Breast-conserving surgery is not associated with increased local recurrence in patients with early-stage node-negative triple-negative breast cancer treated with neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NACT) is routinely used for patients with triple-negative breast cancer (TNBC). Upfront breast-conserving therapy (BCT) consisting of breast-conserving surgery (BCS) and adjuvant radiotherapy (RT) has been shown to be associated with improved outcome in patients with early TNBC as compared to mastectomy.

METHODS

We identified 2632 patients with early TNBC from the German Breast Group meta-database. Patients with cT1-2 cN0 and ypN0, available surgery and follow-up data were enrolled. Data of 1074 patients from 8 prospective NACT trials were available. Endpoints of interest were locoregional recurrence as first site of relapse (LRR), disease-free survival (DFS) and overall survival (OS). We performed univariate and multivariate Fine-Gray analysis and Cox regression models.

RESULTS

After a median follow-up of 64 months, there were 94 (8.8%) locoregional events as first site of relapse. Absence of pathologic complete response (pCR) was associated with increased LRR upon uni- and multivariate analysis (hazard ratio [HR] = 2.28; p < 0.001 and HR = 2.22; p = 0.001). Type of surgery was not associated with LRR. Patients in the BCS-group had better DFS and OS (DFS: HR = 0.47; p < 0.001 and OS: HR = 0.40; p < 0.001). BCS was associated with improved DFS and OS upon multivariate analysis (DFS: HR = 0.51; p < 0.001; and OS HR = 0.43; p < 0.001), whereas absence of pCR was associated with worse DFS and OS (DFS: HR = 2.43; p < 0.001; and OS: HR = 3.15; p < 0.001).

CONCLUSIONS

In this retrospective analysis of patients with early stage node-negative TNBC treated with NACT, BCS was not associated with an increased risk of LRR but with superior DFS and OS.

Can multi-modal radiomics using pretreatment ultrasound and tomosynthesis predict response to neoadjuvant systemic treatment in breast cancer?

OBJECTIVES

Response assessment to neoadjuvant systemic treatment (NAST) to guide individualized treatment in breast cancer is a clinical research priority. We aimed to develop an intelligent algorithm using multi-modal pretreatment ultrasound and tomosynthesis radiomics features in addition to clinical variables to predict pathologic complete response (pCR) prior to the initiation of therapy.

METHODS

We used retrospective data on patients who underwent ultrasound and tomosynthesis before starting NAST. We developed a support vector machine algorithm using pretreatment ultrasound and tomosynthesis radiomics features in addition to patient and tumor variables to predict pCR status (ypT0 and ypN0). Findings were compared to the histopathologic evaluation of the surgical specimen. The main outcome measures were area under the curve (AUC) and false-negative rate (FNR).

RESULTS

We included 720 patients, 504 in the development set and 216 in the validation set. Median age was 51.6 years and 33.6% (242 of 720) achieved pCR. The addition of radiomics features significantly improved the performance of the algorithm (AUC 0.72 to 0.81; p = 0.007). The FNR of the multi-modal radiomics and clinical algorithm was 6.7% (10 of 150 with missed residual cancer). Surface/volume ratio at tomosynthesis and peritumoral entropy characteristics at ultrasound were the most relevant radiomics. Hormonal receptors and HER-2 status were the most important clinical predictors.

CONCLUSION

A multi-modal machine learning algorithm with pretreatment clinical, ultrasound, and tomosynthesis radiomics features may aid in predicting residual cancer after NAST. Pending prospective validation, this may facilitate individually tailored NAST regimens.

CLINICAL RELEVANCE STATEMENT

Multi-modal radiomics using pretreatment ultrasound and tomosynthesis showed significant improvement in assessing response to NAST compared to an algorithm using clinical variables only. Further prospective validation of our findings seems warranted to enable individualized predictions of NAST outcomes.

KEY POINTS

• We proposed a multi-modal machine learning algorithm with pretreatment clinical, ultrasound, and tomosynthesis radiomics features to predict response to neoadjuvant breast cancer treatment. • Compared with the clinical algorithm, the AUC of this integrative algorithm is significantly higher. • Used prior to the initiative of therapy, our algorithm can identify patients who will experience pathologic complete response following neoadjuvant therapy with a high negative predictive value.

Ultrasound Radiomics Features to Identify Patients With Triple-Negative Breast Cancer: A Retrospective, Single-Center Study

OBJECTIVES

Patients with triple-negative breast cancer (TNBC) exhibit a fast tumor growth rate and poor survival outcomes. In this study, we aimed to develop and compare intelligent algorithms using ultrasound radiomics features in addition to clinical variables to identify patients with TNBC prior to histopathologic diagnosis.

METHODS

We used single-center, retrospective data of patients who underwent ultrasound before histopathologic verification and subsequent neoadjuvant systemic treatment (NAST). We developed a logistic regression with an elastic net penalty algorithm using pretreatment ultrasound radiomics features in addition to patient and tumor variables to identify patients with TNBC. Findings were compared to the histopathologic evaluation of the biopsy specimen. The main outcome measure was the area under the curve (AUC).

RESULTS

We included 1161 patients, 813 in the development set and 348 in the validation set. Median age was 50.1 years and 24.4% (283 of 1161) had TNBC. The integrative model using radiomics and clinical information showed significantly better performance in identifying TNBC compared to the radiomics model (AUC: 0.71, 95% confidence interval [CI]: 0.65-0.76 versus 0.64, 95% CI: 0.57-0.71, P = .004). The five most important variables were cN status, shape surface volume ratio (SA:V), gray level co-occurrence matrix (GLCM) correlation, gray level dependence matrix (GLDM) dependence nonuniformity normalized, and age. Patients with TNBC were more often categorized as BI-RADS 4 than BI-RADS 5 compared to non-TNBC patients (P = .002).

CONCLUSION

A machine learning algorithm showed promising potential to identify patients with TNBC using ultrasound radiomics features and clinical information prior to histopathologic evaluation.

Minimally Invasive Breast Biopsy After Neoadjuvant Systemic Treatment to Identify Breast Cancer Patients with Residual Disease for Extended Neoadjuvant Treatment: A New Concept

BACKGROUND

Breast cancer patients with residual disease after neoadjuvant systemic treatment (NAST) have a worse prognosis compared with those achieving a pathologic complete response (pCR). Earlier identification of these patients might allow timely, extended neoadjuvant treatment strategies. We explored the feasibility of a vacuum-assisted biopsy (VAB) after NAST to identify patients with residual disease (ypT+ or ypN+) prior to surgery.

METHODS

We used data from a multicenter trial, collected at 21 study sites (NCT02948764). The trial included women with cT1-3, cN0/+ breast cancer undergoing routine post-neoadjuvant imaging (ultrasound, MRI, mammography) and VAB prior to surgery. We compared the findings of VAB and routine imaging with the histopathologic evaluation of the surgical specimen.

RESULTS

Of 398 patients, 34 patients with missing ypN status and 127 patients with luminal tumors were excluded. Among the remaining 237 patients, tumor cells in the VAB indicated a surgical non-pCR in all patients (73/73, positive predictive value [PPV] 100%), whereas PPV of routine imaging after NAST was 56.0% (75/134). Sensitivity of the VAB was 72.3% (73/101), and 74.3% for sensitivity of imaging (75/101).

CONCLUSION

Residual cancer found in a VAB specimen after NAST always corresponds to non-pCR. Residual cancer assumed on routine imaging after NAST corresponds to actual residual cancer in about half of patients. Response assessment by VAB is not safe for the exclusion of residual cancer. Response assessment by biopsies after NAST may allow studying the new concept of extended neoadjuvant treatment for patients with residual disease in future trials.

Incidence and Risk Assessment of Capsular Contracture in Breast Cancer Patients following Post-Mastectomy Radiotherapy and Implant-Based Reconstruction

Our study aims to identify the risk factors and dosimetry characteristics associated with capsular contracture.

METHODS

We retrospectively analyzed 118 women with breast cancer who underwent PMRT following an IBR between 2010 and 2022. Patients were treated with PMRT of 50.0-50.4 Gy in 25-28 fractions. Capsular contracture was categorized according to the Baker Classification for Reconstructed Breasts.

RESULTS

After a median follow-up of 22 months, the incidence of clinically relevant capsular contracture (Baker III-IV) was 22.9%. Overall, capsular contracture (Baker I-IV) occurred in 56 patients (47.5%) after a median of 9 months after PMRT. The rate of reconstruction failure/implant loss was 25.4%. In the univariate analysis, postoperative complications (prolonged pain, prolonged wound healing, seroma and swelling) and regional nodal involvement were associated with higher rates of capsular contracture (p = 0.017, OR: 2.5, 95% CI: 1.2-5.3 and p = 0.031, respectively). None of the analyzed dosimetric factors or the implant position were associated with a higher risk for capsular contracture.

CONCLUSION

Postoperative complications and regional nodal involvement were associated with an increased risk of capsular contracture following breast reconstruction and PMRT, while none of the analyzed dosimetric factors were linked to a higher incidence. Additional studies are needed to identify further potential risk factors.

Intra- and Interobserver Reliability of Shear Wave Elastography in Breast Cancer Diagnosis

OBJECTIVES

Shear wave elastography (SWE) is increasingly used in breast cancer diagnostics. However, large, prospective, multicenter data evaluating the reliability of SWE is missing. We evaluated the intra- and interobserver reliability of SWE in patients with breast lesions categorized as BIRADS 3 or 4.

METHODS

We used data of 1288 women at 12 institutions in 7 countries with breast lesions categorized as BIRADS 3 to 4 who underwent conventional B-mode ultrasound and SWE. 1243 (96.5%) women had three repetitive conventional B-mode ultrasounds as well as SWE measurements performed by a board-certified senior physician. 375 of 1288 (29.1%) women received an additional ultrasound examination with B-mode and SWE by a second physician. Intraclass correlation coefficients (ICC) were calculated to examine intra- and interobserver reliability.

RESULTS

ICC for intraobserver reliability showed an excellent correlation with ICC >0.9, while interobserver reliability was moderate with ICC of 0.7. There were no clinically significant differences in intraobserver reliability when SWE was performed in lesions categorized as BI-RADS 3 or 4 as well as in histopathologically benign or malignant lesions.

CONCLUSION

Reliability of additional SWE was evaluated on a study cohort consisting of 1288 breast lesions categorized as BI-RADS 3 and 4. SWE shows an excellent intraobserver reliability and a moderate interobserver reliability in the evaluation of solid breast masses.

Deep learning to predict breast cancer sentinel lymph node status on INSEMA histological images

BACKGROUND

Sentinel lymph node (SLN) status is a clinically important prognostic biomarker in breast cancer and is used to guide therapy, especially for hormone receptor-positive, HER2-negative cases. However, invasive lymph node staging is increasingly omitted before therapy, and studies such as the randomised Intergroup Sentinel Mamma (INSEMA) trial address the potential for further de-escalation of axillary surgery. Therefore, it would be helpful to accurately predict the pretherapeutic sentinel status using medical images.

METHODS

Using a ResNet 50 architecture pretrained on ImageNet and a previously successful strategy, we trained deep learning (DL)-based image analysis algorithms to predict sentinel status on hematoxylin/eosin-stained images of predominantly luminal, primary breast tumours from the INSEMA trial and three additional, independent cohorts (The Cancer Genome Atlas (TCGA) and cohorts from the University hospitals of Mannheim and Regensburg), and compared their performance with that of a logistic regression using clinical data only. Performance on an INSEMA hold-out set was investigated in a blinded manner.

