Prognostic Value of Nodal Ratios in Node-Positive Breast Cancer

2006 ◽  
Vol 24 (18) ◽  
pp. 2910-2916 ◽  
Author(s):  
Wendy A. Woodward ◽  
Vincent Vinh-Hung ◽  
Naoto T. Ueno ◽  
Yee Chung Cheng ◽  
Melanie Royce ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Value ◽  
Staging System ◽  
Cancer Staging ◽  
Absolute Number ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Data Sets ◽  
Advantages And Disadvantages ◽  
The Impact

Purpose The American Joint Committee on Cancer staging system for breast cancer was recently updated to reflect the impact of increasing the absolute number of positive lymph nodes on prognosis. However, numerous studies suggest that nodal ratios (absolute number of involved nodes–number of nodes resected) may have greater prognostic value than absolute numbers of involved nodes. Here we examine the data supporting the use of nodal ratios in breast cancer prognosis and consider the potential advantages and disadvantages of including nodal ratios in breast cancer staging. Methods A systematic review of the literature was conducted using the following search engines: http://www.google.com ; Thomson's ISI Web of Science; PubMed. Results In multiple reports from both prospective and retrospectively collected data sets, nodal ratios have been shown to be significant predictors of outcome, including locoregional recurrence and overall survival. These studies span all stages of breast cancer and include various treatments as well as various statistical approaches. Conclusion There is considerable data supporting the use of nodal ratios in breast cancer prognosis. A thorough and methodological evaluation of the potential prognostic importance of nodal ratios in large multicenter data sets is merited and is currently being undertaken by the International Nodal Ratio Working Group.

The impact of chemokine receptor CXCR4 on breast cancer prognosis: A meta-analysis

2013 ◽  
Vol 37 (5) ◽  
pp. 725-731 ◽  
Author(s):  
Tong-peng Xu ◽  
Hua Shen ◽  
Ling-xiang Liu ◽  
Yong-qian Shu
Keyword(s):  
Breast Cancer ◽  
Chemokine Receptor ◽  
Meta Analysis ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Chemokine Receptor Cxcr4 ◽  
The Impact

“Fight fat with fat”: The impact of brown adipose tissue (BAT) on breast cancer prognosis–A retrospective analysis.

2015 ◽  
Vol 33 (15_suppl) ◽  
pp. 1585-1585 ◽  
Author(s):  
Orlando Esteban Silva ◽  
Sean Michael Warsch ◽  
Alfredo Enrique Torres ◽  
Alexandra Gomez Arteaga ◽  
Gustavo Westin ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Adipose Tissue ◽  
Brown Adipose Tissue ◽  
Retrospective Analysis ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Brown Adipose ◽  
The Impact

Incorporating Biology Into Breast Cancer Staging: American Joint Committee on Cancer, Eighth Edition, Revisions and Beyond

2018 ◽  
pp. 38-46 ◽  
Author(s):  
Elizabeth A. Mittendorf ◽  
John M. S. Bartlett ◽  
Daphne L. Lichtensztajn ◽  
Sarat Chandarlapaty
Keyword(s):  
Breast Cancer ◽  
Tumor Biology ◽  
Staging System ◽  
Cancer Staging ◽  
Her2 Status ◽  
Breast Cancer Staging ◽  
Pathologic Evaluation ◽  
Staging Systems ◽  
Eighth Edition ◽  
The Impact

Higher-quality imaging, refined surgical procedures, enhanced pathologic evaluation, and improved understanding of the impact of tumor biology on treatment and prognosis have necessitated revisions of the AJCC breast cancer staging system. The eighth edition includes clinical and pathologic prognostic stages that incorporate biologic variables—grade, estrogen and progesterone receptor status, HER2 status, and multigene panels—with the anatomic extent of disease defined by tumor, node, and metastasis categories. The prognostic staging systems facilitate more refined stratification with respect to survival than anatomic stage alone. Because the prognostic staging systems are dependent on biologic factors, accuracy is dependent on rigorous pathologic evaluation of tumors and on administration of treatment dictated by tumor biology. It is anticipated that technological advances will facilitate even more refined determination of underlying biology within tumors and in the peripheral blood, which increasingly is being evaluated as a compartment that reflects the primary tumor and sites of distant metastases. Diseases should be staged according to the eighth edition staging system to accurately reflect prognosis and to allow standardized data collection. Such standardization will facilitate assessment of the impact of advances in diagnosis and treatment of patients with breast cancer.

