Systematic review, meta-analysis and economic modelling of ...

Assessment of cost-effectiveness evidenceObjectivesThe objectives of the prognostic cost-effectiveness analysis were to:1. estimate the cost-effectiveness of prognostic strategies for troponin-negative patients, in terms of thecost per QALY gained by each strategy2. identify the optimal strategy, defined as the most cost-effective strategy at a willingness to pay perQALY gained threshold of £20,000–30,0003. identify the critical areas of uncertainty in the prognosis of troponin-negative patients with unknownCAD, where future research would produce the most benefit.The costs and benefits of prognostic testingThe main benefits of prognostic testing relate to identification and intervention of patients with risk ofnon-fatal MI and death. The direct costs of prognostic testing include the costs of investigation, hospitalstay for diagnosis, the subsequent costs of providing intervention and also reinfarction, if any. ICA,assumed as gold standard for diagnosing CAD, is the most effective but is also the most expensive andinvasive strategy. CTCA, exercise ECG or biomarkers incur costs and may miss cases owing to suboptimalsensitivity (thus worsening outcomes) but save costs by reducing the number of ICA performed. Webuilt a model to allow us to analyse the effect of different prognostic testing strategies on these costsand benefits.The decision-analysis model structureThe different prognostic strategies were applied to a hypothetical cohort of troponin-negative patientswho initially presented with suspected ACS. The model used the estimated probability of non-fatal MI ordeath for troponin-negative patients from the study of Mills 155 to determine a proportion of the cohortwho would die or suffer non-fatal MI without early investigation and treatment. The sensitivity of eachprognostic strategy for predicting MACEs would then determine which of these patients would have apositive test according to the strategy. We assumed that patients with a TP strategy would be investigatedand treated promptly, and a proportion of those who would have died or suffered non-fatal MI withouttreatment would avoid this outcome. Meanwhile those with a FP strategy would undergo investigationand treatment without any change to their prognosis. Each patient then accrued lifetime QALYs andhealth-care costs according to their age, sex, reinfarction and treatment status. Costs were also accruedfor biomarker costs and hospital stay for prognosis; costs were also accrued for further investigation,treatment and/or reinfarction, depending on the strategy and the patient characteristics.PopulationPatients with a positive 10-hour troponin result were assumed to be admitted for treatment and onlythose with a negative 10-hour troponin result were eligible for additional testing in the prognostic model.Moreover, the model was only tested on the population without known CAD because patients with knownCAD are already known to be at higher risk and will be receiving appropriate treatment.The population age and sex parameters were assumed to be the same as the population without knownCAD in the diagnostic model (see Table 32). We assumed that the prevalence of (unknown) CAD was 10%in this population, based on the prevalence of positive non-invasive tests in the studies of Hollander andGoodacre. 132,142 These tests have suboptimal accuracy for CAD, but the potential bias from suboptimalaccuracy was felt to be much less than the potential selection bias in studies in which all patients receivedinvasive testing. The parameters relating to MI prevalence and timing of symptoms were not relevant tothis phase.Selection of strategiesThe following strategies were tested:1. discharge all patients home without testing or treatment98NIHR Journals Library