Magee Equation 3 predicts pathologic response to neoadjuvant systemic chemotherapy in estrogen receptor positive, HER2 negative/equivocal breast tumors

Correlation of MammaPrint to Histopathologic Variables and Comparison to Magee Equations in Adjuvant and Neoadjuvant Cohorts of Estrogen-Receptor Positive HER2-Negative Breast Carcinoma

MammaPrint (MP) is a multigene assay utilized for prognostic and predictive use in early stage ER+/HER2-negative breast cancer (BC). There is limited data on MP correlation to histopathologic variables, including multivariable model Magee Equations (MEs). We compared pathologic variables to MP on 365 ER+/HER2-negative BCs in the adjuvant setting. Further, we analyzed MP and ME results in 26 core biopsy-proven ER+/HER2-negative BCs subjected to neoadjuvant chemotherapy (NACT). Post-NACT response was assessed by residual cancer burden (RCB) score. In the adjuvant cohort (n=365), high-risk (HR) MP correlated with high Nottingham score, low progesterone receptor H-score, ductal morphology, high Ki-67 index, and high ME score. In the neoadjuvant cohort (n=26), 24 were MP-HR and 2 were MP low-risk (MP-LR). The 2 MP-LR cases correlated with average ME scores of ≤25 and showed RCB scores of 2 or 3. Of the 24 MP-HR, 2 showed RCB-0 or RCB-1. Average ME>25 was seen in both of these cases and 7 others corresponding to an RCB-0 and RCB-1 rate of 22% (2 of 9) with ME>25 compared with 8% (2 of 24) with MP-HR. Lack of significant benefit from NACT (RCB-2 or RCB-3) was accurately predicted by average ME≤25 in 17 of 26 cases (65%) compared with only 2 of 26 cases (8%) with MP-LR. MP correlates with aggressive histopathologic features. While both MP and ME identified cases with robust chemotherapeutic response, MP overpredicted cases that would benefit. Therefore, MEs may more accurately predict response to NACT.

Navigating Endocrine Sensitivity Assessment in Nonmetastatic Breast Cancer Through Early On-Treatment Ki67 Understanding

In the landscape of breast cancer management, precise assessment of endocrine sensitivity significantly influences therapeutic strategies. The utilization of Ki67, an immunohistochemical marker of tumor proliferation, in tumor rebiopsy holds paramount importance in unraveling breast cancer's response to endocrine therapy. This narrative review aims to elucidate the pivotal role of Ki67 in endocrine sensitivity assessment. We explore the nuanced process of Ki67 evaluation, its timing, and its implications for clinical outcomes in breast cancer patients. From a clinical perspective to pathological response and risk of recurrence, we navigate the spectrum of Ki67's impact. By delving into these facets, we underscore Ki67's potential to guide personalized treatment strategies, shedding light on the intricate interplay between endocrine therapy and clinical outcomes in breast cancer patients.

The Clinical Significance of the Magee Equations in Breast Cancer Prognostication

The landscape of breast cancer management has been revolutionized by advancements in molecular diagnostics, yet accessibility and cost remain significant barriers for many patients. Limited-resource settings often face significant challenges in accessing expensive molecular tests, which can impact timely diagnosis and treatment decisions. The Magee equations present a practical, cost-effective solution that can bridge this gap, ensuring that patients, regardless of their financial or geographic limitations, receive appropriate and timely treatment. Originally developed at the University of Pittsburgh Medical Center, these equations offer a reliable alternative for estimating recurrence scores without the prohibitive costs associated with genomic assays.

Prognostic Implications of Magee Equation 3 and Residual Cancer Burden in Patients Receiving Neoadjuvant Chemotherapy for Hormone Receptor-Positive HER2-Negative Breast Cancer

Breast cancer (BC) presents significant molecular heterogeneity, complicating prognosis and treatment strategies. Although molecular testing enhances our understanding of BC, high costs can limit accessibility in certain health care settings. This retrospective cohort study evaluates the prognostic value of Magee equation 3 (ME3) and residual cancer burden (RCB) in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative BC treated at the Instituto do Câncer do Estado de São Paulo from January 2011 to January 2024. We included 203 women, with a mean age of 50.2 years, diagnosed with hormone receptor-positive, human epidermal growth factor receptor 2-negative BC (stages I-III), who completed neoadjuvant chemotherapy followed by surgery. ME3 scores were categorized as low (<18), intermediate (18-25), and high (>25), whereas RCB was classified into 4 groups (0, 1, 2, or 3). Associations between ME3 and RCB categories were analyzed using χ2 and Cochran-Mantel-Haenszel tests. Overall survival (OS) and disease-free survival (DFS) were assessed using the Kaplan-Meier method with log-rank tests. Prior to neoadjuvant chemotherapy, 60.1% of patients had tumors >5 cm, 69.5% had positive lymph nodes, and 85.7% had invasive carcinoma of nonspecial type, with a mean Ki67 index of 35.5%. Analysis revealed that 22.2% of patients had ME3 >25, 39.9% had ME3 18-25, and 37.9% had ME3 <18. A significant inverse association was found between RCB and ME3 (P < .0001). At a median follow-up of 91.4 months (range: 8-157 months), significant associations were noted for OS (log-rank P = .0059) and DFS (log-rank P = .0028) with ME3 categories; patients with low ME3 showed better outcomes. In patients with RCB-3, those with ME3 <18 had a lower risk of recurrence compared with those with ME3 18-25 (hazard ratio: 4.70, 95% CI: 2.00-11.02; P = .0004) and ME3 > 25 (hazard ratio: 5.18, 95% CI: 1.85-14.15; P = .0017). Similarly, lower risks of death were observed for ME3 < 18 versus higher ME3 categories. In conclusion, ME3 significantly correlates with OS and DFS, suggesting that it may serve as a valuable alternative to molecular assays in resource-limited settings. Combining ME3 with RCB enhances individualized risk stratification, providing a more precise prognostic assessment for patients with high RCB.

