In a recent study published in the journal EClinicalMedicine, a group of researchers evaluated the cost-effectiveness and health impact of implementing a combined genomic screening program for hereditary breast and ovarian cancer (HBOC), Lynch syndrome (LS), and familial hypercholesterolemia (FH) in young Australian adults, within the national public healthcare system.
Population genomic screening offers a significant public health opportunity for early detection and prevention of cancer and heart disease from high-risk genetic conditions like HBOC, LS, and FH.
Approximately 1.3% of people carry pathogenic variants linked to these conditions, which are optimal candidates for screening due to their prevalence and actionable interventions. Current detection is limited due to restrictive testing criteria, missing many who could benefit from early risk-reducing strategies like surgery or medication. Further research is needed to optimize and fully understand the implications of widespread genomic screening for high-risk conditions, addressing its feasibility, ethical considerations, and equitable access within public healthcare systems.
About the study
Researchers developed three decision-analysis models with Markov components to investigate outcomes related to pathogenic variants (PVs) for HBOC in Breast Cancer (BRCA)1 and BRCA2 genes; LS in MutL Homolog (MLH)1 and MutS Homolog (MSH)2 genes for colorectal and endometrial cancer; and FH in LDLR (Low-Density Lipoprotein Receptor), Apolipoprotein B (APOB), and Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) genes for coronary heart disease (CHD).
Partner And Localizer of BRCA2 (PALB2) and MSH6 were omitted due to insufficient data.
Each model commenced with exclusive condition analysis, progressing to integrated multistate transition models for broader cohorts, encompassing health state transitions based on probabilities.
Two strategies were assessed: existing Australian criteria-based testing (Strategy 1) and a proposed universal genomic screening (Strategy 2) with an ideal detection rate, assuming 50% uptake and perfect test sensitivity among Australians aged 18–40, beginning in the model's first year.
A life-table approach evaluated morbidity and mortality among identified PV carriers over a lifetime, incorporating genetic counseling, standard risk management, and intervention costs.
Risk reduction followed Australian guidelines, with intervention uptake reflecting published data and models targeted the incremental cost-effectiveness ratio (ICER) in terms of cost per quality-adjusted life year (QALY) against an AU$50,000/QALY threshold, including life years and cancer/CHD incidents prevented by screening.
The models incorporated Australian data for an 18–40 population, with an anticipated 50% screening uptake from 2023. Strategies addressed cancer surveillance and preventative surgeries for HBOC, intensive surveillance for LS, and statins for FH with varying adherence rates.
Utility scores and associated costs were sourced from existing studies. For Costs for Strategy 1 mirrored current genetic testing rates in Australia, Strategy 2 was priced at AU$200 per test.
Vitality was tested through scenario and sensitivity analyses, which included Monte Carlo simulations to determine factors affecting cost-effectiveness. The analyses were from a healthcare perspective with a 5% annual discount.
Researchers compared the current practice of criteria-based genetic testing to an alternate strategy of comprehensive population genomic screening for three high-risk health conditions.
The results were striking: the screening approach was projected to avert numerous health events over the population's lifetime - 2,612 cancer cases, 542 non-fatal CHD events, and 4,047 cancer or CHD deaths.
Translated to a per-100,000-person basis, this meant 63 fewer cancer cases, 31 fewer CHD cases, and 97 fewer deaths. In terms of life years, genomic screening could yield an additional 20,553 years of life and 31,094 QALYs compared to the status quo, equating to 494 more years lived and 747 more QALYs per 100,000 individuals tested.
In a financial overview, initiating genomic screening at a 50% participation rate would incur an upfront cost of AU$832 million above Australia's current genetic testing expenditure, plus AU$282 million in continuous care for detected pathogenic variant carriers.
The strategy's preventative benefits are expected to outweigh its costs, potentially saving over AU$394 million by reducing expenses from chronic diseases and mortality, leading to a net screening cost of AU$825.54 million. The approach is projected to stay cost-effective, even if test costs were to increase to AU$325.
Scenario analyses explored the cost-effectiveness of expanding population genomic screening to different age ranges. Extending screening to ages 18–50 or 25–50 remained cost-effective, with ICERs significantly below the willingness-to-pay threshold.
However, the original 18–40 age group proved to be the most cost-efficient strategy, offering the best balance of costs and QALYs gained. When assessing individual conditions, screening for FH was economically justifiable, while screening solely for HBOC or LS was not within the same population framework.
From a broader societal perspective, considering productivity losses, genomic screening at AU$200 per test was cost-saving. Even at a raised cost of AU$325 per test, screening stayed within acceptable cost-effectiveness margins.
However, an increase to AU$500 per test breached the cost-effectiveness threshold. Moreover, adjusting the base-case discount rate from 5% to 3% dramatically decreased the ICER, showcasing a more favorable cost-benefit scenario often adopted outside Australia.
Sensitivity analyses assessed the robustness of the base-case model for combined genomic screening of HBCO, LS, and FH at AU$200 per test. The one-way sensitivity analysis confirmed that all variations in input parameters resulted in ICERs below the AU$50,000/QALY threshold. Probabilistic sensitivity analysis further supported the cost-effectiveness of the screening, showing in simulations that the approach would be cost-effective in 70% of cases, cost-saving in 25%, and not cost-effective in only 5%.