RESULTS

None of the generated image analysis algorithms yielded significantly better than random areas under the receiver operating characteristic curves on the test sets, including the hold-out test set from INSEMA. In contrast, the logistic regression fitted on the Mannheim cohort retained a better than random performance on INSEMA and Regensburg. Including the image analysis model output in the logistic regression did not improve performance further on INSEMA.

CONCLUSIONS

Employing DL-based image analysis on histological slides, we could not predict SLN status for unseen cases in the INSEMA trial and other predominantly luminal cohorts.

Noninferiority of Local Control and Comparable Toxicity of Intensity Modulated Radiation Therapy With Simultaneous Integrated Boost in Breast Cancer: 5-Year Results of the IMRT-MC2 Phase III Trial

PURPOSE

The IMRT-MC2 trial was conducted to demonstrate the noninferiority of conventionally fractionated intensity modulated radiation therapy with a simultaneous integrated boost to 3-dimensional conformal radiation therapy with a sequential boost for adjuvant breast radiation therapy.

METHODS AND MATERIALS

A total of 502 patients were randomized between 2011 and 2015 for the prospective, multicenter, phase III trial (NCT01322854). Five-year results of late toxicity (late effects normal tissue task force-subjective, objective, management, and analytical), overall survival, disease-free survival, distant disease-free survival, cosmesis (Harvard scale), and local control (noninferiority margin at hazard ratio [HR] of 3.5) were analyzed after a median follow-up of 62 months.

RESULTS

The 5-year local control rate for the intensity modulated radiation therapy with simultaneous integrated boost arm was non-inferior to the control arm (98.7% vs 98.3%, respectively; HR, 0.582; 95% CI, 0.119-2.375; P = .4595). Furthermore, there was no significant difference in overall survival (97.1% vs 98.3%, respectively; HR, 1.235; 95% CI, 0.472-3.413; P = .6697), disease-free survival (95.8% vs 96.1%, respectively; HR, 1.130; 95% CI, 0.487-2.679; P = .7758), and distant disease-free survival (97.0% vs 97.8%, respectively; HR, 1.667; 95% CI, 0.575-5.434; P = .3601). After 5 years, late toxicity evaluation and cosmetic assessment further showed no significant differences between treatment arms.

CONCLUSIONS

The 5-year results of the IMRT-MC2 trial provide strong evidence that the application of conventionally fractionated simultaneous integrated boost irradiation for patients with breast cancer is both safe and effective, with noninferior local control compared with 3-dimensional conformal radiation therapy with sequential boost.

Best Practice Guideline - DEGUM Recommendations on Breast Ultrasound

Alongside mammography, breast ultrasound is an important and well-established method in assessment of breast lesions. With the "Best Practice Guideline", the DEGUM Breast Ultrasound (in German, "Mammasonografie") working group, intends to describe the additional and optional application modalities for the diagnostic confirmation of breast findings and to express DEGUM recommendations in this Part II, in addition to the current dignity criteria and assessment categories published in Part I, in order to facilitate the differential diagnosis of ambiguous lesions.The present "Best Practice Guideline" has set itself the goal of meeting the requirements for quality assurance and ensuring quality-controlled performance of breast ultrasound. The most important aspects of quality assurance are explained in this Part II of the Best Practice Guideline.

Conventional specimen radiography in breast-conserving therapy: a useful tool for intraoperative margin assessment after neoadjuvant therapy?

PURPOSE

A previous study in our breast unit showed that the diagnostic accuracy of intraoperative specimen radiography and its potential to reduce second surgeries in a cohort of patients treated with neoadjuvant chemotherapy were low, which questions the routine use of Conventional specimen radiography (CSR) in this patient group. This is a follow-up study in a larger cohort to further evaluate these findings.

METHODS

This retrospective study included 376 cases receiving breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) of primary breast cancer. CSR was performed to assess potential margin infiltration and recommend an intraoperative re-excision of any radiologically positive margin. The histological workup of the specimen served as gold standard for the evaluation of the accuracy of CSR and the potential reduction of second surgeries by CSR-guided re-excisions.

RESULTS

362 patients with 2172 margins were assessed. The prevalence of positive margins was 102/2172 (4.7%). CSR had a sensitivity of 37.3%, a specificity of 85.6%, a positive predictive value (PPV) of 11.3%, and a negative predictive value (NPV) of 96.5%. The rate of secondary procedures was reduced from 75 to 37 with a number needed to treat (NNT) of CSR-guided intraoperative re-excisions of 10. In the subgroup of patients with clinical complete response (cCR), the prevalence of positive margins was 38/1002 (3.8%), PPV was 6.5% and the NNT was 34.

CONCLUSION

This study confirms our previous finding that the rate of secondary surgeries cannot be significantly reduced by CSR-guided intraoperative re-excisions in cases with cCR after NACT. The routine use CSR after NACT is questionable, and alternative tools of intraoperative margin assessment should be evaluated.

Prevalence of Pathogenic Germline Variants in Women with Non-Familial Unilateral Triple-Negative Breast Cancer

INTRODUCTION

International guidelines recommend genetic testing for women with familial breast cancer at an expected prevalence of pathogenic germline variants (PVs) of at least 10%. In a study sample of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), we have previously shown that women with TNBC diagnosed before the age of 50 years but without a family history of breast or ovarian cancer (sTNBC) meet this criterion. The present study investigates the PV prevalence in BRCA1, BRCA2, and nine additional cancer predisposition genes in an extended sTNBC study sample including a cohort of women with a later age at sTNBC diagnosis.

PATIENTS AND METHODS

In 1,600 women with sTNBC (median age at diagnosis: 41 years, range 19-78 years), we investigated the association between age at diagnosis and PV occurrence in cancer predisposition genes using logistic regression.

RESULTS

260 sTNBC patients (16.2%) were found to have a PV in cancer predisposition genes (BRCA1: n = 170 [10.6%]; BRCA2: n = 46 [2.9%], other: n = 44 [2.8%]). The PV prevalence in women diagnosed between 50 and 59 years (n = 194) was 11.3% (22/194). Logistic regression showed a significant increase in PV prevalence with decreasing age at diagnosis (OR 1.41 per 10 years younger age at diagnosis; 95% confidence interval: 1.21-1.65; p < 0.001). The PV prevalence predicted by the model was above 10% for diagnoses before the age of 56.8 years.

CONCLUSION

Based on the data presented, we recommend genetic testing by gene panel analysis for sTNBC patients diagnosed before the age of 60 years. Due to the still uncertain estimate for women with sTNBC diagnosed above the age of 60 years, further studies are needed.

Imaging of lumpectomy surface with large field-of-view confocal laser scanning microscopy 'Histolog® scanner' for breast margin assessment in comparison with conventional specimen radiography

PURPOSE

The Histolog® Scanner (SamanTree Medical SA, Lausanne, Switzerland) is a large field-of-view confocal laser scanning microscope designed to allow intraoperative margin assessment by the production of histological images ready for assessment in the operating room. We evaluated the feasibility and the performance of the Histolog® Scanner (HS) to correctly identify infiltrated margins in clinical practice of lumpectomy specimens. It was extrapolated if the utilization of the HS has the potential to reduce infiltrated margins and therefore reduce re-operation rates in patients undergoing breast conserving surgery (BCS) due to a primarily diagnosed breast cancer including ductal carcinoma in situ.

METHODS

This is a single-center, prospective, non-interventional, diagnostic pilot study including 50 consecutive patients receiving BCS. The complete surface of the specimen was scanned using the HS intraoperatively. The surgery and the intraoperative margin assessment of the specimen was performed according to the clinical routine consisting of conventional specimen radiography as well as the clinical impression of the surgeon. Three surgeons and an experienced pathologist assessed the scans produced by the HS for cancer cells on the surface. The potential of the HS to correctly identify involved margins was compared to the results of the conventional specimen radiography alone as well as the clinical routine. The histopathological report served as the gold standard.

RESULTS

50 specimens corresponding to 300 surfaces were scanned by the HS. The mean sensitivity of the surgeons to identify involved margins with the HS was 37.5% ± 5.6%, the specificity was 75.2% ± 13.0%. The assessment of resection margins by the pathologist resulted in a sensitivity of 37.5% and a specificity of 81.0%, while the local clinical routine resulted in a sensitivity of 37.5% and a specificity of 78.2%.

CONCLUSION

Acquisition of high-resolution histological images using the HS was feasible in clinical practice. Sensitivity and specificity were comparable to clinical routine. With more specific training and experience on image interpretation and acquisition, the HS may have the potential to enable more accuracy in the margin assessment of BCS specimens.

Predictive value of neutrophil-to-lymphocyte-ratio in neoadjuvant-treated patients with breast cancer

PURPOSE

Breast cancer (BC) is the most common malignancy among women and prognosis is strongly influenced by tumor subtype. Neoadjuvant chemotherapy (NAC) is the standard treatment for both locally advanced- and early-stage triple-negative and Her2-positive BC. Pathologic complete response (pCR) to NAC is an important predictor of patient outcomes. Neutrophil-to-lymphocyte-ratio (NLR) in peripheral blood is associated with prognosis in various malignancies. Here, we investigated the value of the pretreatment NLR as a response predictor in neoadjuvant-treated patients with BC.

METHODS

A retrospective chart analysis of 862 patients with invasive BC treated with NAC at the Heidelberg University Hospital during 2003-2015 was conducted. NLR was calculated as the ratio of the absolute neutrophil and lymphocyte counts in peripheral blood, and pCR was defined as absence of invasive or in situ carcinoma in breast and axillary lymph nodes.

RESULTS

A total of 151 patients with invasive BC who underwent NAC were included in this study. NLR tended to be higher in the pCR group than the non-pCR group (p < 0.1). Analyses of BC subtypes demonstrated that NLR was significantly higher in the pCR- compared with the non-pCR group (3.304 vs. 2.379, respectively; p = 0.048) in patients with luminal B/Her2-negative tumors. Further, we found a significant difference in NLR according to remission status in postmenopausal patients (2.861 vs. 2.313, respectively; p = 0.043).

CONCLUSION

NLR was significantly higher only for patients achieving pCR in the Luminal B/Her2-negative and postmenopausal subgroups. Hence, NLR is a candidate additional predictive factor in patients with Luminal B/Her2-negative BC.

The Potential of Shear Wave Elastography to Reduce Unnecessary Biopsies in Breast Cancer Diagnosis: An International, Diagnostic, Multicenter Trial

PURPOSE

 In this prospective, multicenter trial we evaluated whether additional shear wave elastography (SWE) for patients with BI-RADS 3 or 4 lesions on breast ultrasound could further refine the assessment with B-mode breast ultrasound for breast cancer diagnosis.

MATERIALS AND METHODS

 We analyzed prospective, multicenter, international data from 1288 women with breast lesions rated by conventional 2 D B-mode ultrasound as BI-RADS 3 to 4c and undergoing 2D-SWE. After reclassification with SWE the proportion of undetected malignancies should be < 2 %. All patients underwent histopathologic evaluation (reference standard).

RESULTS

 Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6 %). The assessment with B-mode breast ultrasound resulted in 1.39 % (6 of 431) undetected malignancies (malignant lesions in BI-RADS 3) and 53.80 % (495 of 920) unnecessary biopsies (biopsies in benign lesions). Re-classifying BI-RADS 4a patients with a SWE cutoff of 2.55 m/s resulted in 1.98 % (11 of 556) undetected malignancies and a reduction of 24.24 % (375 vs. 495) of unnecessary biopsies.

CONCLUSION

 A SWE value below 2.55 m/s for BI-RADS 4a lesions could be used to downstage these lesions to follow-up, and therefore reduce the number of unnecessary biopsies by 24.24 %. However, this would come at the expense of some additionally missed cancers compared to B-mode breast ultrasound (rate of undetected malignancies 1.98 %, 11 of 556, versus 1.39 %, 6 of 431) which would, however, still be in line with the ACR BI-RADS 3 definition (< 2 % of undetected malignancies).

