Cost-effectiveness analysis of genetic tools to predict treatment response in patients with cystic fibrosis.

BACKGROUND: Cystic fibrosis (CF) transmembrane conductance regulator (CFTR) modulator therapies show variable efficacy for patients with CF. Patient-derived predictive tools may identify individuals likely to respond to CFTRs, but are not in routine use. We aimed to determine the cost-utility of predictive tool-guided treatment with CFTRs as add-on to standard of care (SoC) for individuals with CF. METHODS: This economic evaluation compared two strategies using an individual level simulation: (i) Treat All, where all patients received CFTRs plus SoC and (ii) Test→Treat, where patients who tested positive on predictive tools received CFTRs plus SoC and those who tested negative received SoC only. We simulated 50,000 individuals over their lifetime, and estimated costs (2020 CAD) per quality-adjusted life year (QALY) from the healthcare payer's perspective, discounted at 1.5% annually. The model was populated using Canadian CF registry data and published literature. Probabilistic and deterministic sensitivity were conducted. RESULTS: The Treat All and Test→Treat and strategies yielded 22.41 and 21.36 QALYs, and cost $4.21 M and $3.15 M respectively. Results of probabilistic sensitivity analysis showed that Test→Treat was highly cost-effective compared to Treat All in 100% of simulations at cost-effectiveness thresholds as high as $500,000 per QALY. Test→Treat may save between $931 K to $1.1 M per QALY lost, depending on sensitivity and specificity of predictive tools. CONCLUSION: The use of predictive tools could optimize the health benefits of CFTR modulators while reducing costs. Our findings support the use of pre-treatment predictive testing and may help inform coverage and reimbursement policies for individuals with CF.

Financial Incentives for Transcatheter Aortic Valve Implantation in Ontario, Canada: A Cost-Utility Analysis.

Background Transcatheter aortic valve implantation (TAVI) is a minimally invasive therapy for patients with severe aortic stenosis, which has become standard of care. The objective of this study was to determine the maximum cost-effective investment in TAVI care that should be made at a health system level to meet quality indicator goals. Methods and Results We performed a cost-utility analysis using probabilistic patient-level simulation of TAVI care from the Ontario, Canada, Ministry of Health perspective. Costs and health utilities were accrued over a 2-year time horizon. We created 4 hypothetical strategies that represented TAVI care meeting ≥1 quality indicator targets, (1) reduced wait times, (2) reduced hospital length of stay, (3) reduced pacemaker use, and (4) combined strategy, and compared these with current TAVI care. Per-person costs, quality-adjusted life years, and clinical outcomes were estimated by the model. Using these, incremental net monetary benefits were calculated for each strategy at different cost-effectiveness thresholds between $0 and $100 000 per quality-adjusted life year. Clinical improvements over the current practice were estimated with all comparator strategies. In Ontario, achieving quality indicator benchmarks could avoid ≈26 wait-list deaths and 200 wait-list hospitalizations annually. Compared with current TAVI care, the incremental net monetary benefit for this strategy varied from $10 765 (±$8721) and $17 221 (±$8977). This would translate to an annual investment of between ≈$14 to ≈$22 million by the Ontario Ministry of Health to incentivize these performance measures being cost-effective. Conclusions This study has quantified the modest annual investment required and substantial clinical benefit of meeting improvement goals in TAVI care.