scholarly journals Overview of Breast Cancer and Implications of Overtreatment of Early-Stage Breast Cancer: An Indian Perspective

2020 ◽  
pp. 789-798
Author(s):  
Gouri Shankar Bhattacharyya ◽  
Dinesh C. Doval ◽  
Chirag J. Desai ◽  
Harit Chaturvedi ◽  
Sanjay Sharma ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Stage ◽  
Economic Status ◽  
Breast Cancer Diagnosis ◽  
Distant Recurrence ◽  
Response To Therapy ◽  
Fear Of Recurrence ◽  
Physical And Mental Health ◽  
Her Family ◽  
Anticancer Chemotherapy

The prevalence and mortality of breast cancer is increasing in Asian countries, including India. With advances in medical technology leading to better detection and characterization of the disease, it has been possible to classify breast cancer into various subtypes using markers, which helps predict the risk of distant recurrence, response to therapy, and prognosis using a combination of molecular and clinical parameters. Breast cancer and its therapy, mainly surgery, systemic therapy (anticancer chemotherapy, hormonal therapy, targeted therapy, and immunotherapy), and radiation therapy, are associated with significant adverse influences on physical and mental health, quality of life, and the economic status of the patient and her family. The fear of recurrence and its devastating effects often leads to overtreatment, with a toxic cost to the patient financially and physically in cases in which this is not required. This article discusses some aspects of a breast cancer diagnosis and its impact on the various facets of the life of the patient and her family. It further elucidates the role of prognostic factors, the currently available biomarkers and prognostic signatures, and the importance of ethnically validating biomarkers and prognostic signatures.

Simple and fast isolation of circulating exosomes with chitosan modified shuttle flow microchip towards breast cancer diagnosis

Lab on a Chip ◽  
2021 ◽  
Author(s):  
Wenwen Chen ◽  
Rongkai Cao ◽  
Wentao Su ◽  
xu zhang ◽  
Yuhai Xu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Medical Treatment ◽  
Cancer Diagnosis ◽  
Biological Samples ◽  
Early Stage ◽  
Breast Cancer Diagnosis ◽  
Early Stage Cancer ◽  
Tumor Prognosis ◽  
Huge Challenge

Tumor-derived exosomes have been recognized as promising biomarkers for early-stage cancer diagnosis, tumor prognosis monitoring and individual medical treatment. However, separating exosomes from trace biological samples is a huge challenge...

scholarly journals Development and validation for research assessment of Oncotype DX® Breast Recurrence Score, EndoPredict® and Prosigna®

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Richard Buus ◽  
Zsolt Szijgyarto ◽  
Eugene F. Schuster ◽  
Hui Xiao ◽  
Ben P. Haynes ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Early Stage ◽  
Recurrence Score ◽  
Distant Recurrence ◽  
Research Assessment ◽  
Expression Data ◽  
Her2 Breast Cancer ◽  
Validation Set ◽  
Development And Validation

AbstractMulti-gene prognostic signatures including the Oncotype® DX Recurrence Score (RS), EndoPredict® (EP) and Prosigna® (Risk Of Recurrence, ROR) are widely used to predict the likelihood of distant recurrence in patients with oestrogen-receptor-positive (ER+), HER2-negative breast cancer. Here, we describe the development and validation of methods to recapitulate RS, EP and ROR scores from NanoString expression data. RNA was available from 107 tumours from postmenopausal women with early-stage, ER+, HER2− breast cancer from the translational Arimidex, Tamoxifen, Alone or in Combination study (TransATAC) where previously these signatures had been assessed with commercial methodology. Gene expression was measured using NanoString nCounter. For RS and EP, conversion factors to adjust for cross-platform variation were estimated using linear regression. For ROR, the steps to perform subgroup-specific normalisation of the gene expression data and calibration factors to calculate the 46-gene ROR score were assessed and verified. Training with bootstrapping (n = 59) was followed by validation (n = 48) using adjusted, research use only (RUO) NanoString-based algorithms. In the validation set, there was excellent concordance between the RUO scores and their commercial counterparts (rc(RS) = 0.96, 95% CI 0.93–0.97 with level of agreement (LoA) of −7.69 to 8.12; rc(EP) = 0.97, 95% CI 0.96–0.98 with LoA of −0.64 to 1.26 and rc(ROR) = 0.97 (95% CI 0.94–0.98) with LoA of −8.65 to 10.54). There was also a strong agreement in risk stratification: (RS: κ = 0.86, p < 0.0001; EP: κ = 0.87, p < 0.0001; ROR: κ = 0.92, p < 0.001). In conclusion, the calibrated algorithms recapitulate the commercial RS and EP scores on individual biopsies and ROR scores on samples based on subgroup-centreing method using NanoString expression data.

