Literature DB >> 29075751

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.

Michaela Tsai1, Shelly Lo2, William Audeh3, Rubina Qamar4, Raye Budway5, Ellis Levine6, Pat Whitworth7, Blanche Mavromatis8, Robin Zon9, Dwight Oldham10, Sarah Untch3, Tina Treece3, Lisa Blumencranz3,11, Hatem Soliman12.   

Abstract

IMPORTANCE: Among patients who undergo the 21-gene assay (21-GA), 39% to 67% receive an intermediate risk result and may receive ambiguous treatment guidance. The 70-gene signature assay (70-GS) may be associated with physicians' treatment decisions in this population with early breast cancer.
OBJECTIVE: To determine whether 70-GS findings are associated with physicians' decisions about adjuvant treatment and confidence in their recommendations and to evaluate the dichotomous (high- vs low-risk) and continuous distribution of 70-GS indices among this group of patients with intermediate risk. DESIGN, SETTING, AND PARTICIPANTS: The Prospective Study of MammaPrint in Breast Cancer Patients With an Intermediate Recurrence Score (PROMIS trial) was an impact study conducted from May 20, 2012, through December 31, 2015, that enrolled 840 patients with early-stage breast cancer and a 21-gene assay recurrence score of 18 to 30. Patients were treated in 58 US institutions.
INTERVENTIONS: The 70-GS result was given to physicians before adjuvant treatment. MAIN OUTCOMES AND MEASURES: Change in physician treatment decision before vs after receiving the 70-GS result. With a treatment change of greater than 20%, the odds ratio (OR) was applied.
RESULTS: Among the 840 patients who underwent 70-GS classification (mean age, 59 years; range, 27-93 years), 374 (44.5%) had a low-risk and 466 (55.5%) had a high-risk result. The distribution of 70-GS indices did not correlate with recurrence score within the 21-GA intermediate range, with 70-GS low- and high-risk patients observed at every recurrence score. A significant change in adjuvant treatment was associated with receiving the 70-GS classifications with an OR of 0.64 (95% CI, 0.50-0.82; McNemar test, P < .001) for all patients. Among the low-risk patients, 108 of 374 (28.9%) had chemotherapy removed from their treatment recommendation; among the high-risk patients, 171 of 466 (36.7%) had chemotherapy added. Results of the 70-GS were associated with the physician's adjuvant treatment recommendation; 409 high-risk patients (87.8%) were recommended to receive adjuvant chemotherapy, and 339 low-risk patients (90.6%) were recommended no chemotherapy. Physicians reported having greater confidence in their treatment recommendation in 660 cases (78.6%) based on 70-GS results. CONCLUSIONS AND RELEVANCE: The 70-GS provides clinically actionable information regarding patients classified as intermediate risk by the 21-GA and was associated with a change in treatment decision in 282 of these patients (33.6%). Chemotherapy was added or withheld by the treating physician based on the results of the 70-GS test. Physicians reported more confidence with their treatment recommendation after receiving 70-GS results.

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Year:  2018        PMID: 29075751      PMCID: PMC5833645          DOI: 10.1001/jamaoncol.2017.3470

Source DB:  PubMed          Journal:  JAMA Oncol        ISSN: 2374-2437            Impact factor:   31.777


  24 in total

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

Authors:  Valesca P Retèl; Manuela A Joore; Wim H van Harten
Journal:  Breast Cancer Res Treat       Date:  2011-09-24       Impact factor: 4.872

2.  Cost-effectiveness of the 70-gene signature versus St. Gallen guidelines and Adjuvant Online for early breast cancer.

Authors:  Valesca P Retèl; Manuela A Joore; Michael Knauer; Sabine C Linn; Michael Hauptmann; Wim H van Harten
Journal:  Eur J Cancer       Date:  2010-03-30       Impact factor: 9.162

3.  The 70-gene prognosis-signature predicts disease outcome in breast cancer patients with 1-3 positive lymph nodes in an independent validation study.

Authors:  Stella Mook; Marjanka K Schmidt; Giuseppe Viale; Giancarlo Pruneri; Inge Eekhout; Arno Floore; Annuska M Glas; Jan Bogaerts; Fatima Cardoso; Martine J Piccart-Gebhart; Emiel T Rutgers; Laura J Van't Veer
Journal:  Breast Cancer Res Treat       Date:  2008-07-27       Impact factor: 4.872

4.  Gene expression profiling in breast cancer.

Authors:  Belisario A Arango; Celine L Rivera; Stefan Glück
Journal:  Am J Transl Res       Date:  2013-03-28       Impact factor: 4.060

5.  Gene expression profiling predicts clinical outcome of breast cancer.

Authors:  Laura J van 't Veer; Hongyue Dai; Marc J van de Vijver; Yudong D He; Augustinus A M Hart; Mao Mao; Hans L Peterse; Karin van der Kooy; Matthew J Marton; Anke T Witteveen; George J Schreiber; Ron M Kerkhoven; Chris Roberts; Peter S Linsley; René Bernards; Stephen H Friend
Journal:  Nature       Date:  2002-01-31       Impact factor: 49.962

