Literature DB >> 29659329

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

Shi-Yi Wang1, Weixiong Dang1, Ilana Richman1, Sarah S Mougalian1, Suzanne B Evans1, Cary P Gross1.   

Abstract

Purpose Prior studies examining cost effectiveness of the 21-gene assay (Oncotype DX [ODX]) for women with hormone receptor-positive, early-stage breast cancer have yielded disparate results. We aimed to explore why these analyses may have yielded different conclusions. Methods We conducted a systematic literature review of cost-effectiveness analyses (CEAs) of ODX. We examined the extent to which the structure of CEA modeling, the assumptions of the models, and the selection of input parameters influenced cost-effectiveness estimates. We also explored the prevalence of industry funding and whether industry funding was associated with study designs favoring ODX. Results We identified 27 analyses, 15 of which received industry funding. In 18 studies, the clinical characteristics (eg, tumor size and grade) commonly used to make chemotherapy decisions were not incorporated into simulation modeling; thus, these studies would favor ODX being cost effective and might not reflect clinical practice. Most studies ignored the heterogeneous effect of ODX on chemotherapy use; only five studies assumed that ODX would increase chemotherapy use for clinically low-risk patients but decrease chemotherapy use for clinically high-risk patients. No study used population-based joint distributions of ODX recurrence score and tumor characteristics, and 12 studies inappropriately assumed that chemotherapy would increase distant recurrence for the low recurrence score group; both approaches overestimated the benefits of ODX. Industry-funded studies tended to favor ODX; all five studies that reported ODX as being cost saving were industry funded. In contrast, two studies that reported an incremental cost-effectiveness ratio > $50,000 per quality-adjusted life-year were not funded by industry. Conclusion Although a majority of published analyses indicated that ODX is cost effective, they incorporated study designs that can increase the risk of bias.

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Year:  2018        PMID: 29659329      PMCID: PMC5978470          DOI: 10.1200/JCO.2017.76.5941

Source DB:  PubMed          Journal:  J Clin Oncol        ISSN: 0732-183X            Impact factor:   44.544


  55 in total

Review 1.  Financial relationships in economic analyses of targeted therapies in oncology.

Authors:  Antonis Valachis; Nikolaos P Polyzos; Andreas Nearchou; Pehr Lind; Davide Mauri
Journal:  J Clin Oncol       Date:  2012-03-19       Impact factor: 44.544

Review 2.  Clinical validity/utility, change in practice patterns, and economic implications of risk stratifiers to predict outcomes for early-stage breast cancer: a systematic review.

Authors:  John Hornberger; Michael D Alvarado; Chien Rebecca; Hialy R Gutierrez; Tiffany M Yu; William J Gradishar
Journal:  J Natl Cancer Inst       Date:  2012-07-05       Impact factor: 13.506

3.  Economic implications of 21-gene recurrence score assay: US multicenter experience.

Authors:  John Hornberger; Gary H Lyman; Rebecca Chien
Journal:  J Clin Oncol       Date:  2010-05-24       Impact factor: 44.544

4.  Cost-effectiveness of 21-gene assay in node-positive, early-stage breast cancer.

Authors:  Burton F Vanderlaan; Michael S Broder; Eunice Y Chang; Ruth Oratz; Tanya G K Bentley
Journal:  Am J Manag Care       Date:  2011       Impact factor: 2.229

5.  Impact of a 21-gene RT-PCR assay on treatment decisions in early-stage breast cancer: an economic analysis based on prognostic and predictive validation studies.

Authors:  Gary H Lyman; Leon E Cosler; Nicole M Kuderer; John Hornberger
Journal:  Cancer       Date:  2007-03-15       Impact factor: 6.860

6.  Economic implications of 21-gene breast cancer risk assay from the perspective of an Israeli-managed health-care organization.

Authors:  Shmuel H Klang; Ariel Hammerman; Nicky Liebermann; Noa Efrat; Julie Doberne; John Hornberger
Journal:  Value Health       Date:  2010-04-15       Impact factor: 5.725

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

Review 8.  Is the 21-gene recurrence score a cost-effective assay in endocrine-sensitive node-negative breast cancer?

