The clinical problem this research addresses is the over-prescription of drugs used to treat Candida fungal infection in adults and children in intensive care units (ICU). Treatment with ‘antifungal’ drugs is started when patients are thought to be at risk of fungal infection, even though the large majority turn out not to have this. The majority of ICU patients who are treated with an antifungal drug receive treatment on an empirical basis. Typically, 7% of patients in ICU receive treatment for fungal infection and the majority are started on a presumptive basis. Of these, only 1 in 20 have fungal infection confirmed. Up to 11,000 patients receive potentially unnecessary antifungal treatment each year, at a cost of up to £12million to the NHS. Most patients treated fail to benefit and are disadvantaged by the risk of side effects. Over-treatment can also lead to resistance to these drugs in the wider population. We propose to evaluate how accurately three new, rapid tests can diagnose fungal infection in adults and children, started presumptively on antifungal treatment. We will need to study 1,720 patients in UK ICUs to give us a statistically reliable result. After obtaining consent, we will test blood samples from patients who are being started on antifungal treatment. We will determine the clinical and economic impact of implementing these rapid tests, based on how accurately they diagnose fungal infection. The main aim of this study is to establish the ability of these tests, to rule out fungal infection in this patient group. We will use these results to develop a guideline that could be used by ICU staff to reduce unnecessary antifungal drug use.
The aim of this trial is to assess the performance of three rapid tests to detect fungal infection. The accuracy of these tests will be compared and the optimal test (or combination) will be identified. The emphasis will be on their ability to rule-out infection so that a test-based protocol for early discontinuation of antifungal therapy can be developed. This test-based protocol will be modelled for clinical and cost effectiveness, accounting for expected beneficial and adverse outcomes. This modelling, together with a value of information analysis, will inform the design of a future clinical & cost effectiveness RCT.
Dr Ronan McMullan