Abstract PD15-06: PD15-06 Pathologic complete response and breast-conserving surgery are associated with improved prognosis in patients with early-stage triple-negative breast cancer treated with neoadjuvant chemotherapy

Background: Neoadjuvant chemotherapy (NACT) is standard of care for patients with triple-negative breast cancer (TNBC). Treatment response, especially pathologic complete response (pCR), is a strong predictive factor for treatment outcome. In the setting of up-front surgery, retrospective data have suggested improved outcome in patients with early TNBC that received breast-conserving surgery with adjuvant radiotherapy (BCT) as compared to mastectomy. Methods: We identified 2632 patients with early TNBC from the German Breast Group meta-database. Patients with cT1-2 cN0 and ypN0, available surgery and follow-up data were eligible for this project. A total of 1074 patients from 8 prospective NACT trials were analyzed. Endpoints of interest were locoregional recurrence as first site of relapse (LRR, other sites of recurrence were considered competing events), disease-free survival (DFS) and overall survival (OS); analyses were performed using univariate and multivariate Fine-Gray (for LRR) and Cox models including study, age, cT, surgery type and pCR. For the analyses including pCR as covariable, only patients at risk at the landmark time were evaluated. Results: Median age was 48 years, 69.6% of patients had cT2 tumors and 85.3% underwent BCS. Of the 1074 analyzed patients, 48.8% achieved pCR. After a median follow-up of 64 months, there were 94 (8.8%) locoregional events as first site of relapse. Upon univariate analysis, absence of pCR (hazard ratio [HR]=2.28; 95%CI 1.44-3.61; p&lt; 0.001) and ypT-stage (ypT0/is vs. ypT1-3, HR=0.61; 95%CI 0.40-0.95; p=0.028) were significantly associated with LRR, while type of surgery, age and cT-stage were not. Upon multivariate analysis, absence of pCR was the only factor associated with increased risk of LRR (HR=2.22; 95%CI 1.38-3.58; p=0.001). Patients that underwent mastectomy (N=158) were significantly younger (age ≤ 50 years 72.8% vs. 59.9% for BCT [N=916]; p=0.002) DFS and OS was significantly better in patients who underwent BCT compared to mastectomy (DFS: HR=0.47; 95%CI 0.34-0.66; p&lt; 0.001 and OS: HR=0.40; 95%CI 0.26-0.63; p&lt; 0.001). In multivariate analysis, BCT was associated with a significantly better DFS and OS as compared to mastectomy (DFS: HR=0.51; 95%CI 0.36-0.72; p&lt; 0.001; and OS HR=0.43; 95%CI 0.27-0.68; p&lt; 0.001), whereas absence of pCR was associated with significantly worse DFS and OS (DFS: HR=2.43; 95%CI 1.78-3.31; p&lt; 0.001; and OS: HR=3.15; 95%CI 1.94-5.10; p&lt; 0.001). Conclusions: In this retrospective analysis from the GBG meta-database, treatment response, e.g. pCR, was the main determinant of locoregional recurrence in patients with early stage TNBC treated with NACT. BCT was associated with improved DFS and OS compared to mastectomy, which may at least in part reflect favorable patient selection.

Citation Format: David Krug, Valentina Vladimirova, Michael Untch, Thorsten Kühn, Andreas Schneeweiss, Carsten Denkert, Beyhan Ataseven, Christine Solbach, Bernd Gerber, Hans Tesch, Michael Golatta, Sabine Seiler, Jörg Heil, Valentina Nekljudova, Sibylle Loibl. PD15-06 Pathologic complete response and breast-conserving surgery are associated with improved prognosis in patients with early-stage triple-negative breast cancer treated with neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD15-06.

Potential of Lesion-to-Fat Elasticity Ratio Measured by Shear Wave Elastography to Reduce Benign Biopsies in BI-RADS 4 Breast Lesions

OBJECTIVES

We evaluated whether lesion-to-fat ratio measured by shear wave elastography in patients with Breast Imaging Reporting and Data System (BI-RADS) 3 or 4 lesions has the potential to further refine the assessment of B-mode ultrasound alone in breast cancer diagnostics.

METHODS

This was a secondary analysis of an international diagnostic multicenter trial (NCT02638935). Data from 1288 women with breast lesions categorized as BI-RADS 3 and 4a-c by conventional B-mode ultrasound were analyzed, whereby the focus was placed on differentiating lesions categorized as BI-RADS 3 and BI-RADS 4a. All women underwent shear wave elastography and histopathologic evaluation functioning as reference standard. Reduction of benign biopsies as well as the number of missed malignancies after reclassification using lesion-to-fat ratio measured by shear wave elastography were evaluated.

RESULTS

Breast cancer was diagnosed in 368 (28.6%) of 1288 lesions. The assessment with conventional B-mode ultrasound resulted in 53.8% (495 of 1288) pathologically benign lesions categorized as BI-RADS 4 and therefore false positives as well as in 1.39% (6 of 431) undetected malignancies categorized as BI-RADS 3. Additional lesion-to-fat ratio in BI-RADS 4a lesions with a cutoff value of 1.85 resulted in 30.11% biopsies of benign lesions which correspond to a reduction of 44.04% of false positives.

CONCLUSIONS

Adding lesion-to-fat ratio measured by shear wave elastography to conventional B-mode ultrasound in BI-RADS 4a breast lesions could help reduce the number of benign biopsies by 44.04%. At the same time, however, 1.98% of malignancies were missed, which would still be in line with American College of Radiology BI-RADS 3 definition of <2% of undetected malignancies.

Clinical prototype implementation enabling an improved day-to-day mammography compression

PURPOSE

In mammography, breast compression is achieved by lowering a compression paddle on the breast. Despite the directive that compression is needed, there is no concrete guideline on its execution. To estimate the degree of compression, current mammography units only provide compression force and breast thickness as parameters. Therefore, radiographers could be induced to mainly determine the level of compression based on compression force and apply the same value to all breast sizes. In this case, smaller breast sizes are exposed to higher pressure. This results in a highly varying perception of discomfort or even pain during the procedure, depending on the breast size.

METHODS

To overcome this imbalance, current research results suggest that pressure might be a more qualified parameter for a more uniform compression among all breast sizes. To utilize pressure, the contact area between breast and compression paddle must be determined. In this paper, we present an easy-to-implement prototype enabling a real-time pressure-based measure without the need of direct patient contact. Using an optical camera, the contact area between the breast and the compression paddle is automatically segmented by a deep learning model.

RESULTS

The model provides a mean pixel accuracy of 96.7% (SD: 2.3%), mean frequency-weighted intersection over union of 88.5% (SD: 6.3%), and a Dice score of 93.6% (SD: 2.2%). The subsequent pressure display is updated more than five times per second which enables the use in clinical routines to set the compression level.

CONCLUSION

This prototype could help guiding to an improved breast compression routine in mammography procedures.

Impact of age on indication for chemotherapy in early breast cancer patients: results from 104 German institutions from 2008 to 2017

PURPOSE

Today, the decision to treat patients with chemotherapy for early breast cancer (EBC) is made based on the patient's individual risk stratification and tumor biology. In cases with chemotherapy indication, the neoadjuvant application (NACT) is the preferred option in comparison with primary surgery and adjuvant chemotherapy (ACT). Age remains a relevant factor in the decision-making process. The aim of the present study was to illustrate the impact of age on the use of systemic therapy in clinical routine.

METHODS

The study separately analyzed chemotherapy use among six age cohorts of EBC patients who had been treated at 104 German breast units between January 2008 and December 2017.

RESULTS

In total, 124,084 patients were included, 46,279 (37.3%) of whom had received chemotherapy. For 44,765 of these cases, detailed information on treatment was available. Within this cohort, chemotherapy was administered as NACT to 14,783 patients (33.0%) and as ACT to 29,982 (67.0%) patients. Due to the higher prevalence of unfavorable tumor subtypes, younger patients had a higher rate of chemotherapy (≤ 29y: 74.2%; 30-39y: 71.3%) and a higher proportion of NACT administration ( ≤ 29y: 66.9%; 30-39y: 56.0%) in comparison with elderly patients, who had lower rates for overall chemotherapy (60-69y: 37.5%; ≥ 70y: 17.6%) and NACT (60-69y: 25.5%; ≥ 70y: 22.8%). Pathologic complete response was higher in younger than in older patients (≤ 29y: 30.4% vs. ≥ 70y: 16.7%), especially for HER2- subtypes.

CONCLUSION

The data from the nationwide German cohort reveal relevant age-dependent discrepancies concerning the use of chemotherapy for EBC.

Patient-reported outcomes for the Intergroup Sentinel Mamma study (INSEMA): A randomised trial with persistent impact of axillary surgery on arm and breast symptoms in patients with early breast cancer

BACKGROUND

In clinically node-negative breast cancer patients, the INSEMA trial (NCT02466737) assessed the non-inferiority of avoiding sentinel lymph node biopsy (SLNB) or axillary lymph node dissection (ALND). Here we present patient-reported outcomes (PROs) as a secondary endpoint.

METHODS

PROs were assessed for patients with no axillary surgery, SLNB alone, and ALND. Quality of life (QoL) questionnaire EORTC QLQ-C30 and its breast cancer module (BR23) were used at baseline (pre-surgery) and 1, 3, 6, 12, and 18 months after surgery. The QoL scores were compared using repeated measures mixed models based on the safety set.

FINDINGS

Between 2015 and 2019, 5502 patients were recruited for the first randomization, and 5154 were included in the intent-to-treat set (4124 SLNB versus 1030 no SLNB). In the case of one to three macrometastases after SLNB, 485 patients underwent second randomization (242 SLNB alone versus 243 ALND). Questionnaire completion response remained high throughout the trial: over 70% at all time points for the first randomization. There were significant differences for the BRBS (breast symptoms) and BRAS (arm symptoms) scores favoring the no SLNB group in all post-baseline assessments. Patients in the SLNB group showed significantly and clinically relevant higher scores for BRAS (differences in mean values ≥5.0 points at all times), including pain, arm swelling, and impaired mobility in all postoperative visits, with the highest difference at one month after surgery. Scoring of the QLQ-C30 questionnaire revealed no relevant differences between the treatment groups, although some comparisons were statistically significant.

INTERPRETATION

This is one of the first randomized trials investigating the omission of SLNB in clinically node-negative patients and the first to report comprehensive QoL data. Patients with no SLNB benefitted regarding arm symptoms/functioning, while no relevant differences in other scales were seen.

FUNDING

Supported by German Cancer Aid (Deutsche Krebshilfe, Bonn, Germany), Grant No. 110580 and Grant No. 70110580 to University Medicine Rostock.

COGNITION: a prospective precision oncology trial for patients with early breast cancer at high risk following neoadjuvant chemotherapy

BACKGROUND

COGNITION (Comprehensive assessment of clinical features, genomics and further molecular markers to identify patients with early breast cancer for enrolment on marker driven trials) is a diagnostic registry trial that employs genomic and transcriptomic profiling to identify biomarkers in patients with early breast cancer with a high risk for relapse after standard neoadjuvant chemotherapy (NACT) to guide genomics-driven targeted post-neoadjuvant therapy.

PATIENTS AND METHODS

At National Center for Tumor Diseases Heidelberg patients were biopsied before starting NACT, and for patients with residual tumors after NACT additional biopsy material was collected. Whole-genome/exome and transcriptome sequencing were applied on tumor and corresponding blood samples.

