Patient Selection for Clinical Trials Eliminating Surgery for HER2-Positive Breast Cancer Treated with Neoadjuvant Systemic Therapy

Surgical outcomes and prognosis of HER2+ invasive breast cancer patients with a DCIS component treated with breast-conserving surgery after neoadjuvant systemic therapy

INTRODUCTION

In up to 72 % of HER2+ invasive breast cancer (IBC), a ductal carcinoma in situ (DCIS) component is present. The presence of DCIS is associated with increased positive surgical margins after breast-conserving surgery (BCS). The aim of this study was to assess surgical margins, recurrence and survival in a nationwide cohort of HER2+ IBC with versus without a DCIS component, treated with neoadjuvant systemic therapy (NST) and BCS.

MATERIALS AND METHODS

Women diagnosed with HER2+ IBC treated with NST and BCS, between 2010 and 2019, were selected from the Netherlands Cancer Registry and linked to the Dutch Nationwide Pathology Databank. Kaplan-Meier and Cox regression analyses were performed to determine locoregional recurrence rate (LRR) and overall survival (OS) and associated clinicopathological variables. Surgical outcomes and prognosis were compared between IBC only and IBC+DCIS.

RESULTS

A total of 3056 patients were included: 1832 with IBC and 1224 with IBC+DCIS. Patients with IBC+DCIS had significantly more often positive surgical margins compared to IBC (12.8 % versus 4.9 %, p < 0.001). Five-year LRR was significantly higher in patients with IBC+DCIS compared to IBC (6.8 % versus 3.6 %, p < 0.001), but the presence of DCIS itself was not significantly associated with LRR after adjusting for confounders in multivariable analysis. Five-year OS did not differ between IBC+DCIS and IBC (94.9 % versus 95.7 %, p = 0.293).

CONCLUSION

The presence of DCIS is associated with higher rates of positive surgical margins, but not with LRR and lower OS when adjusted for confounders. Further research is necessary to adequately select IBC+DCIS patients for BCS after NST.

Pathologic complete response of ductal carcinoma in situ to neoadjuvant systemic therapy in HER2-positive invasive breast cancer patients: a nationwide analysis

PURPOSE

Ductal carcinoma in situ (DCIS) is present in more than half of HER2-positive invasive breast cancer (IBC). Recent studies show that DCIS accompanying HER2-positive IBC can be completely eradicated by neoadjuvant systemic therapy (NST). Our aim was to determine the percentage of pathologic complete response of the DCIS component in a nationwide cohort and to assess associated clinicopathologic variables. Furthermore, the impact on surgical treatment after NST was investigated.

METHODS

Women diagnosed with HER2-positive IBC, treated with NST and surgery, between 2010 and 2020, were selected from the Netherlands Cancer Registry. Pre-NST biopsy and postoperative pathology reports were obtained from the Dutch Nationwide Pathology Databank and assessed for the presence of DCIS. Clinicopathologic factors associated with DCIS response were assessed using logistic regression analyses.

RESULTS

A DCIS component was present in the pre-NST biopsy in 1403 (25.1%) of 5598 included patients. Pathologic complete response of the DCIS component was achieved in 730 patients (52.0%). Complete response of DCIS occurred more frequently in case of complete response of IBC (63.4% versus 33.8%, p < 0.001). ER-negative IBC (OR 1.79; 95%CI 1.33-2.42) and more recent years of diagnosis (2014-2016 OR 1.60; 95%CI 1.17-2.19, 2017-2019 OR 1.76; 95%CI 1.34-2.34) were associated with DCIS response. Mastectomy rates were higher in IBC+DCIS compared to IBC (53.6% versus 41.0%, p < 0.001).

CONCLUSION

Pathologic complete response of DCIS occurred in 52.0% of HER2-positive IBC patients and was associated with ER-negative IBC and more recent years of diagnosis. Future studies should investigate imaging evaluation of DCIS response to improve surgical decision making.

