Literature DB >> 27595437

Adjust cut-off values of immunohistochemistry models to predict risk of distant recurrence in invasive breast carcinoma patients.

Yen-Ying Chen1, Ling-Ming Tseng2, Ching-Fen Yang1, Pei-Ju Lien3, Chih-Yi Hsu4.   

Abstract

BACKGROUND: Multigene assays are recommended for hormone receptor-positive invasive breast carcinoma to determine the risk of recurrence, but they are highly expensive. We investigated the prognostic values of immunohistochemistry (IHC)-based prognostic models as an alternative to multigene assays.
METHODS: The risk categories estimated by the IHC-based prognostic models were correlated to those estimated by the multigene assays in 71 cases and the follow-up results in 642 consecutive cases of HER2- luminal-type early breast cancer. Cut-off values of IHC-based models were adjusted based on survival outcome to reveal maximum Harrell C index or based on the maximum positive likelihood ratio correlated to multigene assay.
RESULTS: All investigated IHC-based models could predict the risk of distant recurrence, but their cut-off values required adjustment. Using distant recurrence-free survival (DRFS) to refine the cut-off values could improve the prognostic values. Adjusting the cut-off values using the results of multigene assays, the positive predictive values of an estimate of low risk or low recurrence score (≤ 21) were higher than 90%. On average, 23% of cases got different results of risk assessment after adjustment. Although cut-off values adjusted by multigene assay were not identical to those refined by survival, the adjusted values (17.1 and 23.8) and the refined values (17.5 and 24.5) of the best model (Magee Eq. 1) were close. Among all the evaluated models, Magee equation 2 was the only one without Ki67, and its prognostic values were the lowest. Using 20% as cut-off for Ki67 as suggested by St. Gallen consensus, we could confidently define luminal A cancer.
CONCLUSION: It is necessary to adjust the cut-off values of IHC-based prognostic models to fit the purpose. If the estimated risk is clearly high or low, it may be reasonable to omit multigene assays when cost is a consideration. Copyright Â
© 2016. Published by Elsevier Taiwan LLC.

Entities:  

Keywords:  breast neoplasms; gene expression profiling; immunohistochemistry; prognosis

Mesh:

Substances:

Year:  2016        PMID: 27595437     DOI: 10.1016/j.jcma.2016.06.004

Source DB:  PubMed          Journal:  J Chin Med Assoc        ISSN: 1726-4901            Impact factor:   2.743


  4 in total

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

Authors:  Rohit Bhargava; Nicole N Esposito; Siobhan M OʹConnor; Zaibo Li; Bradley M Turner; Ioana Moisini; Aditi Ranade; Ronald P Harris; Dylan V Miller; Xiaoxian Li; Harrison Moosavi; Beth Z Clark; Adam M Brufsky; David J Dabbs
Journal:  Mod Pathol       Date:  2020-07-13       Impact factor: 7.842

2.  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.

Authors:  Rohit Bhargava; Beth Z Clark; David J Dabbs
Journal:  Am J Clin Pathol       Date:  2019-02-04       Impact factor: 2.493

3.  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.

Authors:  Atilla Soran; Kaori Tane; Efe Sezgin; Rohit Bhargava
Journal:  Eur J Breast Health       Date:  2020-04-01

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

Authors:  Rohit Bhargava; Beth Z Clark; Gloria J Carter; Adam M Brufsky; David J Dabbs
Journal:  Mod Pathol       Date:  2020-03-17       Impact factor: 7.842

  4 in total

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