scholarly journals Assessment of the predictive role of oestrogen and progesterone receptor status in breast cancer patients treated with neoadjuvant chemotherapy: A retrospective analysis for 689 patients

2020 ◽  
Author(s):  
Ying Ye ◽  
Rui Chen ◽  
Yong Fu ◽  
Yang Peng ◽  
Fanli Qu ◽  
...  

Abstract Background : To explore the predictive indicators in hormone receptor (HR)-positive breast cancer (BC) patients receiving neoadjuvant chemotherapy (NACT) and to evaluate the value of quantitative oestrogen receptor (ER) and progesterone receptor (PR) in predicting tumour response. Methods : Six hundred eighty-nine BC patients with HR-positive status who were treated with anthracycline, epirubicin and taxane NACT treatment were retrospectively analysed. Clinical and pathological features of the patients were used to evaluate the response to NACT. Results : Patients with larger tumour sizes ( OR 1.657 CI 1.186-2.313 p=0.003 ), those who were in a premenopausal status ( OR 1.458 CI 1.039-2.045 p=0.029 ) and those with higher Ki67 levels ( OR 1.735 CI 1.231-2.444 p=0.002 ) exhibited a better therapy response. Among the patients in the postmenopausal subgroup, a lower pretreatment ER or PR expression were associated with a reduction in tumour size, and the cut-off values for ER and PR were 87.5% and 65%, respectively ( p=0.006 and p=0.05 ). Decreased expression of ER and PR was also observed after NACT treatment ( p=0.028 and p<0.001, respectively ) but played only a predictive role in the Her-2-negative subgroup; the cut-off values for decreased ER and PR were 17.5% and 26.5%, respectively ( p=0.044 and p<0.001 ). Conclusions : Semiquantified pretreatment HR expression can be used to predict the response of NACT in postmenopausal BC patients. Decreased ER and PR expression is also associated with a reduction in tumour size in Her-2-negative subtypes treated with NACT.

2019 ◽  
Vol Volume 11 ◽  
pp. 9563-9569 ◽  
Author(s):  
Claudia Omarini ◽  
Patrizia Palumbo ◽  
Annarita Pecchi ◽  
Stefano Draisci ◽  
Sara Balduzzi ◽  
...  

2016 ◽  
Vol 50 (1) ◽  
pp. 73-79 ◽  
Author(s):  
Alberto Bouzón ◽  
Benigno Acea ◽  
Rafaela Soler ◽  
Ángela Iglesias ◽  
Paz Santiago ◽  
...  

Background The aim, of the study was to estimate the accuracy of magnetic resonance imaging (MRI) in assessing residual disease in breast cancer patients receiving neoadjuvant chemotherapy (NAC) and to identify the clinico-pathological factors that affect the diagnostic accuracy of breast MRI to determine residual tumour size following NAC. Patients and methods 91 breast cancer patients undergoing NAC (92 breast lesions) were included in the study. Breast MRI was performed at baseline and after completion of NAC. Treatment response was evaluated by MRI and histopathological examination to investigate the ability of MRI to predict tumour response. Residual tumour size was measured on post-treatment MRI and compared with pathology in 89 lesions. Clinicopathological factors were analyzed to compare MRI-pathologic size differences. Results The overall sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for diagnosing invasive residual disease by using MRI were 75.00%, 78.57%, 88.89%, 57.89%, and 76.09% respectively. The Pearson’s correlation coefficient (r) between tumour sizes determined by MRI and pathology was r = 0.648 (p < 0.001). The size discrepancy was significantly lower in cancers with initial MRI size ≤ 5 cm (p = 0.050), in cancers with high tumour grade (p < 0.001), and in patients with hormonal receptor-negative cancer (p = 0.033). Conclusions MRI is an accurate tool for evaluating tumour response after NAC. The accuracy of MRI in estimating residual tumour size varies with the baseline MRI tumour size, the tumour grade and the hormonal receptor status.


2012 ◽  
Vol 13 (10) ◽  
pp. 5019-5022 ◽  
Author(s):  
Yun-Lu Bai ◽  
Bing Zhou ◽  
Xiao-Yue Jing ◽  
Bin Zhang ◽  
Xiao-Qing Huo ◽  
...  

2019 ◽  
Vol Volume 12 ◽  
pp. 2171-2180 ◽  
Author(s):  
Muwen Yang ◽  
Xingsong Qin ◽  
Guangyuan Qin ◽  
Xinyu Zheng

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