Association of higher axillary pathologic complete response rate with breast pathologic complete response after neoadjuvant chemotherapy

The nodal positivity rate in breast pCR patients with initially, clinically node-negative breast cancer after neoadjuvant systemic therapy: A systematic review and meta-analysis

Background

The axillary lymph node positive (ypN+) rate in patients with clinically node-negative (cN0) breast cancer who have achieved breast pathologic complete response (bpCR) after neoadjuvant systemic therapy (NST) is extremely low, and this population has the potential to be exempt from sentinel lymph node biopsy (SLNB). However, an overview of the ypN+ rate in this population for different breast cancer subtypes is lacking.

Objective

To provide the pooled ypN+ rate in cN0 patients who achieved bpCR after NST in different breast cancer subtypes defined by hormone receptor (HR) status and human epidermal growth factor receptor 2 (HER2) status.

Methods

A systematic literature search was conducted in Embase and PubMed on July 20, 2022. Two authors independently selected studies that met the inclusion criteria and extracted all data. The pooled ypN+ rates for each subtype were calculated by a random-effects model using the Stata 16.0 metaprop command.

Results

The pooled analysis of 9609 cN0 patients who achieved bpCR showed that the ypN+ rate was lowest for the HR+/HER2+ (0%) subtype, followed by HR+/HER2- (5.1%), HR-/HER2+ (0.6%), and HR-/HER2- (0.3%). Additionally, 6571 cT1-T2N0 patients who achieved bpCR had a pooled ypN+ rate of 0.6%, and the ypN+ rates for different subtypes were as follows: HR+/HER2+ (1.7%), HR+/HER2- (2.7%), HR-/HER2+ (0.1%), and HR-/HER2- (0.8%).

Conclusion

Our results suggested that cN0 patients who achieve bpCR may be exempt from axillary surgery in the HR+/HER2-, HR+/HER2+, and HR-/HER2- subtypes because of the extremely low probability of residual axillary lymph node disease. However, the safety of omitting axillary surgery needs to be further confirmed by prospective studies.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier CRD42022351739.

Relationship Between Breast and Axillary Pathologic Complete Response According to Clinical Nodal Stage: A Nationwide Study From Korean Breast Cancer Society

Purpose

We evaluated the relationship between breast pathologic complete response (BpCR) and axillary pathologic complete response (ApCR) after neoadjuvant chemotherapy (NACT) according to nodal burden at presentation. As the indications for NACT have expanded, clinicians have started clinical trials for the omission of surgery from the treatment plan in patients with excellent responses to NACT. However, the appropriate indications for axillary surgery omission after excellent NACT response remain unclear.

Methods

Data were collected from patients in the Korean Breast Cancer Society Registry who underwent NACT followed by surgery between 2010 and 2020. We analyzed pathologic axillary nodal positivity after NACT according to BpCR stratified by tumor subtype in patients with cT1-3/N0-2 disease at diagnosis.

Results

A total of 6,597 patients were identified. Regarding cT stage, 528 (9.5%), 3,778 (67.8%), and 1,268 (22.7%) patients had cT1, cT2, and cT3 disease, respectively. Regarding cN stage, 1,539 (27.7%), 2,976 (53.6%), and 1,036 (18.7%) patients had cN0, cN1, and cN2 disease, respectively. BpCR occurred in 21.6% (n = 1,427) of patients, while ApCR and pathologic complete response (ypCR) occurred in 59.7% (n = 3,929) and ypCR 19.4% (n = 1,285) of patients, respectively. The distribution of biologic subtypes included 2,329 (39.3%) patients with hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (HER2)-negative disease, 1,122 (18.9%) with HR-positive/HER2-positive disease, 405 (6.8%) with HR-negative/HER2-positive disease, and 2,072 (35.0%) with triple-negative breast cancer . Among the patients with BpCR, 89.6% (1,122/1,252) had ApCR. Of those with cN0 disease, most (99.0%, 301/304) showed ApCR. Among patients with cN1-2 disease, 86.6% (821/948) had ApCR.

Conclusion

BpCR was highly correlated with ApCR after NACT. In patients with cN0 and BpCR, the risk of missing axillary nodal metastasis was low after NACT. Further research on axillary surgery omission in patients with cN0 disease is needed.

A Clinical–Radiomics Model for Predicting Axillary Pathologic Complete Response in Breast Cancer With Axillary Lymph Node Metastases

Purpose

To develop a clinical–radiomics model based on radiomics features extracted from MRI and clinicopathologic factors for predicting the axillary pathologic complete response (apCR) in breast cancer (BC) patients with axillary lymph node (ALN) metastases.

