Literature DB >> 32284770

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

.   

Abstract

BACKGROUND: Breast cancer is a disease in which cells in the breast grow out of control. They often form a tumour that may be seen on an x-ray or felt as a lump.Gene expression profiling (GEP) tests are intended to help predict the risk of metastasis (spread of the cancer to other parts of the body) and to identify people who will most likely benefit from chemotherapy. We conducted a health technology assessment of four GEP tests (EndoPredict, MammaPrint, Oncotype DX, and Prosigna) for people with early-stage invasive breast cancer, which included an evaluation of effectiveness, safety, cost effectiveness, the budget impact of publicly funding GEP tests, and patient preferences and values.
METHODS: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using either the Cochrane Risk of Bias tool, Prediction model Risk Of Bias ASsessment Tool (PROBAST), or Risk of Bias Assessment tool for Non-randomized Studies (RoBANS), depending on the type of study and outcome of interest, and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We also performed a literature survey of the quantitative evidence of preferences and values of patients and providers for GEP tests.We performed an economic evidence review to identify published studies assessing the cost-effectiveness of each of the four GEP tests compared with usual care or with one another for people with early-stage invasive breast cancer. We adapted a decision-analytic model to compare the costs and outcomes of care that includes a GEP test with usual care without a GEP test over a lifetime horizon. We also estimated the budget impact of publicly funding GEP tests to be conducted in Ontario, compared with funding tests conducted through the out-of-country program and compared with no funding of tests in any location.To contextualize the potential value of GEP tests, we spoke with people who have been diagnosed with early-stage invasive breast cancer.
RESULTS: We included 68 studies in the clinical evidence review. Within the lymph-node-negative (LN-) population, GEP tests can prognosticate the risk of distant recurrence (GRADE: Moderate) and may predict chemotherapy benefit (GRADE: Low). The evidence for prognostic and predictive ability (ability to indicate the risk of an outcome and ability to predict who will benefit from chemotherapy, respectively) was lower for the lymph-node-positive (LN+) population (GRADE: Very Low to Low). GEP tests may also lead to changes in treatment (GRADE: Low) and generally may increase physician confidence in treatment recommendations (GRADE: Low).Our economic evidence review showed that GEP tests are generally cost-effective compared with usual care.Our primary economic evaluation showed that all GEP test strategies were more effective (led to more quality-adjusted life-years [QALYs]) than usual care and can be considered cost-effective below a willingness-to-pay of $20,000 per QALY gained. There was some uncertainty in our results. At a willingness-to-pay of $50,000 per QALY gained, the probability of each test being cost-effective compared to usual care was 63.0%, 89.2%, 89.2%, and 100% for EndoPredict, MammaPrint, Oncotype DX, and Prosigna, respectively.Sensitivity analyses showed our results were robust to variation in subgroups considered (i.e., LN+ and premenopausal), discount rates, age, and utilities. However, cost parameter assumptions did influence our results. Our scenario analysis comparing tests showed Oncotype DX was likely cost-effective compared with MammaPrint, and Prosigna was likely cost-effective compared with EndoPredict. When the GEP tests were compared with a clinical tool, the cost-effectiveness of the tests varied. Assuming a higher uptake of GEP tests, we estimated the budget impact to publicly fund GEP tests in Ontario would be between $1.29 million (Year 1) and $2.22 million (Year 5) compared to the current scenario of publicly funded GEP tests through the out-of-country program.Gene expression profiling tests are valued by patients and physicians for the additional information they provide for treatment decision-making. Patients are satisfied with what they learn from GEP tests and feel GEP tests can help reduce decisional uncertainty and anxiety.
CONCLUSIONS: Gene expression profiling tests can likely prognosticate the risk of distant recurrence and some tests may also predict chemotherapy benefit. In people with breast cancer that is ER+, LN-, and human epidermal growth factor receptor 2 (HER2)-negative, GEP tests are likely cost-effective compared with no testing. The GEP tests are also likely cost-effective in LN+ and premenopausal people. Compared with funding GEP tests through the out-of-country program, publicly funding GEP tests in Ontario would cost an additional $1 million to $2 million annually, assuming a higher uptake of tests. GEP tests are valued by both patients and physicians for chemotherapy treatment decision-making.
Copyright © Queen's Printer for Ontario, 2020.

Entities:  

Mesh:

Year:  2020        PMID: 32284770      PMCID: PMC7143374     

Source DB:  PubMed          Journal:  Ont Health Technol Assess Ser        ISSN: 1915-7398


  195 in total

1.  A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.

Authors:  Soonmyung Paik; Steven Shak; Gong Tang; Chungyeul Kim; Joffre Baker; Maureen Cronin; Frederick L Baehner; Michael G Walker; Drew Watson; Taesung Park; William Hiller; Edwin R Fisher; D Lawrence Wickerham; John Bryant; Norman Wolmark
Journal:  N Engl J Med       Date:  2004-12-10       Impact factor: 91.245

2.  Testing a tool for assessing the risk of bias for nonrandomized studies showed moderate reliability and promising validity.

Authors:  Soo Young Kim; Ji Eun Park; Yoon Jae Lee; Hyun-Ju Seo; Seung-Soo Sheen; Seokyung Hahn; Bo-Hyoung Jang; Hee-Jung Son
Journal:  J Clin Epidemiol       Date:  2013-01-18       Impact factor: 6.437

3.  First Prospective Multicenter Italian Study on the Impact of the 21-Gene Recurrence Score in Adjuvant Clinical Decisions for Patients with ER Positive/HER2 Negative Breast Cancer.