Pathologic Response of Associated Ductal Carcinoma In Situ to Neoadjuvant Systemic Therapy: A Systematic Review

Contrary to traditional assumptions, recent evidence suggests that neoadjuvant systemic therapy (NST) given for invasive breast cancer may eradicate co-existent ductal carcinoma in-situ (DCIS), which may facilitate de-escalation of breast resections. The aim of this systematic review was to assess the eradication rate of DCIS by NST given for invasive breast cancer. Searches were performed in MEDLINE using appropriate search terms. Six studies (N = 659) in which pathological data were available regarding the presence of DCIS prior to neoadjuvant chemotherapy (NACT) were identified. Only one study investigating the impact of neoadjuvant endocrine therapy (NET) met the search criteria. After pooled analysis, post-NACT pathology showed no residual DCIS in 40.5% of patients (267/659; 95% CI: 36.8-44.3). There was no significant difference in DCIS eradication rate between triple negative breast cancer (TNBC) and HER2-positive disease (45% vs. 46% respectively). NET achieved eradication of DCIS in 15% of patients (9/59). Importantly, residual widespread micro-calcifications after NST did not necessarily indicate residual disease. In view of the results of the pooled analysis, the presence of extensive DCIS prior to NST should not mandate mastectomy and de-escalation to breast conserving surgery (BCS) should be considered in patients identified by contrast enhanced magnetic resonance imaging (CE-MRI).

Intelligent Vacuum-Assisted Biopsy to Identify Breast Cancer Patients With Pathologic Complete Response (ypT0 and ypN0) After Neoadjuvant Systemic Treatment for Omission of Breast and Axillary Surgery

PURPOSE

Neoadjuvant systemic treatment (NST) elicits a pathologic complete response in 40%-70% of women with breast cancer. These patients may not need surgery as all local tumor has already been eradicated by NST. However, nonsurgical approaches, including imaging or vacuum-assisted biopsy (VAB), were not able to accurately identify patients without residual cancer in the breast or axilla. We evaluated the feasibility of a machine learning algorithm (intelligent VAB) to identify exceptional responders to NST.

METHODS

We trained, tested, and validated a machine learning algorithm using patient, imaging, tumor, and VAB variables to detect residual cancer after NST (ypT+ or in situ or ypN+) before surgery. We used data from 318 women with cT1-3, cN0 or +, human epidermal growth factor receptor 2-positive, triple-negative, or high-proliferative Luminal B-like breast cancer who underwent VAB before surgery (ClinicalTrials.gov identifier: NCT02948764, RESPONDER trial). We used 10-fold cross-validation to train and test the algorithm, which was then externally validated using data of an independent trial (ClinicalTrials.gov identifier: NCT02575612). We compared findings with the histopathologic evaluation of the surgical specimen. We considered false-negative rate (FNR) and specificity to be the main outcomes.

RESULTS

In the development set (n = 318) and external validation set (n = 45), the intelligent VAB showed an FNR of 0.0%-5.2%, a specificity of 37.5%-40.0%, and an area under the receiver operating characteristic curve of 0.91-0.92 to detect residual cancer (ypT+ or in situ or ypN+) after NST. Spiegelhalter's Z confirmed a well-calibrated model (z score -0.746, P = .228). FNR of the intelligent VAB was lower compared with imaging after NST, VAB alone, or combinations of both.

CONCLUSION

An intelligent VAB algorithm can reliably exclude residual cancer after NST. The omission of breast and axillary surgery for these exceptional responders may be evaluated in future trials.

De-escalation in breast cancer surgery

In recent years, several trials of breast cancer treatment have failed to demonstrate a survival benefit for some previously routine surgical therapies in selected patient groups. As each of these therapeutic approaches has been deemed of low value deimplementation has varied significantly. This demonstrates that effective de-escalation in breast cancer surgery relies on more than the availability of data from randomized controlled trials and other high-quality evidence, but is also influenced by various stakeholders, social expectations, and environmental contexts.

Innovative Standards in Surgery of the Breast after Neoadjuvant Systemic Therapy

BACKGROUND

The goal of neoadjuvant systemic therapy (NST) in breast cancer is to downstage tumors and downgrade treatment. Indications are constantly evolving. These changes raise practical questions for planning of surgery after NST.

SUMMARY

In this review we discuss current evolving aspects of surgery of the breast after NST. Breast-conserving surgery (BCS) eligibility increases after NST - both neoadjuvant chemotherapy (NAC) and neoadjuvant endocrine therapy. Adequate margin width in NST and upfront surgery are similar - "no tumor on ink" for invasive cancer. Oncoplastic breast surgery after NST is feasible - both for BCS and mastectomy with reconstruction. There is increasing interest in the possibility of omitting surgery in patients with a complete response to NAC. Several trials are being conducted in aim of achieving acceptable prediction of pathological complete response, by combination of imaging and percutaneous biopsy of the tumor bed, as well as assessing the safety of such an approach.

KEY MESSAGES

Surgery of the breast after NST should be determined not only according to biologic and anatomic parameters at diagnosis, but is dynamic, and must be tailored according to the response to therapy. The omission of surgery in exceptional responders after NAC is being explored.

