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Dhungana A, Vannier A, Zhao F, Freeman JQ, Saha P, Sullivan M, Yao K, Flores EM, Olopade OI, Pearson AT, Huo D, Howard FM. Development and validation of a clinical breast cancer tool for accurate prediction of recurrence. NPJ Breast Cancer 2024; 10:46. [PMID: 38879577 PMCID: PMC11180107 DOI: 10.1038/s41523-024-00651-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 06/01/2024] [Indexed: 06/18/2024] Open
Abstract
Given high costs of Oncotype DX (ODX) testing, widely used in recurrence risk assessment for early-stage breast cancer, studies have predicted ODX using quantitative clinicopathologic variables. However, such models have incorporated only small cohorts. Using a cohort of patients from the National Cancer Database (NCDB, n = 53,346), we trained machine learning models to predict low-risk (0-25) or high-risk (26-100) ODX using quantitative estrogen receptor (ER)/progesterone receptor (PR)/Ki-67 status, quantitative ER/PR status alone, and no quantitative features. Models were externally validated on a diverse cohort of 970 patients (median follow-up 55 months) for accuracy in ODX prediction and recurrence. Comparing the area under the receiver operating characteristic curve (AUROC) in a held-out set from NCDB, models incorporating quantitative ER/PR (AUROC 0.78, 95% CI 0.77-0.80) and ER/PR/Ki-67 (AUROC 0.81, 95% CI 0.80-0.83) outperformed the non-quantitative model (AUROC 0.70, 95% CI 0.68-0.72). These results were preserved in the validation cohort, where the ER/PR/Ki-67 model (AUROC 0.87, 95% CI 0.81-0.93, p = 0.009) and the ER/PR model (AUROC 0.86, 95% CI 0.80-0.92, p = 0.031) significantly outperformed the non-quantitative model (AUROC 0.80, 95% CI 0.73-0.87). Using a high-sensitivity rule-out threshold, the non-quantitative, quantitative ER/PR and ER/PR/Ki-67 models identified 35%, 30% and 43% of patients as low-risk in the validation cohort. Of these low-risk patients, fewer than 3% had a recurrence at 5 years. These models may help identify patients who can forgo genomic testing and initiate endocrine therapy alone. An online calculator is provided for further study.
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Affiliation(s)
- Asim Dhungana
- Pritzker School of Medicine, University of Chicago, Chicago, IL, USA
| | - Augustin Vannier
- Pritzker School of Medicine, University of Chicago, Chicago, IL, USA
| | - Fangyuan Zhao
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Jincong Q Freeman
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Poornima Saha
- Department of Medicine, NorthShore University HealthSystem, Evanston, IL, USA
| | - Megan Sullivan
- Department of Pathology, NorthShore University HealthSystem, Evanston, IL, USA
| | - Katharine Yao
- Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | - Elbio M Flores
- Department of Pathology, Ingalls Memorial Hospital, Harvey, IL, USA
| | | | | | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
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Krystel-Whittemore M, Tan PH, Wen HY. Predictive and prognostic biomarkers in breast tumours. Pathology 2024; 56:186-191. [PMID: 38212230 PMCID: PMC10949537 DOI: 10.1016/j.pathol.2023.10.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/23/2023] [Accepted: 10/29/2023] [Indexed: 01/13/2024]
Abstract
In the age of precision medicine, extensive research has investigated tumour biomarkers to predict the behaviour of cancer and/or response to treatment in order to better understand the prognosis and treatment of disease. In breast cancer, significant progress has been made to categorise a common disease into subtypes defined by intrinsic tumour biology, measured by tumour biomarkers. This review encompasses the established biomarkers within breast cancer with the most up-to-date information regarding their understanding and clinical use as predictive and/or prognostic markers of breast cancer.
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Affiliation(s)
| | | | - Hannah Y Wen
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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Paiva CE, Zonta MPM, Granero RC, Guimarães VS, Pimenta LM, Teixeira GR, Paiva BSR. The Magee 3 Equation Predicts Favorable Pathologic Response to Neoadjuvant Endocrine Therapy in Breast Cancer Patients. Cancers (Basel) 2024; 16:339. [PMID: 38254828 PMCID: PMC10813970 DOI: 10.3390/cancers16020339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 10/27/2023] [Accepted: 11/01/2023] [Indexed: 01/24/2024] Open
Abstract
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.
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Affiliation(s)
- Carlos Eduardo Paiva
- Department of Clinical Oncology, Barretos Cancer Hospital, Barretos 14784-400, SP, Brazil;
| | - Maria Paola Montesso Zonta
- Barretos School of Health Sciences Dr. Paulo Prata—FACISB, Barretos 14785-002, SP, Brazil; (M.P.M.Z.); (R.C.G.); (G.R.T.)
| | - Rafaela Carvalho Granero
- Barretos School of Health Sciences Dr. Paulo Prata—FACISB, Barretos 14785-002, SP, Brazil; (M.P.M.Z.); (R.C.G.); (G.R.T.)
| | - Vitor Souza Guimarães
- Department of Clinical Oncology, Barretos Cancer Hospital, Barretos 14784-400, SP, Brazil;
| | - Layla Melo Pimenta
- Department of Pathology, Barretos Cancer Hospital, Barretos 14784-400, SP, Brazil;
| | - Gustavo Ramos Teixeira
- Barretos School of Health Sciences Dr. Paulo Prata—FACISB, Barretos 14785-002, SP, Brazil; (M.P.M.Z.); (R.C.G.); (G.R.T.)
- Department of Pathology, Barretos Cancer Hospital, Barretos 14784-400, SP, Brazil;
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Bhargava R, Dabbs DJ. The Story of the Magee Equations: The Ultimate in Applied Immunohistochemistry. Appl Immunohistochem Mol Morphol 2023; 31:490-499. [PMID: 36165933 PMCID: PMC10396078 DOI: 10.1097/pai.0000000000001065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 08/19/2022] [Indexed: 11/25/2022]
Abstract
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.
