The Gene Expression Profiling in Early-Stage Breast Cancer Risk-Benefit Analysis Case Study

One component of the project described above is applying RBA methods to assess the clinical benefits, harms, and uncertainty associated with the use of gene expression profiling (GEP) to inform adjuvant chemotherapy decisions in patients with early-stage breast cancer.  Adjuvant chemotherapy can reduce the risk of disease recurrence in women who have undergone mastectomy or lumpectomy and radiation therapy to treat early-stage breast cancer. [1] However, a large proportion of women who receive standard adjuvant chemotherapy regimens experience adverse events, and subsequent declines in health related quality of life. [2] As a result of these factors, ongoing efforts are focused on identifying risk stratification strategies that identify high-risk women to receive adjuvant chemotherapy, and spare low-risk women the toxicity and health related quality of life impacts associated with chemotherapy.  A standard approach to risk stratification of this nature is the National Comprehensive Cancer Network (NCCN) guidelines. [3] The NCCN guidelines utilize demographic and clinical information to inform decisions about which patients should undergo adjuvant chemotherapy and which should not. [3] An alternative risk stratification approach, GEP, involves the use of genetic information from tumor samples to classify patients into different risk groups. Two prominent examples of GEP tests are MammaPrint® and Oncotype Dx®.

Gene Expression Profiling Research to Date

Much of the research about GEP in early stage breast cancer has focused on two tests, Oncotype Dx® and MammaPrint®. Oncotype Dx® utilizes a 21-gene signature to stratify patients into one of three recurrence risk groups: low risk, intermediate risk, or high risk. MammaPrint® utilizes a 70-gene signature to stratify patients into one of two recurrence groups: low risk or high risk. In each respective GEP testing strategy, intermediate and high-risk patients typically receive adjuvant chemotherapy, while low-risk patients do not. Retrospective analyses have demonstrated the prognostic validity of both tests in identifying patients at elevated risk for recurrence. [4,5]. Additionally, a retrospective analysis has demonstrated the predictive validity of Oncotype Dx® to discern which patients derive the greatest benefit from adjuvant chemotherapy. [6] However, to date, no randomized clinical trial results have been reported evaluating the health outcomes of testing relative to standard approaches that utilize demographic and clinical information, like NCCN guidelines.  

Motivation for Developing a GEP in Early-Stage Breast Cancer Risk-Benefit Analysis Model

The uncertainty surrounding the current level of evidence for GEP, lack of consensus on what constitutes clinically significant outcome improvement based on GEP, and lack of a formalized process to evaluate these factors, highlight the need for additional tools to aid stakeholders in making decisions about the clinical application of GEP. The linked excel-based GEP risk-benefit analysis model seeks to serve this important function. Using this model, stakeholders can examine quantitative estimates of the clinical utility of GEP in a variety of plausible scenarios.

GEP in Early-Stage Breast Cancer Risk-Benefit Analysis Model


[1] Early Breast Cancer Trialists' Collaborative Group (EBCTCG). Effects of Chemotherapy and Hormonal Therapy for Early Breast Cancer on Recurrence and 15-Year Survival: An Overview of the Randomized Trials. Lancet. 2005; 365: 1687-1717.

[2] Cole BF et al. Polychemotherapy for early breast cancer: an overview of the randomized clinical trials with quality-adjusted survival analysis. Lancet. 2001; 358: 277-286.

[3] National Comprehensive Cancer Network. Breast Cancer, Version 2. Clinical Practice Guidelines in Oncology, v.2.2010.

[4]Buyse M et al. Validation and Clinical Utility of a 70-Gene Prognostic Signature for Women With Node-Negative Breast Cancer. Journal of the National Cancer Institute. 2006; 98(17): 1183-1192.

[5] Paik S. et al. A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer. New England Journal of Medicine. 2004; 351: 2817-2826.

[6] Paik S. et al. Gene Expression and Benefit of Chemotherapy in Women With Node-Negative, Estrogen Receptor-Positive Breast Cancer. Journal of Clinical Oncology. 2006; 24(23): 1-12.





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