Literature DB >> 22359236

Cost effectiveness of gene expression profiling for early stage breast cancer: a decision-analytic model.

Mo Yang1, Suja Rajan, Amalia M Issa.   

Abstract

BACKGROUND: Gene expression profiling (GEP) is being used increasingly for risk stratification to identify women with lymph node-negative, estrogen receptor-positive, early stage breast cancer who are most likely to benefit from adjuvant chemotherapy. The authors of this report evaluated the cost effectiveness of recurrence score-guided treatment using 2 commercially available GEP tests, Oncotype DX (Genomic Health, Redwood City, Calif) and MammaPrint (Agendia Inc., Irvine, Calif), from a third-party payer's perspective.
METHODS: A 10-year Markov model was developed to compare the costs and quality-adjusted life-years (QALYs) of treatment decisions guided by either Oncotype DX or MammaPrint in a hypothetical cohort of women with early stage, lymph node-negative, estrogen receptor-positive breast cancer who may experience recurrence. Outcomes included no recurrence, recurrence, and death. The costs considered included gene test costs, the costs of adjuvant chemotherapy and other chemotherapy (including premedication, oncology visits, and monitoring for adverse events), the cost of treating recurrence, costs associated with the treatment of adverse events, and end-of-life care costs.
RESULTS: The model demonstrated that the patients who received the Oncotype DX test to guide treatment spent $27,882 (in US dollars) and gained 7.364 QALYs, whereas patients who received the MammaPrint test to guide treatment spent $21,598 and gained 7.461 QALYs. Sensitivity analyses demonstrated that the results were robust to changes in all parameters.
CONCLUSIONS: The model suggested that MammaPrint is a more cost-effective GEP test compared with Oncotype DX at a threshold willingness-to-pay of $50,000 per QALY. Because Oncotype DX is the most frequently used GEP in clinical practice in the United States, the authors concluded that the current findings have implications for health policy, particularly health insurance reimbursement decisions.
Copyright © 2012 American Cancer Society.

Entities:  

Mesh:

Year:  2012        PMID: 22359236     DOI: 10.1002/cncr.27443

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  21 in total

1.  Modern Risk Assessment for Individualizing Treatment Concepts in Early-stage Breast Cancer.

Authors:  Alex Farr; Rachel Wuerstlein; Annika Heiduschka; Christian F Singer; Nadia Harbeck
Journal:  Rev Obstet Gynecol       Date:  2013

Review 2.  Genome-based risk prediction for early stage breast cancer.

Authors:  Christina Adaniel; Komal Jhaveri; Adriana Heguy; Francisco J Esteva
Journal:  Oncologist       Date:  2014-09-03

Review 3.  Diagnostic tests based on gene expression profile in breast cancer: from background to clinical use.

Authors:  Laura Zanotti; Alberto Bottini; Camillo Rossi; Daniele Generali; Maria Rosa Cappelletti
Journal:  Tumour Biol       Date:  2014-07-23

4.  Exploring the potential cost-effectiveness of precision medicine treatment strategies for diffuse large B-cell lymphoma.

Authors:  Qiushi Chen; Ashley D Staton; Turgay Ayer; Daniel A Goldstein; Jean L Koff; Christopher R Flowers
Journal:  Leuk Lymphoma       Date:  2017-10-25

5.  Prospective, multicenter study on the economic and clinical impact of gene-expression assays in early-stage breast cancer from a single region: the PREGECAM registry experience.

Authors:  S Pérez Ramírez; M Del Monte-Millán; S López-Tarruella; N Martínez Jáñez; I Márquez-Rodas; F Lobo Samper; Y Izarzugaza Perón; C Rubio Terres; D Rubio Rodríguez; J Á García-Sáenz; F Moreno Antón; P Zamora Auñón; M Arroyo Yustos; M Á Lara Álvarez; E M Ciruelos Gil; L Manso Sánchez; M J Echarri González; J A Guerra Martínez; C Jara Sánchez; C Bueno Muiño; S García Adrián; J R Carrión Galindo; V Valentín Maganto; M Martín
Journal:  Clin Transl Oncol       Date:  2019-07-12       Impact factor: 3.405

Review 6.  Clinical utility of gene-expression signatures in early stage breast cancer.

Authors:  Maryann Kwa; Andreas Makris; Francisco J Esteva
Journal:  Nat Rev Clin Oncol       Date:  2017-05-31       Impact factor: 66.675

7.  Adjuvant Chemotherapy Use and Health Care Costs After Introduction of Genomic Testing in Breast Cancer.

Authors:  Andrew J Epstein; Yu-Ning Wong; Nandita Mitra; Anil Vachani; Sakhena Hin; Lin Yang; Aaron Smith-McLallen; Katrina Armstrong; Peter W Groeneveld
Journal:  J Clin Oncol       Date:  2015-11-23       Impact factor: 44.544

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.  Gene Expression Profiling Tests for Early-Stage Invasive Breast Cancer: A Health Technology Assessment.

Authors: 
Journal:  Ont Health Technol Assess Ser       Date:  2020-03-06

10.  Treatment Choices Based on OncotypeDx in the Breast Oncology Care Setting.

Authors:  Teri L Malo; Isaac Lipkus; Tobi Wilson; Hyo S Han; Geza Acs; Susan T Vadaparampil
Journal:  J Cancer Epidemiol       Date:  2012-08-13
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