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Affiliation(s)
- Rohit Bhargava
- Department of Pathology, UPMC Magee-Womens Hospital, Pittsburgh, PA
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Lashen A, Toss MS, Fadhil W, Oni G, Madhusudan S, Rakha E. Evaluation oncotype DX ® 21-gene recurrence score and clinicopathological parameters: a single institutional experience. Histopathology 2023; 82:755-766. [PMID: 36631400 DOI: 10.1111/his.14863] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 12/29/2022] [Accepted: 01/05/2023] [Indexed: 01/13/2023]
Abstract
AIMS Oncotype DX recurrence score (RS) is a clinically validated assay, which predicts the likelihood of disease recurrence in oestrogen receptor-positive/HER2-negative (ER+/HER2-) breast cancer (BC). In this study we aimed to compare the performance of Oncotype DX against the conventional clinicopathological parameters using a large BC cohort diagnosed in a single institution. METHODS AND RESULTS A cohort (n = 430) of ER+/HER2- BC patients who were diagnosed at the Nottingham University Hospitals NHS Trust and had Oncotype DX testing was included. Correlation with the clinicopathological and other biomarkers, including the proliferation index, was analysed. The median Oncotype DX RS was 17.5 (range = 0-69). There was a significant association between high RS and grade 3 tumours. No grade 1 BC or grade 2 tumours with mitosis score 1 showed high RS. Low RS was significantly associated with special tumour types where none of the patients with classical lobular or tubular carcinomas had a high RS. There was an inverse association between RS and levels of ER and progesterone receptor (PR) expression and a positive linear correlation with Ki67 labelling index. Notably, six patients who developed recurrence had an intermediate RS; however, four of these six cases (67%) were identified as high-risk disease when the conventional clinical and molecular parameters were considered. CONCLUSION Oncotype DX RS is correlated strongly with the conventional clinicopathological parameters in BC. Some tumour features such as tumour grade, type, PR status and Ki67 index can be used as surrogate markers in certain scenarios.
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Affiliation(s)
- Ayat Lashen
- Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.,Department of Pathology, Faculty of Medicine, Menoufia University, Shebin El Kom, Egypt
| | - Michael S Toss
- Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.,Department of Histopathology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Wakkas Fadhil
- Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Georgette Oni
- Nottingham Breast Institute, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Srinivasan Madhusudan
- Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.,Department of Oncology, Nottingham University Hospitals, Nottingham, UK
| | - Emad Rakha
- Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.,Department of Pathology, Faculty of Medicine, Menoufia University, Shebin El Kom, Egypt.,Nottingham Breast Institute, Nottingham University Hospitals NHS Trust, Nottingham, UK.,Pathology Department, Hamad Medical Corporation, Doha, Qatar
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Turner BM, Finkelman BS, Hicks DG, Numbereye N, Moisini I, Dhakal A, Skinner K, Sanders MAG, Wang X, Shayne M, Schiffhauer L, Katerji H, Zhang H. The Rochester Modified Magee Algorithm (RoMMa): An Outcomes Based Strategy for Clinical Risk-Assessment and Risk-Stratification in ER Positive, HER2 Negative Breast Cancer Patients Being Considered for Oncotype DX ® Testing. Cancers (Basel) 2023; 15:cancers15030903. [PMID: 36765860 PMCID: PMC9913115 DOI: 10.3390/cancers15030903] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 01/19/2023] [Accepted: 01/26/2023] [Indexed: 02/04/2023] Open
Abstract
INTRODUCTION Multigene genomic profiling has become the standard of care in the clinical risk-assessment and risk-stratification of ER+, HER2- breast cancer (BC) patients, with Oncotype DX® (ODX) emerging as the genomic profile test with the most support from the international community. The current state of the health care economy demands that cost-efficiency and access to testing must be considered when evaluating the clinical utility of multigene profile tests such as ODX. Several studies have suggested that certain lower risk patients can be identified more cost-efficiently than simply reflexing all ER+, HER2- BC patients to ODX testing. The Magee equationsTM use standard histopathologic data in a set of multivariable models to estimate the ODX recurrence score. Our group published the first outcome data in 2019 on the Magee equationsTM, using a modification of the Magee equationsTM combined with an algorithmic approach-the Rochester Modified Magee algorithm (RoMMa). There has since been limited published outcome data on the Magee equationsTM. We present additional outcome data, with considerations of the TAILORx risk-stratification recommendations. METHODS 355 patients with an ODX recurrence score, and at least five years of follow-up or a BC recurrence were included in the study. All patients received either Tamoxifen or an aromatase inhibitor. None of the patients received adjuvant systemic chemotherapy. RESULTS There was no significant difference in the risk of recurrence in similar risk categories (very low risk, low risk, and high risk) between the average Modified Magee score and ODX recurrence score with the chi-square test of independence (p > 0.05) or log-rank test (p > 0.05). Using the RoMMa, we estimate that at least 17% of individuals can safely avoid ODX testing. CONCLUSION Our study further reinforces that BC patients can be confidently stratified into lower and higher-risk recurrence groups using the Magee equationsTM. The RoMMa can be helpful in the initial clinical risk-assessment and risk-stratification of BC patients, providing increased opportunities for cost savings in the health care system, and for clinical risk-assessment and risk-stratification in less-developed geographies where multigene testing might not be available.
