms which were RF, LG, and KNN generated confusion matrices for two classes, with a threshold of 17 and 25. The algorithms were then applied to the dataset with risk score thresholds of 1-10, 11-25, and greater than 25, resulting in three classes. The dataset was analyzed using recall, precision, and F1 score values. The results showed that RF had the most accurate predictions for RS = 17 (Table). Conclusions: The use of artificial intelligence algorithms in predicting the risk of recurrence in early stage breast cancer is promising in determining treatment decisions for clinicians who cannot access genetic results. [Table: see text]

Can early post-operative MRI describe a predictor model for the likelihood of early breast cancer recurrence after conservative surgery?

Can early post-operative MRI describe a predictor model for the likelihood of early breast cancer recurrence after conservative surgery?

Abstract PO2-01-11: Demographic, Lifestyle, and Clinical Factors Associated with Early vs. Late Recurrence among Women with Early-Stage Estrogen Receptor-Positive Breast Cancer in the Prospective Pathways Study

Abstract Background: Although women diagnosed with early-stage estrogen receptor (ER)-positive breast cancer generally have a favorable prognosis, they face a lingering risk of late recurrence that can occur years to decades after diagnosis. Relatively little is known about the demographic, lifestyle, or clinical factors associated with the risk of late recurrence, or whether the associations differ between early vs. late recurrence. Methods: We performed a comprehensive analysis of factors related to early vs. late recurrence in early-stage ER-positive breast cancer in the Pathways Study, an established prospective cohort of women diagnosed with invasive breast cancer at Kaiser Permanente Northern California (KPNC) between 2006 and 2013. Recurrences were identified through monthly searches of the KPNC Cancer Registry, follow-up interviews with participants, and confirmation with electronic medical records. For this analysis, 2,473 women with stage I-IIB, ER-positive breast cancer were included, with ascertainment of recurrence and death through December 31, 2021. Univariate analysis and multivariable Cox regression models were used to examine the factors associated with early (&amp;lt; 5 years since diagnosis) and late (≥ 5 years since diagnosis) recurrence. Results: The median age of diagnosis was 57 (± 10) years, with 35% diagnosed before menopause. While 64% of patients self-reported as White, 16% identified as Asian, 6% Black, 12% Hispanic, and 2% other ethnicity. After a median 13.3 (range: 0.6-16.8) years of follow up, a total of 341 (13.8%) recurrences occurred, with 158 before and 181 at or after 5 years from diagnosis. Approximately a third of recurrences were local or regional and the other two thirds were distant. In univariate analysis, increasing stage and tumor grade were associated with higher risk of both early and late recurrence (p&amp;lt; 0.05). Progesterone receptor (PR) negativity was associated with only early (hazard ratio [HR]=1.49, 95% confidence interval [CI] 1.06-2.09) but not late recurrence (HR=0.90, 95% CI 0.63-1.28). In unadjusted models, receiving lumpectomy (vs. mastectomy), chemotherapy, radiation therapy, or endocrine therapy were associated with lower risk of both early and late recurrence. Among the demographic and lifestyle factors examined, postmenopausal status at diagnosis was associated with lower risk of early (HR=0.69, 95% CI 0.51-0.96) but not late recurrence (HR=1.00, 95% CI 0.73-1.36). No association was found with body mass index, socioeconomic measures (education, income, employment, marital status), smoking, alcohol intake, or physical activity assessed at the time close to diagnosis. Notably, minoritized racial/ethnic groups all had higher risk of early recurrence than White women (Asian: HR=1.76, 95% CI 1.16-2.66; Black: HR=2.33, 95% CI 1.38-3.93; Hispanic: HR=1.80, 95% CI 1.15-2.82), but no association was found with late recurrence (Asian: HR=0.99, 95% CI 0.65-1.51; Black: HR=0.80, 95% CI 0.41-1.58; Hispanic: HR=0.80, 95% CI 0.48-1.33). In multivariable Cox models adjusted for age, cancer stage, grade, PR status, surgery, radiation therapy, chemotherapy, and endocrine therapy, the trend of higher risk of early recurrence among minoritized racial/ethnic groups remained, although the association remained significant only in Black women (HR=1.89, 95% CI 1.08-3.31). Conclusion: Most histopathological features and cancer treatment modality had similar impact on early vs. late recurrence among women with early-stage ER-positive breast cancer, although PR negativity might be an adverse risk factor for early recurrence only. The findings of higher risk of early but not late recurrence among Asian, Black, and Hispanic relative to White women provide some novel data on the racial/ethnic disparities of prognosis for ER-positive breast cancer and may warrant further investigation. Citation Format: Alfredo Chua, Haiyang Sheng, Shipra Gandhi, Marilyn Kwan, Isaac Ergas, Janise Roh, Cecile Laurant, Thaer Khoury, Scarlett Gomez, Christine Ambrosone, Lawrence Kushi, Song Yao. Demographic, Lifestyle, and Clinical Factors Associated with Early vs. Late Recurrence among Women with Early-Stage Estrogen Receptor-Positive Breast Cancer in the Prospective Pathways Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-01-11.