Neo-adjuvant therapies for ER positive/HER2 negative breast cancers: from chemotherapy to hormonal therapy, CDK inhibitors, and beyond

INTRODUCTION

Chemotherapy has been traditionally used as neo-adjuvant therapy in breast cancer for down-staging of locally advanced disease in all sub-types. In the adjuvant setting, genomic assays have shown that a significant proportion of ER positive/HER2 negative patients do not derive benefit from the addition of chemotherapy to adjuvant endocrine therapy. An interest in hormonal treatments as neo-adjuvant therapies in ER positive/HER2 negative cancers has been borne by their documented success in the adjuvant setting. Moreover, cytotoxic chemotherapy is less effective in ER positive/HER2 negative disease compared with other breast cancer subtypes in obtaining pathologic complete responses.

AREAS COVERED

Neo-adjuvant therapies for ER positive/HER2 negative breast cancers and associated biomarkers are reviewed, using a Medline survey. A focus of discussion is the prediction of patients that are unlikely to derive extra benefit from chemotherapy and have the highest probabilities of benefiting from hormonal and other targeted therapies.

EXPERT OPINION

Predictive biomarkers of response to neo-adjuvant chemotherapy and hormonal therapies are instrumental for selecting ER positive/HER2 negative breast cancer patients for each treatment. Chemotherapy remains the standard of care for many of those patients requiring neo-adjuvant treatment, but other neo-adjuvant therapies are increasingly used.

The Magee 3 Equation Predicts Favorable Pathologic Response to Neoadjuvant Endocrine Therapy in Breast Cancer Patients

BACKGROUND

Breast cancer (BC) remains a significant health care challenge, and treatment approaches continue to evolve. Among these, neoadjuvant endocrine therapy (NET) has gained prominence, particularly for postmenopausal, hormone-receptor positive, HER2-negative (HR+/HER2-) BC patients. Despite this, a significant gap exists in identifying patients who stand to benefit from NET. The objective of this study was to assess whether Magee equations (MEs) could serve as predictors of response to NET.

METHODS

This retrospective study included adult patients with invasive BC who underwent NET followed by curative surgery. Assessment of sociodemographic, clinical, and tumor-related variables was conducted. The ME1, ME2, ME3, and ME mean were analyzed to explore their predictive role for NET response. Receiver operating characteristic (ROC) curves were employed, along with the determination of optimal cutoff points. Logistic regression models were utilized to identify the most significant predictors of pathological response.

RESULTS

Among the 75 female participants, the mean age was 69.4 years, with the majority being postmenopausal (n = 72, 96%) and having an ECOG-PS of 0/1 (n = 63, 84%). Most patients were classified as luminal A (n = 41, 54.7%). ME3 emerged as a promising predictor, boasting an AUC of 0.734, with sensitivity of 90.62% and specificity of 57.50% when the threshold was ≤ 19.97. In univariate analysis, clinical staging (p = 0.002), molecular subtype (p = 0.001), and ME3 (continuous = 0.001, original 3-tier: p = 0.013, new 2-tier: <0.001) categories exhibited significant associations with pathological response. In the multivariate model, clinical staging and new 2-tier ME3 (<20 vs. ≥20) were included as significant variables.

CONCLUSIONS

Patients with ME3 < 20 have a higher likelihood of presenting a pathological response, offering a cost-effective alternative tool to Oncotype DX. Larger future studies with a prospective design are awaited to confirm our findings.

Conventional Tools for Predicting Satisfactory Response to Neoadjuvant Chemotherapy in HR+/HER2- Breast Cancer Patients

Aim

The aim of the study was to assess the role of Magee Equation 3 (MagEq3), IHC4 score, and HER2-low status in predicting "satisfactory response (SR)" to neoadjuvant chemotherapy (NAC) in HR+/HER2- breast cancer (BC) patients.

Methods

In a retrospective study, female patients of any age with T1-4, N0-2, M0 HR+/HER2- BC who received NAC and underwent adequate locoregional surgical treatment were included. Patients were grouped according to 2 outcomes: (a) overall response to NAC in breast and axilla by using residual cancer burden (RCB) criteria and (b) axillary downstaging after NAC by using N staging. 2 cohorts for overall response were overall SR (RCB 0-1) and no SR (RCB 2-3). On the other hand, for axillary downstaging, 2 cohorts constituted from axillary SR (ypN0 and ypN0i+) and no SR (ypNmic-N3). MagEq3 and IHC4 scores were calculated from their pathological tumor slides in each patient. HER2 status was categorized as either "no" or "low." In addition, patient age, family history, tumor histology, stage at admission, and Ki-67 status were compared between cohorts according to predefined outcomes.

Results

In a total of 230 BC patients, 228 patients were included to compare according to their RCB levels. The mean age of patients with overall SR was significantly lower than those without. Patients with high Ki-67 expression, high (>30) MagEq3 score, high ICH4 quartile, and HER2-low status had significantly more overall SR. On the other hand, only patients with high Ki-67 expression had significantly more axillary SR. MagEq3 score levels, ICH4 quartiles, and HER2 status were similar between patients with axillary SR and not.