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Affiliation(s)
- Bradley M. Turner
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14620, USA
- Correspondence: ; Tel.: +1-(585)-275-2228; Fax: +1-(585)-341-6725
| | - Brian S. Finkelman
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14620, USA
| | - David G. Hicks
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14620, USA
| | - Numbere Numbereye
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14620, USA
| | - Ioana Moisini
- M. Health Fairview Ridges, Burnsville, MN 55337, USA
| | - Ajay Dhakal
- Department of Medical Oncology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Kristin Skinner
- Department of Surgical Oncology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Mary Ann G. Sanders
- Norton Healthcare, University of Louisville Department of Pathology, Louisville, KY 40292, USA
| | - Xi Wang
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14620, USA
| | - Michelle Shayne
- Department of Medical Oncology, University of Rochester Medical Center, Rochester, NY 14642, USA
| | - Linda Schiffhauer
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14620, USA
| | - Hani Katerji
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14620, USA
| | - Huina Zhang
- Department of Pathology and Laboratory Medicine, University of Rochester Medical Center, 601 Elmwood Ave., Rochester, NY 14620, USA
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Finkelman BS, Zhang H, Hicks DG, Turner BM. The Evolution of Ki-67 and Breast Carcinoma: Past Observations, Present Directions, and Future Considerations. Cancers (Basel) 2023; 15:cancers15030808. [PMID: 36765765 PMCID: PMC9913317 DOI: 10.3390/cancers15030808] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 01/19/2023] [Accepted: 01/24/2023] [Indexed: 01/31/2023] Open
Abstract
The 1983 discovery of a mouse monoclonal antibody-the Ki-67 antibody-that recognized a nuclear antigen present only in proliferating cells represented a seminal discovery for the pathologic assessment of cellular proliferation in breast cancer and other solid tumors. Cellular proliferation is a central determinant of prognosis and response to cytotoxic chemotherapy in patients with breast cancer, and since the discovery of the Ki-67 antibody, Ki-67 has evolved as an important biomarker with both prognostic and predictive potential in breast cancer. Although there is universal recognition among the international guideline recommendations of the value of Ki-67 in breast cancer, recommendations for the actual use of Ki-67 assays in the prognostic and predictive evaluation of breast cancer remain mixed, primarily due to the lack of assay standardization and inconsistent inter-observer and inter-laboratory reproducibility. The treatment of high-risk ER-positive/human epidermal growth factor receptor-2 (HER2) negative breast cancer with the recently FDA-approved drug abemaciclib relies on a quantitative assessment of Ki-67 expression in the treatment decision algorithm. This further reinforces the urgent need for standardization of Ki-67 antibody selection and staining interpretation, which will hopefully lead to multidisciplinary consensus on the use of Ki-67 as a prognostic and predictive marker in breast cancer. The goals of this review are to highlight the historical evolution of Ki-67 in breast cancer, summarize the present literature on Ki-67 in breast cancer, and discuss the evolving literature on the use of Ki-67 as a companion diagnostic biomarker in breast cancer, with consideration for the necessary changes required across pathology practices to help increase the reliability and widespread adoption of Ki-67 as a prognostic and predictive marker for breast cancer in clinical practice.
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Uras C, Cabioglu N, Tokat F, Er O, Kara H, Korkmaz T, Bese N, Ince U. Favorable locoregional control in clinically node-negative hormone-receptor positive breast cancer with low 21-gene recurrence scores: a single-institution study with 10-year follow-up. BMC Cancer 2022; 22:1217. [PMID: 36434599 PMCID: PMC9700873 DOI: 10.1186/s12885-022-10308-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/11/2022] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Recent studies have shown a lower likelihood of locoregional recurrences in patients with a low 21-gene recurrence score (RS). In this single-institution study, we investigated whether there are any associations between different cutoff values of 21-gene RS, histopathological factors, and outcome in patients with long-term follow-up. METHODS The study included 61 patients who had early-stage (I-II) clinically node-negative hormone receptor-positive and HER2-negative breast cancer and were tested with the 21-gene RS assay between February 2010 and February 2013. Demographic, clinicopathological, treatment, and outcome characteristics were analyzed. RESULTS The median age was 48 years (range, 29-72 years). Patients with high histologic grade (HG), Ki-67 ≥ 25%, or Ki-67 ≥ 30% were more likely to have intermediate/high RS (≥ 18). Based on the 21-gene RS assay, only 19 patients (31%) received adjuvant chemotherapy. At a median follow-up of 112 months, 3 patients developed locoregional recurrences (4.9%), which were treated with endocrine therapy alone. Among patients treated with endocrine treatment alone (n = 42), the following clinicopathological characteristics were not found to be significantly associated with 10-year locoregional recurrence free survival (LRRFS): age < 40 years, age < 50 years, high histological or nuclear grade, high Ki-67-scores (≥ 15%, ≥ 20%, ≥ 25%, ≥ 30%), presence of lymphovascular invasion, luminal-A type, multifocality, lymph node positivity, tumor size more than 2 cm, RS ≥ 18, and RS > 11. However, patients with RS ≥ 16 had significantly poorer 10-year LRRFS compared to those with RS < 16 (75% vs. 100%, respectively; p = 0.039). CONCLUSIONS The results suggest that patients with clinically node-negative disease and RS ≥ 16 are more likely to benefit from adjuvant chemotherapies. However, those with RS < 16 have an excellent outcome and local control in long-term follow-up with endocrine treatment alone.
