Role of Clinical and Imaging Risk Factors in Predicting Breast Cancer Diagnosis Among BI-RADS 4 Cases

2019 ◽  
Vol 19 (1) ◽  
pp. e142-e151 ◽  
Author(s):  
William Hsu ◽  
Xinkai Zhou ◽  
Antonia Petruse ◽  
Ngan Chau ◽  
Stephanie Lee-Felker ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis

scholarly journals The Changing Role of Pathology in Breast Cancer Diagnosis and Treatment

Pathobiology ◽  
2011 ◽  
Vol 78 (2) ◽  
pp. 99-114 ◽  
Author(s):  
Anthony S.-Y. Leong ◽  
Zhengping Zhuang
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Diagnosis And Treatment ◽  
Changing Role

scholarly journals The Role of Sentinel Lymph Node Biopsy in Patients With B5c Breast Cancer Diagnosis

In Vivo ◽  
2019 ◽  
Vol 34 (1) ◽  
pp. 355-359
Author(s):  
PIERO FREGATTI ◽  
MARCO GIPPONI ◽  
RAQUEL DIAZ ◽  
RAFFAELE DE ROSA ◽  
FEDERICA MURELLI ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Sentinel Lymph Node ◽  
Sentinel Lymph Node Biopsy ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Lymph Node Biopsy ◽  
Node Biopsy

scholarly journals Predictors of resignation and sick leave after cancer diagnosis among Japanese breast cancer survivors

2020 ◽  
Author(s):  
Kiyomi Mitsui ◽  
Motoki Endo ◽  
Yuya Imai ◽  
Yuito Ueda ◽  
Hiroko Ogawa ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Sick Leave ◽  
Cancer Survivors ◽  
Cancer Diagnosis ◽  
Breast Cancer Survivors ◽  
Breast Cancer Diagnosis ◽  
Age At Diagnosis ◽  
Breast Cancer Patients ◽  
After Cancer

Abstract Background The number of breast cancer patients of working age is increasing in Japan . Consequently, there is a need for support for working individuals concomitantly undergoing breast cancer treatment. The present study aimed to clarify the risk factors for resignation and taking sick leave among breast cancer survivors in continued employment at the time of diagnosis. Methods As part of a Japanese national research project (Endo-Han), the investigators conducted a web-based survey of cancer survivors (CSs) in 2018. The investigators analyzed the risk factors for post-breast cancer diagnosis resignation and sick leave using a logistic regression model, including age at diagnosis, educational level, cancer stage, surgery, pharmacotherapy, radiotherapy, employment status, and occupational type. Results 40 of 269 breast cancer survivors (14.9%) quit their job after cancer diagnosis. Predictors of resignation included lower education level (odds ratio [OR]: 3.802; 95%CI: 1.233-11.729), taking sick leave (OR: 2.514; 95%CI: 1.202-5.261), and younger age at diagnosis (OR: 0.470; 95%CI: 0.221-0.998). Of 229 patients who continued working, sick leave was taken by 72 (31.4%); having surgery was a predictor for taking sick leave (OR: 8.311; 95%CI: 1.007-68.621). Conclusions 14.9% of Japanese employees quit their jobs after being diagnosed with breast cancer. Being younger at breast cancer diagnosis, having lower educational attainment level, and utilizing sick leave were identified as predictors of post-cancer diagnosis resignation. Surgery was associated with the highest risk of taking sick leave. Breast cancer survivors exhibit higher risks for resignation, and may require more carefully follow-up after diagnosis by healthcare providers and employers to protect work sustainability.

scholarly journals refMiR 142 5p inhibits cell invasion and migration by targeting DNMT1 in breast cancer

2021 ◽  
Author(s):  
Hui Li ◽  
Han-Han Li ◽  
Qian Chen ◽  
Yu-Yang Wang ◽  
Chang Chang Fan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Cell Invasion ◽  
Feedback Loop ◽  
Regulatory Element ◽  
Breast Cancer Diagnosis ◽  
Invasion And Migration ◽  
And Migration ◽  
Abnormal Cell Proliferation