Authors:  Maria Vittoria Dieci; Valentina Guarneri; Tommaso Giarratano; Marta Mion; Giampaolo Tortora; Costanza De Rossi; Stefania Gori; Cristina Oliani; Laura Merlini; Felice Pasini; Giorgio Bonciarelli; Gaia Griguolo; Enrico Orvieto; Silvia Michieletto; Tania Saibene; Paola Del Bianco; Gian Luca De Salvo; PierFranco Conte
Journal:  Oncologist       Date:  2017-11-13

4.  Uptake of BRCA 1/2 and oncotype DX testing by medical and surgical oncologists.

Authors:  Yonina R Murciano-Goroff; Anne Marie McCarthy; Mirar N Bristol; Peter Groeneveld; Susan M Domchek; U Nkiru Motanya; Katrina Armstrong
Journal:  Breast Cancer Res Treat       Date:  2018-05-08       Impact factor: 4.872

5.  Incorporating Tumor Characteristics to Maximize 21-Gene Assay Utility: A Cost-Effectiveness Analysis.

Authors:  Shi-Yi Wang; Tiange Chen; Weixiong Dang; Sarah S Mougalian; Suzanne B Evans; Cary P Gross
Journal:  J Natl Compr Canc Netw       Date:  2019-01       Impact factor: 11.908

6.  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

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

Review 8.  Gene expression profiling and expanded immunohistochemistry tests to guide the use of adjuvant chemotherapy in breast cancer management: a systematic review and cost-effectiveness analysis.

Authors:  S Ward; A Scope; R Rafia; A Pandor; S Harnan; P Evans; L Wyld
Journal:  Health Technol Assess       Date:  2013-10       Impact factor: 4.014

9.  Cost-effectiveness analysis of Mammostrat® compared with Oncotype DX® to inform the treatment of breast cancer.

Authors:  Kimberly Mislick; Warren Schonfeld; Carolyn Bodnar; Kuo Bianchini Tong
Journal:  Clinicoecon Outcomes Res       Date:  2014-01-16

10.  Comparison of the Performance of 6 Prognostic Signatures for Estrogen Receptor-Positive Breast Cancer: A Secondary Analysis of a Randomized Clinical Trial.

Authors:  Ivana Sestak; Richard Buus; Jack Cuzick; Peter Dubsky; Ralf Kronenwett; Carsten Denkert; Sean Ferree; Dennis Sgroi; Catherine Schnabel; Frederick L Baehner; Elizabeth Mallon; Mitch Dowsett
Journal:  JAMA Oncol       Date:  2018-04-01       Impact factor: 31.777

View more
  7 in total

1.  Recognition of Immune Microenvironment Landscape and Immune-Related Prognostic Genes in Breast Cancer.

Authors:  Huiling Wang; Shuo You; Meng Fang; Qian Fang
Journal:  Biomed Res Int       Date:  2020-11-15       Impact factor: 3.411

2.  Personalised medicine and the decision to withhold chemotherapy in early breast cancer with intermediate risk of recurrence - a systematic review and meta-analysis.

Authors:  Susanna M Wallerstedt; Astrid Nilsson Ek; Roger Olofsson Bagge; Anikó Kovács; Annika Strandell; Barbro Linderholm
Journal:  Eur J Clin Pharmacol       Date:  2020-06-05       Impact factor: 2.953

Review 3.  A narrative review of prognosis prediction models for non-small cell lung cancer: what kind of predictors should be selected and how to improve models?

Authors:  Yuhang Wang; Xuefeng Lin; Daqiang Sun
Journal:  Ann Transl Med       Date:  2021-10

4.  RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer.

Authors:  Johan Staaf; Jari Häkkinen; Cecilia Hegardt; Lao H Saal; Siker Kimbung; Ingrid Hedenfalk; Tonje Lien; Therese Sørlie; Bjørn Naume; Hege Russnes; Rachel Marcone; Ayyakkannu Ayyanan; Cathrin Brisken; Rebecka R Malterling; Bengt Asking; Helena Olofsson; Henrik Lindman; Pär-Ola Bendahl; Anna Ehinger; Christer Larsson; Niklas Loman; Lisa Rydén; Martin Malmberg; Åke Borg; Johan Vallon-Christersson
Journal:  NPJ Breast Cancer       Date:  2022-08-16

5.  Prognostic Significance of BIRC5/Survivin in Breast Cancer: Results from Three Independent Cohorts.

Authors:  Nina Oparina; Malin C Erlandsson; Anna Fäldt Beding; Toshima Parris; Khalil Helou; Per Karlsson; Zakaria Einbeigi; Maria I Bokarewa
Journal:  Cancers (Basel)       Date:  2021-05-04       Impact factor: 6.639

6.  A Systematic Review of the Value Assessment Frameworks Used within Health Technology Assessment of Omics Technologies and Their Actual Adoption from HTA Agencies.

Authors:  Ilda Hoxhaj; Laurenz Govaerts; Steven Simoens; Walter Van Dyck; Isabelle Huys; Iñaki Gutiérrez-Ibarluzea; Stefania Boccia
Journal:  Int J Environ Res Public Health       Date:  2020-10-30       Impact factor: 3.390

Review 7.  The Role of the 21-Gene Recurrence Score® Assay in Hormone Receptor-Positive, Node-Positive Breast Cancer: The Canadian Experience.

Authors:  Mariya Yordanova; Saima Hassan
Journal:  Curr Oncol       Date:  2022-03-16       Impact factor: 3.677

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.