Literature DB >> 18457476

Impact of gene expression profiling tests on breast cancer outcomes.

Luigi Marchionni, Renee F Wilson, Spyridon S Marinopoulos, Antonio C Wolff, Giovanni Parmigiani, Eric B Bass, Steven N Goodman.   

Abstract

OBJECTIVES: To assess the evidence that three marketed gene expression-based assays improve prognostic accuracy, treatment choice, and health outcomes in women diagnosed with early stage breast cancer. REVIEW
METHODS: We evaluated the evidence for three gene expression assays on the market; Oncotype DX, MammaPrint and the Breast Cancer Profiling (BCP or H/I ratio) test, and for gene expression signatures underlying the assays. We sought evidence on: analytic performance of tests, clinical validity (i.e., prognostic accuracy and discrimination), clinical utility (i.e., prediction of treatment benefit), harms, impact on clinical decision making and health care costs.
RESULTS: Few papers were found on the analytic validity of the Oncotype DX and MammaPrint tests, but these showed reasonable within-laboratory replicability. Pre-analytic issues related to sample storage and preparation may play a larger role than within-laboratory variation. For clinical validity, studies differed according to whether they examined the actual test that is currently being offered to patients or the underlying gene signature. Almost all of the Oncotype DX evidence was for the marketed test, the strongest validation study being from one arm of a randomized controlled trial (NSABP-14) with a clinically homogeneous population. This study showed that the test, added in a clinically meaningful manner to standard prognostic indices. The MammaPrint signature and test itself was examined in studies with clinically heterogeneous populations (e.g., mix of ER positivity and tamoxifen treatment) and showed a clinically relevant separation of patients into risk categories, but it was not clear exactly how many predictions would be shifted across decision thresholds if this were used in combination with traditional indices. The BCP test itself was examined in one study, and the signature was tested in a variety of formulations in several studies. One randomized controlled trial provided high quality retrospective evidence of the clinical utility of Oncotype DX to predict chemotherapy treatment benefit, but evidence for clinical utility was not found for MammaPrint or the H/I ratio. Three decision analyses examined the cost-effectiveness of breast cancer gene expression assays, and overall were inconclusive.
CONCLUSIONS: Oncotype DX is furthest along the validation pathway, with strong retrospective evidence that it predicts distant spread and chemotherapy benefit to a clinically relevant extent over standard predictors, in a well-defined clinical subgroup with clear treatment implications. The evidence for clinical implications of using MammaPrint was not as clear as with Oncotype DX, and the ability to predict chemotherapy benefit does not yet exist. The H/I ratio test requires further validation. For all tests, the relationship of predicted to observed risk in different populations still needs further study, as does their incremental contribution, optimal implementation, and relevance to patients on current therapies.

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Mesh:

Year:  2007        PMID: 18457476      PMCID: PMC4781418     

Source DB:  PubMed          Journal:  Evid Rep Technol Assess (Full Rep)        ISSN: 1530-4396


  26 in total

1.  Pharmacogenomics, evidence, and the role of payers.

Authors:  P A Deverka
Journal:  Public Health Genomics       Date:  2009-02-10       Impact factor: 2.000

2.  Patients' perceptions of gene expression profiling in breast cancer treatment decisions.

Authors:  Y Bombard; L Rozmovits; M E Trudeau; N B Leighl; K Deal; D A Marshall
Journal:  Curr Oncol       Date:  2014-04       Impact factor: 3.677

3.  The value of personalizing medicine: medical oncologists' views on gene expression profiling in breast cancer treatment.

Authors:  Yvonne Bombard; Linda Rozmovits; Maureen Trudeau; Natasha B Leighl; Ken Deal; Deborah A Marshall
Journal:  Oncologist       Date:  2015-03-06

4.  Breast cancer metastasis and the lymphatic system.

Authors:  Munazzah Rahman; Sulma Mohammed
Journal:  Oncol Lett       Date:  2015-07-13       Impact factor: 2.967

5.  Is extracapsular tumour spread a prognostic factor in patients with early breast cancer?

Authors:  Erion Dobi; Fernando Bazan; Armelle Dufresne; Martin Demarchi; Cristian Villanueva; Loic Chaigneau; Philipe Montcuquet; Arben Ivanaj; Jean Loup Sautière; Yolande Maisonnette-Escot; Laurent Cals; Marie Paule Algros; Anne-Sophie Woronoff; Xavier Pivot
Journal:  Int J Clin Oncol       Date:  2012-07-05       Impact factor: 3.402

6.  Comparing transcription rate and mRNA abundance as parameters for biochemical pathway and network analysis.

Authors:  Brewster Hayles; Sailu Yellaboina; Degeng Wang
Journal:  PLoS One       Date:  2010-03-26       Impact factor: 3.240

7.  Gene expression profiling for guiding adjuvant chemotherapy decisions in women with early breast cancer: an evidence-based and economic analysis.

Authors: 
Journal:  Ont Health Technol Assess Ser       Date:  2010-12-01

8.  Quantitation of fixative-induced morphologic and antigenic variation in mouse and human breast cancers.

Authors:  Robert D Cardiff; Neil E Hubbard; Jesse A Engelberg; Robert J Munn; Claramae H Miller; Judith E Walls; Jane Q Chen; Héctor A Velásquez-García; Jose J Galvez; Katie J Bell; Laurel A Beckett; Yue-Ju Li; Alexander D Borowsky
Journal:  Lab Invest       Date:  2013-02-11       Impact factor: 5.662

9.  Sample parameters affecting the clinical relevance of RNA biomarkers in translational breast cancer research.

Authors:  Vassiliki Kotoula; Konstantine T Kalogeras; George Kouvatseas; Despoina Televantou; Ralf Kronenwett; Ralph M Wirtz; George Fountzilas
Journal:  Virchows Arch       Date:  2012-12-20       Impact factor: 4.064

10.  Access to personalized medicine: factors influencing the use and value of gene expression profiling in breast cancer treatment.

Authors:  Y Bombard; L Rozmovits; M Trudeau; N B Leighl; K Deal; D A Marshall
Journal:  Curr Oncol       Date:  2014-06       Impact factor: 3.677

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