Early-stage health technology assessment of fractional flow reserve coronary computed tomography versus standard diagnostics in patients with stable chest pain in The Netherlands

Abstract

Objectives: The aim of this early-stage Health Technology Assessment (HTA) was to assess the difference in healthcare costs and effects of fractional flow reserve derived from coronary computed tomography (FFRct) compared to standard diagnostics in patients with stable chest pain in The Netherlands.

Methods: A decision-tree model was developed to assess the difference in total costs from the hospital perspective, probability of correct diagnoses, and risk of major adverse cardiovascular events at one year follow-up. One-way sensitivity analyses were conducted to determine the main drivers of the cost difference between the strategies. A threshold analysis on the added price of FFRct analysis (computational analysis only) was conducted.

Results: The mean one-year costs were €2,680 per patient for FFRct and €2,915 per patient for standard diagnostics. The one-year probability of correct diagnoses was 0.78 and 0.61, and the probability of major adverse cardiovascular events was 1.92x10-5 and 0.01, respectively. The probability and costs of revascularization and the specificity of coronary computed tomography angiography had the greatest effect on the difference in costs between the strategies. The added price of FFRct analysis should be below €935 per patient to be considered the least costly option.

Conclusions: The early-stage HTA findings suggest that FFRct may reduce total healthcare spending, probability of incorrect diagnoses, and major adverse cardiovascular events compared to current diagnostics for patients with stable chest pain in the Dutch healthcare setting over one year. Future cost-effectiveness studies should determine a value-based pricing for FFRct and quantify the economic value of the anticipated therapeutic impact.

Fig 1. Diagnostic care path for patients with stable chest pain in The Netherlands.

Abbreviations: GP: general practitioner; FFR: fractional flow reserve.

Fig 2. Flow chart of literature review.

Fig 3. Tornado diagram of the one-way sensitivity analyses.

This figure shows the model input parameters that have the greatest impact (indicated at the top) on the difference in costs between FFRct and standard diagnostics using a tornado diagram. The vertical axis indicates the names of the variables with the upper and lower values of the range used in the analysis in parentheses. The horizontal axis indicates the incremental (or difference in) cost between the two strategies. The dotted line indicates the expected value of the difference in cost using the base case values of the parameters. Using the base case values, FFRct is less expensive (-€234.95) compared to standard diagnostics. The red bars to the left of the dotted line indicate that when the value of that parameter increases, the difference in cost also increases (i.e., FFRct becomes more favourable); the blue bars to the left of the dotted line indicate that the difference in cost between the strategies will increase with decreasing values of that parameter. For example, if the specificity of CCTA decreases from 67% to 39%, the difference in costs will increase in favour of the FFRct strategy. Abbreviations: pSC_PCI: probability of percutaneous coronary intervention (PCI) in standard diagnostics arm; pCCTA_spec_wo: specificity of coronary computed tomography angiography (CCTA); pFFR_PCI: probability of PCI in the fractional flow reserve from coronary computed tomography (FFRct) arm; pMACE_noninv_US: probability of major adverse cardiovascular events (MACE) after a non-invasive test in the standard diagnostics arm; cPCI: costs of PCI; cFFRct: cost of FFR analysis (baseline: €700 per analysis); pMACE_noninv_FFR: probability of MACE after a non-invasive test in the FFRct arm; pTestIncon: probability of an inconclusive test result; pFFRct_spec: specificity of FFRct; pSC_CABG: probability of coronary artery bypass grafting (CABG) in the standard diagnostics arm; p_FFR_CABG: probability of CABG in the FFRct arm; p_FFRct_sens: sensitivity of FFRct; pCCTA_sens_wo: sensitivity of CCTA; cMACE: costs of MACE; pMACE_inv_US: probability of MACE after an invasive test in the standard diagnostics arm; pMACE_inv_FFR: probability of MACE after an invasive test in the FFRct arm; p_MRI_sens: sensitivity of magnetic resonance imaging (MRI); cCABG: costs of CABG; pFFR_Meds: probability of medications in the FFRct arm; pSC_Meds: probability of medications in the standard diagnostics arm; pICA_spec_wo: specificity of invasive coronary angiography (ICA); p_FFR_ICA_spec: specificity of fractional flow reserve from invasive coronary angiography; pICA_sens_wo: sensitivity of ICA; p_MRI_spec: specificity of MRI; p_FFR_ICA_sens: sensitivity of fractional flow reserve from invasive coronary angiography; cMedsMild: costs of medications for mild obstructive coronary artery disease patients; cMedsSevere: costs for severe obstructive coronary artery disease (CAD) patients; cCCTA: costs of CCTA; cFFR_ICA: costs of fractional flow reserve from ICA; cICA: costs of ICA; cMRI: costs of MRI.