Evidence map›Paper›PMID 28548119›Full record

ArticleModern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc2017

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

Daniel J Farrugia, Alessandra Landmann, Li Zhu, Emilia J Diego, Ronald R Johnson, Marguerite Bonaventura, Atilla Soran, David J Dabbs, Beth Z Clark, Shannon L Puhalla and 6 more

Abstract read
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Article in Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Trial
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  9. Magee Equations™ and response to neoadjuvant chemotherapy in ER+/HER2-negative breast cancer: a multi-institutional study.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2021
    Article
  10. The healthcare value of the Magee Decision Algorithm™: use of Magee Equations™ and mitosis score to safely forgo molecular testing in breast cancer.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2020
    Article
  11. The Correlation of Magee EquationsEuropean journal of breast health · 2020
    Article
  12. Article
  13. Combined quantitative measures of ER, PR, HER2, and KI67 provide more prognostic information than categorical combinations in luminal breast cancer.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2019
    Article
  14. Breast cancer global tumor biomarkers: a quality assurance study of intratumoral heterogeneity.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2019
    Article
  15. Article
  16. Combined pathologic-genomic algorithm for early-stage breast cancer improves cost-effective use of the 21-gene recurrence score assay.Annals of oncology : official journal of the European Society for Medical Oncology · 2018
    Article
  17. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Daniel J FarrugiaDivision of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Alessandra LandmannDivision of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Li ZhuDepartment of Biostatistics University of Pittsburgh, Pittsburgh, PA, USA.
Emilia J DiegoDivision of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Ronald R JohnsonDivision of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Marguerite BonaventuraDivision of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Atilla SoranDivision of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
David J DabbsDivision of Breast and Gynecologic Pathology, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Beth Z ClarkDivision of Breast and Gynecologic Pathology, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Shannon L PuhallaDivision of Hematology/Oncology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Rachel C JankowitzDivision of Hematology/Oncology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Adam M BrufskyDivision of Hematology/Oncology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Barry C LemberskyDivision of Hematology/Oncology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Gretchen M AhrendtDivision of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Priscilla F McAuliffeDivision of Surgical Oncology, Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Rohit BhargavaDivision of Breast and Gynecologic Pathology, Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Magee Equations were derived as an inexpensive, rapid alternative to Oncotype DX. The Magee Equation 3 utilizes immunohistochemical and FISH data for estrogen receptor (ER), progesterone receptor (PR), HER2 and Ki-67 for its calculation (24.30812+ERIHC × (-0.02177)+PRIHC × (-0.02884)+(0 for HER2 negative, 1.46495 for equivocal, 12.75525 for HER2 positive)+Ki-67 × 0.18649). We hypothesize that Magee Equation 3 scores from pre-therapy core biopsy can predict response to neoadjuvant systemic chemotherapy. A prospectively-maintained database of patients who received neoadjuvant systemic therapy from 2010 to 2014 at a single institution was retrospectively reviewed. Pathologic complete response was defined as absence of invasive tumor in the breast and regional lymph nodes. Of the 614 cases, tumors with missing immunohistochemical results and those that were ER negative or HER2 positive were excluded. This resulted in 237 ER positive, HER2 negative/equivocal tumors that formed the basis of this study. Magee Equation 3 scores were divided into 3 categories similar to Oncotype DX, ie, 0 to <18 (low), 18 to <31 (intermediate), and 31 or higher (high) scores. The pathologic complete response rate for low, intermediate and high Magee Equation 3 scores was 0%, 4%, and 36%, respectively. Patients with high Magee Equation 3 scores were 13 times more likely to achieve pathologic complete response compared to those with Magee Equation 3 scores less than 31 (95% CI 5.09-32.87, P<0.0001). For patients that did not achieve pathologic complete response, high Magee Equation 3 correlated with higher recurrence rate, with the majority occurring in patients with positive lymph nodes in the resection specimen. Magee Equation 3 score ≥31 predicts pathologic complete response in the neoadjuvant setting and for tumor recurrence, when pathologic complete response is not achieved. These results show the utility of Magee Equation 3 in predicting patients who will benefit from chemotherapy but warrant prospective multi-institutional validation.

Indexed as

Decision Making, Computer-AssistedAdultAgedAntineoplastic AgentsBiomarkers, TumorBreast NeoplasmsChemotherapy, AdjuvantDisease-Free SurvivalErb-b2 Receptor Tyrosine KinasesFemaleHumansKaplan-Meier EstimateMiddle AgedMultivariate AnalysisNeoadjuvant TherapyReceptors, EstrogenAntineoplastic AgentsBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesReceptors, Estrogen

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.