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Affiliation(s)
- Cihan Uras
- grid.411117.30000 0004 0369 7552Departments of Surgery, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Neslihan Cabioglu
- grid.411117.30000 0004 0369 7552Departments of Surgery, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey ,grid.9601.e0000 0001 2166 6619Department of Surgery, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey
| | - Fatma Tokat
- grid.411117.30000 0004 0369 7552Department of Pathology, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Ozlem Er
- grid.411117.30000 0004 0369 7552Department of Medical Oncology, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Halil Kara
- grid.411117.30000 0004 0369 7552Departments of Surgery, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Taner Korkmaz
- grid.411117.30000 0004 0369 7552Department of Medical Oncology, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Nuran Bese
- grid.411117.30000 0004 0369 7552Department of Radiation Oncology, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
| | - Umit Ince
- grid.411117.30000 0004 0369 7552Department of Pathology, Acibadem Mehmet Ali Aydinlar University, School of Medicine, Istanbul, Turkey
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Dannehl D, Engler T, Volmer LL, Staebler A, Fischer AK, Weiss M, Hahn M, Walter CB, Grischke EM, Fend F, Taran FA, Brucker SY, Hartkopf AD. Recurrence Score ® Result Impacts Treatment Decisions in Hormone Receptor-Positive, HER2-Negative Patients with Early Breast Cancer in a Real-World Setting-Results of the IRMA Trial. Cancers (Basel) 2022; 14:5365. [PMID: 36358784 PMCID: PMC9657368 DOI: 10.3390/cancers14215365] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 10/18/2022] [Accepted: 10/22/2022] [Indexed: 08/10/2023] Open
Abstract
BACKGROUND Patients with hormone receptor-positive (HR+), HER2-negative (HER2-) early breast cancer (eBC) with a high risk of relapse often undergo adjuvant chemotherapy. However, only a few patients will gain benefit from chemotherapy. Since classical tumor characteristics (grade, tumor size, lymph node involvement, and Ki67) are of limited value to predict chemotherapy efficacy, multigene expression assays such as the Oncotype DX® test were developed to reduce over- and undertreatment. The IRMA trial analyzed the impact of Recurrence Score® (RS) assessment on adjuvant treatment recommendations. MATERIALS AND METHODS The RS result was assessed in patients with HR+/HER2- unilateral eBC with 0-3 pathologic lymph nodes who underwent primary surgical treatment at the Department for Women's Health of Tuebingen University, Germany. Therapy recommendations without knowledge of the RS result were compared to therapy recommendations with awareness of the RS result. RESULTS In total, 245 patients underwent RS assessment. Without knowledge of the RS result, 92/245 patients (37.6%) would have been advised to receive chemotherapy. After RS assessment, 56/245 patients (22.9%) were advised to undergo chemotherapy. Chemotherapy was waived in 47/92 patients (51.1%) that were initially recommended to receive it. Chemotherapy was added in 11/153 patients (7.2%) that were recommended to not receive it initially. SUMMARY Using the RS result to guide adjuvant treatment decisions in HR+/HER2- breast cancer led to a substantial reduction of chemotherapy. In view of the results achieved in prospective studies, the RS result is among other risk-factors suitable for the individualization of adjuvant systemic therapy.
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Affiliation(s)
- Dominik Dannehl
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
| | - Tobias Engler
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
| | - Lea L. Volmer
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
| | - Annette Staebler
- Department for Pathology and Neuropathology, Tuebingen University, 72076 Tübingen, Germany
| | - Anna K. Fischer
- Department for Pathology and Neuropathology, Tuebingen University, 72076 Tübingen, Germany
| | - Martin Weiss
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
| | - Markus Hahn
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
| | - Christina B. Walter
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
| | - Eva-Maria Grischke
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
| | - Falko Fend
- Department for Pathology and Neuropathology, Tuebingen University, 72076 Tübingen, Germany
| | - Florin-Andrei Taran
- Department for Gynecology and Obstetrics, Freiburg University, 79085 Freiburg im Breisgau, Germany
| | - Sara Y. Brucker
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
| | - Andreas D. Hartkopf
- Department for Womens’ Health, Tuebingen University, 72076 Tübingen, Germany
- Department for Gynecology and Obstetrics, Ulm University, 89081 Ulm, Germany
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The potential of predictive and prognostic breast MRI (P2-bMRI). Eur Radiol Exp 2022; 6:42. [PMID: 35989400 PMCID: PMC9393116 DOI: 10.1186/s41747-022-00291-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 06/08/2022] [Indexed: 11/10/2022] Open
Abstract
Magnetic resonance imaging (MRI) is an important part of breast cancer diagnosis and multimodal workup. It provides unsurpassed soft tissue contrast to analyse the underlying pathophysiology, and it is adopted for a variety of clinical indications. Predictive and prognostic breast MRI (P2-bMRI) is an emerging application next to these indications. The general objective of P2-bMRI is to provide predictive and/or prognostic biomarkers in order to support personalisation of breast cancer treatment. We believe P2-bMRI has a great clinical potential, thanks to the in vivo examination of the whole tumour and of the surrounding tissue, establishing a link between pathophysiology and response to therapy (prediction) as well as patient outcome (prognostication). The tools used for P2-bMRI cover a wide spectrum: standard and advanced multiparametric pulse sequences; structured reporting criteria (for instance BI-RADS descriptors); artificial intelligence methods, including machine learning (with emphasis on radiomics data analysis); and deep learning that have shown compelling potential for this purpose. P2-bMRI reuses the imaging data of examinations performed in the current practice. Accordingly, P2-bMRI could optimise clinical workflow, enabling cost savings and ultimately improving personalisation of treatment. This review introduces the concept of P2-bMRI, focusing on the clinical application of P2-bMRI by using semantic criteria.
