Evidence map›Paper›PMID 22419257›Full record

ArticleEuropean journal of nuclear medicine and molecular imaging2012

Cost-effectiveness analysis of FET PET-guided target selection for the diagnosis of gliomas.

Alexander Heinzel, Stephanie Stock, Karl-Josef Langen, Dirk Müller

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Article in European journal of nuclear medicine and molecular imaging, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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, 3 syntheses or guidelines pooled it.

  1. Interval brain imaging for adults with cerebral glioma.The Cochrane database of systematic reviews · 2019
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  9. The Use ofDiagnostics (Basel, Switzerland) · 2022
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  11. Cost-Effectiveness of [Frontiers in oncology · 2019
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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

4 authors.

Alexander HeinzelDepartment of Nuclear Medicine of the Heinrich-Heine University of Duesseldorf, Research Centre Juelich, 52426 Juelich, Germany. a.heinzel@fz-juelich.de
Stephanie Stock
Karl-Josef Langen
Dirk Müller

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeSeveral diagnostic trials have indicated that the combined use of (18)F-fluoroethyl-L: -tyrosine (FET) PET and MRI may be superior to MRI alone in selecting the biopsy site for the diagnosis of gliomas. We estimated the cost-effectiveness of the use of amino acid PET compared to MRI alone from the perspective of the German statutory health insurance.

methodsTo evaluate the incremental cost-effectiveness of the use of amino acid PET, a decision tree model was built. The effectiveness of FET PET was determined by the probability of a correct diagnosis. Costs were estimated for a baseline scenario and for a more expensive scenario in which disease severity was considered. The robustness of the results was tested using deterministic and probabilistic sensitivity analyses.

resultsThe combined use of PET and MRI resulted in an increase of 18.5% in the likelihood of a correct diagnosis. The incremental cost-effectiveness ratio for one additional correct diagnosis using FET PET was €6,405 for the baseline scenario and €9,114 for the scenario based on higher disease severity. The probabilistic sensitivity analysis confirmed the robustness of the results.

conclusionThe model indicates that the use of amino acid PET may be cost-effective in patients with glioma. As a result of several limitations in the data used for the model, further studies are needed to confirm the results.

Indexed as

RadiopharmaceuticalsBiopsyBrain NeoplasmsCost-Benefit AnalysisDecision TreesGliomaHumansMagnetic Resonance ImagingMonte Carlo MethodPositron-Emission TomographyTyrosine(18F)fluoroethyltyrosineRadiopharmaceuticalsTyrosine

Identifiers

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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.