A simulation model-based clinical decision tool to guide personalized treatment based on individual characteristics: Does 21-gene recurrence score assay testing change decisions?

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12507-e12507
Author(s):  
Jinani Jayasekera ◽  
Joseph A. Sparano ◽  
Young Chandler ◽  
Claudine Isaacs ◽  
Allison W. Kurian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Simulation Model ◽  
Early Stage ◽  
Clinical Decision ◽  
Distant Recurrence ◽  
Decision Tool ◽  
Decision Tools ◽  
Model Based ◽  
Life Years ◽  
Size Grade

e12507 Background: There is a need for web-based decision tools that integrate clinicopathologic features and genomic information to guide breast cancer therapy for women with node-negative, hormone receptor positive, HER2 negative (“early-stage”) breast cancer. We developed a novel simulation model-based clinical decision tool that provides prognostic estimates of treatment outcomes based on age, tumor size, grade, and comorbidities with and without 21-gene recurrence scores (RS). Methods: We adapted an extant breast cancer simulation model developed within the NCI-funded Cancer Intervention and Surveillance Modeling Network (CISNET) to derive estimates for the 10-year risks of distant recurrence, breast cancer-specific mortality, other cause mortality and life-years gained with endocrine vs. chemo-endocrine therapy for individual women based on their age, tumor size, grade, and comorbidity-level with and without RS test results. The model used an empiric Bayesian analytical approach to combine information from clinical trials, registry and claims data to provide individual estimates. External validation of the model was performed by comparing model-based breast cancer mortality rates and observed rates in the Surveillance Epidemiology and End Results (SEER) registry. Results: Several exemplar profiles were selected to illustrate the clinical utility of the decision tool. For example, the absolute chemotherapy benefit for 10-year distant recurrence risk and life-years gained, without RS testing, and the outcomes if a woman got tested and had a RS 16-20 are provided below for a 40-44-year-old woman and a 65–69-year-old woman diagnosed with a small (≤2cm), intermediate grade tumor and mild comorbidities. Conclusions: Simulation modeling is useful for creating clinical decision tools to support shared decision making for early-stage breast cancer treatment.[Table: see text]

Cholesterol, Cholesterol-Lowering Medication Use, and Breast Cancer Outcome in the BIG 1-98 Study

2017 ◽  
Vol 35 (11) ◽  
pp. 1179-1188 ◽  
Author(s):  
Signe Borgquist ◽  
Anita Giobbie-Hurder ◽  
Thomas P. Ahern ◽  
Judy E. Garber ◽  
Marco Colleoni ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Endocrine Therapy ◽  
Early Stage ◽  
Cancer Recurrence ◽  
Disease Free Survival ◽  
Distant Recurrence ◽  
Cholesterol Lowering ◽  
Hormone Receptor Positive ◽  
Cholesterol Levels ◽  
Free Interval

Purpose Cholesterol-lowering medication (CLM) has been reported to have a role in preventing breast cancer recurrence. CLM may attenuate signaling through the estrogen receptor by reducing levels of the estrogenic cholesterol metabolite 27-hydroxycholesterol. The impact of endocrine treatment on cholesterol levels and hypercholesterolemia per se may counteract the intended effect of aromatase inhibitors. Patients and Methods The Breast International Group (BIG) conducted a randomized, phase III, double-blind trial, BIG 1-98, which enrolled 8,010 postmenopausal women with early-stage, hormone receptor–positive invasive breast cancer from 1998 to 2003. Systemic levels of total cholesterol and use of CLM were measured at study entry and every 6 months up to 5.5 years. Cumulative incidence functions were used to describe the initiation of CLM in the presence of competing risks. Marginal structural Cox proportional hazards modeling investigated the relationships between initiation of CLM during endocrine therapy and outcome. Three time-to-event end points were considered: disease-free-survival, breast cancer–free interval, and distant recurrence–free interval. Results Cholesterol levels were reduced during tamoxifen therapy. Of 789 patients who initiated CLM during endocrine therapy, the majority came from the letrozole monotherapy arm (n = 318), followed by sequential tamoxifen-letrozole (n = 189), letrozole-tamoxifen (n = 176), and tamoxifen monotherapy (n = 106). Initiation of CLM during endocrine therapy was related to improved disease-free-survival (hazard ratio [HR], 0.79; 95% CI, 0.66 to 0.95; P = .01), breast cancer–free interval (HR, 0.76; 95% CI, 0.60 to 0.97; P = .02), and distant recurrence–free interval (HR, 0.74; 95% CI, 0.56 to 0.97; P = .03). Conclusion Cholesterol-lowering medication during adjuvant endocrine therapy may have a role in preventing breast cancer recurrence in hormone receptor–positive early-stage breast cancer. We recommend that these observational results be addressed in prospective randomized trials.