scholarly journals Clinical and prognostic impact of changes in the tnm system of the american joint committee for cancer, eighth edition, in patients with breast cancer

Mastology ◽  
2020 ◽  
Vol 30 (Suppl 1) ◽  
Author(s):  
Cynthia Mara Brito Lins Pereira ◽  
Yasmin de Farias Khayat ◽  
Mariana Rocha Bohone
Keyword(s):  
Breast Cancer ◽  
Staging System ◽  
Cancer Staging ◽  
Tnm Staging ◽  
Prognostic Impact ◽  
Tnm System ◽  
American Joint Committee ◽  
Therapeutic Decisions ◽  
Eighth Edition ◽  
The Impact

In Brazil, breast cancer is the first among the most prevalent malignancies in women, without considering non-melanoma skin cancer. However, in spite of the high number of deaths caused by breast cancer, there has been a great reduction in mortality rates and greater survival of patients with metastatic disease in the last decades. Such improvements are related to advances in treatment and greater knowledge about the biology of breast cancer. The American Joint Committee for Cancer (AJCC) cancer staging system is one of the important tools for doctors, and helps to predict disease progression and make therapeutic decisions. Therapeutic planning and prognosis of patients is possible through staging. Since the publication of the first edition of the Cancer Staging Manual, AJCC has insisted on seeing anatomical information. TNM staging (T: tumor; N: lymph nodes; M: metastasis). Limitations regarding this staging method were evidenced, as it is based only on anatomy and does not take biological factors into account. Through immunohistochemical study, breast cancer is subdivided into different molecular subtypes. When considering the modifications of the new edition of the TNM/AJCC system with respect to the prognostic and predictive factors of cancer, there may be a reclassification of patients, leading to a more reliable approach to their real disease condition. Objective: To analyze the impact generated by the update of the TNM/AJCC staging system (eighth edition), in the classification of patients with breast cancer seen at Hospital Ophir Loyola, a referral oncology hospital in the city of Belém, state of Pará, in 2018. Method: 176 medical records of patients undergoing treatment at Hospital Ophir Loyola, in 2018, were analyzed, which had information on the staging of the seventh edition and with immunohistochemical results. Result: 61.93% were between 40-60 years old, 46.2% were from the capital. Regarding the stage of diagnosis according to the 7th edition, 23 patients (13%) were in stage I, 66 cases (37.5%) in stage II, and the vast majority, totaling 77 cases (43.8%), in stage III. In addition, there were 03 cases (1.7%) in stage 0 (zero), and 07 cases (4%) in stage IV. There was a change in disease staging for 60.8% (107/176; 95%CI 53.4‒67.7) of the cases, 36.5% (39/107; 95%CI 28.0‒45.9) of these cases were upstaged, and in the others (63.5%, 68/107; 95%CI 54.1‒72.1), the change was to a lower prognostic category (down-staged). There was a significant increase in the proportion of cases staged in 2018 as IB and a significant reduction in cases staged by the most recent criterion such as IIB and IIIA (p<0.0001). Conclusion: the changes to new staging have shown to be more effective on the behavior of the tumor, helping in therapeutic decisions.

Effect of cyclin-dependent kinase 4 and 6 inhibitors (CDKIs) on body composition (BC) in patients (pts) with hormone receptor-positive, HER2-negative (HR+/HER2-) metastatic breast cancer (MBC).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13033-e13033
Author(s):  
Lisa Phuong ◽  
Janki Patel ◽  
Nadia Baka ◽  
Jessica Goldman ◽  
Michael Lyudmer ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Skeletal Muscle ◽  
Adipose Tissue ◽  
Metastatic Breast ◽  
Median Number ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis ◽  
Muscle Area ◽  
Hormone Receptor Positive ◽  
The Impact

