A data driven framework for improved therapeutic outcomes in IA
Research type
Research Study
Full title
Study Title: Development of a data driven precision framework for improved therapeutic outcomes in invasive aspergillosis (IA)– a multicentre, observational, retrospective data analysis study
IRAS ID
318846
Contact name
Lisa Nwankwo
Contact email
Sponsor organisation
Royal Brompton and Harefield Hospital NHS Trust
Duration of Study in the UK
1 years, 0 months, 1 days
Research summary
About 0.2 million people suffer from invasive aspergillosis(IA) each year, which imparts a significant burden to patients and health care systems. Aspergillosis adds 9.8 days to a patient's hospital stay and costs £31501 more to treat than a patient without it. Aspergillosis mainly affects immunocompromised, underlying disease, or critically ill people and has a 40-90% fatality rate. Standard care involves voriconazole use first and additional medicines as salvage therapy.
There are no head-to-head comparison studies of all the available treatments (triazoles, the polyenes and echinocandins) in clinical trials in terms of efficacy and safety profile, and there are no real-world objective evaluations of the various triazoles for the treatment of invasive aspergillosis. Based on a medical database search, only one network meta-analysis in this setting has been published. It showed isavuconazole to be comparable to the standard of care (voriconazole) and to liposomal amphotericin B.
Despite a decline in mortality rates with the use of voriconazole in the last two decades, treatment remains sub-optimal due to adverse events and drug-drug interactions with immunosuppressive drugs. Additionally, antifungal resistance poses a significant threat and is a major cause of treatment failure. Patients with Azole-resistant A. fumigatus infections are up to 33% more likely to die than patients with infections that can be treated with azoles. While inappropriate antifungal use or overuse is known to result in resistance, there is a lack of specific information from health record data on patient predictors of treatment failure, including antifungal resistance.
This study aims to evaluate the effectiveness of current therapies in an invasive aspergillosis disease setting on a real-world large dataset of patients from multiple centres, and to identify patient parameters that predispose to earlier treatment failure, including antifungal resistance, using machine learning techniques. This data-driven research could provide patient-centered therapy recommendations to reduce unfavourable treatment outcomes, treatment failure, and antifungal resistance.
REC name
East of England - Cambridge South Research Ethics Committee
REC reference
22/EE/0302
Date of REC Opinion
9 Feb 2023
REC opinion
Further Information Favourable Opinion