Multimodality Imaging of Postmastectomy Breast Reconstruction Techniques, Complications, and Tumor Recurrence.

For women undergoing mastectomy, breast reconstruction can be performed by using implants or autologous tissue flaps. Mastectomy options include skin- and nipple-sparing techniques. Implant-based reconstruction can be performed with saline or silicone implants. Various autologous pedicled or free tissue flap reconstruction methods based on different tissue donor sites are available. The aesthetic outcomes of implant- and flap-based reconstructions can be improved with oncoplastic surgery, including autologous fat graft placement and nipple-areolar complex reconstruction. The authors provide an update on recent advances in implant reconstruction techniques and contemporary expanded options for autologous tissue flap reconstruction as it relates to imaging modalities. As breast cancer screening is not routinely performed in this clinical setting, tumor recurrence after mastectomy and reconstruction is often detected by palpation at physical examination. Most local recurrences occur within the skin and subcutaneous tissue. Diagnostic breast imaging continues to have a critical role in confirmation of disease recurrence. Knowledge of the spectrum of benign and abnormal imaging appearances in the reconstructed breast is important for postoperative evaluation of patients, including recognition of early and late postsurgical complications and breast cancer recurrence. The authors provide an overview of multimodality imaging of the postmastectomy reconstructed breast, as well as an update on screening guidelines and recommendations for this unique patient population. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Abstract 7653: Role of ITGB2 in patients with luminal B1 breast cancer

Abstract Purpose: Luminal-type breast cancers are the most commonly diagnosed in women. Among them, the luminal B1 subtype exhibits higher proliferation rates and a worse prognosis compared to the luminal A subtype. Despite significant advancements in detection and therapies, recurrence still occurs after primary treatment. In this study, our aim is to identify genomic alterations in early recurrent luminal B1 breast cancer. Experimental Design: In this VGHTPE cohort, we recruited a total of 42 patients diagnosed with stage I-III luminal B1 breast cancer, comprising 15 subjects who experienced recurrence within five years and 27 subjects who did not. Genomic DNA was extracted from formalin-fixed paraffin-embedded samples and subjected to targeted next-generation sequencing. We assessed cell aggressiveness through in vitro transwell migration, invasion, and sphere assays. Results: Luminal B1 breast cancer patients with advanced stage and poorly differentiated tumors were associated with recurrence within five years. Driver gene mutation analysis revealed that TP53 mutations were present in 46.7% of patients who experienced recurrence within five years, compared to 29.6% in the non-recurrence group. In the analysis of copy number variations, the most common amplifications/gains observed in luminal B1 breast cancer patients were in MCL1, MYC, and KLF6. Remarkably, patients who experienced recurrence within five years showed a higher occurrence of gain in ITGB2, the gene encoding the integrin β chain, compared to those who remained recurrence-free. Patients with ITGB2 amplifications/gains had a shorter 5-year recurrence-free survival compared to those with a neutral status. In vitro studies revealed that the knockdown of ITGB2 suppressed cell migration, invasion, and sphere formation in estrogen receptor-positive HER2-negative breast cancer cells. Conclusion: Our study has identified ITGB2 amplifications/gains as a potential biomarker for early recurrence in luminal B1 breast cancer. Citation Format: Chun-Yu Liu, Ji-Lin Chen, Yi-Fang Tsai, Ta-Chung Chao, Wan-Lun Wang, Pei-Ju Lien, Chih-Yi Hsu, Jiun-I Lai, Chi-Cheng Huang, Jen-Hwey Chiu, Ling-Ming Tseng. Role of ITGB2 in patients with luminal B1 breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7653.