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11
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Li H, Wang J, Li Z, Dababneh M, Wang F, Zhao P, Smith GH, Teodoro G, Li M, Kong J, Li X. Deep Learning-Based Pathology Image Analysis Enhances Magee Feature Correlation With Oncotype DX Breast Recurrence Score. Front Med (Lausanne) 2022; 9:886763. [PMID: 35775006 PMCID: PMC9239530 DOI: 10.3389/fmed.2022.886763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 05/18/2022] [Indexed: 11/13/2022] Open
Abstract
Background Oncotype DX Recurrence Score (RS) has been widely used to predict chemotherapy benefits in patients with estrogen receptor-positive breast cancer. Studies showed that the features used in Magee equations correlate with RS. We aimed to examine whether deep learning (DL)-based histology image analyses can enhance such correlations. Methods We retrieved 382 cases with RS diagnosed between 2011 and 2015 from the Emory University and the Ohio State University. All patients received surgery. DL models were developed to detect nuclei of tumor cells and tumor-infiltrating lymphocytes (TILs) and segment tumor cell nuclei in hematoxylin and eosin (H&E) stained histopathology whole slide images (WSIs). Based on the DL-based analysis, we derived image features from WSIs, such as tumor cell number, TIL number variance, and nuclear grades. The entire patient cohorts were divided into one training set (125 cases) and two validation sets (82 and 175 cases) based on the data sources and WSI resolutions. The training set was used to train the linear regression models to predict RS. For prediction performance comparison, we used independent variables from Magee features alone or the combination of WSI-derived image and Magee features. Results The Pearson's correlation coefficients between the actual RS and predicted RS by DL-based analysis were 0.7058 (p-value = 1.32 × 10-13) and 0.5041 (p-value = 1.15 × 10-12) for the validation sets 1 and 2, respectively. The adjusted R 2 values using Magee features alone are 0.3442 and 0.2167 in the two validation sets, respectively. In contrast, the adjusted R 2 values were enhanced to 0.4431 and 0.2182 when WSI-derived imaging features were jointly used with Magee features. Conclusion Our results suggest that DL-based digital pathological features can enhance Magee feature correlation with RS.
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Affiliation(s)
- Hongxiao Li
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, United States
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin, China
| | - Jigang Wang
- Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States
| | - Zaibo Li
- Department of Pathology, The Ohio State University, Columbus, OH, United States
| | - Melad Dababneh
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States
| | - Fusheng Wang
- Department of Computer Science, Stony Brook University, Stony Brook, NY, United States
| | - Peng Zhao
- Department of Pathology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Geoffrey H. Smith
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States
| | - George Teodoro
- Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, Brazil
| | - Meijie Li
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, United States
| | - Jun Kong
- Department of Mathematics and Statistics, Georgia State University, Atlanta, GA, United States
- Department of Computer Science, Georgia State University, Atlanta, GA, United States
- Department of Computer Science, Emory University, Atlanta, GA, United States
| | - Xiaoxian Li
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, United States
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12
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Yordanova M, Hassan S. The Role of the 21-Gene Recurrence Score ® Assay in Hormone Receptor-Positive, Node-Positive Breast Cancer: The Canadian Experience. Curr Oncol 2022; 29:2008-2020. [PMID: 35323363 PMCID: PMC8947241 DOI: 10.3390/curroncol29030163] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Revised: 03/02/2022] [Accepted: 03/04/2022] [Indexed: 01/02/2023] Open
Abstract
The management of patients with hormone receptor-positive breast cancer has changed dramatically with use of the 21-gene Recurrence Score® (RS) Assay. While the utility of the assay was initially demonstrated among node-negative patients, recent studies have also demonstrated the assay's prognostic and predictive value in node-positive patients. In Canada, the RS assay is reimbursed by provincial health insurance plans, but not all provinces have approved the use of the assay for patients with node-positive disease. Here, we provide an overview of the clinical factors that influence physician recommendation of the RS assay and, alternatively, the impact of the RS assay on patient treatment decisions in Canada. We performed a comprehensive review of the impact of the assay upon physician treatment decisions and cost in node-positive breast cancer patients within Canada and other countries. Furthermore, we evaluated biomarkers that can predict the RS result, in addition to other genomic assays that predict recurrence risk among node-positive patients. Overall, the 21-gene RS assay was shown to be a cost-effective tool that significantly reduced the use of chemotherapy in node-positive breast cancer patients in Canada.
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Affiliation(s)
- Mariya Yordanova
- Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada;
| | - Saima Hassan
- Faculty of Medicine, Université de Montréal, Montréal, QC H3C 3T5, Canada
- Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), l’Institut de Cancer de Montréal, Montréal, QC H2X 0A9, Canada
- Division of Surgical Oncology, Department of Surgery, Centre Hospitalier de l’Université de Montréal (CHUM), Montréal, QC H2X 0C1, Canada
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13
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Carleton N, Nasrazadani A, Gade K, Beriwal S, Barry PN, Brufsky AM, Bhargava R, Berg WA, Zuley ML, van Londen GJ, Marroquin OC, Thull DL, Mai PL, Diego EJ, Lotze MT, Oesterreich S, McAuliffe PF, Lee AV. Personalising therapy for early-stage oestrogen receptor-positive breast cancer in older women. THE LANCET. HEALTHY LONGEVITY 2022; 3:e54-e66. [PMID: 35047868 PMCID: PMC8765742 DOI: 10.1016/s2666-7568(21)00280-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
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.
