Neoadjuvant Chemotherapy In Breast Cancer Research Articles

Successful Breast Conservation After Neoadjuvant Chemotherapy in Lobular Breast Cancer: The Role of Menopausal Status in Response to Treatment.

While neoadjuvant chemotherapy (NAC) has been shown to increase rates of breast conservation surgery (BCS) for breast cancer, response rates in invasive lobular carcinoma (ILC) appear lower than other histologic subtypes. Some data suggest higher response rates to NAC in premenopausal versus postmenopausal patients, but this has not been studied in ILC. We evaluatedthe rates of successful BCS after NAC in patients with ILC stratified by menopausal status. We analyzed data from a single-institution cohort of 666 patients with stage I-III hormone receptor positive HER-2 negative ILC. We used t-tests, chi-squared tests, and multivariable logistic regression to investigate rates of NAC use, attempted BCS, and associations between NAC and successful BCS by menopausal status. In 217 premenopausal and 449 postmenopausal patients, NAC was used more often in the premenopausal group (15.2% vs. 9.8%, respectively, p = 0.041). Among those who attempted breast conservation (51.3% of pre- and 64.8% of postmenopausal cohorts), NAC was not associated with successful BCS in either group. Interestingly, for postmenopausal patients, receipt of NAC was significantly associated with increased rates of completion mastectomy in those who had positive margins at thefirst attempt at BCS. NAC was not associated with successful BCS in either premenopausal or postmenopausal patients with ILC. Although premenopausal patients were more likely to receive NAC, these data suggest that menopausal status may not be a good predictor of response to chemotherapy. Better predictors of response and more efficacious treatment for patients with ILC are needed.

Value of ultrasound in assessing response to neoadjuvant chemotherapy in breast cancer

To analyse the utility of ultrasound in assessing response to neoadjuvant chemotherapy (NAC) and predicting residual cancer burden (RCB) index and pathological complete response (pCR) MATERIALS AND METHODS: This was a retrospective study with 417 patients over 7 years. The difference in longest diameter (LD) of the index lesion from baseline to end, baseline to mid, and mid to end was evaluated with respect to RCB class using logistic regression and ordered logistic regression. Change in LD measurements from baseline to end, baseline to mid, and mid to end of chemotherapy as a predictor of RCB class show a negative relationship with a statistically significant association. This would suggest that a smaller change in LD measurements would be associated with an eventual higher RCB class. Change in LD measurements from baseline to end and baseline to mid chemotherapy as a predictor of pCR class show a negative relationship with a statistically significant association (p<0.05). This similarly indicates an inversely proportional relationship between changes in LD measurements and RCB class 0 for baseline to end and baseline to mid. This study has shown significance in reducing LD measurements on ultrasound as a predictor of PCR and RCB class. This adds weight to the current practice of using ultrasound at the start, mid and end of chemotherapy cycles to monitor NACT responses.

Development and External Validation of 18F-FDG PET-Based Radiomic Model for Predicting Pathologic Complete Response after Neoadjuvant Chemotherapy in Breast Cancer.

The aim of our retrospective study is to develop and externally validate an 18F-FDG PET-derived radiomics model for predicting pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients. A total of 87 breast cancer patients underwent curative surgery after NAC at Soonchunhyang University Seoul Hospital and were randomly assigned to a training cohort and an internal validation cohort. Radiomic features were extracted from pretreatment PET images. A radiomic-score model was generated using the LASSO method. A combination model incorporating significant clinical variables was constructed. These models were externally validated in a separate cohort of 28 patients from Soonchunhyang University Buscheon Hospital. The model performances were assessed using area under the receiver operating characteristic (AUC). Seven radiomic features were selected to calculate the radiomic-score. Among clinical variables, human epidermal growth factor receptor 2 status was an independent predictor of pCR. The radiomic-score model achieved good discriminability, with AUCs of 0.963, 0.731, and 0.729 for the training, internal validation, and external validation cohorts, respectively. The combination model showed improved predictive performance compared to the radiomic-score model alone, with AUCs of 0.993, 0.772, and 0.906 in three cohorts, respectively. The 18F-FDG PET-derived radiomic-based model is useful for predicting pCR after NAC in breast cancer.

The effect of ferroptosis - related proteins and histone deacetylases1 on neoadjuvant chemotherapy in breast cancer.