6.  A Validated Model for Identifying Patients Unlikely to Benefit From the 21-Gene Recurrence Score Assay.

Authors:  Michele M Gage; Martin Rosman; W Charles Mylander; Erica Giblin; Hyun-Seok Kim; Leslie Cope; Christopher Umbricht; Antonio C Wolff; Lorraine Tafra
Journal:  Clin Breast Cancer       Date:  2015-04-23       Impact factor: 3.225

7.  American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer.

Authors:  Antonio C Wolff; M Elizabeth H Hammond; Jared N Schwartz; Karen L Hagerty; D Craig Allred; Richard J Cote; Mitchell Dowsett; Patrick L Fitzgibbons; Wedad M Hanna; Amy Langer; Lisa M McShane; Soonmyung Paik; Mark D Pegram; Edith A Perez; Michael F Press; Anthony Rhodes; Catharine Sturgeon; Sheila E Taube; Raymond Tubbs; Gail H Vance; Marc van de Vijver; Thomas M Wheeler; Daniel F Hayes
Journal:  J Clin Oncol       Date:  2006-12-11       Impact factor: 44.544

Review 8.  Integrating comparative effectiveness design elements and endpoints into a phase III, randomized clinical trial (SWOG S1007) evaluating oncotypeDX-guided management for women with breast cancer involving lymph nodes.

Authors:  Scott D Ramsey; William E Barlow; Ana M Gonzalez-Angulo; Sean Tunis; Laurence Baker; John Crowley; Patricia Deverka; David Veenstra; Gabriel N Hortobagyi
Journal:  Contemp Clin Trials       Date:  2012-09-18       Impact factor: 2.226

9.  Use of Molecular Tools to Identify Patients With Indolent Breast Cancers With Ultralow Risk Over 2 Decades.

Authors:  Laura J Esserman; Christina Yau; Carlie K Thompson; Laura J van 't Veer; Alexander D Borowsky; Katherine A Hoadley; Nicholas P Tobin; Bo Nordenskjöld; Tommy Fornander; Olle Stål; Christopher C Benz; Linda S Lindström
Journal:  JAMA Oncol       Date:  2017-11-01       Impact factor: 31.777

10.  Validation and clinical utility of a 70-gene prognostic signature for women with node-negative breast cancer.

Authors:  Marc Buyse; Sherene Loi; Laura van't Veer; Giuseppe Viale; Mauro Delorenzi; Annuska M Glas; Mahasti Saghatchian d'Assignies; Jonas Bergh; Rosette Lidereau; Paul Ellis; Adrian Harris; Jan Bogaerts; Patrick Therasse; Arno Floore; Mohamed Amakrane; Fanny Piette; Emiel Rutgers; Christos Sotiriou; Fatima Cardoso; Martine J Piccart
Journal:  J Natl Cancer Inst       Date:  2006-09-06       Impact factor: 13.506

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  19 in total

1.  Propensity score analysis of the prognostic value of genomic assays for breast cancer in diverse populations using the National Cancer Data Base.

Authors:  Abiola Ibraheem; Olufunmilayo I Olopade; Dezheng Huo
Journal:  Cancer       Date:  2020-06-10       Impact factor: 6.860

2.  Can precision medicine help achieve the goal of reducing care when the risks exceed the benefits?

Authors:  Kathryn A Phillips; Deborah A Marshall; Allison W Kurian
Journal:  Per Med       Date:  2019-09-25       Impact factor: 2.512

Review 3.  Advancement of prognostic models in breast cancer: a narrative review.

Authors:  Ningning Min; Yufan Wei; Yiqiong Zheng; Xiru Li
Journal:  Gland Surg       Date:  2021-09

4.  Open Access Information Added.

Authors: 
Journal:  JAMA Oncol       Date:  2018-01-01       Impact factor: 31.777

5.  Prognostic gene expression assays in breast cancer: are two better than one?

Authors:  Joseph A Sparano
Journal:  NPJ Breast Cancer       Date:  2018-05-22

6.  The PROMISe to increase precision in adjuvant therapy for early breast cancer: To "Type" or to "Print"?

Authors:  Fatima Cardoso; Giuseppe Curigliano
Journal:  NPJ Breast Cancer       Date:  2018-05-22

7.  Clinicopathological characteristics, adjuvant chemotherapy decision and disease outcome in patients with breast cancer with a 21-gene recurrence score of 26-30.

Authors:  Jing Yu; Jiayi Wu; Ou Huang; Jianrong He; Li Zhu; Weiguo Chen; Yafen Li; Xiaosong Chen; Kunwei Shen
Journal:  Oncol Lett       Date:  2020-06-16       Impact factor: 2.967

Review 8.  An Update on Breast Cancer Multigene Prognostic Tests-Emergent Clinical Biomarkers.

Authors:  André Filipe Vieira; Fernando Schmitt
Journal:  Front Med (Lausanne)       Date:  2018-09-04

Review 9.  Genomic Signatures in Luminal Breast Cancer.

Authors:  Julian Puppe; Tabea Seifert; Christian Eichler; Henryk Pilch; Peter Mallmann; Wolfram Malter
Journal:  Breast Care (Basel)       Date:  2020-07-21       Impact factor: 2.860

10.  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
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