A cost-benefit analysis of genetic screening test for breast cancer in Iran

Abstract

Background This study aimed to evaluate the implementation of the population- and family history (FH) -based screening for BReast CAncer (BRCA) in Iran, a country where less than 10% of breast cancer cases are attributable to a gene mutation. Methods This was an economic evaluation study. The Benefit-Cost Ratio (BCR) for genetic screening test strategies in Iranian women older than 30 was calculated. To this end, the monetary value of the test was estimated using the willingness-to-pay (WTP) approach using the contingent valuation method (CVM) by payment card. From a healthcare perspective, direct medical and non-medical costs were considered and a decision model for the strategies was developed to simulate the costs. A one-way sensitivity analysis assessed the robustness of the analysis. The data were analyzed using Excel 2010. Results 660 women were included for estimating WTP and 2,176,919 women were considered in the costing model. The cost per genetic screening test for population- and FH-based strategies was $167 and $8, respectively. The monetary value of a genetic screening test was $20 and it was $27 for women with a family history or gene mutation in breast cancer. The BCR for population-based and FH-based screening strategies was 0.12 and 3.37, respectively. Sensitivity analyses confirmed the robustness of the results. Conclusions This study recommends the implementation of a FH-based strategy instead of a population-based genetic screening strategy in Iran, although a cascade genetic screening test strategy should be evaluated in future studies.

A cost-benefit analysis of mass prostate cancer screening

“…Using WTP is a common method to measure the benefit alongside detecting the acceptance of strategies in economic evaluation and cost benefit analysis of implementing cancer interventions [ 17 – 19 ]. Also, the willingness to pay approach has the capacity to compute false positive and negative results of diagnostic tests, which help promote the accuracy of evaluation indicators and the elimination of potential biases [ 20 ].…”