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10 Global economic evaluation of population-based BRCA1/BRCA2 mutation testing
  1. R Manchanda1,2,3,
  2. L Sun1,4,
  3. S Patel1,
  4. J Wilschut5,
  5. A Lopes Carolina de Freitas6,
  6. A Brentnall7,
  7. S Duffy7,
  8. B Cui8,
  9. P Soarez Coelho de6,
  10. Z Husain9,
  11. T Vanni10,
  12. J Hopper11,
  13. Z Sadique4,
  14. A Mukopadhyay12,13,
  15. L Yang8,
  16. H Berkof5 and
  17. R Legood4
  1. 1Barts Cancer Institute- Queen Mary University of London, Centre for Experimental Cancer Medicine, London, UK
  2. 2Royal London Hospital, Department of Gynaecological Oncology- Barts Health NHS Trust, London, UK
  3. 3University College London, MRC Clinical Trials Unit at UCL- Institute of Clinical Trials and Methodology- Faculty of Population Health Sciences, London, UK
  4. 4London School of Hygiene and Tropical Medicine, Department of Health Services Research and Policy, London, UK
  5. 5Amsterdam University Medical Centre, Department of Epidemiology and biostatistics, Amsterdam, The Netherlands
  6. 6Faculdade de Medicina da Universidade de São Paulo, Departamento de Medicina Preventiva, São Paulo, Brazil
  7. 7Wolfson Institute of Preventive Medicine- Queen Mary University of London, Centre for Cancer Prevention, London, UK
  8. 8Peking University, School of Public Health, Beijing, China
  9. 9Indian Institute of Technology, Dept. of Humanities and Social Sciences, Kharagpur, India
  10. 10Instituto Bhutanan, Instituto Bhutanan, São Paulo, Brazil
  11. 11University of Melbourne, Centre for Epidemiology and Biostatistics- Melbourne School of Population and Global Health- Faculty of Medicine- Dentistry and Health Sciences, Melbourne, Australia
  12. 12Tata Medical Centre, Tata Medical Centre, Kolkata, India
  13. 13Newcastle University, Northern Institute for Cancer Research, Newcastle, UK


Objectives To evaluate cost-effectiveness and population-impact of unselected population-based BRCA-testing compared to clinical-criteria/family-history(FH) based BRCA-testing across Lower-middle-income/LMIC (India), Upper-middle-income/UMIC (Brazil/China) and High-income-countries/HIC (US/UK/Netherlands) health-systems.

Methods Markov-modelling compared lifetime costs-&-effects of BRCA1/BRCA2-testing all general-population women ≥30years compared with clinical-criteria/FH-based testing. Analyses undertaken for UK/USA/Netherlands/China/Brazil/India using both health-system/payer and societal perspectives. All women ≥30years in the Population-Testing arm and only those fulfilling clinical/FH-criteria in the Clinical-Criteria/FH-based testing arm undergo BRCA-mutation testing. We collected primary-data on direct medical costs from China, Brazil, India. Costing-data were obtained from published NHS-reference-costs for the UK/Netherlands and published literature for USA. Future costs/health-effects discount-rate=3.5%. Parameter-uncertainty was explored using one-way and probabilistic-sensitivity-analyses. Specific health-economic cost-effectiveness threshold guidelines were used where available for UK=£20,000-£30,000; USA=$50,000-$100,000; Netherlands=€20,000-€50,000. Main-outcome=ICER/QALY. For comparison local currency values are converted to $s using purchasing-power-parity factor.

Results From ‘societal-perspective’, population-based BRCA-testing is ‘cost-saving’ in HIC: UK-ICER=$-3,508/QALY; USA-ICER=$-1,327/QALY; Netherlands-ICER=$-8,663/QALY. It is potentially Cost-effective in UMIC depending on willingness-to-pay thresholds chosen and genetic-testing costs. UMIC-ICERs are just above 1*GDP-threshold: China-ICER=$20,988/QALY; Brazil-ICER=$15,587/QALY. It becomes under 3*GDP threshold in India if BRCA-testing cost is $148/test (ICER=$19,676/QALY). From ‘payer-perspective’, population-based BRCA-testing is cost-effective in HIC: UK-ICER=$24,101/QALY; USA-ICER=$19,804/QALY; Netherlands-ICER=$28,668/QALY. Results are sensitive to genetic-testing costs. Population-based BRCA-testing can prevent an additional 2319-to-2666 breast-cancers and 327-to-449 ovarian-cancers/million-women translating to tens-of-thousands more breast/ovarian-cancers prevented across the population.

Conclusions Population-based BRCA-testing is cost-effective in HIC and potentially in UMIC depending on the local willingness-to-pay thresholds. Genetic-testing costs need to fall further for LMIC cost-effectiveness. Population-testing can prevent tens-of-thousands more breast/ovarian-cancers than the current clinical strategy.

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