Value of information analysis of multiparameter tests for chemotherapy in early breast cancer:: the OPTIMA prelim trial

Peter S. Hall; Alison Smith; Claire Hulme; Armando Vargas-Palacios; Andreas Makris; Luke Hughes-Davies; Janet A Dunn; John M S Bartlett; David A. Cameron; Andrea Marshall; Amy Campbell; Iain R. Macpherson; Daniel Rea; Adele Francis; Helena Earl; Adrienne Morgan; Robert C. Stein; Christopher McCabe; OPTIMA Trial Management Group

doi:10.1016/j.jval.2017.04.021

Value of information analysis of multiparameter tests for chemotherapy in early breast cancer: the OPTIMA prelim trial

Peter S. Hall, Alison Smith, Claire Hulme, Armando Vargas-Palacios, Andreas Makris, Luke Hughes-Davies, Janet A Dunn, John M S Bartlett, David A. Cameron, Andrea Marshall, Amy Campbell, Iain R. Macpherson, Daniel Rea, Adele Francis, Helena Earl, Adrienne Morgan, Robert C. Stein, Christopher McCabe, OPTIMA Trial Management Group

Research output: Contribution to journal › Article › peer-review

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Abstract

BACKGROUND: Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy.

OBJECTIVES: To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators.

METHODS: Women with surgically treated breast cancer (estrogen receptor-positive and lymph node-positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom.

RESULTS: There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range -£1892 to £195) and quality-adjusted life-year gains (range 0.17-0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research.

CONCLUSIONS: Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency.

Original language	English
Pages (from-to)	1311-1318
Number of pages	8
Journal	Value in Health
Volume	20
Issue number	10
Early online date	11 Jul 2017
DOIs	https://doi.org/10.1016/j.jval.2017.04.021
Publication status	Published - Dec 2017

Keywords

Journal Article
breast cancer
efficient research design
personalized medicine
value of information analysis

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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Hall_et_al_Value_of_information_analysis_Value_in_Health_2017Accepted author manuscript, 671 KBLicence: Creative Commons: Attribution-NonCommercial-NoDerivs (CC BY-NC-ND)

Cite this

Hall, P. S., Smith, A., Hulme, C., Vargas-Palacios, A., Makris, A., Hughes-Davies, L., Dunn, J. A., Bartlett, J. M. S., Cameron, D. A., Marshall, A., Campbell, A., Macpherson, I. R., Rea, D., Francis, A., Earl, H., Morgan, A., Stein, R. C., McCabe, C., & OPTIMA Trial Management Group (2017). Value of information analysis of multiparameter tests for chemotherapy in early breast cancer: the OPTIMA prelim trial. Value in Health, 20(10), 1311-1318. https://doi.org/10.1016/j.jval.2017.04.021

@article{daa60c5cb62b48b6a91d9d35b90ce39d,

title = "Value of information analysis of multiparameter tests for chemotherapy in early breast cancer:: the OPTIMA prelim trial",

abstract = "BACKGROUND: Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy.OBJECTIVES: To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators.METHODS: Women with surgically treated breast cancer (estrogen receptor-positive and lymph node-positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX{\texttrademark}. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA{\texttrademark} (NexCourse Breast{\texttrademark}). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom.RESULTS: There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range -£1892 to £195) and quality-adjusted life-year gains (range 0.17-0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research.CONCLUSIONS: Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency.",

keywords = "Journal Article, breast cancer , efficient research design , personalized medicine , value of information analysis",

author = "Hall, {Peter S.} and Alison Smith and Claire Hulme and Armando Vargas-Palacios and Andreas Makris and Luke Hughes-Davies and Dunn, {Janet A} and Bartlett, {John M S} and Cameron, {David A.} and Andrea Marshall and Amy Campbell and Macpherson, {Iain R.} and Daniel Rea and Adele Francis and Helena Earl and Adrienne Morgan and Stein, {Robert C.} and Christopher McCabe and {OPTIMA Trial Management Group}",