α-Smooth Muscle Actin as Predictors of Early Recurrence in Early-Stage Ductal Type Breast Cancer After Mastectomy and Chemotherapy.

Breast cancer recurrence after surgery was a sign that the progress of the disease was continuing. Early detection of breast cancer patients who are at risk requires development of a marker. Alfa smooth muscle actin (α-SMA) plays a role in the local recurrence process of invasive ductal carcinoma (IDC). Currently, existing tumor markers are used to predict the prognosis of breast cancer in general, not the early stages. Therefore, it was thought that finding α-SMA expression might predict early recurrence in early-stage IDC more accurately than others. This study investigated the potential role of α-SMA expression as a predictor of early recurrence in early-stage IDC and its relationship to clinicopathological factors. The study design was cross-sectional, with data obtained from the medical records of Dr. Koesnadi, General Hospital, Bondowoso, Indonesia. Bivariate and multivariate analysis was performed to analyze data. We included 50 subjects divided into the local recurrence group (n=25) and the non-local recurrence group (n=25). We found a statistically significant correlation between the incidence of local recurrence in early-stage IDC and the high expression of α-SMA (odd ratio [OR]=23.22, 95% confidence interval [CI]=5.101-105.7, P=0.001). Clinicopathological variables and α-SMA expression did not have a significant correlation. In early-stage IDC, α-SMA expression had the potential to predict and could be an independent prognostic factor for early recurrence.

Multicenter Prospective Study in HER2-Positive Early Breast Cancer for Detecting Minimal Residual Disease by Circulating Tumor DNA Analysis With Neoadjuvant Chemotherapy: HARMONY Study

Background: Biomarkers to predict the recurrence risk are required to optimize perioperative treatment. Adjuvant chemotherapy for patients with human epidermal growth factor 2-positive (HER2-positive) early breast cancer is decided by pathological responses of neoadjuvant chemotherapy (NAC). However, whether pathological responses are appropriate biomarkers is unclear. Currently, there are several studies using minimal residual disease (MRD) as a predictor of prognosis in solid tumors. However, there is no standard method for detecting MRD. Objectives: This study aimed at prospectively evaluating the relationship between MRD detection and recurrence in Asian patients with HER2-positive early breast cancer. Design: Prospective, observational, single-group, and exploratory. This study will include 60 patients from 2 institutions in Japan and the Philippines. The invasive disease-free survival (IDFS) rates of the MRD-positive and MRD-negative groups are compared in patients with HER2-positive early breast cancer who undergo surgery after receiving NAC. Methods and analysis: Circulating tumor DNA (ctDNA) levels of patients will be evaluated 6 times: before NAC, after NAC, after surgery, and annually after surgery for 3 years. We will analyze the genetic profile of blood and tissue samples using the Todai OncoPanel (TOP) and the methylation level of DNA. The primary endpoint is IDFS. Secondary endpoints include overall survival (OS) and disease-free survival (DFS). Patient enrollment began in June 2022, and new participants are still being recruited. Ethics: This study has been approved by the National Cancer Center Hospital Certified Review Board in March 2022 and has been approved by the Research Ethics Board of the participating center. Discussion: Our findings will contribute to determining whether MRD detection using TOP is useful for predicting the recurrence of HER2-positive early breast cancer. If this is proven, MRD detected by TOP could be used in the future as a biomarker to assist in the de-/escalation of treatment strategies in the next interventional trial, thereby avoiding overtreatment in patients at low risk, and in the addition of intensive treatment modalities for those in patients at high risk.

