scholarly journals Breast Cancer Metastatic Relapse in Young Moroccan Women According to Prognostic Factors (A Study about 60 Cases)

2021 ◽  
Vol 4 (4) ◽  
pp. 124-130
Author(s):  
  Benlghazi Abdelhamid ◽  
Belouad Moad ◽  
Saad Benali ◽  
Aitbouhou Rachid ◽  
Kouach Jawad
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Metastatic Relapse ◽  
Moroccan Women

Axillary lymph node nanometastases are prognostic factors for metastatic relapse in breast cancer patients

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 610-610
Author(s):  
S. Alberti ◽  
P. Querzoli ◽  
M. Pedriali ◽  
R. Rinaldi ◽  
E. Biganzoli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factor ◽  
Prognostic Factors ◽  
Lymph Node ◽  
Adverse Events ◽  
Competing Risks ◽  
Axillary Lymph ◽  
Prognostic Impact ◽  
T Stage ◽  
Metastatic Relapse

610 Background: Early breast cancer presents with a remarkable and largely unaccounted for heterogeneity of outcomes. Undetected, microscopic lymph node tumor deposits may account for a significant fraction of this prognostic diversity. Thus, we systematically evaluated the presence of lymph node tumor cell deposits <0.2 mm in diameter [pN0(i+), nanometastases], and analysed their prognostic impact. Methods: Seven hundred and two single institution, consecutive patients with 8 years of median follow-up were studied. To maximize the chances of detecting micro and nanometastases, whole-axilla dissections were analysed. pN0 cases were systematically reevaluated by step sectioning and anti-cytokeratin immunohistochemical analysis of 6676 corresponding dissected lymph nodes. The risk of first adverse events and of distant relapse of bona fide pN0 patients was compared with that of pN0(i+), pN1mi and pN1 cases. Crude cumulative incidence (CCI) curves were used to estimate the cumulative probability of occurrence of adverse events. CCI curves were compared by the Gray’s test. A proportional sub distribution hazard (SDH) regression model was utilized to assess the difference among CCI curves of pN0(i+) versus pN0(i-), and of pN1mi versus pN0(i+). Competing risks were accounted for and regression models were adjusted for established breast cancer prognostic factors, i.e. grading, pathological T stage and age. Proportional SDH assumptions were checked using Schoenfeld-type residuals. Results: A pN0(i+) status was shown to be a strong risk factor for event-free survival (P<0.0005) and for metastatic relapse in both univariate and multivariate analyses accounting for competing risks and adjusted for grading, pathological T stage and age. Conclusions: Our findings demonstrate that nanometastases are an important risk factor in breast cancer. These results support the inclusion of procedures for nanometastasis detection in TNM pathological staging. No significant financial relationships to disclose.

scholarly journals Axillary Lymph Node Nanometastases Are Prognostic Factors for Disease-Free Survival and Metastatic Relapse in Breast Cancer Patients

2006 ◽  
Vol 12 (22) ◽  
pp. 6696-6701 ◽  
Author(s):  
Patrizia Querzoli ◽  
Massimo Pedriali ◽  
Rosa Rinaldi ◽  
Anna Rita Lombardi ◽  
Elia Biganzoli ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Lymph Node ◽  
Cancer Patients ◽  
Disease Free Survival ◽  
Axillary Lymph ◽  
Breast Cancer Patients ◽  
Free Survival ◽  
Metastatic Relapse ◽  
Disease Free

Prognostic Factors in Breast Cancer

1989 ◽  
Vol 3 (4) ◽  
pp. 641-652 ◽  
Author(s):  
Douglas E. Merkel ◽  
C. Kent Osborne
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors

Prognostic Factors in Breast Cancer.