scholarly journals A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Lian Zou ◽  
Shaode Yu ◽  
Tiebao Meng ◽  
Zhicheng Zhang ◽  
Xiaokun Liang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Convolutional Neural Network ◽  
Cancer Diagnosis ◽  
Early Stage ◽  
Breast Cancer Diagnosis ◽  
Fine Tuning ◽  
Learning Tools ◽  
Pros And Cons ◽  
Future Work

This study reviews the technique of convolutional neural network (CNN) applied in a specific field of mammographic breast cancer diagnosis (MBCD). It aims to provide several clues on how to use CNN for related tasks. MBCD is a long-standing problem, and massive computer-aided diagnosis models have been proposed. The models of CNN-based MBCD can be broadly categorized into three groups. One is to design shallow or to modify existing models to decrease the time cost as well as the number of instances for training; another is to make the best use of a pretrained CNN by transfer learning and fine-tuning; the third is to take advantage of CNN models for feature extraction, and the differentiation of malignant lesions from benign ones is fulfilled by using machine learning classifiers. This study enrolls peer-reviewed journal publications and presents technical details and pros and cons of each model. Furthermore, the findings, challenges and limitations are summarized and some clues on the future work are also given. Conclusively, CNN-based MBCD is at its early stage, and there is still a long way ahead in achieving the ultimate goal of using deep learning tools to facilitate clinical practice. This review benefits scientific researchers, industrial engineers, and those who are devoted to intelligent cancer diagnosis.

scholarly journals Non-Invasive Biomarkers for Early Detection of Breast Cancer

Cancers ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2767
Author(s):  
Jiawei Li ◽  
Xin Guan ◽  
Zhimin Fan ◽  
Lai-Ming Ching ◽  
Yan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Early Stage ◽  
False Negative ◽  
Breast Cancer Diagnosis ◽  
Diagnostic Biomarkers ◽  
Circulating Micrornas ◽  
Non Invasive ◽  
Common Cancer ◽  
Volatile Organic

Breast cancer is the most common cancer in women worldwide. Accurate early diagnosis of breast cancer is critical in the management of the disease. Although mammogram screening has been widely used for breast cancer screening, high false-positive and false-negative rates and radiation from mammography have always been a concern. Over the last 20 years, the emergence of “omics” strategies has resulted in significant advances in the search for non-invasive biomarkers for breast cancer diagnosis at an early stage. Circulating carcinoma antigens, circulating tumor cells, circulating cell-free tumor nucleic acids (DNA or RNA), circulating microRNAs, and circulating extracellular vesicles in the peripheral blood, nipple aspirate fluid, sweat, urine, and tears, as well as volatile organic compounds in the breath, have emerged as potential non-invasive diagnostic biomarkers to supplement current clinical approaches to earlier detection of breast cancer. In this review, we summarize the current progress of research in these areas.

Taking control of cancer: Women’s choice for mastectomy.

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 11-11
Author(s):  
Andrea Marie Covelli ◽  
Nancy Baxter ◽  
Margaret Fitch ◽  
Frances Catriona Wright
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Prophylactic Mastectomy ◽  
Early Stage ◽  
Qualitative Interviews ◽  
Contralateral Prophylactic Mastectomy ◽  
Active Role ◽  
Breast Conserving Surgery ◽  
Fear Of Recurrence ◽  
Extensive Surgery