The percentage of residual DCIS in patients diagnosed with primary invasive breast cancer treated with neoadjuvant systemic therapy: A nationwide retrospective study

INTRODUCTION

Neoadjuvant systemic therapy (NST) is increasingly applied in breast cancer to improve surgical and oncological outcome. Approximately 21% of patients receiving NST achieve pathological complete response (pCR) of the breast. There is disagreement on the definition of pCR with respect to residual DCIS (ypT0 versus ypT0/is). The aim of this retrospective study was to determine the percentage of breast pCR (ypT0) and residual DCIS (ypTis), and its association with clinicopathological variables, in patients treated with NST and surgery.

MATERIALS AND METHODS

Patients with invasive breast cancer treated with neoadjuvant chemotherapy, with or without targeted therapy, in the period of 2010-2019 were selected from the Netherlands Cancer Registry (NCR). Descriptive statistics and multivariable logistic regression analyses were used to analyse the percentage of ypT0 and ypTis and its association with clinicopathological variables.

RESULTS

From the NCR database, 20495 patients were included, of whom 5847 (28.5%) achieved breast pCR (ypT0) and 881 (4.3%) showed residual DCIS (ypTis). The percentage of ypTis was highest in HER2+ tumour subtypes (ER+HER2+ 7.9%, ER-HER2+ 9.8%, ER+HER2- 2.1%, triple negative 3.3%, p < 0.001). Multivariable logistic regression analyses demonstrated high tumour grade (OR 2.00, p = 0.003) and HER2+ tumour subtype (ER+HER2+ OR 3.58, ER-HER2+ OR 4.37, p < 0.001) as independent predictors for ypTis.

CONCLUSION

pCR (ypT0) was achieved in 5847 (28.5%) patients receiving NST and residual DCIS (ypTis) was found in 881 (4.3%) patients. Consequently, the rate of pCR may be affected by ypTis when not excluded from the definition. The percentage of ypTis is highest in HER2+ subtypes.

Vacuum-Assisted Breast Biopsy After Neoadjuvant Systemic Treatment for Reliable Exclusion of Residual Cancer in Breast Cancer Patients

Background

About 40 % of women with breast cancer achieve a pathologic complete response in the breast after neoadjuvant systemic treatment (NST). To identify these women, vacuum-assisted biopsy (VAB) was evaluated to facilitate risk-adaptive surgery. In confirmatory trials, the rates of missed residual cancer [false-negative rates (FNRs)] were unacceptably high (> 10%). This analysis aimed to improve the ability of VAB to exclude residual cancer in the breast reliably by identifying key characteristics of false-negative cases.

Methods

Uni- and multivariable logistic regressions were performed using data of a prospective multicenter trial (n = 398) to identify patient and VAB characteristics associated with false-negative cases (no residual cancer in the VAB but in the surgical specimen). Based on these findings FNR was exploratively re-calculated.

Results

In the multivariable analysis, a false-negative VAB result was significantly associated with accompanying ductal carcinoma in situ (DCIS) in the initial diagnostic biopsy [odds ratio (OR), 3.94; p < 0.001], multicentric disease on imaging before NST (OR, 2.74; p = 0.066), and age (OR, 1.03; p = 0.034). Exclusion of women with DCIS or multicentric disease (n = 114) and classication of VABs that did not remove the clip marker as uncertain representative VABs decreased the FNR to 2.9% (3/104).

Conclusion

For patients without accompanying DCIS or multicentric disease, performing a distinct representative VAB (i.e., removing a well-placed clip marker) after NST suggests that VAB might reliably exclude residual cancer in the breast without surgery. This evidence will inform the design of future trials evaluating risk-adaptive surgery for exceptional responders to NST.

Pathologic response of ductal carcinoma in situ to neoadjuvant systemic treatment in HER2-positive breast cancer

Purpose

The presence of extensive ductal carcinoma in situ (DCIS) adjacent to HER2-positive invasive breast cancer (IBC) is often a contra-indication for breast-conserving surgery, even in case of excellent treatment response of the invasive component. Data on the response of DCIS to neoadjuvant systemic treatment (NST) are limited. Therefore, we estimated the response of adjacent DCIS to NST-containing HER2-blockade in HER2-positive breast cancer patients and assessed the association of clinicopathological and radiological factors with response.