Conclusion

MagEq3 and IHC4 tools seemed to be useful to predict those HR+/HER2- BC patients who are most likely to get benefit from NAC. But, only high Ki-67 expression level significantly predicted satisfactory axillary downstaging in HR+/HER2- BC patients.

Applications of Artificial Intelligence in Breast Pathology

CONTEXT.—

Increasing implementation of whole slide imaging together with digital workflow and advances in computing capacity enable the use of artificial intelligence (AI) in pathology, including breast pathology. Breast pathologists often face a significant workload, with diagnosis complexity, tedious repetitive tasks, and semiquantitative evaluation of biomarkers. Recent advances in developing AI algorithms have provided promising approaches to meet the demand in breast pathology.

OBJECTIVE.—

To provide an updated review of AI in breast pathology. We examined the success and challenges of current and potential AI applications in diagnosing and grading breast carcinomas and other pathologic changes, detecting lymph node metastasis, quantifying breast cancer biomarkers, predicting prognosis and therapy response, and predicting potential molecular changes.

DATA SOURCES.—

We obtained data and information by searching and reviewing literature on AI in breast pathology from PubMed and based our own experience.

CONCLUSIONS.—

With the increasing application in breast pathology, AI not only assists in pathology diagnosis to improve accuracy and reduce pathologists' workload, but also provides new information in predicting prognosis and therapy response.

The Story of the Magee Equations: The Ultimate in Applied Immunohistochemistry

Magee equations (MEs) are a set of multivariable models that were developed to estimate the actual Onco type DX (ODX) recurrence score in invasive breast cancer. The equations were derived from standard histopathologic factors and semiquantitative immunohistochemical scores of routinely used biomarkers. The 3 equations use slightly different parameters but provide similar results. ME1 uses Nottingham score, tumor size, and semiquantitative results for estrogen receptor (ER), progesterone receptor, HER2, and Ki-67. ME2 is similar to ME1 but does not require Ki-67. ME3 includes only semiquantitative immunohistochemical expression levels for ER, progesterone receptor, HER2, and Ki-67. Several studies have validated the clinical usefulness of MEs in routine clinical practice. The new cut-off for ODX recurrence score, as reported in the Trial Assigning IndividuaLized Options for Treatment trial, necessitated the development of Magee Decision Algorithm (MDA). MEs, along with mitotic activity score can now be used algorithmically to safely forgo ODX testing. MDA can be used to triage cases for molecular testing and has the potential to save an estimated $300,000 per 100 clinical requests. Another potential use of MEs is in the neoadjuvant setting to appropriately select patients for chemotherapy. Both single and multi-institutional studies have shown that the rate of pathologic complete response (pCR) to neoadjuvant chemotherapy in ER+/HER2-negative patients can be predicted by ME3 scores. The estimated pCR rates are 0%, <5%, 14%, and 35 to 40% for ME3 score <18, 18 to 25, >25 to <31, and 31 or higher, respectively. This information is similar to or better than currently available molecular tests. MEs and MDA provide valuable information in a time-efficient manner and are available free of cost for anyone to use. The latter is certainly important for institutions in resource-poor settings but is also valuable for large institutions and integrated health systems.

Multigene profiles to guide the use of neoadjuvant chemotherapy for breast cancer: a Copenhagen Breast Cancer Genomics Study

Estrogen receptor (ER) and human epidermal growth factor 2 (HER2) expression guide the use of neoadjuvant chemotherapy (NACT) in patients with early breast cancer. We evaluate the independent predictive value of adding a multigene profile (CIT256 and PAM50) to immunohistochemical (IHC) profile regarding pathological complete response (pCR) and conversion of positive to negative axillary lymph node status. The cohort includes 458 patients who had genomic profiling performed as standard of care. Using logistic regression, higher pCR and node conversion rates among patients with Non-luminal subtypes are shown, and importantly the predictive value is independent of IHC profile. In patients with ER-positive and HER2-negative breast cancer an odds ratio of 9.78 (95% CI 2.60;36.8), P < 0.001 is found for pCR among CIT256 Non-luminal vs. Luminal subtypes. The results suggest a role for integrated use of up-front multigene subtyping for selection of a neoadjuvant approach in ER-positive HER2-negative breast cancer.

Development of a nomogram for predicting pathological complete response in luminal breast cancer patients following neoadjuvant chemotherapy

Background

Given the low chance of response to neoadjuvant chemotherapy (NACT) in luminal breast cancer (LBC), the identification of predictive factors of pathological complete response (pCR) represents a challenge. A multicenter retrospective analysis was performed to develop and validate a predictive nomogram for pCR, based on pre-treatment clinicopathological features.

Methods

Clinicopathological data from stage I-III LBC patients undergone NACT and surgery were retrospectively collected. Descriptive statistics was adopted. A multivariate model was used to identify independent predictors of pCR. The obtained log-odds ratios (ORs) were adopted to derive weighting factors for the predictive nomogram. The receiver operating characteristic analysis was applied to determine the nomogram accuracy. The model was internally and externally validated.

Results

In the training set, data from 539 patients were gathered: pCR rate was 11.3% [95% confidence interval (CI): 8.6-13.9] (luminal A-like: 5.3%, 95% CI: 1.5-9.1, and luminal B-like: 13.1%, 95% CI: 9.8-13.4). The optimal Ki67 cutoff to predict pCR was 44% (area under the curve (AUC): 0.69; p < 0.001). Clinical stage I-II (OR: 3.67, 95% CI: 1.75-7.71, p = 0.001), Ki67 ⩾44% (OR: 3.00, 95% CI: 1.59-5.65, p = 0.001), and progesterone receptor (PR) <1% (OR: 2.49, 95% CI: 1.15-5.38, p = 0.019) were independent predictors of pCR, with high replication rates at internal validation (100%, 98%, and 87%, respectively). According to the nomogram, the probability of pCR ranged from 3.4% for clinical stage III, PR > 1%, and Ki67 <44% to 53.3% for clinical stage I-II, PR < 1%, and Ki67 ⩾44% (accuracy: AUC, 0.73; p < 0.0001). In the validation set (248 patients), the predictive performance of the model was confirmed (AUC: 0.7; p < 0.0001).