RESULTS

In the pilot phase 255 patients were enrolled, among which 213 were assessable: thereof 48.8% were identified to be at a high risk for relapse following NACT; 86.4% of 81 patients discussed in the molecular tumor board were eligible for a targeted therapy within the interventional multiarm phase II trial COGNITION-GUIDE (Genomics-guided targeted post neoadjuvant therapy in patients with early breast cancer) starting enrolment in Q4/2022. An in-depth longitudinal analysis at baseline and in residual tumor tissue of 16 patients revealed some cases with clonal evolution but largely stable genetic alterations, suggesting restricted selective pressure of broad-acting cytotoxic neoadjuvant chemotherapies.

CONCLUSIONS

While most precision oncology initiatives focus on metastatic disease, the presented concept offers the opportunity to empower novel therapy options for patients with high-risk early breast cancer in the post-neoadjuvant setting within a biomarker-driven trial and provides the basis to test the value of precision oncology in a curative setting with the overarching goal to increase cure rates.

Intelligent multi-modal shear wave elastography to reduce unnecessary biopsies in breast cancer diagnosis (INSPiRED 002): a retrospective, international, multicentre analysis

BACKGROUND

Breast ultrasound identifies additional carcinomas not detected in mammography but has a higher rate of false-positive findings. We evaluated whether use of intelligent multi-modal shear wave elastography (SWE) can reduce the number of unnecessary biopsies without impairing the breast cancer detection rate.

METHODS

We trained, tested, and validated machine learning algorithms using SWE, clinical, and patient information to classify breast masses. We used data from 857 women who underwent B-mode breast ultrasound, SWE, and subsequent histopathologic evaluation at 12 study sites in seven countries from 2016 to 2019. Algorithms were trained and tested on data from 11 of the 12 sites and externally validated using the additional site's data. We compared findings to the histopathologic evaluation and compared the diagnostic performance between B-mode breast ultrasound, traditional SWE, and intelligent multi-modal SWE.

RESULTS

In the external validation set (n = 285), intelligent multi-modal SWE showed a sensitivity of 100% (95% CI, 97.1-100%, 126 of 126), a specificity of 50.3% (95% CI, 42.3-58.3%, 80 of 159), and an area under the curve of 0.93 (95% CI, 0.90-0.96). Diagnostic performance was significantly higher compared to traditional SWE and B-mode breast ultrasound (P < 0.001). Unlike traditional SWE, positive-predictive values of intelligent multi-modal SWE were significantly higher compared to B-mode breast ultrasound. Unnecessary biopsies were reduced by 50.3% (79 versus 159, P < 0.001) without missing cancer compared to B-mode ultrasound.

CONCLUSION

The majority of unnecessary breast biopsies might be safely avoided by using intelligent multi-modal SWE. These results may be helpful to reduce diagnostic burden for patients, providers, and healthcare systems.

Best Practice Guideline - DEGUM Recommendations on Breast Ultrasound

For many years, breast ultrasound has been used in addition to mammography as an important method for clarifying breast findings. However, differences in the interpretation of findings continue to be problematic 1 2. These differences decrease the diagnostic accuracy of ultrasound after detection of a finding and complicate interdisciplinary communication and the comparison of scientific studies 3. In 1999, the American College of Radiology (ACR) created a working group (International Expert Working Group) that developed a classification system for ultrasound examinations based on the established BI-RADS classification of mammographic findings under consideration of literature data 4. Due to differences in content, the German Society for Ultrasound in Medicine (DEGUM) published its own BI-RADS-analogue criteria catalog in 2006 3. In addition to the persistence of differences in content, there is also an issue with formal licensing with the current 5th edition of the ACR BI-RADS catalog, even though the content is recognized by the DEGUM as another system for describing and documenting findings. The goal of the Best Practice Guideline of the Breast Ultrasound Working Group of the DEGUM is to provide colleagues specialized in senology with a current catalog of ultrasound criteria and assessment categories as well as best practice recommendations for the various ultrasound modalities.

Shear wave elastography as a supplemental tool in the assessment of unsuspicious axillary lymph nodes in patients undergoing breast ultrasound examination

Objectives:

To define reference values for shear wave elastography (SWE) in unsuspicious axillary lymph nodes in patients undergoing breast ultrasound examination.

Methods:

In total, 177 clinically and sonographically unsuspicious axillary lymph nodes were prospectively evaluated with SWE using Virtual Touch Tissue Imaging Quantification (VTIQ) in 175 women. Mean values of tissue stiffness for axillary fatty tissue, lymph node cortex, and lymph node hilus were measured. Additionally, test-retest reliability of SWE in the assessment of axillary lymph node stiffness was evaluated by repeating each measurement three times.

Results:

In 177 axillary lymph nodes, the mean stiffness of lymph node cortex, hilus, and surrounding fatty tissue as quantified by SWE was 1.90 m/s (SD: 0.34 m/s), 2.02 m/s (SD: 0.37 m/s), and 1.75 m/s (SD: 0.38 m/s), respectively. The mean stiffness of cortex and hilus was significantly higher compared to fatty tissue (p < 0.0001). SWE demonstrated good test–retest reliability in the assessment of stiffness of the lymph node hilus, cortex, and the surrounding fatty tissue with an intraclass correlation of 0.79 (95% CI: 0.75; 0.83), 0.75 (95% CI: 0.70; 0.79), and 0.78 (95% CI: 0.74; 0.82), respectively, (p < 0.0001).

Conclusions:

Reference values for SWE in unsuspicious axillary lymph nodes are determined. These results may help to better identify axillary lymph node metastasis for breast cancer patients when combined with other lymph node features. SWE is a reliable method for the objective quantification of tissue stiffness of axillary lymph nodes.

Advances in knowledge:

This study presents physiological reference values for tissue stiffness by examining the axillary lymph nodes with SWE in 175 women with sonomorphologically unsuspicious lymph nodes.

Methods of Esthetic Assessment after Adjuvant Whole-Breast Radiotherapy in Breast Cancer Patients: Evaluation of the BCCT.core Software and Patients' and Physicians' Assessment from the Randomized IMRT-MC2 Trial

Simple Summary

To validate the BCCT.core software, the present analysis compares the esthetics assessment by the software in relation to patients’ and physicians’ rating in breast cancer patients after surgery and adjuvant radiotherapy. Agreement rates of the different assessments and their correlation with breast asymmetry indices were evaluated. The assessments of the software and the physicians were significantly correlated with all asymmetry indices, while for patients’ self-assessment, this general correlation was first seen after 2 years. Only a slight agreement between the BCCT.core software and the physicians’ or patients’ assessment was seen, while a moderate and substantial agreement was detected between the physicians’ and the patients’ assessments. The BCCT.core software is a reliable tool to measure asymmetries, but may not sufficiently evaluate the esthetic outcome as perceived by patients. It may be more appropriate for a long-term follow-up, when symmetry seems to increase in importance.

Abstract

The present analysis compares the esthetics assessment by the BCCT.core software in relation to patients’ and physicians’ ratings, based on the IMRT-MC2 trial. Within this trial, breast cancer patients received breast-conserving surgery (BCS) and adjuvant radiotherapy. At the baseline, 6 weeks, and 2 years after radiotherapy, photos of the breasts were assessed by the software and patients’ and physicians’ assessments were performed. Agreement rates of the assessments and their correlation with breast asymmetry indices were evaluated. The assessments of the software and the physicians were significantly correlated with asymmetry indices. Before and 6 weeks after radiotherapy, the patients’ self-assessment was only correlated with the lower breast contour (LBC) and upward nipple retraction (UNR), while after 2 years, there was also a correlation with other indices. Only a slight agreement between the BCCT.core software and the physicians’ or patients’ assessment was seen, while a moderate and substantial agreement was detected between the physicians’ and the patients’ assessment after 6 weeks and 2 years, respectively. The BCCT.core software is a reliable tool to measure asymmetries, but may not sufficiently evaluate the esthetic outcome as perceived by patients. It may be more appropriate for a long-term follow-up, when symmetry appears to increase in importance.

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.

Diagnosing Pathologic Complete Response in the Breast After Neoadjuvant Systemic Treatment of Breast Cancer Patients by Minimal Invasive Biopsy: Oral Presentation at the San Antonio Breast Cancer Symposium on Friday, December 13, 2019, Program Number GS5-03

OBJECTIVE

We evaluated the ability of minimally invasive, image-guided vacuum-assisted biopsy (VAB) to reliably diagnose a pathologic complete response in the breast (pCR-B).

SUMMARY BACKGROUND DATA

Neoadjuvant systemic treatment (NST) elicits a pathologic complete response in up to 80% of women with breast cancer. In such cases, breast surgery, the gold standard for confirming pCR-B, may be considered overtreatment.

METHODS

This multicenter, prospective trial enrolled 452 women presenting with initial stage 1-3 breast cancer of all biological subtypes. Fifty-four women dropped out; 398 were included in the full analysis. All participants had an imaging-confirmed partial or complete response to NST and underwent study-specific image-guided VAB before guideline-adherent breast surgery. The primary endpoint was the false-negative rate (FNR) of VAB-confirmed pCR-B.

RESULTS

Image-guided VAB alone did not detect surgically confirmed residual tumor in 37 of 208 women [FNR, 17.8%; 95% confidence interval (CI), 12.8-23.7%]. Of these 37 women, 12 (32.4%) had residual DCIS only, 20 (54.1%) had minimal residual tumor (<5 mm), and 19 of 25 (76.0%) exhibited invasive cancer cellularity of ≤10%. In 19 of the 37 cases (51.4%), the false-negative result was potentially avoidable. Exploratory analysis showed that performing VAB with the largest needle by volume (7-gauge) resulted in no false-negative results and that combining imaging and image-guided VAB into a single diagnostic test lowered the FNR to 6.2% (95% CI, 3.4%-10.5%).

CONCLUSIONS

Image-guided VAB missed residual disease more often than expected. Refinements in procedure and patient selection seem possible and necessary before omitting breast surgery.

Abstract PD7-02: Intelligent vacuum-assisted breast biopsy to identify breast cancer patients with pathologic complete response after neoadjuvant systemic treatment for omission of breast and axillary surgery

Background: Neoadjuvant systemic treatment (NST) elicits a pathologic complete response (pCR, ypT0, ypN0) in 40-70% of women with HER2 positive, triple-negative, and high-proliferative Luminal B breast cancer. These patients may not need surgery as all local tumor has already been eradicated by NST. However, their safe identification prior to surgery is a major challenge: imaging after NST, minimally-invasive biopsies, or combinations of both using narrow patient selection criteria are not accurate enough either because they showed high rates of missed cancer or high rates of missed pCR. Recently, the concept of an intelligent, minimally-invasive, vacuum-assisted biopsy (intelligent VAB) was introduced to identify exceptional responders to NST. The intelligent VAB is a multivariate risk algorithm that uses artificial intelligence techniques to analyze conventional VAB results alongside contextualizing patient, imaging, and tumor information. It showed great potential to reliably identify patients with a pCR in the breast (ypT0). However, the absent integration of the axillary status impairs clinical applicability. In this study, we evaluated the feasibility of an intelligent VAB to identify exceptional responders to NST in the breast and axilla. Methods: We trained, tested, and validated a machine learning algorithm (Extreme Gradient Boosting Tree) using patient, imaging, tumor, and conventional VAB variables to detect residual cancer after NST (ypT+/is or ypN+) prior to surgery. We used data from 318 women with cT1-3, cN0/+, HER2 positive, triple-negative breast or high-proliferative Luminal B breast cancer who underwent VAB before surgery (NCT02948764). We used 10-fold cross-validation to train and test the algorithm which was externally validated using data of an independent, similar trial (NCT02575612). Findings were compared to the histopathologic evaluation of the surgical specimen. False-negative rate (FNR), specificity, and area under the ROC curve (AUROC) were the main outcome measures. Results: In the development set (n=318), mean patient age was 52.5 years and 45.3% (144 of 318) achieved a pCR (ypT0 and ypN0). Using resampling methods, the intelligent VAB showed an FNR of 5.2% (9 of 174, 95% CI 2.4-9.5), a specificity of 37.5% (54 of 144, 95% CI 29.6-45.9), and an AUROC of 0.92 (95% CI 0.90-0.94) in the development set to detect residual cancer (ypT+/is or ypN+) after NST. In the external validation set (n=45), mean patient age was 48.1 years and 44.4% (20 of 45) achieved a pCR. The intelligent VAB showed an FNR of 0% (0 of 25, 95% CI 0.0-13.7), a specificity of 40.0% (8 of 20, 95% CI 19.1-63.9) and an AUROC of 0.91 (95% CI 0.82-0.97). Spiegelhalter’s Z confirmed a well-calibrated model (z score -0.746, P 0.228). FNR of the intelligent VAB was lower compared to imaging after NST, conventional VAB, or combinations of both using narrow patient selection criteria. Conclusion: An intelligent VAB can reliably exclude residual cancer after NST for women with cT1-3, cN0/+, HER2 positive, triple-negative breast or high-proliferative Luminal B breast cancer. The omission of breast and axillary surgery for these exceptional responders may be evaluated in future trials. Trial registration: NCT02948764 and NCT02575612. Funding: German Research Foundation (DFG)