Authors:  Nathan W D Lamond; Chris Skedgel; Tallal Younis
Journal:  Expert Rev Pharmacoecon Outcomes Res       Date:  2013-04       Impact factor: 2.217

9.  Cost-effectiveness of the 21-gene assay for guiding adjuvant chemotherapy decisions in early breast cancer.

Authors:  Mike Paulden; Jacob Franek; Ba' Pham; Philippe L Bedard; Maureen Trudeau; Murray Krahn
Journal:  Value Health       Date:  2013-07-01       Impact factor: 5.725

10.  Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine.

Authors:  Gillian D Sanders; Peter J Neumann; Anirban Basu; Dan W Brock; David Feeny; Murray Krahn; Karen M Kuntz; David O Meltzer; Douglas K Owens; Lisa A Prosser; Joshua A Salomon; Mark J Sculpher; Thomas A Trikalinos; Louise B Russell; Joanna E Siegel; Theodore G Ganiats
Journal:  JAMA       Date:  2016-09-13       Impact factor: 56.272

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  27 in total

1.  Cost-utility analysis of 21-gene assay for node-positive early breast cancer.

Authors:  L Masucci; S Torres; A Eisen; M Trudeau; I Tyono; H Saunders; K W Chan; W Isaranuwatchai
Journal:  Curr Oncol       Date:  2019-10-01       Impact factor: 3.677

2.  Talking the Talk About Tumor Genomic Testing.

Authors:  Richard L Schilsky
Journal:  J Natl Cancer Inst       Date:  2020-05-01       Impact factor: 13.506

Review 3.  Research on the Economics of Cancer-Related Health Care: An Overview of the Review Literature.

Authors:  Amy J Davidoff; Kaitlin Akif; Michael T Halpern
Journal:  J Natl Cancer Inst Monogr       Date:  2022-07-05

4.  Protein expression profiling identifies a prognostic model for ovarian cancer.

Authors:  Luyang Xiong; Jiahong Tan; Yuchen Feng; Daoqi Wang; Xudong Liu; Yun Feng; Shusheng Li
Journal:  BMC Womens Health       Date:  2022-07-15       Impact factor: 2.742

5.  Cost effectiveness of Gene Expression Profiling in Patients with Early-Stage Breast Cancer in a Middle-Income Country, Turkey: Results of a Prospective Multicenter Study.

Authors:  Vahit Özmen; Burcu Çakar; Erhan Gökmen; Mustafa Özdoğan; Nilufer Güler; Cihan Uras; Engin Ok; Orhan Demircan; Abdurrahman Işıkdoğan; Pınar Saip
Journal:  Eur J Breast Health       Date:  2019-07-01

6.  A Value of Information Analysis of Research on the 21-Gene Assay for Breast Cancer Management.

Authors:  Natalia R Kunst; Fernando Alarid-Escudero; A David Paltiel; Shi-Yi Wang
Journal:  Value Health       Date:  2019-08-07       Impact factor: 5.101

7.  Identification of 6 gene markers for survival prediction in osteosarcoma cases based on multi-omics analysis.

Authors:  Runmin Li; Guosheng Wang; ZhouJie Wu; HuaGuang Lu; Gen Li; Qi Sun; Ming Cai
Journal:  Exp Biol Med (Maywood)       Date:  2021-02-09

8.  The concordance of treatment decision guided by OncotypeDX and the PREDICT tool in real-world early-stage breast cancer.

Authors:  Daniel A Goldstein; Chen Mayer; Tzippy Shochat; Daniel Reinhorn; Assaf Moore; Michal Sarfaty; Rinat Yerushalmi; Hadar Goldvaser
Journal:  Cancer Med       Date:  2020-05-06       Impact factor: 4.452

9.  A robust twelve-gene signature for prognosis prediction of hepatocellular carcinoma.

Authors:  Guoqing Ouyang; Bin Yi; Guangdong Pan; Xiang Chen
Journal:  Cancer Cell Int       Date:  2020-06-03       Impact factor: 5.722

10.  Second Primary Lung Cancer After Breast Cancer: A Population-Based Study of 6,269 Women.

Authors:  Rong Wang; Zhiqiang Yin; Lingxiang Liu; Wen Gao; Wei Li; Yongqian Shu; Jiali Xu
Journal:  Front Oncol       Date:  2018-10-09       Impact factor: 6.244

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