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Cost-effectiveness and Value of Information Analysis of NephroCheck and NGAL Tests Compared to Standard Care for the Diagnosis of Acute Kidney Injury

Overview
Journal BMC Nephrol
Publisher Biomed Central
Specialty Nephrology
Date 2021 Dec 2
PMID 34852765
Citations 8
Authors
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Abstract

Background: Early and accurate acute kidney injury (AKI) detection may improve patient outcomes and reduce health service costs. This study evaluates the diagnostic accuracy and cost-effectiveness of NephroCheck and NGAL (urine and plasma) biomarker tests used alongside standard care, compared with standard care to detect AKI in hospitalised UK adults.

Methods: A 90-day decision tree and lifetime Markov cohort model predicted costs, quality adjusted life years (QALYs) and incremental cost-effectiveness ratios (ICERs) from a UK NHS perspective. Test accuracy was informed by a meta-analysis of diagnostic accuracy studies. Clinical trial and observational data informed the link between AKI and health outcomes, health state probabilities, costs and utilities. Value of information (VOI) analysis informed future research priorities.

Results: Under base case assumptions, the biomarker tests were not cost-effective with ICERs of £105,965 (NephroCheck), £539,041 (NGAL urine BioPorto), £633,846 (NGAL plasma BioPorto) and £725,061 (NGAL urine ARCHITECT) per QALY gained compared to standard care. Results were uncertain, due to limited trial data, with probabilities of cost-effectiveness at £20,000 per QALY ranging from 0 to 99% and 0 to 56% for NephroCheck and NGAL tests respectively. The expected value of perfect information (EVPI) was £66 M, which demonstrated that additional research to resolve decision uncertainty is worthwhile.

Conclusions: Current evidence is inadequate to support the cost-effectiveness of general use of biomarker tests. Future research evaluating the clinical and cost-effectiveness of test guided implementation of protective care bundles is necessary. Improving the evidence base around the impact of tests on AKI staging, and of AKI staging on clinical outcomes would have the greatest impact on reducing decision uncertainty.

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References
1.
Wilson F, Shashaty M, Testani J, Aqeel I, Borovskiy Y, Ellenberg S . Automated, electronic alerts for acute kidney injury: a single-blind, parallel-group, randomised controlled trial. Lancet. 2015; 385(9981):1966-74. PMC: 4475457. DOI: 10.1016/S0140-6736(15)60266-5. View

2.
Wilson F, Martin M, Yamamoto Y, Partridge C, Moreira E, Arora T . Electronic health record alerts for acute kidney injury: multicenter, randomized clinical trial. BMJ. 2021; 372:m4786. PMC: 8034420. DOI: 10.1136/bmj.m4786. View

3.
Ara R, Brazier J . Using health state utility values from the general population to approximate baselines in decision analytic models when condition-specific data are not available. Value Health. 2011; 14(4):539-45. DOI: 10.1016/j.jval.2010.10.029. View

4.
Kent S, Schlackow I, Lozano-Kuhne J, Reith C, Emberson J, Haynes R . What is the impact of chronic kidney disease stage and cardiovascular disease on the annual cost of hospital care in moderate-to-severe kidney disease?. BMC Nephrol. 2015; 16:65. PMC: 4424521. DOI: 10.1186/s12882-015-0054-0. View

5.
Petrovic S, Bogavac-Stanojevic N, Lakic D, Peco-Antic A, Vulicevic I, Ivanisevic I . Cost-effectiveness analysis of acute kidney injury biomarkers in pediatric cardiac surgery. Biochem Med (Zagreb). 2015; 25(2):262-71. PMC: 4470097. DOI: 10.11613/BM.2015.027. View