Conclusion

The combination of commonly available clinicopathological pre-NACT factors allows to develop a nomogram which appears to reliably predict pCR in LBC.

Tumor-Infiltrating Lymphocytes Improve Magee Equation-Based Prediction of Pathologic Complete Response in HR-Positive/HER2-Negative Breast Cancer

OBJECTIVES

Magee equation 3 (ME3) is predictive of the pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer but with insufficient predictive performance. This study was designed to improve predictive ability by combining ME3 with additional clinicopathologic markers.

METHODS

We retrospectively enrolled 460 patients with HR-positive/HER2-negative breast cancer from 2 centers. We obtained baseline characteristics, the ME3 score, and the number of stromal tumor-infiltrating lymphocytes (sTILs). After performing a logistic regression analysis, a predictive nomogram was built and validated externally.

RESULTS

ME3 score (adjusted odds ratio [OR], 1.14 [95% confidence interval (CI), 1.10-1.17]; P < .001) and TILs (adjusted OR, 5.21 [95% CI, 3.33-8.14]; P < .001) were independently correlated with pCR. The nomogram (named ME3+) was established using ME3 and sTILs, and it demonstrated an area under the curve of 0.816 and 0.862 in internal and external validation, respectively, outperforming the ME3 score alone. sTILs and ME3 scores were also found to be positively correlated across the entire cohort (P < .001).

CONCLUSIONS

The combination of sTILs and ME3 score potentially shows better performance for predicting pCR than ME3 alone. Larger validations are required for widespread application of ME3+ nomogram in NAC settings for HR-positive/HER2-negative breast cancer.

Personalising therapy for early-stage oestrogen receptor-positive breast cancer in older women

Age is one of the most important risk factors for the development of breast cancer. Nearly a third of all breast cancer cases occur in older women (aged ≥70 years), with most cases being oestrogen receptor-positive (ER+). Such tumours are often indolent and unlikely to be the ultimate cause of death for older women, particularly when considering other comorbidities. This Review focuses on unique clinical considerations for screening, detection, and treatment regimens for older women who develop ER+ breast cancers-specifically, we focus on recent trends for de-implementation of screening, staging, surgery, and adjuvant therapies along the continuum of care. Additionally, we also review emerging basic and translational research that will further uncover the unique underlying biology of these tumours, which develop in the context of systemic age-related inflammation and changing hormone profiles. With prevailing trends of clinical de-implementation, new insights into mechanistic biology might provide an opportunity for precision medicine approaches to treat patients with well tolerated, low-toxicity agents to extend patients' lives with a higher quality of life, prevent tumour recurrences, and reduce cancer-related burdens.

Magee Equations™ and response to neoadjuvant chemotherapy in ER+/HER2-negative breast cancer: a multi-institutional study

Magee Equations™ (ME) are multivariable models that can estimate oncotype DX^® recurrence score. One of the equations, Magee Equation 3 (ME3) which utilizes only semi-quantitative receptor results has been shown to provide chemopredictive value in the neoadjuvant setting in a single institutional study. This multi-institutional study (seven institutions contributed cases) was undertaken to examine the validity of ME3 in predicting response to neoadjuvant chemotherapy in estrogen receptor positive, HER2-negative breast cancers. Stage IV cases were excluded. The primary endpoint was the pathologic complete response (pCR) rate in different categories of ME3 scores calculated based on receptor results in the pre-therapy core biopsy. A total of 166 cases met the inclusion criteria. The patient age ranged from 24 to 83 years (median 53 years). The average pre-therapy tumor size was 3.9 cm, and axillary lymph nodes were confirmed positive by pre-therapy core biopsy in 85 of 166 cases (51%). The pCR rate according to ME3 scores was 0% (0 of 64) in ME3 < 18, 0% (0 of 46) in ME3 18-25, 14% (3 of 21) in ME3 > 25 to <31, and 40% (14 of 35) in ME3 score 31 or higher (p value: <0.0001). There were no distant recurrences and no deaths in the 17 patients with pCR. In the remaining 149 cases with residual disease, ME3 score of >25 was significantly associated with shorter distant recurrence-free survival and showed a trend for shorter breast cancer-specific survival. The results of this multi-institutional study are similar to previously published data from a single institution (PMID: 28548119) and confirm the chemo-predictive value of ME3 in the neoadjuvant setting. In addition, ME3 may provide prognostic information in patients with residual disease which should be further evaluated.