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Affiliation(s)
- Neil Carleton
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Azadeh Nasrazadani
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Kristine Gade
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Sushil Beriwal
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Parul N Barry
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Adam M Brufsky
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Rohit Bhargava
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Wendie A Berg
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Margarita L Zuley
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - G J van Londen
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Oscar C Marroquin
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Darcy L Thull
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Phuong L Mai
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Emilia J Diego
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Michael T Lotze
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Steffi Oesterreich
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Priscilla F McAuliffe
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
| | - Adrian V Lee
- (N Carleton BS, Prof S Oesterreich PhD, P F McAuliffe MD, Prof A V Lee PhD) (S Beriwal MD, P N Barry MD), (N Carleton, Prof S Oesterreich, P F McAuliffe, Prof A V Lee); (A Nasrazadani MD, K Gade MD, Prof A M Brufksy MD, G J van Londen MD), (Prof R Bhargava MD), (D L Thull MS, P L Mai MD), (E J Diego MD, Prof M T Lotze MD, P F McAuliffe), (Prof M T Lotze), (Prof M T Lotze), (Prof S Oesterreich, Prof A V Lee), (Prof W A Berg MD, Prof M L Zuley MD); (O C Marroquin MD)
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14
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Salgado R, Peg V, Rüschoff J, Vincent-Salomon A, Castellano I, Perner S, Van de Vijver K, Quinn CM, Varga Z. Gene expression signatures for tailoring adjuvant chemotherapy of luminal breast cancer: the pathologists' perspective. Ann Oncol 2021; 32:1316-1321. [PMID: 34461263 DOI: 10.1016/j.annonc.2021.08.1993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 07/04/2021] [Accepted: 08/22/2021] [Indexed: 10/20/2022] Open
Affiliation(s)
- R Salgado
- Department of Pathology, GZA-ZNA Hospitals, Antwerp, Belgium; Division of Research, Peter MacCallum Cancer Centre, Melbourne, Australia.
| | - V Peg
- Universidad Autónoma de Barcelona, Barcelona, Spain; Department of Pathology, Vall D'Hebron University Hospital, Barcelona, Spain; Spanish Biomedical Research Network Centre in Oncology (CIBERONC), Madrid, Spain
| | - J Rüschoff
- Targos Molecular Pathology GmbH and Institute of Pathology Nordhessen, Kassel, Germany
| | - A Vincent-Salomon
- Department of Pathology and Department of Diagnostic and Theranostic Medicine, Institut Curie, PSL Research University, Paris, France
| | - I Castellano
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - S Perner
- Institute of Pathology, University Hospital of Schleswig-Holstein, Campus Lübeck, Lübeck, Germany; Pathology, Research Center Borstel, Leibniz Lung Center, Borstel, Germany
| | - K Van de Vijver
- Department of Pathology, Ghent University Hospital, Ghent, Belgium
| | - C M Quinn
- Department of Pathology, St. Vincent's University Hospital, Dublin and University College Dublin, Dublin, Ireland
| | - Z Varga
- Department of Pathology and Molecular Pathology, University Hospital Zurich, Zurich, Switzerland
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15
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Viswanathan K, Johncilla M. Highlights and Perspectives From a Collaborative Global Health Pathology Experience in Trinidad and Tobago. Am J Clin Pathol 2021; 156:340-349. [PMID: 33712837 DOI: 10.1093/ajcp/aqaa246] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVES Global health education is important during residency training in exposing doctors to conditions that are not common in the United States and developing their awareness of global health care disparities. Most medical decisions are based on results from anatomic or clinical pathology laboratories, which are essential services for appropriate medical care in international settings. Nevertheless, US pathology residency trainees have limited global health exposure and thus are rarely exposed to diagnostic services in these settings. Moreover, literature documenting what is needed to create a global health elective in pathology is limited. METHODS We designed an international pathology elective in Trinidad and Tobago involving one main public hospital site and several off-site laboratories. Objectives and goals were established before the rotation. Apart from daily mentor-led education sessions, the trainee participated in teaching, quality improvement projects, and cultural experiences. Engagement with medical officers, personnel staff, and people in the community was encouraged.Results: Challenges encountered included funding, transportation, limited laboratory resources, medical registration, and malpractice insurance. These were mitigated through carefully planned steps, including communicating with registration bodies and liaising with pathology organizations for funding. CONCLUSIONS Overall, the global health rotation was successful. We provide a detailed roadmap for other pathology training programs interested in establishing similar global health electives.
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Affiliation(s)
- Kartik Viswanathan
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | - Melanie Johncilla
- Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA
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16
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Pellegrino B, Hlavata Z, Migali C, De Silva P, Aiello M, Willard-Gallo K, Musolino A, Solinas C. Luminal Breast Cancer: Risk of Recurrence and Tumor-Associated Immune Suppression. Mol Diagn Ther 2021; 25:409-424. [PMID: 33974235 PMCID: PMC8249273 DOI: 10.1007/s40291-021-00525-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/12/2021] [Indexed: 12/24/2022]
Abstract
Hormone-receptor positive (HR+) breast cancer (BC) (including the luminal A and the luminal B subtypes) is the most common type of tumor in women diagnosed with early-stage BC (EBC). It represents a highly heterogeneous subgroup that is characterized by different risks of relapse. The aim of this review is to discuss the possible role played by the immune response in predicting this risk, along with the most common clinical and pathological factors and molecular tools that have been developed and are already in use. As opposed to what has previously been observed in the most aggressive human epidermal growth factor receptor 2 (HER2)-positive and triple-negative breast cancer (TNBC) subtypes, a high proportion of tumor-infiltrating lymphocytes (TILs)-reflecting a spontaneous and pre-existing immune response to the tumor-has been linked to a worse prognosis in HR+ EBC. This work provides some immune biological rationale explaining these findings and provides the basics to understand the principal clinical trials that are testing immunotherapy in HR+ (luminal) BC.
