Literature DB >> 21947677

Head-to-head comparison of the 70-gene signature versus the 21-gene assay: cost-effectiveness and the effect of compliance.

Valesca P Retèl1, Manuela A Joore, Wim H van Harten.   

Abstract

Both the 70-gene signature and the 21-gene assay are novel prognostic tests used to guide adjuvant chemotherapy decisions in patients with early breast cancer. Although the results of ongoing prospective trials will only become available in some years, the tests have already been included in clinical guidelines such as St. Gallen's. In literature, the cost-effectiveness (CE) of both tests as compared to conventional prognostic tests has been described. We report on a direct comparison of CE; as different compliance rates were reported, we also taken these into account. A Markov decision model with a time horizon of 20 years was developed to assess the effects, costs and CE of three alternatives; 21-gene, 70-gene, and St. Gallen (SG) or Adjuvant Online (AO), dependent on the dataset used in patients with early, node-negative, breast cancer. Sensitivity and specificity were based on two datasets, incorporating compliances rates based on literature. For both datasets, whereas the 70-gene signature yielded more quality adjusted life years (QALYs) and was less costly; the 21-gene amounted more life years (LYs) but was more costly. The decision uncertainty surrounding the probability of CE of the Thomassen-series amounted 55% for both cost/LY and cost/QALY, for the Fan-series 80% for LY and 65% for QALYs. Taking reported compliance with discordant test results into account, in general, the effect of all strategies decreased, while the costs increased, without relatively influencing the CEA performance. This comparison indicates that the performances of the 70-gene and the 21-gene based on reported studies are close. The 21-gene has the highest probability of being cost-effective when focusing on cost/LY, while focusing on cost/QALY, the 70-gene signature was most cost-effective. The level of compliance can have serious impact on the CE. With additional data, preferably from head-to-head outcome studies and especially on compliance concerning discordant test results, calculations can be made with higher degrees of certainty.

Entities:  

Mesh:

Year:  2011        PMID: 21947677     DOI: 10.1007/s10549-011-1769-7

Source DB:  PubMed          Journal:  Breast Cancer Res Treat        ISSN: 0167-6806            Impact factor:   4.872


  8 in total

Review 1.  Hormonal therapy in breast cancer: a model disease for the personalization of cancer care.

Authors:  Shannon Puhalla; Saveri Bhattacharya; Nancy E Davidson
Journal:  Mol Oncol       Date:  2012-02-24       Impact factor: 6.603

2.  Cost-Effectiveness Analyses of the 21-Gene Assay in Breast Cancer: Systematic Review and Critical Appraisal.

Authors:  Shi-Yi Wang; Weixiong Dang; Ilana Richman; Sarah S Mougalian; Suzanne B Evans; Cary P Gross
Journal:  J Clin Oncol       Date:  2018-04-16       Impact factor: 44.544

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

Review 4.  Is individualized medicine more cost-effective? A systematic review.

Authors:  Maximilian H M Hatz; Katharina Schremser; Wolf H Rogowski
Journal:  Pharmacoeconomics       Date:  2014-05       Impact factor: 4.981

5.  Innovations that reach the patient: early health technology assessment and improving the chances of coverage and implementation.

Authors:  W H van Harten; V P Retèl
Journal:  Ecancermedicalscience       Date:  2016-10-28

6.  Association of 70-Gene Signature Assay Findings With Physicians' Treatment Guidance for Patients With Early Breast Cancer Classified as Intermediate Risk by the 21-Gene Assay.

Authors:  Michaela Tsai; Shelly Lo; William Audeh; Rubina Qamar; Raye Budway; Ellis Levine; Pat Whitworth; Blanche Mavromatis; Robin Zon; Dwight Oldham; Sarah Untch; Tina Treece; Lisa Blumencranz; Hatem Soliman
Journal:  JAMA Oncol       Date:  2018-01-11       Impact factor: 31.777

7.  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

Review 8.  Multigene assays and molecular markers in breast cancer: systematic review of health economic analyses.

Authors:  Roman Rouzier; Paolo Pronzato; Elisabeth Chéreau; Josh Carlson; Barnaby Hunt; William J Valentine
Journal:  Breast Cancer Res Treat       Date:  2013-05-31       Impact factor: 4.872

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.