Ferroptosis may improve the efficacy of tumor treatment, according to recent evidences. This study is to explore value of histone deacetylases 1 (HDAC1), ATP binding cassette subfamily B member 1 and ferroptosis-related proteins as potential predictive biomarkers. Eighty-two women who received neoadjuvant chemotherapy (NAC) confirmed breast cancer was included. Immunohistochemistry staining of HDAC1, ATP binding cassette subfamily B member 1 and ferroptosis-related proteins was performed in core needle biopsy and tumor resection tissue. Univariate and multivariate logistic regression were conducted to explore the potential biomarkers for breast cancer undergoing NAC. There was a weak positive correlation of HDAC1 level before and after NAC with imaging outcome (R = 0.390, P < .001). The expression of HDAC1 and glutathione peroxidase 4 before NAC was an independent predictor of imaging efficacy (OR = 7.633, CI 1.831-31.821, P < .001; OR = 0.700, CI 0.505-0.971, P < .05, respectively). HDAC1 and Glutathione peroxidase 4 may act as a new predictive biomarker for NAC in breast cancer. And personalized treatment can be provided based on them.

Neoadjuvant chemotherapy response, disease-free survival, and overall survival of breast cancer in a single institution

BackgroundBreast cancer is the most common malignancy among women worldwide. Previous studies have shown factors influencing breast cancer patients' survival, including histopathological grading, stage, histopathological type, hormone receptors, and the number of mitotic images. This study aimed to determine the survival rate in breast cancer patients based on neoadjuvant chemotherapy (NAC) response and regimen. MethodsThis was an observational analytic study with a retrospective design. The population was breast cancer patients at our institution who had undergone NAC. Kaplan–Meier analysis using the log-rank method was used to determine the level of survivability (overall survival [OS] and disease-free survival [DFS]) of patients based on chemotherapy response and regimen. ResultsThe NAC overall response rate of breast cancer patients was 93.17 %, whereas the non-response rate was 6.83 %. Significant differences existed in the DFS of patients by chemotherapy response (p = 0.010). Patients with a complete response had a mean survival of 71.37 ± 2.92 months, those with progressive disease had a mean survival of 64.80 ± 15.58 months, and overall patients had a mean survival of 68.56 ± 10.452 months. Patients with a complete response had a mean recurrence time of 69.54 ± 7.48 months; this was 57.53 ± 19.06 months in those with progressive disease, for an overall time of 65.41 ± 13.81 months. No significant difference existed between the NAC regimens in OS and DFS (p = 0.901 and p = 0.798, respectively). ConclusionGenerally, the response to NAC in breast cancer was very good. The DFS rates were significantly different from the chemotherapy response but not from the NAC regimen.

Multiparametric Contrast-Enhanced Ultrasound in Early Prediction of Response to Neoadjuvant Chemotherapy and Recurrence-Free Survival in Breast Cancer.

We aimed to explore the value of contrast-enhanced ultrasound (CEUS) in early prediction of pathologic complete response (pCR) and recurrence-free survival (RFS) in locally advanced breast cancer (LABC) patients treated with neoadjuvant chemotherapy (NAC). LABC patients who underwent CEUS before and during NAC from March 2014 to October 2018 were included and assessed. Logistic regression analysis and the Cox proportional hazards model were used to identify independent variables associated with pCR and RFS. Among 122 women, 44 underwent pCR. Molecular subtype, peak intensity (PEAK) and change in diameter were independent predictors of pCR after one cycle of NAC (area under the receiver operating characteristic curve [AUC], 0.81; 95% CI: 0.73, 0.88); Molecular subtype, PEAK and change in time to peak (TTP) were independently associated with pCR after two cycles of NAC (AUC, 0.85; 95% CI: 0.77, 0.91). A higher clinical T (hazard ratio [HR] = 4.75; 95% CI: 1.75, 12.87; p = 0.002) and N stages (HR = 3.39; 95% CI: 1.25, 9.19; p = 0.02) and a longer TTP (HR = 1.06; 95% CI: 1.01, 1.11; p = 0.02) at pre-NAC CEUS were independently associated with poorer RFS. CEUS can be used as a technique to predict pCR and RFS early in LABC patients treated with NAC.

Radiomics of contrast-enhanced spectral mammography for prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer.