Matrix Metalloproteinase as Predictors of Local Recurrence in Early-Stage Breast Cancer After Mastectomy and Chemotherapy A Cross-Sectional Study in Single Centre

Introduction: The prognosis for early-stage breast cancer is generally favourable. However, in cases when a recurrence manifests after therapy, the prognosis becomes significantly poor. To determine early breast cancer recurrence risk, a marker is needed. Currently, previous tumour markers are used to predict general breast cancer, lacking specificity in the context of early breast cancer. Matrix Metalloproteinase1 (MMP1) is already acquainted with the local recurrence process of invasive ductal carcinoma (IDC). MMP1 expression may better predict early recurrence in early-stage IDC than other approaches. This research examined the potential predictive value of MMP1 expression in early-stage IDC for early local recurrence and its correlation with clinicopathological factors. Methods: This study was a cross-sectional analysis of a single center's medical records. The sample size was 25 subjects for the group without recurrence and 25 subjects with recurrence. Mastectomy and chemotherapy were performed from January 2014 through December 2019. Using immunohistochemistry, paraffin blocks of surgical specimens were examined for MMP1. The data processing was done utilising the trial version of IBM SPSS 25. and Openepi 3.0 programs and analysed using Bivariate, which is performed using the Chi-square test or Fisher's exact test. Result: The statistic test showed a significant difference (p &lt; 0.000) in the average expression of MMP1 for non-recurrence cases (3,95±5,36) compared to recurrence cases (14,95±5,36). We also found a statistically significant correlation between recurrence and high expression of MMP1 (odd ratio [OR]= 60.38, 95% confidence interval [CI]=10.01-364.3, p&lt;0.001). Clinicopathological variables and MMP1 expression did not have a significant correlation. Conclusions: In early-stage IDC, MMP1 expression had the potential to predict and could be an independent prognostic factor for early recurrence.

Early Breast Cancer Fast Facts: Results, Recurrence, Resources

Despite successful treatment, there is always a risk of recurrence in early breast cancer. The risk of recurrence varies depending on various factors such as the size of the tumor, lymph node involvement, hormone receptor status, and other individual characteristics.

Predictive factors of axillary lymph node involvement in Tunisian women with early breast cancer.

Axillary lymph node involvement (ALNI) is associated with an increased risk of local recurrence and poor prognosis in early breast cancer. The determination of the risk of positive axillary lymph node contributes to therapeutic decisions. The aim of this study was to identify clinicopathological predictive factors of axillary lymph node metastases in patients with early breast cancer. We included patients with clinical T0, T1 andT2 invasive breast carcinoma who underwent resection of the primary tumor and axillary staging by sentinel lymph node biopsy and/or axillar lymph node dissection between 2012 and 2018. Of the 135patients included, 41.5% had ALNI. Regarding univariate analysis, clinical factors correlated with positive ALNM were clinical tumour size>30mm, clinical tumour stage, clinical number of tumours, clinical axillary nodal status and nodal status on ultrasound. Pathologic factors associated with nodal involvement were pathologic tumour stage, tumour grade SBR, number of foci, lymphovascular invasion, perineural invasion and Ki67>20%.In multivariate logistic regression, clinical axillary nodal status, pathologic tumour stage and lymphovascular invasion (LVI) remained as independent predictors of ALNI. Based on these results, we suggest that clinical axillary nodal status, pathologic tumour stage and LVI are predictive factors for ALNM in Tunisian women with early breast cancer.

Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2–4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008–2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

Estimating the overall survival benefit of adjuvant chemo-endocrine therapy in women over age 50 with pT1-2N0 early stage breast cancer and 21-gene recurrence score ≥26: A National Cancer Database analysis.