11 Background: Rates of both unilateral (UM) and contralateral prophylactic mastectomy (CPM) for early stage breast cancer (ESBC) have been increasing since 2003. Studies suggest that the increase is due to women playing an active role in decision-making. We do not know what factors are influencing the choice for more extensive surgery. Methods: To identify these factors we completed a multi-method study; conducting a systematic review of quantitative literature and qualitative interviews. Decision-making literature was identified from 5 databases and underwent thematic analysis. Purposive sampling identified women across the Toronto Area (Ontario, Canada), who were suitable candidates for breast conserving surgery (BCS) but underwent UM or CPM. Data saturation was achieved after 29 in-person interviews. Constant comparative analysis identified key concepts and themes. Results: ‘Taking control of cancer’ was the dominant theme. Literature illustrated that patients markedly overestimate risk of local recurrence, contralateral cancer and particularly, mortality. Similarly, interviews revealed that fear of breast cancer was expressed at diagnosis and drives the decision-making process. Despite surgeons discussing survival equivalence of BCS and UM, patients chose UM due to fear of recurrence and an overestimated survival advantage. Similarly, patients chose CPM to eliminate contralateral cancer and a misperceived survival benefit. Women were actively trying to Control Outcomes, as more surgery was believed to offer greater survival and therefore greater control. Conclusions: Both the literature and our interviews have illustrated that women seek UM and CPM for treatment of their ESBC to manage their fear of cancer mortality by undergoing more extensive surgery; this in turn drives mastectomy rates. It is important to understand this process so that we may improve our ability to communicate issues of importance to women and facilitate informed decision-making.

Taking control of cancer: Why women are choosing mastectomy.

2013 ◽  
Vol 31 (26_suppl) ◽  
pp. 108-108
Author(s):  
Andrea Marie Covelli ◽  
Nancy N. Baxter ◽  
Margaret Fitch ◽  
Frances Catriona Wright
Keyword(s):  
Breast Cancer ◽  
Decision Making ◽  
Prophylactic Mastectomy ◽  
Early Stage ◽  
Survival Advantage ◽  
Early Stage Breast Cancer ◽  
Fear Of Recurrence ◽  
Cancer Center ◽  
Structured Interviews ◽  
Extensive Surgery

108 Background: Rates of both unilateral (UM) and contralateral prophylactic mastectomy (CPM) for early stage breast cancer (ESBC) have been increasing since 2003. More extensive surgery is not a benign procedure without the risk of complications. Studies suggest that the increase is due to women choosing UM and CPM; we do not know what factors are influencing the choice for more extensive surgery. Methods: We conducted a qualitative study using grounded theory to identify factors for the choice of mastectomy. Purposive sampling was used to identify women across the Toronto Area (Ontario, Canada), who were suitable candidates for breast conserving surgery (BCS) but underwent UM or CPM. Data were collected through semi-structured interviews. Constant comparative analysis identified key concepts and themes. Results: Data saturation was achieved after 29 in-person interviews. 12 interviewees were treated at academic cancer centers, 6 at an academic non-cancer center and 11 at community centers. 15 women underwent UM; 14 underwent UM+CPM. Median age was 55. ‘Taking control of cancer’ was the dominant theme. Fear of breast cancerwas expressed at diagnosisand remains throughout decision making. Fear translates into the overestimated risk of local recurrenceand contralateral cancer. Despite discussion of the equivalence of BCS and UM, patients chose UM due to fear of recurrence and misperceived survival advantage. Similarly, patients chose CPM to eliminate the risk of contralateral cancer and misperceived survival advantage. Women were actively trying to Control Outcomes, as more surgery was seen as greater control. Conclusions: Women seeking UM and CPM for treatment of their early stage breast cancer manage their fear of cancer by undergoing more extensive surgery which in turn drives mastectomy rates. It is important to understand this process so that we may improve our ability to discuss issues of importance to women and facilitate informed decision-making.

Correlation of Breast Cancer Index (BCI) prognostic and predictive results to Ki67 and tumor grade in early stage HR+ breast cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e12075-e12075
Author(s):  
Carla Isadora Falkson ◽  
Jeffrey Kepes ◽  
Graham M. Poage ◽  
Junmei Liu ◽  
Catherine A. Schnabel
Keyword(s):  
Breast Cancer ◽  
High Risk ◽  
Early Stage ◽  
Tumor Biology ◽  
Tumor Grade ◽  
Distant Recurrence ◽  
Wide Distribution ◽  
Individual Risk ◽  
Chi Squared ◽  
Extended Endocrine Therapy

