Evidence map›Paper›PMID 26334528›Full record

SynthesisApplied health economics and health policy2016

A Systematic Review of Health Economic Evaluations of Diagnostic Biomarkers.

Marije Oosterhoff, Marloes E van der Maas, Lotte M G Steuten

Open access · hybridAbstract readSystematic Review
In one paragraph

Synthesis in Applied health economics and health policy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 6 pooled it
18.6field-weighted citation impact, top 1% 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

21 citing papers in PubMed, 6 syntheses or guidelines pooled it, 48 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Review
  8. Review
  9. Article
  10. Review
  11. Article
  12. Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Review
  13. Article
  14. Has the development of cancer biomarkers to guide treatment improved health outcomes?The European journal of health economics : HEPAC : health economics in prevention and care · 2021
    Article
  15. Review
  16. Toward Alignment in the Reporting of Economic Evaluations of Diagnostic Tests and Biomarkers: The AGREEDT Checklist.Medical decision making : an international journal of the Society for Medical Decision Making · 2018
    Review
  17. Article
  18. Precision Medicine: From Science To Value.Health affairs (Project Hope) · 2018
    Review
  19. The economic case for precision medicine.Expert review of precision medicine and drug development · 2018
    Article
  20. Review
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

3 authors at 3 institutions in 3 countries.

Marije OosterhoffPanaxea b.v., Hengelosestraat 221, 7521 AC, Enschede, The Netherlands. marije.oosterhoff@panaxea.eu.
Marloes E van der MaasPanaxea b.v., Hengelosestraat 221, 7521 AC, Enschede, The Netherlands. marloes.vandermaas@panaxea.eu.
Lotte M G SteutenPanaxea b.v., Hengelosestraat 221, 7521 AC, Enschede, The Netherlands. lotte.steuten@panaxea.eu.
Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa · ZAGlaxoSmithKline (United Kingdom) · GBOntwikkelingsmaatschappij Oost Nederland · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiagnostic biomarkers have multiple applications along the care process and have a large potential in optimizing treatment decisions. However, many diagnostic biomarkers struggle to gain market access and obtain appropriate coverage because of a lack of evidence on their health economic impact.

objectivesThe aim was to review the (methodological) characteristics of recent economic evaluations on diagnostic biomarkers and examine whether these studies dealt with specific issues such as different payer perspectives, preference heterogeneity, and multiple applications in subpopulations.

methodsThe PubMed database and the National Health Service Economic Evaluation Database were searched. Full economic evaluations published after 2009 assessing diagnostic biomarkers for the main non-communicable diseases in middle-income or high-income countries were considered eligible. Empirical and methodological study characteristics were summarized, as was the handling of specific issues related to the economic evaluation of personalized medicine.

resultsThirty-three economic evaluations were included, of which 25 were model-based analyses. The number of strategies compared ranged from two to 17 per study, and was especially large in studies assessing genetic testing in patients and their relatives. Cost-effectiveness results were most sensitive to test accuracy and costs of the biomarker (N = 7), the relative risk of an event (N = 4), and the proportion of people accepting genetic testing (N = 2). One study incorporated patient preferences, and none of the studies considered different payer perspectives, cost sharing arrangements or variable opportunity costs due to population density variability.

conclusionsPublished health economic evaluations of biomarkers used for diagnosing, staging diseases, and guiding treatment selection are characterized by a large number of comparators to model the potential clinical applications and to determine their value. Assessing outcomes beyond health as well as specific issues, such as different payer perspectives and patient preferences, is crucial to fully capture the potential health economic impact of diagnostic biomarkers and to inform value-based reimbursement.

Indexed as

Cost-Benefit AnalysisBiomarkersHumansBiomarkers

Identifiers

PMID26334528
PMCPMC4740568
OpenAlexW1782512405

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.