Literature DB >> 27130929

Comparing Breast Cancer Multiparameter Tests in the OPTIMA Prelim Trial: No Test Is More Equal Than the Others.

John M S Bartlett1, Jane Bayani2, Andrea Marshall2, Janet A Dunn2, Amy Campbell2, Carrie Cunningham2, Monika S Sobol2, Peter S Hall2, Christopher J Poole2, David A Cameron2, Helena M Earl2, Daniel W Rea2, Iain R Macpherson2, Peter Canney2, Adele Francis2, Christopher McCabe2, Sarah E Pinder2, Luke Hughes-Davies2, Andreas Makris2, Robert C Stein2.   

Abstract

BACKGROUND: Previous reports identifying discordance between multiparameter tests at the individual patient level have been largely attributed to methodological shortcomings of multiple in silico studies. Comparisons between tests, when performed using actual diagnostic assays, have been predicted to demonstrate high degrees of concordance. OPTIMA prelim compared predicted risk stratification and subtype classification of different multiparameter tests performed directly on the same population.
METHODS: Three hundred thirteen women with early breast cancer were randomized to standard (chemotherapy and endocrine therapy) or test-directed (chemotherapy if Oncotype DX recurrence score >25) treatment. Risk stratification was also determined with Prosigna (PAM50), MammaPrint, MammaTyper, NexCourse Breast (IHC4-AQUA), and conventional IHC4 (IHC4). Subtype classification was provided by Blueprint, MammaTyper, and Prosigna.
RESULTS: Oncotype DX predicted a higher proportion of tumors as low risk (82.1%, 95% confidence interval [CI] = 77.8% to 86.4%) than were predicted low/intermediate risk using Prosigna (65.5%, 95% CI = 60.1% to 70.9%), IHC4 (72.0%, 95% CI = 66.5% to 77.5%), MammaPrint (61.4%, 95% CI = 55.9% to 66.9%), or NexCourse Breast (61.6%, 95% CI = 55.8% to 67.4%). Strikingly, the five tests showed only modest agreement when dichotomizing results between high vs low/intermediate risk. Only 119 (39.4%) tumors were classified uniformly as either low/intermediate risk or high risk, and 183 (60.6%) were assigned to different risk categories by different tests, although 94 (31.1%) showed agreement between four of five tests. All three subtype tests assigned 59.5% to 62.4% of tumors to luminal A subtype, but only 121 (40.1%) were classified as luminal A by all three tests and only 58 (19.2%) were uniformly assigned as nonluminal A. Discordant subtyping was observed in 123 (40.7%) tumors.
CONCLUSIONS: Existing evidence on the comparative prognostic information provided by different tests suggests that current multiparameter tests provide broadly equivalent risk information for the population of women with estrogen receptor (ER)-positive breast cancers. However, for the individual patient, tests may provide differing risk categorization and subtype information.
© The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Year:  2016        PMID: 27130929      PMCID: PMC5939629          DOI: 10.1093/jnci/djw050

Source DB:  PubMed          Journal:  J Natl Cancer Inst        ISSN: 0027-8874            Impact factor:   13.506


  30 in total

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5.  Supervised risk predictor of breast cancer based on intrinsic subtypes.

Authors:  Joel S Parker; Michael Mullins; Maggie C U Cheang; Samuel Leung; David Voduc; Tammi Vickery; Sherri Davies; Christiane Fauron; Xiaping He; Zhiyuan Hu; John F Quackenbush; Inge J Stijleman; Juan Palazzo; J S Marron; Andrew B Nobel; Elaine Mardis; Torsten O Nielsen; Matthew J Ellis; Charles M Perou; Philip S Bernard
Journal:  J Clin Oncol       Date:  2009-02-09       Impact factor: 44.544

6.  OPTIMA prelim: a randomised feasibility study of personalised care in the treatment of women with early breast cancer.

Authors:  Robert C Stein; Janet A Dunn; John M S Bartlett; Amy F Campbell; Andrea Marshall; Peter Hall; Leila Rooshenas; Adrienne Morgan; Christopher Poole; Sarah E Pinder; David A Cameron; Nigel Stallard; Jenny L Donovan; Christopher McCabe; Luke Hughes-Davies; Andreas Makris
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7.  Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement.

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10.  The agreement chart.

Authors:  Shrikant I Bangdiwala; Viswanathan Shankar
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2.  Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

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3.  [Update of the German S3 breast cancer guideline : What is new for pathologists?]

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Authors:  F Cardoso; J M S Bartlett; L Slaets; C H M van Deurzen; E van Leeuwen-Stok; P Porter; B Linderholm; I Hedenfalk; C Schröder; J Martens; J Bayani; C van Asperen; M Murray; C Hudis; L Middleton; J Vermeij; K Punie; J Fraser; M Nowaczyk; I T Rubio; S Aebi; C Kelly; K J Ruddy; E Winer; C Nilsson; L Dal Lago; L Korde; K Benstead; O Bogler; T Goulioti; A Peric; S Litière; K C Aalders; C Poncet; K Tryfonidis; S H Giordano
Journal:  Ann Oncol       Date:  2018-02-01       Impact factor: 32.976

Review 5.  Clinical utility of gene-expression signatures in early stage breast cancer.

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Review 8.  Genomic Signatures in Luminal Breast Cancer.

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10.  Effect of the Expression of ELOVL5 and IGFBP6 Genes on the Metastatic Potential of Breast Cancer Cells.

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