Prosigna® breast cancer assay: histopathologic correlation, development, and assessment of size, nodal status, Ki-67 (SiNK™) index for breast cancer prognosis

The Prosigna® assay is a United States Food and Drug Administration (US-FDA) cleared molecular test for prognostic use in hormone receptor-positive stage I/II breast cancer in postmenopausal women. We analyzed histopathologic features of 79 cases with Prosigna® assay results and found a significant correlation between tumor size, grade, and Ki-67 labeling index with Prosigna® score (0-40, 41-60, and 61-100) and Prosigna® risk categories. Since the Prosigna® risk stratification is influenced by lymph node status, we designed an index that included lymph node status and the two most correlated variables (size and Ki-67 labeling index). This was termed the size, nodal, and Ki-67 (SiNK™) index and is calculated as follows: (size in mm) + (pN × 10) + (Ki-67 labeling index). The SiNK™ index was divided into ≤40 and >40 to test its prognostic significance in a well-characterized dataset of 106 ER+/HER2-negative stage I-II invasive breast cancers treated with standard multi-modality therapy with long term follow-up (average 101 months follow-up). Patients with SiNK™ ≤40 showed significantly improved distant recurrence-free survival (96% distant recurrence-free survival in SiNK™ ≤40 compared to 81% in SiNK™ >40; log-rank test p value: 0.0027). SiNK™ provides strong prognostic information in ERo+/HER2-negative breast cancers. SiNK™ index is simple to calculate using data from routine pathology reports. This should be further evaluated in larger datasets.

Breast cancer tumor heterogeneity has only little impact on the estimation of the Oncotype DX® recurrence score using Magee Equations and Magee Decision Algorithm™

Oncotype DX® assay is used to guide therapeutic decisions in early-stage invasive breast carcinoma but remains expensive. Magee Equations (MEs) and Magee Decision Algorithm (MDA) predict the Oncotype DX® recurrence score (RS) on the basis of histopathological parameters. The influence of intratumor heterogeneity on MEs and MDA remains uncertain. We compared Ki-67, estrogen and progesterone receptors, and human erb-b2 receptor tyrosine kinase 2 (HER2) status on tissue microarray cores with the corresponding findings on the whole slides to calculate MEs scores and to decide if Oncotype DX® testing was required as per MDA in two sets of 175 and 59 tumors, without and with Oncotype DX® results, respectively. Agreements in the interpretation of Ki-67, estrogen and progesterone receptors, and HER2 status were very good between limited areas and whole-slide analyses. This resulted also in very good agreements about the results of MEs and MDA. For 7 of 175 (4%) and 3 of 59 (5.1%) cases, MEs and MDA results in different tumor areas would have changed the indication to perform or not perform Oncotype DX® assays. Oncotype DX® RSs were significantly correlated with MEs and MDA results, but among cases initially predicted to have an RS ≤25 using MDA, 3 of 34 cases (8.8%) had in fact an RS >25. Tumor heterogeneity appears to have little impact on the estimation of the Oncotype DX® RS using MEs and MDA and would have permitted to avoid half of Oncotype DX® assays in our series. Caution is nevertheless required in discarding Oncotype DX® assay in cases with ME scores >18 associated with low mitotic activity.

Evaluating biomarkers for treatment selection from reproducibility studies

We consider evaluating new or more accurately measured predictive biomarkers for treatment selection based on a previous clinical trial involving standard biomarkers. Instead of rerunning the clinical trial with the new biomarkers, we propose a more efficient approach which requires only either conducting a reproducibility study in which the new biomarkers and standard biomarkers are both measured on a set of patient samples, or adopting replicated measures of the error-contaminated standard biomarkers in the original study. This approach is easier to conduct and much less expensive than studies that require new samples from patients randomized to the intervention. In addition, it makes it possible to perform the estimation of the clinical performance quickly, since there will be no requirement to wait for events to occur as would be the case with prospective validation. The treatment selection is assessed via a working model, but the proposed estimator of the mean restricted lifetime is valid even if the working model is misspecified. The proposed approach is assessed through simulation studies and applied to a cancer study.

Estrogen and Progesterone Receptor Testing in Breast Cancer: American Society of Clinical Oncology/College of American Pathologists Guideline Update

PURPOSE.—

To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen receptor (ER) and progesterone receptor (PgR) testing in breast cancer guideline.

METHODS.—

A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature.

RECOMMENDATIONS.—

The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines .

The Evaluation of Magee Equation 2 in Predicting Response and Outcome in Hormone Receptor-Positive and HER2-Negative Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Background and Purpose

Magee Equations have been developed as accurate tools for predicting response and clinical outcomes in breast cancer patients treated with adjuvant systemic therapy using basic clinicopathological parameters. This study aims to evaluate the alternative application of Magee Equation 2 score in predicting pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in hormone receptor (HR)-positive, HER2-negative breast cancer.

Patients and Methods

Patients with HR-positive, HER2-negative breast cancer who received NAC from January 2010 to May 2018 at Siriraj Hospital, Mahidol University, Thailand, were recruited. Pre-treatment status of HR and HER2 was used to calculate the Magee Equation 2 scores. The pCR rates among different clinicopathological parameters were analyzed. Survival analysis was performed by Log-rank test. Kaplan-Meier survival curves were analyzed.

Results

A total of 215 patients were eligible. The pCR rates for low, intermediate, and high scores were 4.8%, 3.6%, and 23.8%, respectively. Patients with high scores had significantly higher size reduction and pCR rates compared to those with intermediate or low scores (p<0.001). Those with high scores had higher rates of locoregional recurrence and death. The patients with high score had significantly lower overall survival (p=0.034).

Conclusion

Among patients with HR-positive and HER2-negative breast cancer treated with NAC, Magee Equation 2 might be used as a tool for predicting the pCR and clinical outcome.

Estrogen and Progesterone Receptor Testing in Breast Cancer: ASCO/CAP Guideline Update

PURPOSE

To update key recommendations of the American Society of Clinical Oncology/College of American Pathologists estrogen (ER) and progesterone receptor (PgR) testing in breast cancer guideline.

METHODS

A multidisciplinary international Expert Panel was convened to update the clinical practice guideline recommendations informed by a systematic review of the medical literature.