Neoadjuvant chemotherapy (NAC) has been regarded as one of the standard treatments for patients with locally advanced breast cancer. No previous study has investigated the feasibility of using a contrast-enhanced spectral mammography (CESM)-based radiomics nomogram to predict pathological complete response (pCR) after NAC. To develop and validate a CESM-based radiomics nomogram to predict pCR after NAC in breast cancer. A total of 118 patients were enrolled, which are divided into a training dataset including 82 patients (with 21 pCR and 61 non-pCR) and a testing dataset of 36 patients (with 9 pCR and 27 non-pCR). The tumor regions of interest (ROIs) were manually segmented by two radiologists on the low-energy and recombined images and radiomics features were extracted. Intraclass correlation coefficients (ICCs) were used to assess the intra- and inter-observer agreements of ROI features extraction. In the training set, the variance threshold, SelectKBest method, and least absolute shrinkage and selection operator regression were used to select the optimal radiomics features. Radiomics signature was calculated through a linear combination of selected features. A radiomics nomogram containing radiomics signature score (Rad-score) and clinical risk factors was developed. The receiver operating characteristic (ROC) curve and calibration curve were used to evaluate prediction performance of the radiomics nomogram, and decision curve analysis (DCA) was used to evaluate the clinical usefulness of the radiomics nomogram. The intra- and inter- observer ICCs were 0.769-0.815 and 0.786-0.853, respectively. Thirteen radiomics features were selected to calculate Rad-score. The radiomics nomogram containing Rad-score and clinical risk factor showed an encouraging calibration and discrimination performance with area under the ROC curves of 0.906 (95% confidence interval (CI): 0.840-0.966) in the training dataset and 0.790 (95% CI: 0.554-0.952) in the test dataset. The CESM-based radiomics nomogram had good prediction performance for pCR after NAC in breast cancer; therefore, it has a good clinical application prospect.

MRI-based Quantification of Intratumoral Heterogeneity for Predicting Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer.

Background Breast cancer is highly heterogeneous, resulting in different treatment responses to neoadjuvant chemotherapy (NAC) among patients. A noninvasive quantitative measure of intratumoral heterogeneity (ITH) may be valuable for predicting treatment response. Purpose To develop a quantitative measure of ITH on pretreatment MRI scans and test its performance for predicting pathologic complete response (pCR) after NAC in patients with breast cancer. Materials and Methods Pretreatment MRI scans were retrospectively acquired in patients with breast cancer who received NAC followed by surgery at multiple centers from January 2000 to September 2020. Conventional radiomics (hereafter, C-radiomics) and intratumoral ecological diversity features were extracted from the MRI scans, and output probabilities of imaging-based decision tree models were used to generate a C-radiomics score and ITH index. Multivariable logistic regression analysis was used to identify variables associated with pCR, and significant variables, including clinicopathologic variables, C-radiomics score, and ITH index, were combined into a predictive model for which performance was assessed using the area under the receiver operating characteristic curve (AUC). Results The training data set was comprised of 335 patients (median age, 48 years [IQR, 42-54 years]) from centers A and B, and 590, 280, and 384 patients (median age, 48 years [IQR, 41-55 years]) were included in the three external test data sets. Molecular subtype (odds ratio [OR] range, 4.76-8.39 [95% CI: 1.79, 24.21]; all P < .01), ITH index (OR, 30.05 [95% CI: 8.43, 122.64]; P < .001), and C-radiomics score (OR, 29.90 [95% CI: 12.04, 81.70]; P < .001) were independently associated with the odds of achieving pCR. The combined model showed good performance for predicting pCR to NAC in the training data set (AUC, 0.90) and external test data sets (AUC range, 0.83-0.87). Conclusion A model that combined an index created from pretreatment MRI-based imaging features quantitating ITH, C-radiomics score, and clinicopathologic variables showed good performance for predicting pCR to NAC in patients with breast cancer. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Rauch in this issue.

