Decision analytical modelling of strategies for investigating suspected acute aortic syndrome.

Abstract

Background: Acute aortic syndrome (AAS) requires urgent diagnosis with computed tomographic angiography (CTA). Diagnostic strategies need to weigh the benefits of detecting AAS against the costs of using CTA with a low yield of AAS when the prevalence of AAS is low. We aimed to estimate the cost-effectiveness of diagnostic strategies using clinical probability scoring and D-dimer to select patients with potential symptoms of AAS for CTA.

Methods: We developed a decision analytical model to simulate the management of patients attending hospital with possible AAS. We modelled diagnostic strategies that used the Aortic Dissection Detection Risk Score (ADD-RS) and D-dimer to select patients for CTA. We used estimates from our meta-analysis, existing literature and clinical experts to model the consequences of diagnostic strategies on survival, health utility, and health and social care costs. We estimated the incremental cost per quality-adjusted life-years gained by each strategy compared with the next most effective alternative on the efficiency frontier.

Results: A strategy based on the Canadian guideline (CTA if ADD-RS>1 or ADD-RS=1 with D-dimer >500 ng/mL) is cost-effective but would result in high rates of CTA if applied to an unselected population (AAS prevalence 0.26%). The strategy is also cost-effective and would result in lower rates of CTA if applied to a more selected population, such as those with a non-zero clinical suspicion of AAS (prevalence 0.61%). For patients currently receiving CTA, using ADD-RS>1 or D-dimer >500 ng/mL to select patients for CTA is cost-effective.

Conclusions: A strategy using ADD-RS>1 or ADD-RS=1 with D-dimer >500 ng/mL to select patients for CTA appears cost-effective but primary research is required to evaluate this strategy in practice and determine how suspicion of AAS is identified.