Diagnostic Performance ComparisonFalse-negative rate - % (95% CI); no.Specificity - % (95% CI); no.Negative predictive value - % (95% CI); no.Positive predictive value - % (95% CI); no.AUROC - value (95% CI)Development set (n=318)Imaging after NST24.4% (18.0-13.7); 40 of 16452.2% (43.4-61.0); 69 of 13263.3% (53.5-72.3); 69 of 10966.3% (59.1-73.0); 124 of 187-Conventional VAB32.8% (25.8-40.3); 57 of 174100% (97.5-100); 144 of 14471.6% (64.9-77.8); 144 of 201100% (96.9-100); 117 of 117-Imaging after NST + VAB16.7% (11.4-23.2); 28 of 16832.1% (24.4-40.6); 44 of 13761.1% (48.9-72.4); 44 of 7260.1% (56.1-69.1); 140 of 223-VAB + patient selection9.1% (5.0-14.1) 15 of 17036.3% (28.2-45.0); 49 of 13576.6% (64.3-86.2); 49 of 6464.3% (57.9-70.4); 155 of 241-Intelligent VAB (Extreme Gradient Boosting tree)5.2% (2.4-9.6); 9 of 17437.5% (29.6-45.9); 54 of 14485.7% (74.6-93.3); 54 of 6364.7% (58.5-70.6); 165 of 2550.92 (0.90-0.94)External validation (n=45)Imaging after NST24.0% (9.4-45.1%);6 of 2565.0% (40.8-84.6%);13 of 2068.4% (43.4-87.4%);13 of 1973.1% (52.2-88.4%);19 of 26-Conventional VAB28.0% (12.1-49.4%);7 of 25100% (83.2-100%);20 of 2074.1% (53.7-88.9%);20 of 27100% (81.5-100%);18 of 18-Imaging after NST + VAB12.0% (2.5-31.2); 3 of 2565.0% (40.8-84.6%);13 of 2081.3% (54.4-96.0%); 13 of 1675.9% (56.5-89.7%); 22 of 29-VAB + patient selection4.0% (1.0-2.4); 1 of 2530.0% (9.4-45.1%); 6 of 2085.7% (69.8-99.8); 6 of 763.2% (46.0-78.2); 24 of 38-Intelligent VAB (Extreme Gradient Boosting tree)0.0% (0.0-13.7%);0 of 2540.0% (19.1-63.9%);8 of 20100% (63.1-100%);8 of 867.8% (50.2-82.0%);25 of 370.91 (0.82 - 0.97)AUROC = Area under the receiver operating characteristic curve; CI = confidence interval

Citation Format: André Pfob, Chris Sidey-Gibbons, Geraldine Rauch, Bettina Thomas, Benedikt Schaefgen, Sherko Kuemmel, Toralf Reimer, Markus Hahn, Marc Thill, Jens-Uwe Blohmer, John Hackmann, Wolfram Malter, Inga Bekes, Kay Friedrichs, Sebastian Wojcinski, Sylvie Joos, Stefan Paepke, Tom Degenhardt, Joachim Rom, Achim Rody, Regina Große, Marion van Mackelenbergh, Mattea Reinisch, Maria Karsten, Michael Golatta, Joerg Heil. Intelligent vacuum-assisted breast biopsy to identify breast cancer patients with pathologic complete response after neoadjuvant systemic treatment for omission of breast and axillary surgery [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD7-02.

Abstract P2-12-08: Impact of summation dose intensity product on pathologic response in patients receiving neoadjuvant chemotherapy for early breast cancer

Background: Pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is associated with beneficial long-term outcome in early breast cancer (EBC). pCR is defined as ypT0/is, ypN0. It is well known that pCR rates depend on tumor subtype. However, the impact of different therapy regimens, dose delays and dose reductions on pCR rates is still unclear. This retrospective study analyzed the therapy dose of patients with pCR and non-pCR after NACT for EBC using referenced and delivered summation dose intensity product (SDIP) and relative dose intensity (RDI) calculations. Methods: SDIP of different therapy regimens were calculated by defining a unit dose intensity (UDI) for each therapy (Hryniuk et al. JCO 1998). The UDI is defined as the dose in mg/m2/week that produces a 30% complete or partial remission rate as a single agent in first-line therapy for metastatic breast cancer. For each regimen, the planned dose intensities (PDI) were divided by the UDI for every single drug. The summation dose intensity (SDI) is the addition of the resulting decimal fractions. Multiplying the SDI by the treatment intervals and number of cycles gives the SDIP. SDIP can be divided into referenced SDIP (rSDIP) and delivered SDIP (dSDIP). RDI is the ratio of dSDIP in comparison to rSDIP. Therapy dose calculations were performed for patients who received NACT for EBC at the National Center for Tumor Diseases (NCT) Heidelberg, Germany, between 01/2015 and 08/2019. Results: 590 patients (median age 51 years) were included, median follow up was 38 months, 225 patients (38.1%) achieved pCR. 65 patients (11.0%) were hormone receptor positive HER2 negative (HR+HER2-), 164 (27.8%) were HR-HER2-, 133 (22.5%) were HR+HER2+, 97 (16.4%) were HR-HER2+. Significant difference between the pCR and non-pCR group was observed for HR-status (p&lt;0.001), HER2-status (p&lt;0.001), tumor grading (p&lt;0.001) and Ki-67 (p&lt;0.001). Age of diagnosis (p=0.611), menopause-status (p=0.769), tumor size (p=0.183) and nodal status (p=0.163) did not significantly vary between patients with pCR versus non-pCR. Patients with pCR had significantly higher rates of anemia II° (p=0.006). No significant difference was seen for anemia ≥III°, neutropenia ≥II°, deviation of liver enzymes ≥II°, nephrotoxicity ≥II°, polyneuropathy ≥II° or the administration of red cell and platelet concentrate as well as the use of Granulocyte-Colony Stimulating Factor (G-CSF). 3 year overall survival (OS), metastasis-free survival (MFS) and recurrence-free survival (RFS) were found to be significantly better in patients with pCR (OS: 98.0% vs. 90.2%, p&lt;0.001; MFS: 94.5% vs. 84.6%, p&lt;0.001; RFS: 97.7% vs. 94.0 %, p=0.029). Patients with pCR had a significantly higher mean rSDIP (69.8 vs. 58.9, p=0.001) and dSDIP (59.5 vs. 49.1, p=0.001). Mean RDI did not significantly vary between pCR and non-pCR (0.853 vs. 0.840, p=0.350). Mean rSDIP and dSDIP significantly vary between the tumor subtypes HR+HER2-, HR-HER2-, HR+HER2+, and HR-HER2+ (rSDIP: 47.4, 54.5, 74.3, 76.7; p&lt;0.001; dSDIP: 39.5, 43.3, 62.0, 67.0; p&lt;0.001). Mean rSDIP and dSDIP did not significantly vary between patients with pCR and non-pCR within the tumor subtypes. Conclusion: Outcomes for NACT are consistent with published data concerning pCR rates. It is notable that the pCR group had significantly higher rSDIP and dSDIP than the non-pCR group whereas RDI and toxicity did not significantly vary between the two groups. rSDIP and dSDIP were mainly depending on the tumor subtype. This data confirms that the tumor subtype has a major impact on pCR rate. Whilst this retrospective analysis must be interpreted with caution, the results show that SDIP is an integral parameter for assessing the efficacy and adequate application of combination therapy and is associated with pCR rate and overall survival.

Citation Format: Thomas M Deutsch, Michelle Kobel, Manuel Feisst, Fabian Riedel, Katharina Smetanay, Carlo Fremd, Laura Michel, Michael Golatta, Joerg Heil, Markus Wallwiener, Andreas Schneeweiss. Impact of summation dose intensity product on pathologic response in patients receiving neoadjuvant chemotherapy for early breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-12-08.

Abstract GS4-03: Patient-reported outcomes (PROs) for the intergroup sentinel mamma study (INSEMA, GBG75, ABCSG43): Persistent impact of axillary surgery on arm and breast symptoms in early breast cancer

Background: Despite increasing evidence disfavoring axillary lymph node dissection (ALND) for locoregional control, it remains part of guidelines for breast cancer (BC) treatment. In an attempt to re-evaluate standard local therapy, the INSEMA trial was designed to assess non-inferiority of avoiding sentinel lymph node biopsy (SLNB) or completion ALND (cALND) in early-stage clinically node-negative BC patients. Here we present PROs from the INSEMA trial. Methods: INSEMA (NCT02466737) investigates non-inferiority of invasive disease-free survival (iDFS) after no axillary surgical staging versus SLNB (first randomization 1:4) in patients with clinically node-negative BC (tumor size ≤5 cm) and primary breast-conserving surgery (BCS). In case of pN1a(sn) in the SLNB arm, patients underwent a second randomization to either SLNB alone or cALND (1:1). PROs were assessed at baseline (pre-surgery) and at 1, 3, 6, 12, and 18 months after final axillary surgery using the European Organisation for Research and Treatment of Cancer Quality-of-Life Questionnaire (EORTC QLQ-C30) and its breast cancer (BR23) module. Higher scores of C30 and BR23 (range 0-100) indicate better functioning and global health status (GHS)/quality of life (QoL) or worse symptom severity, respectively. The QoL scores were compared using the Mann-Whitney U test based on the safety set. Results: Between September 2015 and April 2019, 5,502 patients were recruited for the 1st randomization and 5,173 of them were included in the intent-to-treat set (4,138 SLNB vs 1,035 no SLNB). Patient and tumor characteristics were well-balanced between treatment arms. Median age at diagnosis was 62.0 years (range 24.0 - 89.0). Overall, recruited patients presented with low-risk BC marked by 85.6% clinically stage T1, 98.5% hormone-receptor positivity, 2.4% HER2-positivity, and 3.7% G3 tumors. The majority (73.5%) had an invasive carcinoma of no special type (72.8% in SLNB vs 76.0% in no SLNB arm) and 87.0% had Ki-67 ≤ 20%. Questionnaire completion response remained high throughout the trial: n=3,915 (75.7%) returned questionnaires at 1 month after final axillary surgery, n=3,938 (76.1%) at 3 months, n=4,024 (77.8%) at 6 months, n=3,907 (75.5%) at 12 months, and n=3,637 (70.3%) at 18 months. All QoL baseline parameters regarding GHS, functional scales, and symptom scales/items were well-balanced between arms (total 4,117 SLNB vs 1,056 no SLNB as treated; 270 of 4,117 received cALND). There were significant differences for the BRBS (breast symptoms) and BRAS (arm symptoms) scores favoring the no SLNB group in all post-baseline assessments Patients in the SLNB group showed persistent higher scores for BRAS (differences in mean values ≥5.0 points at all times of assessment) including pain, arm swelling, and impaired mobility in all postoperative visits with the highest difference at 1 month after final surgery (mean scores, 23.6 vs. 12.8, p&lt;0.001). Differences between treatment arms regarding BRBS including pain, breast swelling, hypersensitivity, and other skin problems showed a smaller range, but still a continuous trend for improved QoL in the no SLNB arm. Scoring of the QLQ-C30 questionnaire revealed no relevant differences between the treatment groups postoperatively. Conclusions: This is one of the first randomized trials investigating the omission of SLNB in clinically node-negative patients and the first to report QoL data. Patients with no SLNB benefitted regarding arm symptoms/functioning while no relevant differences in other QoL scales were seen. Data for the primary outcome of the study (iDFS) are expected for the end of 2024.