EVALUATION OF THE EFFECTIVENESS OF NEOADJUVANT CHEMOTHERAPY IN BREAST CANCER

Relevance: Breast cancer is the most common cancer among women. Modern treatment of locally advanced breast cancer requires a multidisciplinary approach, including local treatment: surgical and radiotherapy, systemic treatment, and a wide range of medications. The importance of systemic therapy is to improve relapse-free survival based on the control of micrometastases with the potential to spread throughout the body.&#x0D; Systemic therapy for operable breast cancer includes adjuvant therapy and neoadjuvant therapy. Hormone therapy, chemotherapy, and targeted therapy represent systemic therapy, which can be prescribed individually or in combination.&#x0D; For the most effective breast cancer treatment, tumors are classified into subtypes depending on the expression of biological markers. The presence of expression of the estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and the rate at which tumor cells divide are determined by determining the Ki67.&#x0D; It is known that neoadjuvant chemotherapy (NCT) has clinical significance in locally advanced and inoperable breast cancer. NCT increases the frequency of organ-preserving operations and the overall survival rate when a complete pathomorphological regression of the tumor (pCR) is achieved.&#x0D; The study aimed to conduct a literature review of previously published publications on the effectiveness and expediency of neoadjuvant chemotherapy for breast cancer.&#x0D; Methods: The search and analysis of scientific publications were carried out in the databases Web of Science, Pubmed, and Scopus for ten years, from 2013 to 2023. According to the search, about 3000 articles were found, and 39 sources were left during the selection according to the inclusion and exclusion criteria&#x0D; Results: Efficiency of NСT depending on different immunophenotypes in breast cancer patients was established. Tumor response was assessed according to RECIST criteria. A complete pathological response was observed more often in more aggressive subtypes of breast cancer – Her2-positive and triple-negative cancer. The relationship between pCR and long-term outcomes – OS and DFS have also been established.&#x0D; Conclusion: Neoadjuvant chemotherapy is a systemic treatment of breast cancer, the main purpose of which is to reduce the size of the tumor for the possibility of performing organ-preserving surgery, as well as to increase the overall and relapse-free survival rates. NCT allows for evaluating the effectiveness of therapy in vivo and using alternative treatment regimens without tu-mor response to the therapy.

EVALUATION OF THE EFFECTIVENESS OF NEOADJUVANT CHEMOTHERAPY IN BREAST CANCER

Relevance: Breast cancer is the most common cancer among women. Modern treatment of locally advanced breast cancer requires a multidisciplinary approach, including local treatment: surgical and radiotherapy, systemic treatment, and a wide range of medications. The importance of systemic therapy is to improve relapse-free survival based on the control of micrometastases with the potential to spread throughout the body.&#x0D; Systemic therapy for operable breast cancer includes adjuvant therapy and neoadjuvant therapy. Hormone therapy, chemotherapy, and targeted therapy represent systemic therapy, which can be prescribed individually or in combination.&#x0D; For the most effective breast cancer treatment, tumors are classified into subtypes depending on the expression of biological markers. The presence of expression of the estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and the rate at which tumor cells divide are determined by determining the Ki67.&#x0D; It is known that neoadjuvant chemotherapy (NCT) has clinical significance in locally advanced and inoperable breast cancer. NCT increases the frequency of organ-preserving operations and the overall survival rate when a complete pathomorphological regression of the tumor (pCR) is achieved.&#x0D; The study aimed to conduct a literature review of previously published publications on the effectiveness and expediency of neoadjuvant chemotherapy for breast cancer.&#x0D; Methods: The search and analysis of scientific publications were carried out in the databases Web of Science, Pubmed, and Scopus for ten years, from 2013 to 2023. According to the search, about 3000 articles were found, and 39 sources were left during the selection according to the inclusion and exclusion criteria&#x0D; Results: Efficiency of NСT depending on different immunophenotypes in breast cancer patients was established. Tumor response was assessed according to RECIST criteria. A complete pathological response was observed more often in more aggressive subtypes of breast cancer – Her2-positive and triple-negative cancer. The relationship between pCR and long-term outcomes – OS and DFS have also been established.&#x0D; Conclusion: Neoadjuvant chemotherapy is a systemic treatment of breast cancer, the main purpose of which is to reduce the size of the tumor for the possibility of performing organ-preserving surgery, as well as to increase the overall and relapse-free survival rates. NCT allows for evaluating the effectiveness of therapy in vivo and using alternative treatment regimens without tu-mor response to the therapy.

Ultrasound features combined with tumor-infiltrating lymphocytes for prediction of pathological response to neoadjuvant chemotherapy in breast cancer.