Validation studies of the 21-gene recurrence score (RS) previously demonstrated that adjuvant chemotherapy plus endocrine therapy (CET) was associated with a significant survival benefit in women with node negative breast cancer (BC) and RS >31. However, the TAILORx trial, did not quantify the benefit of adjuvant CET in older women with node negative hormone receptor positive (HR+) BC with RS ≥26. We hypothesized that CET would be associated with improved overall survival (OS) compared to endocrine therapy (ET) in women >50 with HR+/HER2-node negative BC and RS ≥26. The National Cancer Database (NCDB) was queried to identify women >50 with RS ≥26 ER+/HER2-BC pT1-2N0M0. Chi-square and logistic regression analysis determined the difference between ET and CET. OS was analyzed using a multivariable Cox model. We included 16,745 women-4740 (28.3%) received ET and 12,005 (71.7%) received CET. Women who received CET had: moderately (OR = 1.853, p < 0.001) or poorly/undifferentiated tumors (OR = 3.875, p < 0.001), pT2 (OR = 1.356, p < 0.001), or lymph-vascular invasion (OR = 1.206, p = 0.001). After accounting for demographic and oncologic factors, 5-year OS rates were significantly superior in women receiving CET vs. ET alone (95.4% vs. 92.0%, Hazard Ratio = 0.680, p < 0.001). We observed that CET was associated with a clinically and statistically significant higher OS compared to ET alone in women >50 years of age with RS ≥26 pT1 and pT2 N0M0 HR+/HER2-breast cancer, and which suggests that cytotoxic chemotherapy has an impact on reducing mortality that is independent of induction of premature ovarian failure.

Expert UK consensus on the definition of high risk of recurrence in HER2-negative early breast cancer: A modified Delphi panel

BackgroundThere is currently no standardised definition for patients at high risk of recurrence of human epidermal growth factor receptor 2 (HER2)-negative early breast cancer (eBC; stages 1–3) after surgery. This modified Delphi panel aimed to establish expert UK consensus on this definition, separately considering hormone receptor (HR)-positive and triple-negative (TN) patients. MethodsOver three consecutive rounds, results were collected from 29, 24 and 22 UK senior breast cancer oncologists and surgeons, respectively. The first round aimed to determine key risk factors in each patient subgroup; subsequent rounds aimed to establish appropriate risk thresholds. Consensus was pre-defined as ≥70% of respondents. ResultsExpert consensus was achieved on need to assess age, tumour size, tumour grade, number of positive lymph nodes, inflammatory breast cancer and risk prediction tools in all HER2-negative patients. There was additional agreement on use of tumour profiling tests and biomarkers in HR-positive patients, and pathologic complete response (pCR) status in TN patients. Thresholds for high recurrence risk were subsequently agreed. In HR-positive patients, these included age <35 years, tumour size >5 cm (as independent risk factors); tumour grade 3 (independently and combined with other high-risk factors); number of positive nodes ≥4 (independently) and ≥1 (combined). For TN patients, the following thresholds reached consensus, both independently and in combination with other factors: tumour size >2 cm, tumour grade 3, number of positive nodes ≥1. ConclusionsThe results may be a valuable reference point to guide recurrence risk assessment and decision-making after surgery in the HER2-negative eBC population.

Breast Cancer Recurrence Prediction Using Data Mining

Today, the Healthcare sector is generating a vast amount of meticulously detailed information on individuals and their medical issues. Medical data may be investigated for hidden patterns or connections using data mining techniques. The spread and return of the illness are the main causes of breast cancer fatalities. One of the most important areas of study in the field of medicine is the early diagnosis of breast cancer. Healthcare businesses can benefit from data mining by forecasting patient illnesses and behaviour trends. This is performed by analyzing data from many angles and by using data mining to find hidden patterns and associations between seemingly unrelated bits of information. Months after the original diagnosis and breast cancer therapy, a metastatic recurrence of the disease may happen. Only a few number of techniques have been researched in the state of the art due to the challenges associated with early breast cancer recurrence prediction during its medication. The aim of the research is to review the work done by different researchers in this field and to compare the various traditional data mining classifiers (Logistic Regression, Naïve Bayes, K-Nearest Neighbours, Decision Tree, Support Vector Machines, and Random Forest) applied to Breast Cancer Data Set from UCI Machine Learning Repository. Out of these, the best results were given by Random Forest Algorithm with 98.4% accuracy.