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Affiliation(s)
- Benedetta Pellegrino
- Department of Medicine and Surgery, University of Parma, Str. dell’Università, 12, 43121 Parma, PR Italy
- Medical Oncology and Breast Unit, University Hospital of Parma, Parma, Italy
| | - Zuzana Hlavata
- Department of Medical Oncology, CHR Mons-Hainaut, Avenue Baudouin de Constantinople, n. 5, Mons, Hainaut Belgium
| | | | - Pushpamali De Silva
- Wellman Center for Photomedicine, Department of Dermatology, Harvard Medical School and Massachusetts General Hospital, Boston, MA USA
| | - Marco Aiello
- Medical Oncology Unit, Azienda Ospedaliero-Universitaria Policlinico San Marco, Catania, Italy
| | | | - Antonino Musolino
- Department of Medicine and Surgery, University of Parma, Str. dell’Università, 12, 43121 Parma, PR Italy
- Medical Oncology and Breast Unit, University Hospital of Parma, Parma, Italy
| | - Cinzia Solinas
- Azienda Tutela della Salute Sardegna, Ospedale A. Segni, Ozieri, Italy
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17
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Concordance between results of inexpensive statistical models and multigene signatures in patients with ER+/HER2- early breast cancer. Mod Pathol 2021; 34:1297-1309. [PMID: 33558657 DOI: 10.1038/s41379-021-00743-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 01/06/2021] [Accepted: 01/06/2021] [Indexed: 12/20/2022]
Abstract
Multigene signatures (MGS) are used to guide adjuvant chemotherapy (aCT) decisions in patients diagnosed with estrogen receptor (ER)-positive HER2-negative early breast cancer. We used results from three MGS (Oncotype DX® (ODX), MammaPrint® (MP) or Prosigna®) and assessed the concordance between high or low risk of recurrence and the predicted risk of recurrence based on statistical models. In addition, we looked at the impact of MGS results on final aCT administration during the multidisciplinary meeting (MDM). We retrospectively included 129 patients with ER-positive HER2-negative early breast cancer for which MGS testing was performed after MDM at University Hospitals Leuven between May 2013 and April 2019 in case there was doubt about aCT recommendation. Tumor tissue was analyzed either by ODX (N = 44), MP (N = 28), or Prosigna® (N = 57). Eight statistical models were computed: Magee equations (ME), Memorial Sloan Kettering simplified risk score (MSK-SRS), Breast Cancer Recurrence Score Estimator (BCRSE), OncotypeDXCalculator (ODXC), new Adjuvant! Online (nAOL), Mymammaprint.com (MyMP), PREDICT, and SiNK. Concordance, negative percent agreement, and positive percent agreement were calculated. Of 129 cases, 53% were MGS low and 47% MGS high risk. Concordances of 100.0% were observed between risk results obtained by ODX and ME. For MP, BCRSE demonstrated the best concordance, and for Prosigna® the average of ME. Concordances of <50.0% were observed between risk results obtained by ODX and nAOL, ODX and MyMP, ODX and SiNK, MP and MSK-SRS, MP and nAOL, MP and MyMP, MP and SiNK, and Prosigna® and ODXC. Integration of MGS results during MDM resulted in change of aCT recommendation in 47% of patients and a 15% relative and 9% absolute reduction. In conclusion, statistical models, especially ME and BCRSE, can be useful in selecting ER-positive HER2-negative early breast cancer patients who may need MGS testing resulting in enhanced cost-effectiveness and reduced delay in therapeutic decision-making.
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Developing a clinical-pathologic model to predict genomic risk of recurrence in patients with hormone receptor positive, human epidermal growth factor receptor-2 negative, node negative breast cancer. Cancer Treat Res Commun 2021; 28:100401. [PMID: 34091374 DOI: 10.1016/j.ctarc.2021.100401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 05/07/2021] [Accepted: 05/16/2021] [Indexed: 12/09/2022]
Abstract
INTRODUCTION Patients with hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative, node negative (NN) breast cancer may be offered a gene expression profiling (GEP) test to determine recurrence risk and benefit of adjuvant chemotherapy. We developed a clinical-pathologic (CP) model to predict genomic recurrence risk and examined its performance characteristics. METHODS Patients diagnosed with HR-positive, HER2-negative, NN breast cancer with a tumour size < 30 mm and who underwent a GEP test [OncotypeDX or Prosigna] in Alberta from October 2017 through March 2019 were identified. Patients were classified as low or high genomic risk. Multivariable logistic regression analysis was performed to examine the associations of CP factors with genomic risk. A CP model was developed using coefficients of regression and sensitivity analyses were performed. RESULTS A total of 366 patients were eligible (135 were tested using OncotypeDX and 231 with Prosigna). Of these, 64 (17.5%) patients were classified as high genomic risk. On multivariable logistic regression, tumour size > 20 mm (odds ratio [OR], 3.58; 95% confidence interval [CI], 1.84-6.98; P<0.001), low expression of progesterone receptor (OR, 3.46; 95% CI, 1.76-6.82; P<0.001), and histological grade III (OR, 7.24; 95% CI, 3.82-13.70; P<0.001) predicted high genomic risk. A CP model using these variables was developed to provide a score of 0-4. A CP cut-point of 0, identified 56% of genomic low risk patients with a specificity of 98.4%. CONCLUSIONS A CP model could be used to narrow the population of breast cancer patients undergoing GEP testing.
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Dietzel M, Clauser P, Kapetas P, Schulz-Wendtland R, Baltzer PAT. Images Are Data: A Breast Imaging Perspective on a Contemporary Paradigm. ROFO-FORTSCHR RONTG 2021; 193:898-908. [PMID: 33535260 DOI: 10.1055/a-1346-0095] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Considering radiological examinations not as mere images, but as a source of data, has become the key paradigm in the diagnostic imaging field. This change of perspective is particularly popular in breast imaging. It allows breast radiologists to apply algorithms derived from computer science, to realize innovative clinical applications, and to refine already established methods. In this context, the terminology "imaging biomarker", "radiomics", and "artificial intelligence" are of pivotal importance. These methods promise noninvasive, low-cost (e. g., in comparison to multigene arrays), and workflow-friendly (automated, only one examination, instantaneous results, etc.) delivery of clinically relevant information. METHODS AND RESULTS This paper is designed as a narrative review on the previously mentioned paradigm. The focus is on key concepts in breast imaging and important buzzwords are explained. For all areas of breast imaging, exemplary studies and potential clinical use cases are discussed. CONCLUSION Considering radiological examination as a source of data may optimize patient management by guiding individualized breast cancer diagnosis and oncologic treatment in the age of precision medicine. KEY POINTS · In conventional breast imaging, examinations are interpreted based on patterns perceivable by visual inspection.. · The radiomics paradigm treats breast images as a source of data, containing information beyond what is visible to our eyes.. · This results in radiomic signatures that may be considered as imaging biomarkers, as they provide diagnostic, predictive, and prognostic information.. · Radiomics derived imaging biomarkers may be used to individualize breast cancer treatment in the era of precision medicine.. · The concept and key research of radiomics in the field of breast imaging will be discussed in this narrative review.. CITATION FORMAT · Dietzel M, Clauser P, Kapetas P et al. Images Are Data: A Breast Imaging Perspective on a Contemporary Paradigm. Fortschr Röntgenstr 2021; 193: 898 - 908.