e12075 Background: Markers of tumor proliferative status, e.g., Ki67 and grade (G), are prognostic for early distant recurrence (DR) in HR+ breast cancer and integrated in adjuvant chemotherapy decisions; however, their impact on late DR and extended endocrine therapy (EET) decisions is less clear. BCI is a genomic assay that provides 2 results: BCI Predictive, based on HoxB13/IL17BR (H/I ratio), reports a prediction of likelihood of benefit from EET; BCI Prognostic, based on the algorithmic combination of H/I and proliferation genes, reports risk of late DR. In this study, BCI results were examined within clinicopathologic risk categories based on Ki67 and G. Methods: The BCI Clinical Database for Correlative Studies is an IRB-approved de-identified database that contains > 50 clinicopathologic and molecular variables from cases submitted for BCI testing in clinical practice (N = 14,463). Clinicopathologic variables were abstracted from pathology reports, and were available for a subset of cases. High Ki67 was defined as ≥14%. Chi-squared tests were used to compare BCI results between Ki67 and G subgroups. Results: Analyses included 3395 LN- pts (median age 59.1y; 73% ≥ 50y). BCI Prognostic showed a wide distribution of individual risk assessments in pts with high or low Ki67. A greater proportion of pts with high Ki67 was classified by BCI as high risk of late DR compared to low Ki67 (68.2% vs 26.5%; P < 0.0001); however, substantial proportions of high Ki67 pts were classified as BCI low risk (31.8%) and pts with low Ki67 classified as BCI high risk (26.5%). Overall, there was a moderate correlation between individual BCI Scores and individual Ki67 scores (Correlation = 0.519). 45.5% of pts with high Ki67 were classified as High BCI Predictive (H/I) compared to 35.5% of pts with low Ki67 (p < 0.001). Both BCI Prognostic and BCI Predictive (H/I) classified increasing proportions of pts as high risk or high benefit with increasing G (P < 0.0001). Conclusions: These findings help characterize differential stratification based on tumor biology vs Ki67/G for pts considering EET. While moderately correlated, both BCI Prognostic and BCI Predictive (H/I) identified distinct populations compared to Ki67 and G.

Mammography use in breast cancer survivors: An administrative claims study.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 6531-6531 ◽  
Author(s):  
Kathryn Jean Ruddy ◽  
Lindsey R. Sangaralingham ◽  
Heather B. Neuman ◽  
Caprice Christian Greenberg ◽  
Rachel A. Freedman ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Survivors ◽  
Cancer Diagnosis ◽  
Breast Cancer Survivors ◽  
Breast Tissue ◽  
Early Stage ◽  
Breast Cancer Diagnosis ◽  
First Year ◽  
Administrative Claims ◽  
Mammography Use

6531 Background: Annual mammography is recommended to screen residual breast tissue for new cancers and recurrent disease after treatment for early stage breast cancer. This study aimed to assess mammography rates over time in breast cancer survivors. Methods: We used administrative claims data from a large U.S. commercial insurance database, OptumLabs, to retrospectively identify privately- and Medicare Advantage-insured women with operable breast cancer who had residual breast tissue after definitive breast surgery between 2006 and 2015. We required coverage for at least 13 months following surgery. For each subsequent 13-month time period, we only included women without a loss of coverage, bilateral mastectomy, metastatic breast cancer diagnosis, or non-breast cancer diagnosis. We calculated the proportion of patients who had a mammogram during each 13-month period following breast surgery. We used multivariable logistic regression to test for factors associated with mammography in the first 13 months. Results: The cohort included 26,011 women followed for a median of 2.9 years (IQR 1.9-4.6) after surgery; 63.1% were less than 65 years of age, and 74.4% were white. In their first year of follow-up, 86% underwent mammography, but by year 7, this decreased to 73%. Fewer than 1% underwent MRI instead of mammography. In multivariable analysis, mammograms were less likely during the first year after surgery among women aged < 50 years (odds ratio [OR], 0.7; 95% confidence interval [CI], 0.6 to 0.8), African Americans (OR, 0.7; 95% CI, 0.7 to 0.8), patients who underwent mastectomy (OR, 0.7; 95% CI, 0.6 to 0.7), and patients residing in the Western part of the country (OR, 0.9; 95% CI, 0.7 to 0.9). Those with 1-2 comorbidities were more likely (OR, 1.1; 95% CI 1.1-1.2) than those with none to have a mammogram during that period. Mammography use did not differ significantly by year of diagnosis (2006-2015). Conclusions: Even in an insured cohort, a substantial proportion of breast cancer survivors do not undergo annual surveillance mammography. Mammography use falls as the time from the early stage breast cancer diagnosis increases. Understanding factors associated with lack of mammographic screening may help improve survivorship care.

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