Predicting Successful Conservative Surgery after Neoadjuvant Chemotherapy in Hormone Receptor-Positive, HER2-Negative Breast Cancer.
- Author:
Chang Seok KO
1
;
Kyu Min KIM
;
Jong Won LEE
;
Han Shin LEE
;
Sae Byul LEE
;
Guiyun SOHN
;
Jisun KIM
;
Hee Jeong KIM
;
Il Yong CHUNG
;
Beom Seok KO
;
Byung Ho SON
;
Seung Do AHN
;
Sung Bae KIM
;
Hak Hee KIM
;
Sei Hyun AHN
Author Information
- Publication Type:Original Article
- Keywords: Breast neoplasms; Neoadjuvant therapy; Nomograms; Segmental mastectomy
- MeSH: Biopsy; Body Mass Index; Breast Neoplasms*; Breast*; Cohort Studies; Diagnosis; Drug Therapy*; Humans; Inflammatory Breast Neoplasms; Logistic Models; Mastectomy, Segmental; Neoadjuvant Therapy; Neoplasm Metastasis; Nipples; Nomograms; Receptor, Epidermal Growth Factor; Receptors, Progesterone; ROC Curve
- From: Journal of Breast Disease 2018;6(2):52-59
- CountryRepublic of Korea
- Language:English
- Abstract: PURPOSE: This study aimed to determine whether clinicopathological factors are potentially associated with successful breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NAC) and develop a nomogram for predicting successful BCS candidates, focusing on those who are diagnosed with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative tumors during the pre-NAC period. METHODS: The training cohort included 239 patients with an HR-positive, HER2-negative tumor (≥3 cm), and all of these patients had received NAC. Patients were excluded if they met any of the following criteria: diffuse, suspicious, malignant microcalcification (extent >4 cm); multicentric or multifocal breast cancer; inflammatory breast cancer; distant metastases at the time of diagnosis; excisional biopsy prior to NAC; and bilateral breast cancer. Multivariate logistic regression analysis was conducted to evaluate the possible predictors of BCS eligibility after NAC, and the regression model was used to develop the predicting nomogram. This nomogram was built using the training cohort (n=239) and was later validated with an independent validation cohort (n=123). RESULTS: Small tumor size (p < 0.001) at initial diagnosis, long distance from the nipple (p=0.002), high body mass index (p=0.001), and weak positivity for progesterone receptor (p=0.037) were found to be four independent predictors of an increased probability of BCS after NAC; further, these variables were used as covariates in developing the nomogram. For the training and validation cohorts, the areas under the receiver operating characteristic curve were 0.833 and 0.786, respectively; these values demonstrate the potential predictive power of this nomogram. CONCLUSION: This study established a new nomogram to predict successful BCS in patients with HR-positive, HER2-negative breast cancer. Given that chemotherapy is an option with unreliable outcomes for this subtype, this nomogram may be used to select patients for NAC followed by successful BCS.