Methods

Pre-NST biopsies were examined to determine presence of DCIS in all women with HER2-positive IBC treated with trastuzumab-containing NST ± pertuzumab between 2004 and 2017 in a comprehensive cancer center. When present, multiple DCIS factors, including grade, calcifications, necrosis, hormone receptor, and Ki-67 expression, were scored. Associations of clinicopathological and radiological factors with complete response were assessed using logistic regression models.

Results

Adjacent DCIS, observed in 138/316 patients with HER2-positive IBC, was eradicated after NST in 46% of patients. Absence of calcifications suspicious for malignancy on pre-NST mammography (odds ratio (OR) 3.75; 95% confidence interval (95% CI) 1.72–8.17), treatment with dual HER2-blockade (OR 2.36; 95% CI 1.17–4.75), a (near) complete response on MRI (OR 3.55; 95% CI 1.31–9.64), and absence of calcifications (OR 3.19; 95% CI 1.34–7.60) and Ki-67 > 20% in DCIS (OR 2.74; 95% CI 1.09–6.89) on pre-NST biopsy were significantly associated with DCIS response.

Conclusions

As DCIS can respond to NST containing HER2-blockade, the presence of extensive DCIS in HER2-positive breast cancer before NST should not always indicate a mastectomy. The predictive factors we found could be helpful when considering breast-conserving surgery in these patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10549-021-06235-2.

Accuracy and Reproducibility of Contrast-Enhanced Mammography in the Assessment of Response to Neoadjuvant Chemotherapy in Breast Cancer Patients with Calcifications in the Tumor Bed

This study aimed to evaluate contrast-enhanced mammography (CEM) accuracy and reproducibility in the detection and measurement of residual tumor after neoadjuvant chemotherapy (NAC) in breast cancer (BC) patients with calcifications, using surgical specimen pathology as the reference. Pre- and post-NAC CEM images of 36 consecutive BC patients receiving NAC in 2012–2020, with calcifications in the tumor bed at diagnosis, were retrospectively reviewed by two radiologists; described were absence/presence and size of residual disease based on contrast enhancement (CE) only and CE plus calcifications. Twenty-eight patients (77.8%) had invasive and 5 (13.9%) in situ-only residual disease at surgical specimen pathology. Considering CE plus calcifications instead of CE only, CEM sensitivity for invasive residual tumor increased from 85.7% (95% CI = 67.3–96%) to 96.4% (95% CI = 81.7–99.9%) and specificity decreased from 5/8 (62.5%; 95% CI = 24.5–91.5%) to 1/8 (14.3%; 95% CI = 0.4–57.9%). For in situ-only residual disease, false negatives decreased from 3 to 0 and false positives increased from 1 to 2. CEM pathology concordance in residual disease measurement increased (R squared from 0.38 to 0.45); inter-reader concordance decreased (R squared from 0.79 to 0.66). Considering CE plus calcifications to evaluate NAC response in BC patients increases sensitivity in detection and accuracy in measurement of residual disease but increases false positives.

Identification of breast cancer patients with pathologic complete response in the breast after neoadjuvant systemic treatment by an intelligent vacuum-assisted biopsy

BACKGROUND

Neoadjuvant systemic treatment elicits a pathologic complete response (pCR) in about 35% of women with breast cancer. In such cases, breast surgery may be considered overtreatment. We evaluated multivariate algorithms using patient, tumor, and vacuum-assisted biopsy (VAB) variables to identify patients with breast pCR.

METHODS

We developed and tested four multivariate algorithms: a logistic regression with elastic net penalty, an Extreme Gradient Boosting (XGBoost) tree, Support Vector Machines (SVM), and neural network. We used data from 457 women, randomly partitioned into training and test set (2:1), enrolled in three trials with stage 1-3 breast cancer, undergoing VAB before surgery. False-negative rate (FNR) and specificity were the main outcome measures. The best performing algorithm was validated in an independent fourth trial.

RESULTS

In the test set (n = 152), the logistic regression with elastic net penalty, XGboost tree, SVM, and neural network revealed an FNR of 1.2% (1 of 85 patients with missed residual cancer). Specificity of the logistic regression with elastic net penalty was 52.2% (35 of 67 women with surgically confirmed breast pCR identified), of the XGBoost tree 55.2% (37 of 67), of SVM 62.7% (42 of 67), and of the neural network 67.2% (45 of 67). External validation (n = 50) of the neural network showed an FNR of 0% (0 of 27) and a specificity of 65.2% (15 of 23). Area under the ROC curve for the neural network was 0.97 (95% CI, 0.94-1.00).

CONCLUSION

A multivariate algorithm can accurately select breast cancer patients without residual cancer after neoadjuvant treatment.