Citation Format: Bernd Gerber, Angrit Stachs, Kristina Veselinovic, Silke Polata, Thomas Müller, Thorsten Kühn, Jörg Heil, Beyhan Ataseven, Roland Reitsamer, Guido Hildebrandt, Michael Knauer, Michael Golatta, Andrea Stefek, Dirk-Michael Zahm, Marc Thill, Valentina Nekljudova, David Krug, Fenja Seither, Sibylle Loibl, Toralf Reimer. Patient-reported outcomes (PROs) for the intergroup sentinel mamma study (INSEMA, GBG75, ABCSG43): Persistent impact of axillary surgery on arm and breast symptoms in early breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr GS4-03.

Diagnosis, Therapy and Follow-up of Cervical Cancer. Guideline of the DGGG, DKG and DKH (S3-Level, AWMF Registry No. 032/033OL, May 2021) – Part 1 with Recommendations on Epidemiology, Screening, Diagnostics and Therapy

Aim This update of the interdisciplinary S3 guideline on the Diagnosis, Therapy and Follow-up of Cervical Cancer (AWMF Registry No. 032/033OL) was published in March 2021. This updated guideline was funded by German Cancer Aid (Deutsche Krebshilfe) as part of the German Guideline Program in Oncology. The guideline was coordinated by the German Society of Gynecology and Obstetrics (Deutsche Gesellschaft für Gynäkologie und Geburtshilfe, DGGG) and the Working Group on Gynecological Oncology (Arbeitsgemeinschaft Gynäkologische Onkologie, AGO) of the German Cancer Society (Deutsche Krebsgesellschaft, DKG).

Method The process of updating the S3 guideline dating from 2014 was based on an appraisal of the available evidence using the criteria of evidence-based medicine, adaptations of existing evidence-based national and international guidelines or – if evidence was lacking – on a consensus of the specialists involved in compiling the update. After an initial review of the current literature was carried out according to a prescribed algorithm, several areas were identified which, in contrast to the predecessor version from September 2014, required new recommendations or statements which took account of more recently published literature and the appraisal of the new evidence.

Recommendations The short version of this guideline consists of recommendations and statements on the epidemiology, screening, diagnostic workup and therapy of patients with cervical cancer. The most important new aspects included in this updated guideline include the newly published FIGO classification of 2018, the radical open surgery approach for cervical cancers up to FIGO stage IB1, and use of the sentinel lymph node technique for tumors ≤ 2 cm. Other changes include the use of PET-CT, new options in radiotherapy (e.g., intensity-modulated radiotherapy, image-guided adaptive brachytherapy), and drug therapies to treat recurrence or metastasis.

Diagnosis, Therapy and Follow-up of Cervical Cancer. Guideline of the DGGG, DKG and DKH (S3-Level, AWMF Registry No. 032/033OL, May 2021) – Part 2 with Recommendations on Psycho-oncology, Rehabilitation, Follow-up, Recurrence, Palliative Therapy and Healthcare Facilities

Aim This is an update of the interdisciplinary S3-guideline on the Diagnosis, Therapy and Follow-up of Cervical Cancer (AWMF Registry No. 032/033OL), published in March 2021. The work on the updated guideline was funded by German Cancer Aid (Deutsche Krebshilfe) as part of the German Guideline Program in Oncology. The guideline was coordinated by the German Society of Gynecology and Obstetrics (Deutsche Gesellschaft für Gynäkologie und Geburtshilfe, DGGG) and the Working Group on Gynecological Oncology (Arbeitsgemeinschaft Gynäkologische Onkologie, AGO) of the German Cancer Society (Deutsche Krebsgesellschaft, DKG).

Method The process used to update the 2014 S3-guideline was based on an appraisal of the available evidence using the criteria of evidence-based medicine, adaptations of existing evidence-based national and international guidelines or – if evidence was lacking – on the consensus of the specialists involved in compiling the update. After an initial review of the current literature was carried out according to a prescribed algorithm, several areas were identified which, in contrast to the predecessor version from September 2014, required new recommendations or statements which would take account of more recently published literature and the recent appraisal of new evidence.

Recommendations The short version of this guideline consists of recommendations and statements on palliative therapy and follow-up of patients with cervical cancer. The most important aspects included in this updated guideline are the new FIGO classification published in 2018, the radical open surgery approach used to treat cervical cancer up to FIGO stage IB1, and the use of the sentinel lymph node technique for tumors ≤ 2 cm. Other changes include the use of PET-CT, new options in radiotherapy (e.g., intensity-modulated radiotherapy, image-guided adaptive brachytherapy), and drug therapies to treat recurrence or metastasis.

A New Practical Decision Rule to Better Differentiate BI-RADS 3 or 4 Breast Masses on Breast Ultrasound

OBJECTIVES

The BI-RADS classification provides a standardized way to describe ultrasound findings in breast cancer diagnostics. However, there is little information regarding which BI-RADS descriptors are most strongly associated with malignancy, to better distinguish BI-RADS 3 (follow-up imaging) and 4 (diagnostic biopsy) breast masses.

METHODS

Patients were recruited as part of an international, multicenter trial (NCT02638935). The trial enrolled 1294 women (6 excluded) categorized as BI-RADS 3 or 4 upon routine B-mode ultrasound examination. Ultrasound images were evaluated by three expert physicians according to BI-RADS. All patients underwent histopathological confirmation (reference standard). We performed univariate and multivariate analyses (chi-square test, logistic regression, and Krippendorff's alpha).

RESULTS

Histopathologic evaluation showed malignancy in 368 of 1288 masses (28.6%). Upon performing multivariate analysis, the following descriptors were significantly associated with malignancy (P < .05): age ≥50 years (OR 8.99), non-circumscribed indistinct (OR 4.05) and microlobulated margin (OR 2.95), nonparallel orientation (OR 2.69), and calcification (OR 2.64). A clinical decision rule informed by these results demonstrated a 97% sensitivity and missed fewer cancers compared to three physician experts (range of sensitivity 79-95%) and a previous decision rule (sensitivity 59%). Specificity was 44% versus 22-83%, respectively. The inter-reader reliability of the BI-RADS descriptors and of the final BI-RADS score was fair-moderate.

CONCLUSIONS

A patient should undergo a diagnostic biopsy (BI-RADS 4) instead of follow-up imaging (BI-RADS 3) if the patient is 50 years or older or exhibits at least one of the following features: calcification, nonparallel orientation of mass, non-circumscribed margin, or posterior shadowing.

Pathological Response in the Breast and Axillary Lymph Nodes after Neoadjuvant Systemic Treatment in Patients with Initially Node-Positive Breast Cancer Correlates with Disease Free Survival: An Exploratory Analysis of the GeparOcto Trial

Simple Summary

The extent of axillary surgery has been reduced in recent years to minimize side effects. However, a negative impact of reduced surgery on outcome must be avoided. We investigated for whom the extent of surgery can be safely reduced by examining early-stage breast cancer patients converting from lymph node (LN)-positive to LN-negative disease after neoadjuvant systemic treatment (NAST). Of 242 initially LN-positive patients treated within the GeparOcto trial, 54.5% were classified as LN-negative after NAST, 31.8% as LN-positive, and for 13.6% data were missing. Overall, 92.1% of patients underwent complete axillary LN dissection, with 6.6% undergoing sentinel LN dissection only. At surgery, 55.4% of patients had no signs of cancer in the LN, 45.0% had no signs of cancer in the breast (of those 8.3% had involved LN), and 41.3% had no signs of cancer at all. Patients with involved LN still had a bad prognosis. Conversion from LN-positive to LN-negative after NAST is of highest prognostic value. Surgical axillary staging after NAST is essential in these patients to offer tailored treatment.

Abstract

Background: The conversion of initially histologically confirmed axillary lymph node-positive (pN+) to ypN0 after neoadjuvant systemic treatment (NAST) is an important prognostic factor in breast cancer (BC) patients and may influence surgical de-escalation strategies. We aimed to determine pCR rates in lymph nodes (pCR-LN), the breast (pCR-B), and both (tpCR) in women who present with pN+ BC, to assess predictors for response and the impact of pCR-LN, pCR-B, and tpCR on invasive disease-free survival (iDFS). Methods: Retrospective, exploratory analysis of 242 patients with pN+ at diagnosis from the multicentric, randomized GeparOcto trial. Results: Of 242 patients with initially pN+ disease, 134 (55.4%) had a pCR-LN, and 109 (45.0%) a pCR-B. Of the 109 pCR-B patients, 9 (8.3%) patients had involved LN, and 100 (41.3%) patients had tpCR. Those with involved LN still had a bad prognosis. As expected, pCR-B and intrinsic subtypes (TNBC and HER2+) were identified as independent predictors of pCR-LN. pCR-LN (ypN0; hazard ratio 0.42; 95%, CI 0.23–0.75; p = 0.0028 for iDFS) was the strongest independent prognostic factor. Conclusions: In initially pN+ patients undergoing NAST, the conversion to ypN0 is of high prognostic value. Surgical axillary staging after NAST is still essential in these patients to offer tailored treatment.

The importance of multi-modal imaging and clinical information for humans and AI-based algorithms to classify breast masses (INSPiRED 003): an international, multicenter analysis

OBJECTIVES

AI-based algorithms for medical image analysis showed comparable performance to human image readers. However, in practice, diagnoses are made using multiple imaging modalities alongside other data sources. We determined the importance of this multi-modal information and compared the diagnostic performance of routine breast cancer diagnosis to breast ultrasound interpretations by humans or AI-based algorithms.

METHODS

Patients were recruited as part of a multicenter trial (NCT02638935). The trial enrolled 1288 women undergoing routine breast cancer diagnosis (multi-modal imaging, demographic, and clinical information). Three physicians specialized in ultrasound diagnosis performed a second read of all ultrasound images. We used data from 11 of 12 study sites to develop two machine learning (ML) algorithms using unimodal information (ultrasound features generated by the ultrasound experts) to classify breast masses which were validated on the remaining study site. The same ML algorithms were subsequently developed and validated on multi-modal information (clinical and demographic information plus ultrasound features). We assessed performance using area under the curve (AUC).

RESULTS

Of 1288 breast masses, 368 (28.6%) were histopathologically malignant. In the external validation set (n = 373), the performance of the two unimodal ultrasound ML algorithms (AUC 0.83 and 0.82) was commensurate with performance of the human ultrasound experts (AUC 0.82 to 0.84; p for all comparisons > 0.05). The multi-modal ultrasound ML algorithms performed significantly better (AUC 0.90 and 0.89) but were statistically inferior to routine breast cancer diagnosis (AUC 0.95, p for all comparisons ≤ 0.05).