Neoadjuvant chemotherapy (NAC) plays an important role in the treatment and prognosis of breast cancer. Theearly identification of patients who can truly benefit from preoperative NAC is crucial in clinical practice. The purpose of thisstudy was to explore whether the ultrasound features and clinical characteristics combined with tumor-infiltrating lymphocyte(TIL) levels can improve the performance of predicting NAC efficacy in breast cancer patients. Inthis retrospective study, 202 invasive breast cancer patients who underwent NAC followed by surgery were included. Thebaseline ultrasound features were reviewed by two radiologists. Miller-Payne Grading (MPG) was used to assess pathologicalresponse, and MPG 4-5 was defined as major histologic responders (MHR). Multivariable logistic regression analysis wasused to evaluate independent predictors for MHR and build the prediction models. The receiver operating characteristic (ROC)curve was used to evaluate the performance of the models. Of the 202 patients, 104 patients achieved MHR and 98patients achieved non-MHR. Multivariate logistic regression analysis showed the US size (p=0.042), molecular subtypes(p=0.001), TIL levels (p<0.001), shape (p=0.030), and posterior features (p=0.018) were independent predictors for MHR.The model combined the US features, clinical characteristics, and TIL levels had a better performance with an area under thecurve (AUC) of 0.811, a sensitivity of 0.663, and a specificity of 0.847. The model combined US features, clinicalcharacteristics, and TIL levels had a better performance in predicting pathological response to NAC in breast cancer.

The Immunomodulatory Effects of Dexamethasone on Neoadjuvant Chemotherapy for Triple-Negative Breast Cancer.

The immunomodulatory impact of corticosteroids and concurrent chemotherapy is poorly understood within triple-negative breast cancer (TNBC). On a biochemical level, steroids have been linked to the signaling of chemotherapy-resistant pathways. However, on a clinical level, steroids play an essential role in chemotherapy tolerance through the prevention of chemotherapy-induced nausea and vomiting (CINV) and hypersensitivity reactions. Given these conflicting roles, we wanted to evaluate this interplay more rigorously in the context of early-stage TNBC. We performed a retrospective analysis of patients with operable TNBC who received neoadjuvant chemotherapy (NAC) between January 2012 and November 2018, with the primary goal of examining the dose-dependent relationship between pathological complete response (pCR) rates and corticosteroid use. Secondary endpoints included the impact of steroid dosing on overall survival (OS) and recurrence-free survival (RFS), along with a breakdown in pCR rates based on steroid doses provided during each chemotherapy phase. Further adjusted analyses were performed based on patient age, diabetic status, and anatomical stage. Finally, we explored the relationship between tumor-infiltrating lymphocytes (TILs) seen on tissue samples at baseline and dexamethasone doses in terms of pCR rates. In total, of the 174 patients screened within this study period, 116 met full eligibility criteria. Of these eligible patients, all were female, with a median age of 51.5years (27.0 to 74.0) and a mean body mass index (BMI) of 29.7 [standard deviation (SD) 7.04]. The majority were nondiabetic (80.2%). For cancer stage, 69.8% (n = 81) had stage 2 breast cancer. We found no statistically significant association between pCR rates and dexamethasone use, both in terms of the total dose (p = 0.55) and mean dose per NAC cycle (p = 0.74). Similarly, no difference was noted when adjusting for diabetic status, metformin use, or age at diagnosis, regardless of the total steroid dose provided (p = 0.72) or mean dose per cycle (p = 0.49). No meaningful changes to pCR rate were seen with higher mean or higher total steroid doses during the paclitaxel (T) phase (adjusted p = 0.16 and p = 0.76, respectively) or doxorubicin and cyclophosphamide (AC) phase (adjusted p = 0.83 and p = 0.77, respectively). Furthermore, we found no clinically significant association between dexamethasone dose and either RFS (p = 0.45) or OS (p = 0.89). Of the 56 patients who had available pre-treatment biopsy tissue samples, 27 achieved pCR, with higher TILs at baseline being associated with higher pCR rates, regardless of the mean dexamethasone dose used. Our findings demonstrate that dexamethasone has no clinically significant impact on pCR, RFS, or OS when given concurrently with NAC in patients with curative TNBC, regardless of diabetic status.