RECOMMENDATIONS

The Expert Panel continues to recommend ER testing of invasive breast cancers by validated immunohistochemistry as the standard for predicting which patients may benefit from endocrine therapy, and no other assays are recommended for this purpose. Breast cancer samples with 1% to 100% of tumor nuclei positive should be interpreted as ER positive. However, the Expert Panel acknowledges that there are limited data on endocrine therapy benefit for cancers with 1% to 10% of cells staining ER positive. Samples with these results should be reported using a new reporting category, ER Low Positive, with a recommended comment. A sample is considered ER negative if < 1% or 0% of tumor cell nuclei are immunoreactive. Additional strategies recommended to promote optimal performance, interpretation, and reporting of cases with an initial low to no ER staining result include establishing a laboratory-specific standard operating procedure describing additional steps used by the laboratory to confirm/adjudicate results. The status of controls should be reported for cases with 0% to 10% staining. Similar principles apply to PgR testing, which is used primarily for prognostic purposes in the setting of an ER-positive cancer. Testing of ductal carcinoma in situ (DCIS) for ER is recommended to determine potential benefit of endocrine therapies to reduce risk of future breast cancer, while testing DCIS for PgR is considered optional. Additional information can be found at www.asco.org/breast-cancer-guidelines.

The Correlation of Magee EquationsTM and Oncotype DX® Recurrence Score From Core Needle Biopsy Tissues in Predicting Response to Neoadjuvant Chemotherapy in ER+ and HER2- Breast Cancer

Objective

Oncotype DX^® recurrence score (RS) can be predicted from Magee Equations^TM (MS) postoperatively. The aim of this study is to investigate correlation of MS with RS from pretreatment core needle biopsy (CNB) tissues, and their clinical usefulness in prediction of response to neoadjuvant chemotherapy (NCT) in estrogen receptor-positive and human epidermal growth factor receptor 2-negative (ER+/HER2-) breast cancer (BC).

Materials and Methods

Pretreatment CNB tissue samples from 60 patients with ER+/HER2- invasive BC were analyzed for MS and RS correlation. MS and RS were categorized as follows: low (<18), intermediate (18-30), and high (≥ 31). Percentage Tumor size Reduction (%TR) was used to assess tumor response to NCT, and substantial %TR was defined as at least 50% reduction (≥50%TR). Correlation between MS and RS, and predictive factors for the ≥50%TR achievement were assessed.

Results

MS and RS represented a strong correlation (Spearman's correlation; r=0.58, p<0.0001) as a continuous variable. As a categorical variable, the concordance between MS and RS was 43.3%, and it increased to 80% (r=0.61, p=0.003) with the exclusion of the intermediate risk categories. Although, there was pathologic complete response (pCR), MS showed the highest predictive power for the ≥50% TR achievement, none of the factors were statistically significant (p≥0.07).

Conclusion

Our study demonstrated that there was a strong correlation between MS and RS from pretreatment biopsy tissue samples in ER+ and HER2- invasive BC.

The healthcare value of the Magee Decision Algorithm™: use of Magee Equations™ and mitosis score to safely forgo molecular testing in breast cancer

Magee Equations™ are multivariable models that can estimate oncotype DX® Recurrence Score, and Magee Equation 3 has been shown to have chemopredictive value in the neoadjuvant setting as a standalone test. The current study tests the accuracy of Magee Decision Algorithm™ using a large in-house database. According to the algorithm, if all Magee Equation scores are <18, or 18-25 with a mitosis score of 1, then oncotype testing is not required as the actual oncotype recurrence score is expected to be ≤25 (labeled "do not send"). If all Magee Equation scores are 31 or higher, then also oncotype testing is not required as the actual score is expected to be >25 (also "do not send"). All other cases could be considered for testing (labeled "send"). Of the 2196 ER+, HER2-negative cases sent for oncotype testing, 1538 (70%) were classified as "do not send" and 658 (30%) as "send". The classification accuracy in the "do not send" group was 95.1%. Of the 75 (4.9%) discordant cases (expected score ≤25 by decision algorithm but the actual oncotype score >25), 26 received endocrine therapy alone. None of these 26 patients experienced distant recurrence (average follow-up of 73 months). The Magee Decision Algorithm accurately identifies cases that will not benefit from oncotype testing. Such cases constitute ~70% of the routine clinical oncotype requests, an estimated saving of $300,000 per 100 test requests. The occasional discordant cases (expected ≤25, but actual oncotype score >25) appears to have an excellent outcome on endocrine therapy alone.

Combined pathologic-genomic algorithm for early-stage breast cancer improves cost-effective use of the 21-gene recurrence score assay

Background

The 21-gene recurrence score (RS) (Oncotype DX®; Genomic Health, Redwood City, CA) partitions hormone receptor positive, node negative breast cancers into three risk groups for recurrence. The Anne Arundel Medical Center (AAMC) model has previously been shown to accurately predict RS risk categories using standard pathology data. A pathologic-genomic (P-G) algorithm then is presented using the AAMC model and reserving the RS assay only for AAMC intermediate-risk patients.

Patients and methods

A survival analysis was done using a prospectively collected institutional database of newly diagnosed invasive breast cancers that underwent RS assay testing from February 2005 to May 2015. Patients were assigned to risk categories based on the AAMC model. Using Kaplan-Meier methods, 5-year distant recurrence rates (DRR) were evaluated within each risk group and compared between AAMC and RS-defined risk groups. Five-year DRR were calculated for the P-G algorithm and compared with DRR for RS risk groups and the AAMC model's risk groups.

