Cost-effectiveness of CTA, MRA and DSA in patients with non-traumatic subarachnoid hemorrhage 137 Table 1 continued uDis 0.25 0.21-0.30 triangular 19,23 clinical outcome propabilities Probability of being well after clipping 0.69 0.014 beta 8 Probability of being disabled after clipping 0.21 0.013 beta 8 pClipdead 0.10 0.009 beta 8 pClipwell (probability of being well after survived clipping) 0.77 8 Probability of being well after coiling 0.76 0.013 beta 8 Probability of being disabled after coiling 0.16 0.011 beta 8 pCoildead 0.08 0.008 beta 8 pCoilwell (probability of being well after survived coiling) 0.83 8 Probability of being well after DSA 0.998 0.001 beta 15,16 Probability of being disabled after DSA 0.002 0.001 beta 15,16 pDSAwell (probability of being well after survived DSA) 0.998 probability of being dead/disabled after surgery without aneurysm pSurgdead 0.025 0.004 beta 27 pSurgdisab 0.132 0.008 beta 27 pCoilTP (probability coiling is feasible in true positive aneurysm) 0.585 0.061 beta * pCoilFP (probability coiling is feasible in false positive aneurysm) 0 fixed * Treatment dependent parameters Probabilities pMRAtpD (Sensitivity MRA in diagnosing aneurysm) 0.954 0.018 beta 20 pMRAtnD (Specificity MRA in diagnosing aneurysm) 0.833 0.061 beta 20 pCTAtpD (Sensitivity CTA in diagnosing aneurysm) 0.915 0.024 beta 20 pCTAtnD (Specificity CTA in diagnosing aneurysm) 0.944 0.038 beta 20 pMRAtpT (Sensitivity MRA in determining whether coiling is feasible) 0.606 0.058 beta * pMRAtnT (Specificity MRA in determining whether coiling is feasible) 0.816 0,050 beta * pCTAtpT (Sensitivity CTA in determining whether coiling is feasible) 0.719 0.056 beta * pCTAtnT (Specificity CTA in determining whether coiling is feasible) 0.754 0.057 beta * pDSAtpD (Sensitivity DSA in diagnosing aneurysm) 1 fixed * pDSAtnD (Specificity DSA in diagnosing aneurysm) 1 fixed * pDSAtpT (Sensitivity DSA in determining whether coiling is feasible) 1 fixed * pDSAtnT (Specificity DSA in determining whether coiling is feasible) 1 fixed * * Data based on study with 75 patients (see Chapter 3) To illustrate the results of the simulation, cost-effectiveness acceptability curves (CEACs) were calculated.28 CEACs show the probability that a strategy is cost-effective, given different values of willingness to pay for a QALY. Simulation was also repeated with univariate sensitivity analyses for costs of DSA, MRA and CTA as well as for costs of coiling and clipping to determine association between model parameters and uncertainty in cost-effectiveness outcome.
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