Neoadjuvant Chemotherapy for Breast Cancer: Revisiting the Lymph Node Ratio as a Prognostic Factor

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Can breast MRI predict pathologic response following neoadjuvant chemotherapy for breast cancer? A retrospective cohort study

PurposeFor patients treated with neoadjuvant chemotherapy (NAC) for breast cancer, it is standard of care to perform pre- and post-NAC imaging to evaluate response to therapy prior to surgery. In this study we assess outcome metrics of magnetic resonance imaging (MRI) following NAC. MethodsWe conducted a retrospective analysis of patients with invasive breast cancer who underwent a breast MRI before and after NAC between 2016 and 2021 at a single, multisite academic institution. All breast MRI studies were characterized as either radiologic complete response (rCR) or non-rCR. Corresponding surgical pathology reports were reviewed and categorized as pathologic complete response (pCR) or non-pCR. We defined a positive test as having residual enhancement on MRI (non-rCR) and a positive outcome as having residual disease on final surgical pathology (non-pCR). ResultsThere were 225 patients included in the study (mean age 52 ± 12 years). Breast cancer receptor distribution was HR+/HER2− (n = 71, 32%), HR+/HER2+ (n = 51, 23%), HR−/HER2− (n = 72, 32%), and HR−/HER2+ (n = 31, 14%). In total, 78 (35%) had rCR and 77 (34%) had pCR; 43 (19%) had both rCR and pCR. The overall accuracy rate was 69% (156/225), sensitivity 76% (113/148), specificity 56% (43/77), positive predictive value 77% (113/147), and negative predictive value 55% (43/78). The PPV was significantly associated with receptor status (p = 0.004). No patient or imaging characteristics were associated with sensitivity. ConclusionBreast MRI only moderately predicts pathologic response for invasive breast cancer treated with NAC (overall accuracy 69%). PPV is significantly associated with receptor status.

Response in axillary lymph nodes to neoadjuvant chemotherapy for breast cancers: correlation with breast response, pathologic features, and accuracy of radioactive seed localization

ObjectivesThis study examined the accuracy of radioactive seed localization (RSL) of lymph nodes (LNs) following neoadjuvant chemotherapy (NAC) for invasive breast carcinoma, recorded pathologic features of LNs following NAC, evaluated concordance of response between breast and LNs, and identified clinicopathologic factors associated with higher risk of residual lymph node involvement.MethodsClinical records, imaging, and pathology reports and slides were retrospectively reviewed for 174 breast cancer patients who received NAC. Chi-square and Fisher’s exact tests were used to compare differences in risk of residual lymph node disease.ResultsRetrieval of biopsied pre-therapy positive LN was confirmed in 86/93 (88%) cases overall, and in 75/77 (97%) of cases utilizing RSL. Biopsy clip site was the best pathologic feature to confirm retrieval of a biopsied lymph node. Pre-therapy clinical N stage > 0, positive pre-therapy lymph node biopsy, estrogen and progesterone receptor positivity, Ki67 < 50%, HR + /HER2− tumors, and residual breast disease had higher likelihood of residual lymph node disease after NAC (p < 0.001).ConclusionsRSL-guided LN excision improves retrieval of previously biopsied LNs following NAC. The pathologist can use histologic features to confirm retrieval of targeted LNs, and tumor characteristics can be used to predict a higher risk of residual LN involvement.

A Survey of Practice Patterns for Clinical Nodal Staging Prior to Neoadjuvant Chemotherapy in Breast Cancer.

The importance of clinical staging in breast cancer has increased owing to the wide use of neoadjuvant systemic therapy (NST). This study aimed to investigate the current practice patterns regarding clinical nodal staging in breast cancer in real-world settings. A web-based survey was administered to board-certified oncologists in Korea, including breast surgical, medical, and radiation oncologists, from January to April 2022. The survey included 19 general questions and 4 case-based questions. In total, 122 oncologists (45 radiation, 44 surgical, and 33 medical oncologists) completed the survey. Among them, 108 (88%) responded that clinical staging before NST was primarily performed by breast surgeons. All the respondents referred to imaging studies during nodal staging. Overall, 64 (52.5%) responders determined the stage strictly based on the radiology reports, whereas 58 (47.5%) made their own decision while noting radiology reports. Of those who made their own decisions, 88% referred to the number or size of the suspicious node. Of the 75 respondents involved in prescribing regimens for neoadjuvant chemotherapy, 58 (77.3%) responded that the reimbursement regulations in the selection of NST regimens affected nodal staging in clinical practice. In the case-based questions, high variability was observed among the clinicians in the same cases. Diverse assessments by specialists owing to the lack of a clear, harmonized staging system for the clinical nodal staging of breast cancer can lead to diverse practice patterns. Thus, practical, harmonized, and objective methods for clinical nodal staging and for the outcomes of post-NST response are warranted for appropriate treatment decisions and accurate outcome evaluation.