Results

A total of 1268 cases were included. Five-year DRR were similar between the AAMC low-risk group (2.7%, n = 322) and the RS < 18 low-risk group (3.4%, n = 703), as well as between the AAMC high-risk group (22.8%, n = 230) and the RS > 30 high-risk group (23.0%, n = 141). Using the P-G algorithm, more patients were categorized as either low or high risk and the distant metastasis rate was 3.3% for the low-risk group (n = 739) and 24.2% for the high-risk group (n = 272). Using the P-G algorithm, 44% (552/1268) of patients would have avoided RS testing.

Conclusions

AAMC model is capable of predicting 5-year recurrences in high- and low-risk groups similar to RS. Further, using the P-G algorithm, reserving RS for AAMC intermediate cases, results in larger low- and high-risk groups with similar prognostic accuracy. Thus, the P-G algorithm reliably identifies a significant portion of patients unlikely to benefit from RS assay and with improved ability to categorize risk.

Combined quantitative measures of ER, PR, HER2, and KI67 provide more prognostic information than categorical combinations in luminal breast cancer

Although most women with luminal breast cancer do well on endocrine therapy alone, some will develop fatal recurrence thereby necessitating the need to prospectively determine those for whom additional cytotoxic therapy will be beneficial. Categorical combinations of immunohistochemical measures of ER, PR, HER2, and KI67 are traditionally used to classify patients into luminal A-like and B-like subtypes for chemotherapeutic reasons, but this may lead to the loss of prognostically relevant information. Here, we compared the prognostic value of quantitative measures of these markers, combined in the IHC4-score, to categorical combinations in subtypes. Using image analysis-based scores for all four markers, we computed the IHC4-score for 2498 patients with luminal breast cancer from two European study populations. We defined subtypes (A-like (ER + and PR + : and HER2- and low KI67) and B-like (ER + and/or PR + : and HER2 + or high KI67)) by combining binary categories of these markers. Hazard ratios and 95% confidence intervals for associations with 10-year breast cancer-specific survival were estimated in Cox proportional-hazard models. We accounted for clinical prognostic factors, including grade, tumor size, lymph-nodal involvement, and age, by using the PREDICT-score. Overall, Subtypes [hazard ratio (95% confidence interval) B-like vs. A-like = 1.64 (1.25-2.14); P-value < 0.001] and IHC4-score [hazard ratio (95% confidence interval)/1 standard deviation = 1.32 (1.20-1.44); P-value < 0.001] were prognostic in univariable models. However, IHC4-score [hazard ratio (95% confidence interval)/1 standard deviation = 1.24 (1.11-1.37); P-value < 0.001; likelihood ratio chi-square (LRχ2) = 12.5] provided more prognostic information than Subtype [hazard ratio (95% confidence interval) B-like vs. A-like = 1.38 (1.02-1.88); P-value = 0.04; LRχ2 = 4.3] in multivariable models. Further, higher values of the IHC4-score were associated with worse prognosis, regardless of subtype (P-heterogeneity = 0.97). These findings enhance the value of the IHC4-score as an adjunct to clinical prognostication tools for aiding chemotherapy decision-making in luminal breast cancer patients, irrespective of subtype.

Breast cancer global tumor biomarkers: a quality assurance study of intratumoral heterogeneity

Biomarker analysis of invasive breast carcinoma is useful for prognosis, as surrogate for molecular subtypes of breast cancer, and prediction of response to adjuvant and neoadjuvant systemic therapies. Breast cancer intratumoral heterogeneity is incompletely studied. Comprehensive biomarker analysis of estrogen receptor (ER), progesterone receptor (PR), HER2, and Ki67 labeling index was performed on each tissue block of 100 entirely submitted breast tumors in 99 patients. Invasive carcinoma and in situ carcinoma was scored using semiquantitative histologic score (H-score) for ER and PR, HER2 expression from 0 to 3+, and percentage positive cells for Ki67. Core biopsy results were compared with surgical excision results, invasive carcinoma was compared with in situ carcinoma, and interblock tumoral heterogeneity was assessed using measures of dispersion (coefficient of variation and quartile coefficient of dispersion). Overall concordance between core biopsy and surgical excision was 99% for ER and 95% for PR. Mean histologic score of ER was significantly lower in invasive carcinoma between core biopsy and surgical excision (p = 0.000796). Intratumoral heterogeneity was higher for PR than for ER (mean coefficient of variation for ER 0.08 stdv 0.13 vs. PR 0.26 stdv 0.41). Ki67 labeling index was significantly higher in invasive carcinoma as compared with associated ductal carcinoma in situ on surgical resection specimen (p ≤ 0.0001). Ki67 hotspots were identified in 47% of cases. Of 52 HER2 negative cases on core biopsy, 10 were scored as equivocal on surgical resection. None (0/10) were amplified by Her-2/neu fluorescence in situ hybridization. Overall, biomarkers on core biopsy showed concordance with the surgical excision specimen in the vast majority of cases. Biomarker expression of in situ closely approximates associated invasive carcinoma. Intratumoral heterogeneity of PR is greater than ER. Biomarker expression on diagnostic core biopsy or single tumor block is representative of breast carcinoma as a whole in most cases and is appropriate for clinical decision-making.

Breast Cancers With Magee Equation Score of Less Than 18, or 18-25 and Mitosis Score of 1, Do Not Require Oncotype DX Testing: A Value Study

Objectives

To investigate use of Magee equations (MEs) to determine which breast cancer cases can be excluded from Oncotype DX testing.

Methods

A prospective value study was carried out using data from pathology reports.