year = "2017",

month = dec,

doi = "10.1016/j.jval.2017.04.021",

language = "English",

volume = "20",

pages = "1311--1318",

journal = "Value in Health",

issn = "1098-3015",

publisher = "Elsevier",

number = "10",

}

Hall, PS, Smith, A, Hulme, C, Vargas-Palacios, A, Makris, A, Hughes-Davies, L, Dunn, JA, Bartlett, JMS, Cameron, DA, Marshall, A, Campbell, A, Macpherson, IR, Rea, D, Francis, A, Earl, H, Morgan, A, Stein, RC, McCabe, C & OPTIMA Trial Management Group 2017, 'Value of information analysis of multiparameter tests for chemotherapy in early breast cancer: the OPTIMA prelim trial', Value in Health, vol. 20, no. 10, pp. 1311-1318. https://doi.org/10.1016/j.jval.2017.04.021

TY - JOUR

T1 - Value of information analysis of multiparameter tests for chemotherapy in early breast cancer:

T2 - the OPTIMA prelim trial

AU - Hall, Peter S.

AU - Smith, Alison

AU - Hulme, Claire

AU - Vargas-Palacios, Armando

AU - Makris, Andreas

AU - Hughes-Davies, Luke

AU - Dunn, Janet A

AU - Bartlett, John M S

AU - Cameron, David A.

AU - Marshall, Andrea

AU - Campbell, Amy

AU - Macpherson, Iain R.

AU - Rea, Daniel

AU - Francis, Adele

AU - Earl, Helena

AU - Morgan, Adrienne

AU - Stein, Robert C.

AU - McCabe, Christopher

AU - OPTIMA Trial Management Group

PY - 2017/12

Y1 - 2017/12

N2 - BACKGROUND: Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy.OBJECTIVES: To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators.METHODS: Women with surgically treated breast cancer (estrogen receptor-positive and lymph node-positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom.RESULTS: There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range -£1892 to £195) and quality-adjusted life-year gains (range 0.17-0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research.CONCLUSIONS: Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency.

AB - BACKGROUND: Precision medicine is heralded as offering more effective treatments to smaller targeted patient populations. In breast cancer, adjuvant chemotherapy is standard for patients considered as high-risk after surgery. Molecular tests may identify patients who can safely avoid chemotherapy.OBJECTIVES: To use economic analysis before a large-scale clinical trial of molecular testing to confirm the value of the trial and help prioritize between candidate tests as randomized comparators.METHODS: Women with surgically treated breast cancer (estrogen receptor-positive and lymph node-positive or tumor size ≥30 mm) were randomized to standard care (chemotherapy for all) or test-directed care using Oncotype DX™. Additional testing was undertaken using alternative tests: MammaPrintTM, PAM-50 (ProsignaTM), MammaTyperTM, IHC4, and IHC4-AQUA™ (NexCourse Breast™). A probabilistic decision model assessed the cost-effectiveness of all tests from a UK perspective. Value of information analysis determined the most efficient publicly funded ongoing trial design in the United Kingdom.RESULTS: There was an 86% probability of molecular testing being cost-effective, with most tests producing cost savings (range -£1892 to £195) and quality-adjusted life-year gains (range 0.17-0.20). There were only small differences in costs and quality-adjusted life-years between tests. Uncertainty was driven by long-term outcomes. Value of information demonstrated value of further research into all tests, with Prosigna currently being the highest priority for further research.CONCLUSIONS: Molecular tests are likely to be cost-effective, but an optimal test is yet to be identified. Health economics modeling to inform the design of a randomized controlled trial looking at diagnostic technology has been demonstrated to be feasible as a method for improving research efficiency.

KW - Journal Article

KW - breast cancer

KW - efficient research design

KW - personalized medicine

KW - value of information analysis

U2 - 10.1016/j.jval.2017.04.021

DO - 10.1016/j.jval.2017.04.021

M3 - Article

C2 - 29241890

SN - 1098-3015

VL - 20

SP - 1311

EP - 1318

JO - Value in Health

JF - Value in Health

IS - 10

ER -