Cost-Effectiveness of BRCA 1/2 Genetic Test and Preventive Strategies: Using Real-World Data From an Upper-Middle Income Country

Abstract

Although BRCA1/2 genetic testing in developed countries is part of the reality for high-risk patients for hereditary breast and ovarian cancer (HBOC), the same is not true for upper-middle-income countries. For that reason, this study aimed to evaluate whether the BRCA1/2 genetic test and preventive strategies for women at high risk for HBOC are cost-effective compared to not performing these strategies in an upper-middle-income country. Adopting a payer perspective, a Markov model with a time horizon of 70 years was built to delineate the health states for a cohort of healthy women aged 30 years that fulfilled the BRCA1/2 testing criteria according to the guidelines. Transition probabilities were calculated based on real-world data of women tested for BRCA1/2 germline mutations in a cancer reference hospital from 2011 to 2020. We analyzed 275 BRCA mutated index cases and 356 BRCA mutation carriers that were first- or second-degree relatives of the patients. Costs were based on the Brazilian public health system reimbursement values. Health state utilities were retrieved from literature. The BRCA1/2 genetic test and preventive strategies result in more quality-adjusted life years (QALYs) and costs with an incremental cost-effectiveness ratio of R$ 11,900.31 (U$ 5,504.31)/QALY. This result can represent a strong argument in favor of implementing genetic testing strategies for high-risk women even in countries with upper-middle income, considering not only the cancer prevention possibilities associated with the genetic testing but also its cost-effectiveness to the health system. These strategies are cost-effective, considering a willingness-to-pay threshold of R$ 25,000 (U$ 11,563.37)/QALY, indicating that the government should consider offering them for women at high risk for HBOC. The results were robust in deterministic and probabilistic sensitivity analyses.

Economic evaluation of germline genetic testing for breast cancer in low- and middle-income countries: a systematic review

“…No additional relevant studies were found through the reference lists of the included studies. Ultimately, only six articles met all the inclusion criteria which allowed for data extraction and quality assessment [ 35 – 40 ]. Figure 1 , the PRISMA 2020 flow diagram, provides a detailed summary of the selection process.…”

“…Table 2 demonstrates the key characteristics of the included studies [ 35 – 40 ]. The economic evaluations conducted in LMICs primarily originated from upper-middle-income countries (Upper MICs) like China ( n = 2) Brazil ( n = 2) and Malaysia ( n = 1) [ 35 , 36 , 38 – 40 ] with only one study encompassed multiple countries with varying income levels.…”

“…Table 2 demonstrates the key characteristics of the included studies [ 35 – 40 ]. The economic evaluations conducted in LMICs primarily originated from upper-middle-income countries (Upper MICs) like China ( n = 2) Brazil ( n = 2) and Malaysia ( n = 1) [ 35 , 36 , 38 – 40 ] with only one study encompassed multiple countries with varying income levels. This study included multiple countries evaluating genetic testing in lower-middle-income countries (Lower MICs) such as India, in addition to high-income and upper-income countries [ 37 ].…”

“…This study included multiple countries evaluating genetic testing in lower-middle-income countries (Lower MICs) such as India, in addition to high-income and upper-income countries [ 37 ]. All the studies were published after 2018 and employed both cost-utility and cost-effectiveness analysis, using the incremental cost-effectiveness ratio (ICER) as the outcome measure [ 35 – 40 ]. Half of the included articles ( n = 3) considered a lifetime horizon [ 36 – 38 ] in the analysis of the studies.…”

“…Out of the six studies, only two studies analyzed from both societal and payer perspectives [ 37 , 38 ]. A discount rate of 3% was utilized for costs and effectiveness in more than half of the studies ( n = 4) [ 35 – 38 ], while two studies applied a 5% discount rate specifically in the context of Brazil [ 39 , 40 ]. All selected studies performed both deterministic and probabilistic sensitivity analysis [ 35 – 39 ].…”