Evidence map›Paper›PMID 34852765›Full record

ArticleBMC nephrology2021

Cost-effectiveness and value of information analysis of NephroCheck and NGAL tests compared to standard care for the diagnosis of acute kidney injury.

Elisabet Jacobsen, Simon Sawhney, Miriam Brazzelli, Lorna Aucott, Graham Scotland, Magaly Aceves-Martins, Clare Robertson, Mari Imamura, Amudha Poobalan, Paul Manson and 2 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC nephrology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. How accurate should a precision medical test be to meet cost-effectiveness.Cost effectiveness and resource allocation : C/E · 2026
    Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Urinary NGAL OutperformsTransplant international : official journal of the European Society for Organ Transplantation · 2025
    Article
  11. Article
  12. Observational
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Elisabet JacobsenHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK. elisabet.jacobsen@abdn.ac.uk.
Simon SawhneyAberdeen Centre for Health Data Science, University of Aberdeen, Aberdeen, UK.
Miriam BrazzelliHealth Services Research Unit, University of Aberdeen, Aberdeen, UK.
Lorna AucottHealth Services Research Unit, University of Aberdeen, Aberdeen, UK.
Graham ScotlandHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK.
Magaly Aceves-MartinsHealth Services Research Unit, University of Aberdeen, Aberdeen, UK.
Clare RobertsonHealth Services Research Unit, University of Aberdeen, Aberdeen, UK.
Mari ImamuraHealth Services Research Unit, University of Aberdeen, Aberdeen, UK.
Amudha PoobalanInstitute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK.
Paul MansonHealth Services Research Unit, University of Aberdeen, Aberdeen, UK.
Callum KayeNHS Grampian, Aberdeen Royal Infirmary, Aberdeen, UK.
Dwayne BoyersHealth Economics Research Unit, University of Aberdeen, Aberdeen, UK.
University of Aberdeen · GBAberdeen Royal Infirmary · GB

Funding

Chief Scientist Office HERU1Chief Scientist Office HSRU1
6 · The paper itself

Abstract

backgroundEarly 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.

methodsA 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.

resultsUnder 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.

conclusionsCurrent 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.

Indexed as

Cost-Benefit AnalysisAcute Kidney InjuryBiomarkersDecision TreesFemaleHumansMaleMiddle AgedBiomarkersAcute kidney injuryCost-effectivenessCritical careDiagnostic accuracyEconomic evaluationMarkov modelNephrology

Identifiers

PMID34852765
PMCPMC8638090
OpenAlexW3213520255

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.