CONCLUSIONS

The performance of humans and AI-based algorithms improves with multi-modal information.

KEY POINTS

• The performance of humans and AI-based algorithms improves with multi-modal information. • Multimodal AI-based algorithms do not necessarily outperform expert humans. • Unimodal AI-based algorithms do not represent optimal performance to classify breast masses.

The potential of combined shear wave and strain elastography to reduce unnecessary biopsies in breast cancer diagnostics - An international, multicentre trial

BACKGROUND

Shear wave elastography (SWE) and strain elastography (SE) have shown promising potential in breast cancer diagnostics by evaluating the stiffness of a lesion. Combining these two techniques could further improve the diagnostic performance. We aimed to exploratorily define the cut-offs at which adding combined SWE and SE to B-mode breast ultrasound could help reclassify Breast Imaging Reporting and Data System (BI-RADS) 3-4 lesions to reduce the number of unnecessary breast biopsies.

METHODS

We report the secondary results of a prospective, multicentre, international trial (NCT02638935). The trial enrolled 1288 women with BI-RADS 3 to 4c breast masses on conventional B-mode breast ultrasound. All patients underwent SWE and SE (index test) and histopathologic evaluation (reference standard). Reduction of unnecessary biopsies (biopsies in benign lesions) and missed malignancies after recategorising with SWE and SE were the outcome measures.

RESULTS

On performing histopathologic evaluation, 368 of 1288 breast masses were malignant. Following the routine B-mode breast ultrasound assessment, 53.80% (495 of 920 patients) underwent an unnecessary biopsy. After recategorising BI-RADS 4a lesions (SWE cut-off ≥3.70 m/s, SE cut-off ≥1.0), 34.78% (320 of 920 patients) underwent an unnecessary biopsy corresponding to a 35.35% (320 versus 495) reduction of unnecessary biopsies. Malignancies in the new BI-RADS 3 cohort were missed in 1.96% (12 of 612 patients).

CONCLUSION

Adding combined SWE and SE to routine B-mode breast ultrasound to recategorise BI-RADS 4a patients could help reduce the number of unnecessary biopsies in breast diagnostics by about 35% while keeping the rate of undetected malignancies below the 2% ACR BI-RADS 3 definition.

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.

Quality of life after simultaneously integrated boost with intensity-modulated versus conventional radiotherapy with sequential boost for adjuvant treatment of breast cancer: 2-year results of the multicenter randomized IMRT-MC2 trial

BACKGROUND

We recently published 2-year results of the prospective, randomized IMRT-MC2 trial, showing non-inferior local control and cosmesis in breast cancer patients after conventionally fractionated intensity-modulated radiotherapy with simultaneously integrated boost (IMRT-SIB), compared to 3D-conformal radiotherapy with sequential boost (3D-CRT-seqB). Here, we report on 2-year quality of life results.

PATIENTS AND METHODS

502 patients were enrolled and randomized to IMRT-SIB (50.4 Gy in 1.8 Gy fractions with a 64.4 Gy SIB to the tumor bed) or to 3D-CRT-seqB (50.4 Gy in 1.8 Gy fractions, followed by a sequential boost of 16 Gy in 2 Gy fractions). For quality of life (QoL) assessment, patients completed the QLQ-C30 and QLQ-BR23 questionnaires at baseline, 6 weeks and 2 years after radiotherapy.

RESULTS

Significant differences between treatment arms were seen 6 weeks after radiotherapy for pain (22.3 points for IMRT vs. 27.0 points for 3D-CRT-seqB; p = 0.033) and arm symptoms (18.1 points for IMRT vs. 23.6 points for 3D-CRT-seqB; p = 0.013), both favoring IMRT-SIB. Compared to baseline values, both arms showed significant improvement in global score (IMRT: p = 0.009; 3D-CRT: p = 0.001) after 2 years, with slight deterioration on the role (IMRT: p = 0.008; 3-D-CRT: p = 0.001) and social functioning (IMRT: p = 0.013, 3D-CRT: p = 0.001) as well as the future perspectives scale (IMRT: p = 0.003; 3D-CRT: p = 0.0034).

CONCLUSION

This is the first randomized phase III trial demonstrating that IMRT-SIB was associated with slightly superior QoL compared to 3-D-CRT-seqB. These findings further support the clinical implementation of SIB in adjuvant breast cancer treatment.

Long-Term Patient Satisfaction and Quality of Life After Breast-Conserving Therapy: A Prospective Study Using the BREAST-Q

Background

Poor patient-reported satisfaction after breast-conserving therapy (BCT) has been associated with impaired health-related quality of life (HRQOL) and subsequent depression in retrospective analysis. This prospective cohort study aimed to assess the HRQOL of patients who have undergone BCT using the BREAST-Q, and to identify clinical risk factors for lower patient satisfaction.

Methods

Patients with primary breast cancer undergoing BCT were asked to complete the BREAST-Q preoperatively (T1) for baseline evaluation, then 3 to 4 weeks postoperatively (T2), and finally 1 year after surgery (T3). Clinicopathologic data were extracted from the patients’ charts. Repeated measures analysis of variance (ANOVA) was used to determine significant differences in mean satisfaction and well-being levels among the test intervals. Multiple linear regression was used to evaluate risk factors for lower satisfaction.

Results

The study enrolled 250 patients. The lowest baseline BREAST-Q score was reported for “satisfaction with breast” (mean, 61 ± 19), but this increased postoperatively (mean, 66 ± 18) and was maintained at the 1 year follow-up evaluation (mean, 67 ± 21). “Physical well-being” decreased from T1 (mean, 82 ± 17) to T2 (mean, 28 ± 13) and did not recover much by T3 (mean, 33 ± 13), being the lowest BREAST-Q score postoperatively and in the 1-year follow-up evaluation. In multiple regression, baseline psychosocial well-being, body mass index (BMI), and type of incision were risk factors for lower “satisfaction with breasts.”

Conclusion

Both the aesthetic/surgery-related and psychological aspects are equally important with regard to “satisfaction with breasts” after BCT. The data could serve as the benchmark for future studies.

Contrast of Digital and Health Literacy Between IT and Health Care Specialists Highlights the Importance of Multidisciplinary Teams for Digital Health-A Pilot Study

PURPOSE

Despite their promises, digital innovations have scarcely translated to technologies used in routine clinical practice, making the identification of barriers to successful implementation a research priority. Low levels of transdisciplinary skills represent such a barrier but so far, this has not been evaluated and compared between information technology (IT) and health care specialists. In this study, we evaluated the level of digital health literacy among IT and health care specialists.

MATERIALS AND METHODS

An anonymous questionnaire was distributed to staff at a breast cancer unit and an IT department of two German universities in December 2020. The survey questionnaire consisted of the previously validated eHealth Literacy Assessment Toolkit and additional questions with respect to age, profession, and career stage. Mann-Whitney or Wilcoxon rank-sum tests and two-sample chi-square tests were used for the analysis.

RESULTS

The survey was completed by 113 individuals: 70 (61.9%) IT specialists and 43 (38.1%) health care specialists. Health care specialists scored significantly higher on the health-related scales and IT specialists scored significantly higher on the digitally related scales. No single participant identified themselves to have the highest level of literacy on all survey questions (n = 0 of 113; 0%). Only one person (n = 1 of 113; 0.9%) consistently reported a high or the highest level of literacy.

CONCLUSION

Although IT and health care specialists showed great literacy in their respective disciplines, only few individuals combined both digital and health care literacy. Multidisciplinary teams and transdisciplinary curricula are crucial to bridge skill gaps between disciplines and to drive the implementation of digital health initiatives.

Evaluation of the FUSION-X-US-II prototype to combine automated breast ultrasound and tomosynthesis

OBJECTIVE

The FUSION-X-US-II prototype was developed to combine 3D automated breast ultrasound (ABUS) and digital breast tomosynthesis in a single device. We evaluated the performance of ABUS and tomosynthesis in a single examination in a clinical setting.

METHODS

In this prospective feasibility study, digital breast tomosynthesis and ABUS were performed using the FUSION-X-US-II prototype without any change of the breast position in patients referred for clarification of breast lesions with an indication for tomosynthesis. The tomosynthesis and ABUS images of the prototype were interpreted independently from the clinical standard by a breast diagnostics specialist. Any detected lesion was classified using BI-RADS® scores, and results of the standard clinical routine workup (gold standard) were compared to the result of the separate evaluation of the prototype images. Image quality was rated subjectively and coverage of the breast was measured.

RESULTS

One hundred one patients received both ABUS and tomosynthesis using the prototype. The duration of the additional ABUS acquisition was 40 to 60 s. Breast coverage by ABUS was approximately 80.0%. ABUS image quality was rated as diagnostically useful in 86 of 101 cases (85.1%). Thirty-three of 34 malignant breast lesions (97.1%) were identified using the prototype.

CONCLUSION

The FUSION-X-US-II prototype allows a fast ABUS scan in combination with digital breast tomosynthesis in a single device integrated in the clinical workflow. Malignant breast lesions can be localized accurately with direct correlation of ABUS and tomosynthesis images. The FUSION system shows the potential to improve breast cancer screening in the future after further technical improvements.

KEY POINTS

• The FUSION-X-US-II prototype allows the combination of automated breast ultrasound and digital breast tomosynthesis in a single device without decompression of the breast. • Image quality and coverage of ABUS are sufficient to accurately detect malignant breast lesions. • If tomosynthesis and ABUS should become part of breast cancer screening, the combination of both techniques in one device could offer practical and logistic advantages. To evaluate a potential benefit of a combination of ABUS and tomosynthesis in screening-like settings, further studies are needed.

Abstract PS3-18: Differences in the diagnostic performance of breast ultrasound with or without additional patient information: A secondary analysis of an international multicenter trial

Background and objectives: The Breast Imaging Reporting and Data System (BI-RADS) has helped to standardize radiologic reports and assessment in breast cancer diagnostics. So far, BI-RADS consists of the sole, standardized description of images. Individual patient characteristics like disease and family history or age are no part of the current BI-RADS classification system but are often subjectively considered to evaluate the risk of breast cancer in the clinical setting. It is however unclear how and to which extent such additional patient information influence the evaluation of risk of malignancy. Thus, we compared the performance in the detection of breast cancer between the sole analysis of ultrasound images by physician experts and a physician actually examining and counseling a patient in the clinical setting.

Methods: This multicenter, prospective trial took place at 11 trial sites in Austria, France, Germany, Japan, Netherlands, Portugal, and the US from February 2016 to March 2019. The trial enrolled 1288 women presenting with a lesion ≥0.5 and ≤5 cm in 2D B-mode ultrasound. In the clinical setting, the examiner conducted a routine 2D B-mode ultrasound examination and had additional standard information about the patients’ disease history and family history. The final ultrasound images made in the clinical routine (annotated with size measurements) but not any other information about the patient was given to three physician experts (&gt;15 years of experience in breast cancer diagnostics). The examiner in the clinical setting and each of the three experts evaluated the ultrasound images according to BI-RADS and gave a likelihood score for malignancy according to ACR (American College of Radiology). Following the BI-RADS definition by ACR, malignancy was assumed for a likelihood of malignancy &gt;2% (BI-RADS 4 or higher). All patients underwent histopathological confirmation which was the gold standard against which the clinical examiner and the three experts were compared. AUC, sensitivity, specificity, negative-predictive value (NPV), and positive-predictive value (PPV) were the performance measures.