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Affiliation(s)
| | - Paola Clauser
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria
| | - Panagiotis Kapetas
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria
| | | | - Pascal Andreas Thomas Baltzer
- Department of Biomedical Imaging and Image-Guided Therapy, Division of Molecular and Gender Imaging, Medical University Vienna, Vienna, Austria
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Magee Equations™ and response to neoadjuvant chemotherapy in ER+/HER2-negative breast cancer: a multi-institutional study. Mod Pathol 2021; 34:77-84. [PMID: 32661297 DOI: 10.1038/s41379-020-0620-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 06/29/2020] [Indexed: 11/09/2022]
Abstract
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.
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Prosigna® breast cancer assay: histopathologic correlation, development, and assessment of size, nodal status, Ki-67 (SiNK™) index for breast cancer prognosis. Mod Pathol 2021; 34:70-76. [PMID: 32740650 DOI: 10.1038/s41379-020-0643-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 12/11/2022]
Abstract
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.
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Remoué A, Conan-Charlet V, Deiana L, Tyulyandina A, Marcorelles P, Schick U, Uguen A. Breast cancer tumor heterogeneity has only little impact on the estimation of the Oncotype DX® recurrence score using Magee Equations and Magee Decision Algorithm™. Hum Pathol 2020; 108:51-59. [PMID: 33245987 DOI: 10.1016/j.humpath.2020.11.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 11/15/2020] [Indexed: 01/21/2023]
Abstract
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.
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Affiliation(s)
| | | | - Laura Deiana
- CHRU Brest, Institute of Oncology and Hematology, Brest, F-29220, France
| | | | | | - Ulrike Schick
- CHRU Brest, Department of Radiotherapy, Brest, F-29220, France
| | - Arnaud Uguen
- CHRU Brest, Department of Pathology, Brest, F-29220, France; Univ Brest, Inserm, CHU de Brest, LBAI, UMR1227, Brest, France.
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Glasgow A, Sechrist H, Bomeisl P, Gilmore H, Harbhajanka A. Correlation between modified Magee equation-2 and Oncotype-Dx recurrence scores using both traditional and TAILORx cutoffs and the clinical application of the Magee Decision Algorithm: a single institutional review. Breast Cancer 2020; 28:321-328. [PMID: 32951186 DOI: 10.1007/s12282-020-01163-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 09/11/2020] [Indexed: 01/30/2023]
Abstract
BACKGROUND Oncotype Dx (ODX) is used to predict recurrence risk for estrogen-positive (ER +), HER2-negative and lymph node negative breast cancer, however, due to the cost its use may be limited in low-resource areas. The aim of this study is to assess the concordance between the modified Magee Equation-2 (MME-2) and ODX recurrence scores (RS). The secondary aim is to apply the Magee Decision Algorithm (MDA) using the MME-2 to determine which patients are unlikely to benefit from ODX testing. METHODS All newly diagnosed ER + , HER2 negative, lymph node negative breast cancer patients with available ODX-RS from 2008-2018 were included. The original pathology reports were reviewed and chart review was performed. The MME-2 scores were calculated and correlated with the ODX-RS. The MDA was applied to our cohort to assess which patients would not benefit from ODX testing. RESULTS A total of 579 patients were included. There was an overall moderate correlation between ODX-RS and MME-2 score (Pearson correlation coefficient = 0.635). The overall concordance between ODX and MME-2 scores was similar when using both the traditional and TAILORx cutoffs (63.3% vs. 63.7%, respectively). Applying the MDA, for patients with MME-2 scores < 18, 96.8% of patients had the expected ODX-RS of < 25. For patients with MME-2 RS > 30, 90% had the expected ODX-RS of > 25. Concordance was highest in the high-risk category using both cutoffs. For patients with MME-2 18-25 and a mitotic score of 1, 88.8% had the expected ODX-RS of > 25. CONCLUSION There is a moderate correlation between MME-2 score and ODX-RS. The overall concordance was similar for both traditional and TAILORx cutoffs. The strongest concordance was found in the high-risk category for both cutoffs. The MME-2 can be used to identify patients unlikely to benefit from ODX testing using the MDA.
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Affiliation(s)
- Akisha Glasgow
- Department of Pathology, University Hospitals Cleveland Medical Center/Case Western Reserve University, Cleveland, Ohio, USA.
| | - Haley Sechrist
- School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Phillip Bomeisl
- Department of Pathology, University Hospitals Cleveland Medical Center/Case Western Reserve University, Cleveland, Ohio, USA
| | - Hannah Gilmore
- Department of Pathology, University Hospitals Cleveland Medical Center/Case Western Reserve University, Cleveland, Ohio, USA
| | - Aparna Harbhajanka
- Department of Pathology, University Hospitals Cleveland Medical Center/Case Western Reserve University, Cleveland, Ohio, USA
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