Deep Learning Model Based on Dual-Modal Ultrasound and Molecular Data for Predicting Response to Neoadjuvant Chemotherapy in Breast Cancer

To carry out radiomics analysis/deep convolutional neural network (CNN) based on B-mode ultrasound (BUS) and shear wave elastography (SWE) to predict response to neoadjuvant chemotherapy (NAC) in breast cancer patients. In this prospective study, 255 breast cancer patients who received NAC between September 2016 and December 2021 were included. Radiomics models were designed using a support vector machine classifier based on US images obtained before treatment, including BUS and SWE. And CNN models also were developed using ResNet architecture. The final predictive model was developed by combining the dual-modal US and independently associated clinicopathologic characteristics. The predictive performances of the models were assessed with five-fold cross-validation. Pretreatment SWE performed better than BUS in predicting the response to NAC for breast cancer for both the CNN and radiomics models (P<0.001). The predictive results of the CNN models were significantly better than the radiomics models, with AUCs of 0.72 versus0.69 for BUS and 0.80 versus 0.77 for SWE, respectively (P=0.003). The CNN model based on the dual-modal US and molecular data exhibited outstanding performance in predicting NAC response, with an accuracy of 83.60%±2.63%, a sensitivity of 87.76%±6.44%, and a specificity of 77.45%±4.38%. The pretreatment CNN model based on the dual-modal US and molecular data achieved excellent performance for predicting the response to chemotherapy in breast cancer. Therefore, this model has the potential to serve as a non-invasive objective biomarker to predict NAC response and aid clinicians with individual treatments.

Comparing time to treatment for neoadjuvant chemotherapy for breast cancer across the urban-rural continuum.

e12619 Background: Time-to-treatment is a quality measure in breast cancer care that can impact breast cancer survival as delayed treatment can increase mortality. This study aims to determine whether differences exist in time-to-treatment for breast cancer patients receiving neoadjuvant chemotherapy (NAC) across the urban-rural continuum. Methods: The National Cancer Database (NCDB) was queried for women with a diagnosis of breast cancer between 1 January 2004 – 31 December 2019. Patients who fit criteria for NAC consideration according to NCCN guidelines were included (inflammatory breast cancer, HER2 positive with tumor stage &gt;T1c, triple negative with tumor stage &gt;T1c, HER2 positive or triple negative lymph node positive, and stage III estrogen receptor (ER) positive). Analysis was stratified according to histopathologic subtype and geographic location as defined by the NCDB. Differences were analyzed using χ2 tests. Results: For patients with NAC-eligible breast cancer, there was no statistically significant difference in terms of days until treatment for each histopathologic subtype across the urban-rural continuum. The distance to treatment facility increases the further away patients are from a large metropolitan area, with individuals located in an urban area that is not adjacent to a metro area traveling the furthest distance (12.7mi large metro, 18.1mi small metro, 36.7mi urban adjacent to metro, 62.6mi urban not adjacent to metro, 56.4mi rural). No significant difference in distance traveled was observed between tumor subtype group. Conclusions: While previous studies have determined that rural patients receive NAC at lower rates than those in large urban areas, this study shows that time to treatment and distance traveled is similar across rural urban continuum and different histopathologic subtypes. Future studies are needed to determine why patients receive NAC at lower rates in rural areas.

Use of tumoral LDH to predict residual tumor burden after neoadjuvant chemotherapy in breast cancer.