Abnormal cell proliferation caused by abnormal transcription regulation mechanismseems to be one of the reasons for the progression of breast cancer and also thepathological basis. MicroRNA 142 5p (miR 142 5p) is a low expressed miRNA inbreast cancer. T he role of MKL1's regulation of DNMT1 in breast cancer cellproliferation and migration is still unclear. MKL 1 (myocardi n related transcriptionfactor A) can bind to the conserved cis regulatory element CC (A/T) 6GG (called CarGbox) in the promoter to re gulate the transcription of miR 142 5p. The expression ofmiR 142 5p and MKL 1 are positively correlated. In addition, it has been proved thatDNMT1 is the target of miR 142 5p, which inhibits the expression of DNMT1 bytargeting the 3'UTR of DNMT1, thereby forming a feedback loop and inhibiting themigration and proliferation of breast cancer. Our data provide important and novelinsights into the MKL 1/miR 142 5p/DNMT1/maspin signaling pathway, and maybecome a new idea for breast cancer diagnosis, treatment and prognosis.

scholarly journals Predictors of resignation and sick leave after cancer diagnosis among Japanese breast cancer survivors

2020 ◽  
Author(s):  
Kiyomi Mitsui ◽  
Motoki Endo ◽  
Yuya Imai ◽  
Yuito Ueda ◽  
Hiroko Ogawa ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Sick Leave ◽  
Cancer Survivors ◽  
Cancer Diagnosis ◽  
Breast Cancer Survivors ◽  
Breast Cancer Diagnosis ◽  
Age At Diagnosis ◽  
Breast Cancer Patients ◽  
After Cancer

Abstract Background The number of breast cancer patients of working age is increasing in Japan . Consequently, there is a need for support for working individuals concomitantly undergoing breast cancer treatment. The present study aimed to clarify the risk factors for resignation and taking sick leave among breast cancer survivors in continued employment at the time of diagnosis. Methods As part of a Japanese national research project (Endo-Han), the investigators conducted a web-based survey of cancer survivors (CSs) in 2018. The investigators analyzed the risk factors for post-breast cancer diagnosis resignation and sick leave using a logistic regression model, including age at diagnosis, educational level, cancer stage, surgery, pharmacotherapy, radiotherapy, employment status, and occupational type. Results 40 of 269 breast cancer survivors (14.9%) quit their job after cancer diagnosis. Predictors of resignation included lower education level (odds ratio [OR]: 3.802; 95%CI: 1.233-11.729), taking sick leave (OR: 2.514; 95%CI: 1.202-5.261), and younger age at diagnosis (OR: 0.470; 95%CI: 0.221-0.998). Of 229 patients who continued working, sick leave was taken by 72 (31.4%); having surgery was a predictor for taking sick leave (OR: 8.311; 95%CI: 1.007-68.621). Conclusions 14.9% of Japanese employees quit their jobs after being diagnosed with breast cancer. Being younger at breast cancer diagnosis, having lower educational attainment level, and utilizing sick leave were identified as predictors of post-cancer diagnosis resignation. Surgery was associated with the highest risk of taking sick leave. Breast cancer survivors exhibit higher risks for resignation, and may require more carefully follow-up after diagnosis by healthcare providers and employers to protect work sustainability.

scholarly journals Breast cancer diagnosis: The role of stereotactic vacuum-assisted aspiration biopsy

2008 ◽  
Vol 6 ◽  
pp. S104-S108 ◽  
Author(s):  
Francesca Rovera ◽  
Gianlorenzo Dionigi ◽  
Marina Marelli ◽  
Alberta Ferrari ◽  
Giorgio Limonta ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Diagnosis ◽  
Breast Cancer Diagnosis ◽  
Aspiration Biopsy
Sign in / Sign up

Export Citation Format

Share Document