e13033 Background: CDKIs with endocrine therapy (ET) is first-line treatment in HR+/HER2- MBC. Mouse models have shown that CDKIs prevent pRB phosphorylation in the mediobasal hypothalamus, a pathway hyper-activated in diet-induced obesity; and CDKIs lead to fat mass decrease without significant effect on lean mass. We aimed to assess the impact of CDKIs on weight (wt) and BC in pts with HR+/HER2- MBC. Methods: We identified pts with HR+/HER2- MBC who received CDKIs and ET from 2015-2018. To isolate the effect of CDKIs on BC, we identified another cohort of pts who only received ET. Body mass index (BMI), wt, and computed tomography (CT) records were reviewed. BC was analyzed at L3 on CT scans using Tomovision’s SliceOmatic v5.0 and included skeletal muscle area (SMA), skeletal muscle density (SMD), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and muscle adiposity (MA). Total adipose tissue (TAT) was defined as SAT+VAT+MA. BC changes at 3 and 6 months of therapy were evaluated using paired t-tests. Results: There were 107 pts who received CDKI plus ET - 43% were Black, and 41% were Hispanic. CDKIs used were palbociclib (85%), abemaciclib (9%), and ribociclib (6%). ETs used were letrozole (47%), fulvestrant (39%), anastrozole (12%), and exemestane (2%). Median number of prior chemo and ET lines was 0 (range 0-5). 63 pts received ET alone. There was no difference in age (63 vs. 65 years, p = 0.26), BMI (28.80 vs. 28.12kg/m2, p = 0.48), and visceral disease (69% vs. 65%, p = 0.64) between CDKI plus ET and ET alone group. At month 3 of CDKI plus ET, there was a significant decrease in wt (-0.30kg, Interquartile range [IQR] -2.55-0.95, p = 0.02), BMI (-0.12kg/m2, IQR -1.06-0.46, p = 0.02), SAT (-8.05cm2, IQR -32.58-14.74, p = 0.01), and TAT (-8.51cm2, IQR -50.42-17.84, p < 0.01), with similar results at month 6. These findings were not seen in pts on ET only at 3 months (wt: 0.00kg, IQR -2.65-2.38, p = 0.98; BMI: 0.00kg/m2, IQR -1.07-0.91, p = 0.93; SAT: -2.97cm2, IQR -26.10-25.15, p = 0.60; TAT: -0.58cm2, IQR -44.39-27.43, p = 0.18), or at 6 months. There were no significant changes in VAT, SMA, SMD, or MA in both groups at 3 or 6 months. In the CDKI plus ET group, baseline wt (74.64 vs. 72.72kg, p = 0.60), BMI (29.21 vs. 27.88kg/m2, p = 0.31), and SAT (280.29 vs. 252.75cm2, p = 0.31) were not significantly different for those who did or did not develop grade 3/4 toxicities. We obtained similar results when stratifying toxicities into hematological- and GI-related events. Conclusions: CDKIs are associated with decrease in BMI and SAT with no significant effect on VAT, SMA, or SMD. Given the known effect of obesity on breast cancer prognosis, CDKIs may have an additional effect on breast cancer prognosis by modulating body fat. Further studies are required to determine if decrease in SAT is associated with breast cancer outcomes or toxicities in pts on CDKIs.

scholarly journals A Review of Computer-Aided Expert Systems for Breast Cancer Diagnosis

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2764
Author(s):  
Xin Yu Liew ◽  
Nazia Hameed ◽  
Jeremie Clos
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Deep Learning ◽  
Main Process ◽  
Learning Approaches ◽  
Learning Methods ◽  
Advantages And Disadvantages ◽  
Computer Aided ◽  
Conventional Methods ◽  
The Impact

A computer-aided diagnosis (CAD) expert system is a powerful tool to efficiently assist a pathologist in achieving an early diagnosis of breast cancer. This process identifies the presence of cancer in breast tissue samples and the distinct type of cancer stages. In a standard CAD system, the main process involves image pre-processing, segmentation, feature extraction, feature selection, classification, and performance evaluation. In this review paper, we reviewed the existing state-of-the-art machine learning approaches applied at each stage involving conventional methods and deep learning methods, the comparisons within methods, and we provide technical details with advantages and disadvantages. The aims are to investigate the impact of CAD systems using histopathology images, investigate deep learning methods that outperform conventional methods, and provide a summary for future researchers to analyse and improve the existing techniques used. Lastly, we will discuss the research gaps of existing machine learning approaches for implementation and propose future direction guidelines for upcoming researchers.

scholarly journals Influence of tumor location on breast cancer prognosis

2003 ◽  
Vol 105 (4) ◽  
pp. 542-545 ◽  
Author(s):  
Niels Kroman ◽  
Jan Wohlfahrt ◽  
Henning T. Mouridsen ◽  
Mads Melbye
Keyword(s):  
Breast Cancer ◽  
Tumor Location ◽  
Breast Cancer Prognosis ◽  
Cancer Prognosis
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