Peter S Hall1, Alison Smith2, Claire Hulme2, Armando Vargas-Palacios2, Andreas Makris3, Luke Hughes-Davies4, Janet A Dunn5, John M S Bartlett6, David A Cameron7, Andrea Marshall5, Amy Campbell5, Iain R Macpherson8, Adele Francis9, Helena Earl4, Adrienne Morgan10, Robert C Stein11, Christopher McCabe12. 1. Edinburgh Cancer Research Centre, University of Edinburgh, Edinburgh, UK; Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK. Electronic address: p.s.hall@ed.ac.uk. 2. Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK. 3. Department of Clinical Oncology, Mount Vernon Cancer Centre, East and North Hertfordshire NHS Trust, Northwood, UK. 4. Department of Oncology, Addenbrooke's Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK. 5. Warwick Clinical Trials Unit, Warwick Medical School, University of Warwick, Coventry, UK. 6. Ontario Institute for Cancer Research, Toronto, Ontario, Canada. 7. Edinburgh Cancer Research Centre, University of Edinburgh, Edinburgh, UK. 8. Beatson West of Scotland Cancer Centre, University of Glasgow, Glasgow, UK. 9. Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, UK. 10. Independent Cancer Patients' Voice, London, UK. 11. National Institute for Health Research, University College London Hospitals Biomedical Research Centre, London, UK. 12. University of Alberta, Edmonton, Alberta, Canada.
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.
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.
Authors: Natalia Kunst; Natasha K Stout; Grace O'Brien; Kurt D Christensen; Pamela M McMahon; Ann Chen Wu; Lisa R Diller; Jennifer M Yeh Journal: J Natl Cancer Inst Date: 2022-05-09 Impact factor: 11.816
Authors: Ramona Erber; Miriam Angeloni; Robert Stöhr; Michael P Lux; Daniel Ulbrich-Gebauer; Enrico Pelz; Agnes Bankfalvi; Kurt W Schmid; Robert F H Walter; Martina Vetter; Christoph Thomssen; Doris Mayr; Frederick Klauschen; Peter Sinn; Karl Sotlar; Katharina Stering; Albrecht Stenzinger; Marius Wunderle; Peter A Fasching; Matthias W Beckmann; Oliver Hoffmann; Rainer Kimmig; Nadia Harbeck; Rachel Wuerstlein; Fulvia Ferrazzi; Arndt Hartmann Journal: Int J Mol Sci Date: 2022-08-05 Impact factor: 6.208
Authors: Vladislav Berdunov; Steve Millen; Andrew Paramore; Jane Griffin; Sarah Reynia; Nina Fryer; Rebecca Brown; Louise Longworth Journal: Clinicoecon Outcomes Res Date: 2022-09-19
Authors: Ayat Lashen; Michael S Toss; Mansour Alsaleem; Andrew R Green; Nigel P Mongan; Emad Rakha Journal: Mod Pathol Date: 2022-05-02 Impact factor: 8.209