Results

If all three MEs scores were less than 18 or 31 or higher, the cases were labeled do not send for testing. If any or all scores were 18 to 25, cases were labeled do not send if mitosis score was 1. Of the total 205 cases, 146 (71%) were labeled do not send; of these, the correct call was made in 143 (98%) cases. Two of the three discordant cases had associated nontumor factors, likely resulting in higher scores.

Conclusions

Cases with ME scores less than 18, or 18 to 25 and mitosis score 1, do not require Oncotype DX testing, an estimated saving of US$280,000 per 100 clinical requests.

Ancillary Prognostic and Predictive Testing in Breast Cancer: Focus on Discordant, Unusual, and Borderline Results

Ancillary testing in breast cancer has become standard of care to determine what therapies may be most effective for individual patients with breast cancer. Single-marker tests are required on all newly diagnosed and newly metastatic breast cancers. Markers of proliferation are also used, and include both single-marker tests like Ki67 as well as panel-based gene expression tests, which have made more recent contributions to prognostic and predictive testing in breast cancers. This review focuses on pathologist interpretation of these ancillary test results, with a focus on expected versus unexpected results and troubleshooting borderline, unusual, or discordant results.

Practical Consequences Resulting from the Analysis of a 21-Multigene Array in the Interdisciplinary Conference of a Breast Cancer Center

During the multidisciplinary planning of postoperative therapy after breast cancer, borderline cases can arise with no clear rationale for or against adjuvant chemotherapy. In 50 hormone- receptor-positive, Her2neu-negative carcinomas of the breast with no or only minimal lymph node involvement (max. pT1a) we initiated an Oncotype DX® multigene assay in addition to the evaluation of usual parameters. In the oncology conference a vote for or against chemotherapy was taken on the basis of the conventional criteria for decision-making before the test results were available. The final recommendation was made after the multigene test. In 32 breast carcinomas (64%) a low recurrence score could be documented, while 26 (32%) showed an intermediate RS and 3 (6%) showed a high RS. In most cases the result of the test could validate the choice of therapy established using conventional criteria. In 5 cases the initial recommendation for adjuvant therapy was revised, and in 3 cases chemotherapy was secondarily recommended after evaluation of the test results. Conversely, in some cases a low or intermediate risk constellation did not argue against a recommendation for adjuvant chemotherapy. Altogether, the results of our study do not indicate that a multigene assay should be used as a routine diagnostic tool. Instead a thorough compilation and careful analysis of conventional parameters for therapeutic decision-making should take precedence, with special emphasis on histopathological and immunohistochemical results. In selected cases, however, a multigene assay can be a useful tool in the deliberation for or against a therapeutic pathway.

Low Estrogen Receptor (ER)-Positive Breast Cancer and Neoadjuvant Systemic Chemotherapy: Is Response Similar to Typical ER-Positive or ER-Negative Disease?

OBJECTIVES

Pathologic complete response (pCR) rate after neoadjuvant chemotherapy was compared between 141 estrogen receptor (ER)-negative (43%), 41 low ER+ (13%), 47 moderate ER+ (14%), and 98 high ER+ (30%) tumors.

METHODS

Human epidermal growth factor receptor 2-positive cases, cases without semiquantitative ER score, and patients treated with neoadjuvant endocrine therapy alone were excluded.

RESULTS

The pCR rate of low ER+ tumors was similar to the pCR rate of ER- tumors (37% and 26% for low ER and ER- respectively, P = .1722) but significantly different from the pCR rate of moderately ER+ (11%, P = .0049) and high ER+ tumors (4%, P < .0001). Patients with pCR had an excellent prognosis regardless of the ER status. In patients with residual disease (no pCR), the recurrence and death rate were higher in ER- and low ER+ cases compared with moderate and high ER+ cases.

CONCLUSIONS

Low ER+ breast cancers are biologically similar to ER- tumors. Semiquantitative ER H-score is an important determinant of response to neoadjuvant chemotherapy.

Utilization of the 21-Gene Recurrence Score in a Diverse Breast Cancer Patient Population: Development of a Clinicopathologic Model to Predict High-Risk Scores and Response to Neoadjuvant Chemotherapy

INTRODUCTION

The 21-gene expression profile [Oncotype DX Recurrence Score (RS)] stratifies benefit from adjuvant chemotherapy in hormone receptor (HR)-positive, HER2/neu-negative, node-negative breast cancer. It is not routinely applied to predict neoadjuvant chemotherapy (NACT) response; data in diverse patient populations also are limited. We developed a statistical model based on standard clinicopathologic features to identify high-risk cases (RS > 30) and then evaluated ability of predicted high RS to predict for NACT downstaging.

METHODS

Primary surgery patients with Oncotype DX RS testing 2012-2016 were identified from a prospectively-maintained database. A RS predictive model was created and applied to a dataset of comparable NACT patients. Response was defined as tumor size decrease ≥ 1 cm.

RESULTS

Of 394 primary surgery patients-60.4% white American; 31.0% African American-RS distribution was similar for both groups. No single feature reliably identified high RS patients; however, a model accounting for age, HR expression, proliferative index (MIB1/Ki67), histology, and tumor size was generated, with receiver operator area under the curve 0.909. Fifty-six NACT patients were identified (25 African American). Of 21 cases with all relevant clinicopathology, 14 responded to NACT and the model generated high-risk RS in 14 (100%); conversely, of 16 cases generating high-risk RS, only 2 did not respond.

CONCLUSIONS

Predictive modelling can identify high RS patients; this model also can identify patients likely to experience primary tumor downstaging with NACT. Until this model is validated in other datasets, we recommend that Oncotype-eligible patients undergo primary surgery with decisions regarding chemotherapy made in the adjuvant setting.