Literature DB >> 16024969

Gene expression profiling and breast cancer care: what are the potential benefits and policy implications?

Nina Oestreicher1, Scott D Ramsey, Hannah M Linden, Jeannine S McCune, Laura J van't Veer, Wylie Burke, David L Veenstra.   

Abstract

PURPOSE: Gene expression profiling has been proposed as an alternative to clinical guidelines to identify high-risk patients for adjuvant chemotherapy. However, the outcomes associated with gene expression profiling are not clear, and guidelines for the appropriate use of genomic technologies have not been established.
METHODS: We developed a decision analytic model to evaluate the incremental cost and quality-adjusted life years of gene expression profiling versus NIH clinical guidelines in a hypothetical cohort of premenopausal early stage breast cancer patients 44 years of age. We conducted empirical analyses and identified literature-based data to inform the model, and performed probabilistic sensitivity analyses to evaluate uncertainty in the results. We interpreted the implications of our findings for treatment guidelines and policies.
RESULTS: Use of gene expression profiling resulted in an absolute 5% decrease in the proportion of cases of distant recurrence prevented, 0.21 fewer quality-adjusted life years, and a cost savings of USD 2882. The chosen test cutoff value to identify a tumor as poor prognosis and the cost of adjuvant chemotherapy were the most influential parameters in the analysis, but our findings did not change substantially in sensitivity analyses. Regardless of the test cutoff used to identify a poor prognosis tumor, the gene expression profiling assay studied in our analysis, at its current level of performance, did not attain the threshold sensitivity (95%) necessary to produce equal or greater quality-adjusted life years than NIH guidelines.
CONCLUSION: Although the use of gene expression profiling in breast cancer care holds great promise, our analysis suggests additional refinement and validation are needed before use in clinical practice.

Entities:  

Mesh:

Year:  2005        PMID: 16024969     DOI: 10.1097/01.gim.0000170776.31248.75

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.822


  20 in total

Review 1.  Review on early technology assessments of nanotechnologies in oncology.

Authors:  Valesca P Retèl; Marjan J M Hummel; Wim H van Harten
Journal:  Mol Oncol       Date:  2009-05-20       Impact factor: 6.603

2.  Genomic testing and therapies for breast cancer in clinical practice.

Authors:  Jennifer S Haas; Kathryn A Phillips; Su-Ying Liang; Michael J Hassett; Carol Keohane; Elena B Elkin; Joanne Armstrong; Michele Toscano
Journal:  J Oncol Pract       Date:  2011-05       Impact factor: 3.840

3.  Cost-Effectiveness of a Biopsy-Based 8-Protein Prostate Cancer Prognostic Assay to Optimize Treatment Decision Making in Gleason 3 + 3 and 3 + 4 Early Stage Prostate Cancer.

Authors:  Joshua A Roth; Scott D Ramsey; Josh J Carlson
Journal:  Oncologist       Date:  2015-10-19

4.  Gene expression profile testing for breast cancer and the use of chemotherapy, serious adverse effects, and costs of care.

Authors:  Jennifer S Haas; Su-Ying Liang; Michael J Hassett; Stephen Shiboski; Elena B Elkin; Kathryn A Phillips
Journal:  Breast Cancer Res Treat       Date:  2011-06-17       Impact factor: 4.872

5.  Comparative effectiveness of next generation genomic sequencing for disease diagnosis: design of a randomized controlled trial in patients with colorectal cancer/polyposis syndromes.

Authors:  Carlos J Gallego; Caroline S Bennette; Patrick Heagerty; Bryan Comstock; Martha Horike-Pyne; Fuki Hisama; Laura M Amendola; Robin L Bennett; Michael O Dorschner; Peter Tarczy-Hornoch; William M Grady; S Malia Fullerton; Susan B Trinidad; Dean A Regier; Deborah A Nickerson; Wylie Burke; Donald L Patrick; Gail P Jarvik; David L Veenstra
Journal:  Contemp Clin Trials       Date:  2014-07-03       Impact factor: 2.226

6.  The value of comparative effectiveness research: projected return on investment of the RxPONDER trial (SWOG S1007).

Authors:  William B Wong; Scott D Ramsey; William E Barlow; Louis P Garrison; David L Veenstra
Journal:  Contemp Clin Trials       Date:  2012-08-18       Impact factor: 2.226

7.  Value-of-information analysis within a stakeholder-driven research prioritization process in a US setting: an application in cancer genomics.

Authors:  Josh J Carlson; Rahber Thariani; Josh Roth; Julie Gralow; N Lynn Henry; Laura Esmail; Pat Deverka; Scott D Ramsey; Laurence Baker; David L Veenstra
Journal:  Med Decis Making       Date:  2013-05       Impact factor: 2.583

8.  A Framework for Prioritizing Research Investments in Precision Medicine.

Authors:  Anirban Basu; Josh J Carlson; David L Veenstra
Journal:  Med Decis Making       Date:  2015-10-26       Impact factor: 2.583

9.  Adoption of gene expression profile testing and association with use of chemotherapy among women with breast cancer.

Authors:  Michael J Hassett; Samuel M Silver; Melissa E Hughes; Douglas W Blayney; Stephen B Edge; James G Herman; Clifford A Hudis; P Kelly Marcom; Jane E Pettinga; David Share; Richard Theriault; Yu-Ning Wong; Jonathan L Vandergrift; Joyce C Niland; Jane C Weeks
Journal:  J Clin Oncol       Date:  2012-05-14       Impact factor: 44.544

Review 10.  The impact of the Oncotype Dx breast cancer assay in clinical practice: a systematic review and meta-analysis.

Authors:  Josh J Carlson; Joshua A Roth
Journal:  Breast Cancer Res Treat       Date:  2013-08-24       Impact factor: 4.872

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.