e12566 Background: The Residual Cancer Burden (RCB) score has been validated as an independent prognostic factor in all subtype of breast cancer after neoadjuvant chemotherapy (NAC). Early prediction of NAC response enable better stratification for selecting chemotherapy. Glucose metabolism in cancer cells produces various glycolytic metabolites which are related to breast cancer prognosis. In this study, we evaluated the association of glucose transporters and enzymes involved in glucose metabolism with clinic-pathological factors for early prediction of NAC response. Methods: RCB scores were retrospectively evaluated from patients with stage I-III breast cancer treated with neoadjuvant chemotherapy. We selected 7 target transporters and enzymes [GLUT1, hexokinase 2 (HK2), lactate dehydrogenase (LDH), MCT1, MCT4, IGF1RA, and IGF1RB] involved in glucose metabolism and evaluated in relationships with pretreatment clinical/pathological characteristics and treatment outcomes including RCB. Results: 236 breast cancer patients who underwent NAC followed by surgery between 2010 and 2016 in Kyungpook National University Chilgok Hospital were included. Among them, 145 (61.4%), 44 (18.6%), and 47 (19.9%) were luminal, HER2-enriched, and TNBC subtypes. RCB 0 was determined 50 (21.2%), 35 (14.8%) RCB I, 91 (38.6%) RCB II and 60 (25.4%) RCB III. After a median follow-up of 98 months, 60 (25.4%) relapses, 43 (18.2%) distant relapses, and 34 (14.4%) deaths were observed. RCB score was significantly associated with disease specific survival (DSS) and overall survival (OS). RCB III were significantly increased risk of relapse (HR=13.517, CI [1.809-101.010], P&lt;0.001). The tumoral expression rates of the target molecules were 76.0, 31.1, 42.1, 54.9, 67.9, 78.4, and 49.8% for GLUT1, HK2, LDH, MCT1, MCT4, IGF1RA, and IGF1RB, respectively. Among them, LDH was significantly associated with RCB III (OR=4.533, P=0.014) and worse disease specific survival (HR=2.29 P=0.019). Conclusions: Tumoral expression of LDH could be considered as an independent biomarker in predicting high risk of relapse (RBC III) and survival in all subtype of breast cancer.

Retrospective analysis of Ki-67 as a predictive and prognostic marker for pathological complete response to neoadjuvant chemotherapy in breast cancer.

e12610 Background: According to GLOBOCAN 2020, breast cancer with an estimated 2.3 million new cases (11.7%) is the world's most common cancer. Ki-67 has been established as a proliferation marker in breast cancer. However, there are still some conflicting results on the clinical significance of Ki-67 as predictive and prognostic marker for effectiveness of neoadjuvant chemotherapy. In this retrospective study, Ki-67 is evaluated as predictive and prognostic marker for effectiveness of neoadjuvant chemotherapy (NACT). Methods: Study design: A retrospective observational single institutional study. Place of study: Tata memorial Centre - BBCI, Guwahati. Study period and duration: November 2018 to October 2021 (3 years). Study population: All female patients with biopsy-proven breast cancer. Inclusion criteria: All female patients with the diagnosis of breast cancer, who received NACT. Exclusion criteria: Patients who did not receive NACT, patients who did not undergo surgery after NACT, patients who lost to follow-up after chemotherapy, and patients whose pre-chemo Ki- 67 was not available. Sample size: 2272 patients were reviewed, out of which 127 patients were included in this study. Assuming 30% of patients have a complete response, allowing an error of 8% on these, 127 samples were required for the study at a 95% confidence interval. ROC (receiver operating characteristic) curve analysis was done to know the optimal cut-off value for the Ki-67 labeling index (LI) to discriminate response to treatment. Chi-square test was applied to know the relation between receptor status (ER, PR, HER2neu) and pCR. The pathological response was assessed in reference to Miller-Payne score. Results: Age &lt;40years (22.83%), &gt;40years (77.17%); commonest histology, IDC (95.28%); grade 2 (59.84%), grade 3 (40.16%); ER negative with pCR, 88.2%, p &lt; 0.05; PR negative with pCR, 88.2%, p &lt; 0.05; HER2 positive (treated with trastuzumab) with pCR, 55.8%, p &lt; 0.05; triple negative with pCR, 41.2%, p &lt; 0.05; chemo regimen, 4AC-&gt;4T (37%), 4AC-&gt;4TH (32.3%); pCR, 26.77% (n=34/127); and Ki-67 LI of 27%, sensitivity 95.4%, specificity 21%. Conclusions: Neoadjuvant chemotherapy is more efficient in tumors presenting with at least 32% Ki-67 expression. A high sensitivity of 95.4% and low specificity of 21% indicate Ki-67 LI is not a reliable predictive and prognostic marker. Other markers like ER, PR, and HER-2 influenced the disease outcome significantly. In our study, ‘PR negative’, ‘ER negative’, ‘HER-2 positive treated with trastuzumab’ and ‘triple negative’ were significantly associated with pCR (p &lt; 0.05). This indicates that pCR rate depends on ER/PR/Triple negativity rates or the rate of HER-2 positivity treated with trastuzumab. Ki67 by itself is poor marker. However, when combined with ER/PR/HER2, it can become predictive of responses at cut off 27% in our study to differentiate the subgroups.