Materials and Methods

The MR images and clinicopathologic data of 248 eligible invasive BC patients at the Peking University First Hospital from January 2013 to December 2020 were included in this study. All patients received neoadjuvant chemotherapy (NAC), and the presence of ALN metastases was confirmed through cytology pre-NAC. The data from January 2013 to December 2018 were randomly divided into the training and validation sets in a ratio of 7:3, and the data from January 2019 to December 2020 served as the independent testing set. The following three types of prediction models were investigated in this study. 1) A clinical model: the model was built by independently predicting clinicopathologic factors through logistic regression. 2) Radiomics models: we used an automatic segmentation model based on deep learning to segment the axillary areas, visible ALNs, and breast tumors on post-NAC dynamic contrast-enhanced MRI. Radiomics features were then extracted from the region of interest (ROI). Radiomics models were built based on different ROIs or their combination. 3) A clinical–radiomics model: it was built by integrating radiomics signature and independent predictive clinical factors by logistic regression. All models were assessed using a receiver operating characteristic curve analysis and by calculating the area under the curve (AUC).

Results

The clinical model yielded AUC values of 0.759, 0.787, and 0.771 in the training, validation, and testing sets, respectively. The radiomics model based on the combination of MRI features of breast tumors and visible ALNs yielded the best AUC values of 0.894, 0.811, and 0.806 in the training, validation, and testing sets, respectively. The clinical–radiomics model yielded AUC values of 0.924, 0.851, and 0.878 in the training, validation, and testing sets, respectively, for predicting apCR.

Conclusion

We developed a clinical–radiomics model by integrating radiomics signature and clinical factors to predict apCR in BC patients with ALN metastases post-NAC. It may help the clinicians to screen out apCR patients to avoid lymph node dissection.

Establishment and Verification of a Predictive Model for Node Pathological Complete Response After Neoadjuvant Chemotherapy for Initial Node Positive Early Breast Cancer

Objective

Axillary node status after neoadjuvant chemotherapy (NCT) in early breast cancer patients influences the axillary surgical staging procedure. This study was conducted for the identification of the likelihood of patients being node pathological complete response (pCR) post NCT. We aimed to recognize patients most likely to benefit from sentinel lymph node biopsy (SLNB) following NCT and to reduce the risk of missed detection of positive lymph nodes through the construction and validation of a clinical preoperative scoring prediction model.

Methods

The existing data (from March 2010 to December 2018) of the Chinese Society of Clinical Oncology Breast Cancer Database (CSCO-BC) was used to evaluate the independent related factors of node pCR after NCT by Binary Logistic Regression analysis. A predictive model was established according to the score of considerable factors to identify ypN0. Model performance was confirmed in a cohort of NCT patients treated between January 2019 and December 2019 in Henan Cancer Hospital, and model discrimination was evaluated via assessing the area under the receiver operating characteristic (ROC) curve (AUC).

Results

Multivariate regression analysis showed that the node stage before chemotherapy, the expression level of Ki-67, biologic subtype, and breast pCR were all independent related factors of ypN0 after chemotherapy. According to the transformation and summation of odds ratio (OR) values of each variable, the scoring system model was constructed with a total score of 1–5. The AUC for the ROC curves was 0.715 and 0.770 for the training and the validation set accordingly.

Conclusions

A model was established and verified for predicting ypN0 after chemotherapy in newly diagnosed cN+ patients and the model had good accuracy and efficacy. The underlined effective model can suggest axillary surgical planning, and reduce the risk of missing positive lymph nodes by SLNB after NCT. It has great value for identifying initial cN+ patients who are more appropriate for SLNB post-chemotherapy.

Factors Associated with Nodal Pathologic Complete Response Among Breast Cancer Patients Treated with Neoadjuvant Chemotherapy: Results of CALGB 40601 (HER2+) and 40603 (Triple-Negative) (Alliance)

BACKGROUND

De-escalation of axillary surgery after neoadjuvant chemotherapy (NAC) requires careful patient selection. We seek to determine predictors of nodal pathologic complete response (ypN0) among patients treated on CALGB 40601 or 40603, which tested NAC regimens in HER2+ and triple-negative breast cancer (TNBC), respectively.

PATIENTS AND METHODS

A total of 760 patients with stage II-III HER2+ or TNBC were analyzed. Those who had axillary surgery before NAC (N = 122), or who had missing pretreatment clinical nodal status (cN) (N = 58) or ypN status (N = 41) were excluded. The proportion of patients with ypN0 disease was estimated for those with and without breast pathologic complete response (pCR) according to pretreatment nodal status.

RESULTS

In 539 patients, the overall ypN0 rate was 76.3% (411/539) to 93.2% (245/263) in patients with breast pCR and 60.1% (166/276) with residual breast disease (RD) (P < 0.0001). For patients who were cN0 pretreatment, the ypN0 rate was 88.8% (214/241), 96.3% (104/108) with breast pCR, and 82.7% (110/133) with RD. For patients who were cN1, 66.2% (157/237) converted to ypN0, 91.7% (111/121) with breast pCR and 39.7% (46/116) with RD. For patients who were cN2/3, 65.6% (40/61) converted to ypN0, 88.2% (30/34) with breast pCR and 37.0% (10/27) with RD. On multivariable analysis, only pretreatment clinical nodal status and breast pCR/RD were associated with ypN0 status (both P < 0.0001).

CONCLUSIONS

Breast pCR and pretreatment nodal status are predictive of ypN0 axillary nodal involvement, with < 5% residual nodal disease among cN0 patients who experience breast pCR. These findings support the incorporation of axillary surgery de-escalation strategies into NAC trials.