Results: Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6%). AUC of the examiner in the clinical setting (AUC=0.94; 95% CI 0.92-0.95) was significantly better as for all three experts evaluating images only: expert one AUC=0.78 (95% CI 0.75-0.81); expert two AUC=0.81 (95% CI 0.78-0.84); expert three AUC=0.83 (95% CI 0.80-0.86). Sensitivity, specificity, NPV, and PPV of the examiner in the clinical setting were better as for all three experts evaluating images only. NPV of the examiner in the clinical setting was 98.6% (425 of 431), for expert one 87.8% (381 of 434), for expert two 91.2% (198 of 217), and for expert 3 84.1% (413 of 491).

Conclusion: Our findings suggest that information about individual patient characteristics (e.g. age, disease and family history) has great influence to accurately evaluate the risk of breast cancer. Future research may look into incorporating not only a standardized description of images into the BI-RADS classification system but also a standardized description of these individual patient characteristics to further standardize and objectify the risk evaluation in breast cancer diagnostics. Trial registration: NCT02638935

Performance of the examiner in the clinical setting and the three experts evaluating images onlyExaminer clinical settingImages only – Expert 1Images only – Expert 2Images only – Expert 3AUC (95% CI)0.94 (0.92-0.95)0.78 (0.75-0.81)0.81 (0.78-0.84)0.83 (0.80-0.86)Sensitivity –% (no.)98.4% (362 of 368)85.6% (315 of 368)94.8% (349 of 368)78.8% (290 of 368)Specificity –% (no.)46.2% (425 of 920)41.4% (381 of 920)21.5% (198 of 920)44.9% (413 of 920)Negative Predictive Value –% (no.)98.6% (425 of 431)87.8% (381 of 434)91.2% (198 of 217)84.1% (413 of 491)Positive Predictive Value –% (no.)42.2% (362 of 857)36.9% (315 of 854)32.6% (349 of 1071)36.4% (290 of 797)

Citation Format: André Pfob, Richard G. Barr, Volker Duda, Christopher Buesch, Joerg Heil, Michael Golatta. Differences in the diagnostic performance of breast ultrasound with or without additional patient information: A secondary analysis of an international multicenter trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-18.

Abstract PS3-16: Identifying the most relevant descriptors when evaluating ultrasound images in breast cancer diagnostics: A secondary analysis of an international multicenter trial

Background and objectives: The Breast Imaging Reporting and Data System (BI-RADS) provides a standardized way to describe ultrasound images in breast cancer diagnostics. However, there is little information which descriptors are most strongly associated with malignancy and to which extend the single descriptors (tissue composition, shape, orientation, margin of lesion, echo pattern, posterior features, and calcifications) should be considered for the final evaluation of risk of malignancy. Thus, we aimed to identify which BI-RADS descriptors are most strongly associated with malignancy when evaluating ultrasound images in breast cancer diagnostics.

Methods: This multicenter, prospective trial took place at 11 trial sites in Austria, France, Germany, Japan, Netherlands, Portugal, and the US from February 2016 to March 2019. The trial enrolled 1288 women presenting with a lesion ≥0.5 and ≤5 cm in 2D B-mode ultrasound. The examiner conducted a routine 2D B-mode ultrasound examination and had additional standard information about the patients’ disease history and family history. The examiner described the ultrasound images according to BI-RADS. All patients underwent histopathological confirmation which was the gold standard against which the clinical examiner was compared. We performed univariate and multivariate analyses using descriptive statistics, Chi-Square test, and logistic regression to identify which image descriptors are associated with malignancy.

Results: Histopathologic evaluation showed malignancy in 368 of 1288 lesions (28.6%). The descriptors most strongly associated with malignancy were spiculated margins (rate of malignancy 84.9%; 79 of 93), calcification (69.9%; 51 of 73), un-parallel orientation (65.9%; 187 of 284), angular margins (64.6%; 64 of 99), posterior shadowing (62.4%; 88 of 142), irregular shape (55.2%; 208 of 377), and indistinct margins (52.0%; 185 of 356). Different tissue compositions and echo patterns were least useful to distinguish between malign and benign lesions. Upon multivariate analysis, calcifications (OR 5.52; 95% CI 1.94-15.87) and posterior shadowing (OR 16.13; 95% CI 2.75-90.91) remained significantly (p&lt;0.05) associated with malignancy.

Conclusion: We identified which BI-RADS descriptors are most strongly associated with malignancy when evaluating ultrasound images in breast cancer diagnostics. Future research may look into providing not only a standardized image description but also a standardized final evaluation for the rate of malignancy with respect to the different predictive usefulness of the single descriptors. This may further standardize and objectify the risk evaluation in breast cancer diagnostics.

Trial registration: NCT02638935

Table 1: Association of BI-RADS descriptors with final histopathologic resultsbenign pathologymalignant pathologyp-valuetissue compositionp&lt;0.0001homogeneous background texture; fat —no. (%)185 (60.3)122 (39.74)homogeneous background texture; fibroglandular —no. (%)378 (77.3)111 (22.7)heterogeneous background texture —no. (%)356 (72.7)134 (27.4)shape of lesionp&lt;0.0001oval —no. (%)659 (86.1)106 (13.8)round —no. (%)89 (62.7)53 (37.3)irregular —no. (%)169 (44.8)208 (55.2)orientation of lesionp&lt;0.0001parallel —no. (%)806 (82.6)170 (17.42)not parallel —no. (%)97 (34.15)187 (65.9)margin of lesionp&lt;0.0001circumcised —no. (%)644 (89.0)80 (11.0)indistinct margin —no. (%)171 (48.0)185 (52.0)angular margin —no. (%)35 (35.4)64 (64.6)microlobulated margin —no. (%)117 (60.0)78 (40.0)spiculated margin —no. (%)14 (15.1)79 (84.9)echo patternp=0.02anechoic —no. (%)7 (100)0 (0.0)hyperechoic —no. (%)30 (79.0)8 (21.0)complex cystic and solid —no. (%)52 (82.5)11 (17.5)hypoechoic —no. (%)645 (71.0)264 (29.0)isoechoic —no. (%)40 (78.4)11 (21.6)heterogeneous —no. (%)136 (64.8)74 (35.2)posterior featuresp&lt;0.0001none —no. (%)590 (73.2)216 (26.8)enhancement —no. (%)249 (83.3)50 (16.7)shadowing —no. (%)53 (37.6)88 (62.4)combined pattern —no. (%)20 (58.8)14 (41.2)calcificationp&lt;0.0001no calcification —no. (%)894 (73.8)317 (26.2)calcification —no. (%)22 (30.1)51 (69.9)

Citation Format: André Pfob, Richard G. Barr, Volker Duda, Christopher Buesch, Joerg Heil, Michael Golatta. Identifying the most relevant descriptors when evaluating ultrasound images in breast cancer diagnostics: A secondary analysis of an international multicenter trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-16.

Abstract PS2-42: Identify breast cancer patients with pathologic complete response in the breast after neoadjuvant systemic treatment - an international, multicenter analysis

Purpose: Neoadjuvant systemic treatment elicits a pathologic complete response (pCR) in an average of 35% of women with breast cancer. In such cases, breast surgery may be considered overtreatment. However, imaging and vacuum-assisted biopsy (VAB) alone showed high rates of missed cancer compared to standard breast surgery. We therefore evaluated multivariate algorithms using patient, tumor, and VAB variables to accurately identify patients with breast pCR.

Methods: We developed and tested three multivariate approaches: elastic net regression, Support Vector Machines (SVM), and a deep neural network. We analyzed 452 patients, randomly partitioned into training and test samples (2:1 ratio), who participated in three prospective studies assessing the feasibility of VAB to accurately detect residual disease after neoadjuvant systemic treatment (NST). The studies were conducted at 23 sites in the United States, Germany, and South Korea. The trials enrolled women who presented with clinical stage I-III breast cancer of any biological subtype and a partial or complete response to NST confirmed by ultrasonography, mammography, or magnetic resonance imaging; all patients underwent guideline-adherent surgery. We compared the performance of the multivariate algorithms to the histopathologic evaluation of disease response in the surgical specimen (reference standard) - false-negative rate (FNR, missed residual cancer) and specificity (identification of breast pCR) were the main outcome measures. The best performing algorithm on the test set with respect to sensitivity and specificity was validated using data of an independent fourth trial. We compared the performance of the multivariate approaches to the performance of imaging and/or VAB.

Results: In the test set (n=152), elastic net regression, SVM and the neural network revealed an FNR of 1.2% (1 of 85 patients with missed residual disease). Specificity of the elastic net regression was 46.3% (31 of 67 women with surgically confirmed breast pCR identified), of the SVM 62.7% (42 of 67) and of the neural network 67.2% (45 of 67). All multivariate algorithms performed better than imaging or VAB: FNR 25.9% (22 of 85) and 16.5% (14 of 85), respectively. Subsequent external validation (n=50) of the neural network algorithm showed a false-negative rate of 0% (0 of 27) and a specificity of 65.2% (15 of 23). The area under the ROC curve for the deep neural network was 0.97 (95% CI, 0.94 to 1.00). Analyzing the coefficients of the elastic net regression (regularized beta; ß) showed that the lesion diameter on imaging after NST (ß = 0.31) and VAB results (ß = 0.49) were the most important variables in the prediction of residual tumor. Other variables were also important: age (ß = 0.18), in-situ in the initial diagnostic (not VAB) biopsy (ß = 0.11), difficulties during the pathologic evaluation of the VAB specimen (ß = 0.11); needle size 7G (ß = -0.06, as opposed to 8G, 9G, 10G), multicentricity on imaging after NST (ß = 0.06), hormone-receptor positivity (ß = 0.01), and a clip marker positioned within the (former) lesion (ß = -0.01, as opposed to a clip marker positioned &lt;5mm or &gt;5mm from the lesion

Conclusion: A multivariate algorithm can accurately select breast cancer patients without residual disease after neoadjuvant treatment. This finding may pave the way to study omission of breast surgery in these patients in the future.

Performance of multivariate algorithms compared to imaging and vacuum-assisted biopsyFalse-negative rate - value (95% CI)Specificity - value (95% CI)Negative predictive value - value (95% CI)Positive predictive value - value (95% CI)Test set (n=152)Imaging25.9% (17.0-36.5%)61.2% (48.5-72.9%)65.1% (52.0-76.7%)70.8% (60.2-79.9%)VAB16.5% (9.3-26.1%)89.6% (79.7-95.7%)81.1% (70.3-89.3%)91.0% (82.4-96.3%)Imaging + VAB5.9% (1.9-13.2%)52.2% (39.7-64.6)87.5% (73.2-95.8%)71.4% (62.1-79.6%)Elastic net regression1.2% (0.0-6.4%)46.3% (34.0-58.9%)96.9% (83.8-99.9%)70.0% (61.0%-78.0%)Support Vector Machine1.2% (0.0-6.4%)62.7% (50.0 - 74.2%)97.7% (87.7-99.9%)77.1% (68.0-84.6%)Deep Neural Network1.2% (0.0-6.4%)67.2% (54.6-78.2%)97.8% (88.5-99.9%)79.3% (70.3-86.5%)Validation set (n=50)Deep Neural Network0.0% (0.0-12.8%)65.2% (42.7-83.6%)100% (78.2-100%)77.1% (59.9-89.6%)

Citation Format: André Pfob, Chris Sidey-Gibbons, Han-Byoel Lee, Marios Konstantinos Tasoulis, Vivian Koelbel, Michael Golatta, Gaiane M. Rauch, Benjamin D. Smith, Vicente Valero, Fiona MacNeill, Wonshik Han, Walter Paul Weber, Geraldine Rauch, Henry Kuerer, Joerg Heil. Identify breast cancer patients with pathologic complete response in the breast after neoadjuvant systemic treatment - an international, multicenter analysis [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS2-42.