1995 ◽  
Author(s):  
Jeffery Seidman
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors

Prognostic Factors in Breast Cancer

1997 ◽  
Author(s):  
Timothy J. O'Leary ◽  
Jeffrey D. Seidman
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors

scholarly journals Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors

2015 ◽  
Vol 26 (8) ◽  
pp. 2547-2558 ◽  
Author(s):  
Gene Young Cho ◽  
Linda Moy ◽  
Sungheon G. Kim ◽  
Steven H. Baete ◽  
Melanie Moccaldi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Histogram Analysis ◽  
Intravoxel Incoherent Motion ◽  
Histological Subtype

scholarly journals CD39+PD-1+CD8+ T cells mediate metastatic dormancy in breast cancer

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Paulino Tallón de Lara ◽  
Héctor Castañón ◽  
Marijne Vermeer ◽  
Nicolás Núñez ◽  
Karina Silina ◽  
...  
Keyword(s):  
Breast Cancer ◽  
T Cells ◽  
Human Breast Cancer ◽  
Disease Free Survival ◽  
T Cell Response ◽  
Primary Breast Tumor ◽  
Human Breast ◽  
Primary Tumors ◽  
Metastatic Relapse ◽  
Discrete Population

AbstractSome breast tumors metastasize aggressively whereas others remain dormant for years. The mechanism governing metastatic dormancy remains largely unknown. Through high-parametric single-cell mapping in mice, we identify a discrete population of CD39+PD-1+CD8+ T cells in primary tumors and in dormant metastasis, which is hardly found in aggressively metastasizing tumors. Using blocking antibodies, we find that dormancy depends on TNFα and IFNγ. Immunotherapy reduces the number of dormant cancer cells in the lungs. Adoptive transfer of purified CD39+PD-1+CD8+ T cells prevents metastatic outgrowth. In human breast cancer, the frequency of CD39+PD-1+CD8+ but not total CD8+ T cells correlates with delayed metastatic relapse after resection (disease-free survival), thus underlining the biological relevance of CD39+PD-1+CD8+ T cells for controlling experimental and human breast cancer. Thus, we suggest that a primary breast tumor could prime a systemic, CD39+PD-1+CD8+ T cell response that favors metastatic dormancy in the lungs.

scholarly journals Surgery for primary tumor benefits survival for breast cancer patients with bone metastases: a large cohort retrospective study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhangheng Huang ◽  
Xin Zhou ◽  
Yuexin Tong ◽  
Lujian Zhu ◽  
Ruhan Zhao ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Bone Metastases ◽  
Cancer Patients ◽  
Primary Tumor ◽  
Predictive Accuracy ◽  
Rank Test ◽  
Breast Cancer Patients ◽  
Risk Of Death ◽  
The Impact

Abstract Background The role of surgery for the primary tumor in breast cancer patients with bone metastases (BM) remains unclear. The purpose of this study was to determine the impact of surgery for the primary tumor in breast cancer patients with BM and to develop prognostic nomograms to predict the overall survival (OS) of breast cancer patients with BM. Methods A total of 3956 breast cancer patients with BM from the Surveillance, Epidemiology, and End Results database between 2010 and 2016 were included. Propensity score matching (PSM) was used to eliminate the bias between the surgery and non-surgery groups. The Kaplan-Meier analysis and the log-rank test were performed to compare the OS between two groups. Cox proportional risk regression models were used to identify independent prognostic factors. Two nomograms were constructed for predicting the OS of patients in the surgery and non-surgery groups, respectively. In addition, calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to evaluate the performance of nomograms. Result The survival analysis showed that the surgery of the primary tumor significantly improved the OS for breast cancer patients with BM. Based on independent prognostic factors, separate nomograms were constructed for the surgery and non-surgery groups. The calibration and ROC curves of these nomograms indicated that both two models have high predictive accuracy, with the area under the curve values ≥0.700 on both the training and validation cohorts. Moreover, DCA showed that nomograms have strong clinical utility. Based on the results of the X-tile analysis, all patients were classified in the low-risk-of-death subgroup had a better prognosis. Conclusion The surgery of the primary tumor may provide survival benefits for breast cancer patients with BM. Furthermore, these prognostic nomograms we constructed may be used as a tool to accurately assess the long-term prognosis of patients and help clinicians to develop individualized treatment strategies.

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