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. 2019 Dec 1;5(12):1718-1730.
doi: 10.1001/jamaoncol.2019.3323.

A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer

Li Sun  1   2 , Adam Brentnall  3 , Shreeya Patel  1   2 , Diana S M Buist  4 , Erin J A Bowles  4 , D Gareth R Evans  5 , Diana Eccles  6 , John Hopper  7 , Shuai Li  7 , Melissa Southey  8   9   10 , Stephen Duffy  3 , Jack Cuzick  3 , Isabel Dos Santos Silva  11 , Alec Miners  1 , Zia Sadique  1 , Li Yang  12 , Rosa Legood  1 , Ranjit Manchanda  2   3   13   14
Affiliations

A Cost-effectiveness Analysis of Multigene Testing for All Patients With Breast Cancer

Li Sun et al. JAMA Oncol. .

Abstract

Importance: Moving to multigene testing for all women with breast cancer (BC) could identify many more mutation carriers who can benefit from precision prevention. However, the cost-effectiveness of this approach remains unaddressed.

Objective: To estimate incremental lifetime effects, costs, and cost-effectiveness of multigene testing of all patients with BC compared with the current practice of genetic testing (BRCA) based on family history (FH) or clinical criteria.

Design, setting, and participants: This cost-effectiveness microsimulation modeling study compared lifetime costs and effects of high-risk BRCA1/BRCA2/PALB2 (multigene) testing of all unselected patients with BC (strategy A) with BRCA1/BRCA2 testing based on FH or clinical criteria (strategy B) in United Kingdom (UK) and US populations. Data were obtained from 11 836 patients in population-based BC cohorts (regardless of FH) recruited to 4 large research studies. Data were collected and analyzed from January 1, 2018, through June 8, 2019. The time horizon is lifetime. Payer and societal perspectives are presented. Probabilistic and 1-way sensitivity analyses evaluate model uncertainty.

Interventions: In strategy A, all women with BC underwent BRCA1/BRCA2/PALB2 testing. In strategy B, only women with BC fulfilling FH or clinical criteria underwent BRCA testing. Affected BRCA/PALB2 carriers could undertake contralateral preventive mastectomy; BRCA carriers could choose risk-reducing salpingo-oophorectomy (RRSO). Relatives of mutation carriers underwent cascade testing. Unaffected relative carriers could undergo magnetic resonance imaging or mammography screening, chemoprevention, or risk-reducing mastectomy for BC risk and RRSO for ovarian cancer (OC) risk.

Main outcomes and measures: Incremental cost-effectiveness ratio (ICER) was calculated as incremental cost per quality-adjusted life-year (QALY) gained and compared with standard £30 000/QALY and $100 000/QALY UK and US thresholds, respectively. Incidence of OC, BC, excess deaths due to heart disease, and the overall population effects were estimated.

Results: BRCA1/BRCA2/PALB2 multigene testing for all patients detected with BC annually would cost £10 464/QALY (payer perspective) or £7216/QALY (societal perspective) in the United Kingdom or $65 661/QALY (payer perspective) or $61 618/QALY (societal perspective) in the United States compared with current BRCA testing based on clinical criteria or FH. This is well below UK and US cost-effectiveness thresholds. In probabilistic sensitivity analysis, unselected multigene testing remained cost-effective for 98% to 99% of UK and 64% to 68% of US health system simulations. One year's unselected multigene testing could prevent 2101 cases of BC and OC and 633 deaths in the United Kingdom and 9733 cases of BC and OC and 2406 deaths in the United States. Correspondingly, 8 excess deaths due to heart disease occurred in the United Kingdom and 35 in the United States annually.

Conclusions and relevance: This study found unselected, high-risk multigene testing for all patients with BC to be extremely cost-effective compared with testing based on FH or clinical criteria for UK and US health systems. These findings support changing current policy to expand genetic testing to all women with BC.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Buist reported receiving grants from the National Cancer Institute (NCI) during the conduct of the study. Dr Bowles reported receiving grants from the NCI during the conduct of the study. Dr Evans reported receiving personal fees from AstraZeneca during the conduct of the study and grant IS-BRC-1215-20007 from the Manchester National Institute for Healath Research Biomedical Research Centre during the study. Dr Eccles reported receiving grants from Cancer Research UK during the conduct of the study. Dr Yang reported receiving grants from the National Foundation of Science during the conduct of the study. Dr Manchanda reported receiving grants from The Eve Appeal, Cancer Research UK, Barts Charity, and Rose Trees Trust outside the submitted work and honoraria for grant review from the Israel National Institute for Health Policy Research and for advisory board meetings from Merck Sharp & Dohme and AstraZeneca. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Model Structure
Schematic diagram shows the microsimulation model structure for unselected and clinical criteria–or family history (FH)–based panel genetic testing for patients with breast cancer (BC). CPM indicates contralateral prophylactic mastectomy; OC, ovarian cancer; RRSO, risk-reducing salpingo-oophorectomy; and VUS, variant of uncertain significance. aIncludes individuals testing negative for BRCA1/BRCA2/PALB2 mutations and VUS not reclassified as pathologic variants.
Figure 2.
Figure 2.. Model Structure
Schematic diagram shows the microsimulation model structure for unselected and clinical criteria–or family history (FH)–based panel genetic testing for relatives of patients with breast cancer (BC). CPM indicates contralateral prophylactic mastectomy; OC, ovarian cancer; RRM, risk-reducing mastectomy; RRSO, risk-reducing salpingo-oophorectomy; and VUS, variant of uncertain significance. aIncludes individuals testing negative for BRCA1/BRCA2/PALB2 mutations and VUS not reclassified as pathologic variants. bIn the model structure for relatives, PALB2-positive individuals are identified only through the unselected testing arm. Relatives in the clinical criteria/FH testing arm only undergo BRCA1/BRCA2 testing. cUnaffected relatives can progress from no cancer to germline BC (BRCA1/BRCA2/PALB2), germline OC (BRCA1/BRCA2), sporadic BC, or sporadic OC (or remain in that health state).
Figure 3.
Figure 3.. Cost-effectiveness Acceptability Curves (Probabilistic Sensitivity Analyses)
Probabilistic sensitivity analysis in which all model parameters/variables are varied simultaneously across their distributions to further explore model uncertainty. The results of 1000 simulations were plotted on a cost-effectiveness acceptability curve showing the proportion of simulations that indicated that the intervention was cost-effective at different willingness-to-pay (WTP) thresholds. A and B, The dotted line marks the proportion of simulations found to be cost-effective at the WTP threshold of £30 000 per quality-adjusted life-year (QALY) in the UK analysis. At the £30 000/QALY WTP threshold from the payer perspective, 2% simulations are cost-effective for testing based on clinical criteria or family history (FH) and 98% simulations are cost-effective for unselected genetic testing; from the societal perspective, 1% simulations are cost-effective for testing based on clinical criteria or FH and 99% simulations are cost-effective for unselected genetic testing. C and D, The dotted line marks the proportion of simulations found to be cost-effective at the WTP threshold of $100 000/QALY in the US analysis. At the $100 000/QALY WTP threshold from the payer perspective, 36% simulations are cost-effective for testing based on clinical criteria or FH and 64% simulations are cost-effective for unselected genetic testing; from the societal perspective, 32% simulations are cost-effective for testing based on clinical criteria or FH and 68% simulations are cost-effective for unselected genetic testing.
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