Evidence map›Paper›PMID 34837511›Full record

ArticleEuropean radiology2022

Additional MRI for initial M-staging in pancreatic cancer: a cost-effectiveness analysis.

Felix G Gassert, Sebastian Ziegelmayer, Johanna Luitjens, Florian T Gassert, Fabian Tollens, Johann Rink, Marcus R Makowski, Johannes Rübenthaler, Matthias F Froelich

Open access · hybridAbstract read
In one paragraph

Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 22% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
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  5. Review
  6. Article
  7. Review
  8. 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

9 authors at 3 institutions in 1 country.

Felix G Gassert *Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, München, Germany. felix.gassert@tum.de.ORCID http://orcid.org/0000-0003-2260-8597
Sebastian Ziegelmayer *Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, München, Germany.
Johanna LuitjensDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Florian T GassertDepartment of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, München, Germany.
Fabian TollensDepartment of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany.
Johann RinkDepartment of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany.
Marcus R MakowskiDepartment of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, Technical University of Munich, Ismaninger Str. 22, 81675, München, Germany.
Johannes RübenthalerDepartment of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.
Matthias F FroelichDepartment of Radiology and Nuclear Medicine, University Medical Centre Mannheim, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany.
TUM Klinikum · DEUniversity Medical Centre Mannheim · DELMU Klinikum · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePancreatic cancer is portrayed to become the second leading cause of cancer-related death within the next years. Potentially complicating surgical resection emphasizes the importance of an accurate TNM classification. In particular, the failure to detect features for non-resectability has profound consequences on patient outcomes and economic costs due to incorrect indication for resection. In the detection of liver metastases, contrast-enhanced MRI showed high sensitivity and specificity; however, the cost-effectiveness compared to the standard of care imaging remains unclear. The aim of this study was to analyze whether additional MRI of the liver is a cost-effective approach compared to routinely acquired contrast-enhanced computed tomography (CE-CT) in the initial staging of pancreatic cancer.

methodsA decision model based on Markov simulation was developed to estimate the quality-adjusted life-years (QALYs) and lifetime costs of the diagnostic modalities. Model input parameters were assessed based on evidence from recent literature. The willingness-to-pay (WTP) was set to $100,000/QALY. To evaluate model uncertainty, deterministic and probabilistic sensitivity analyses were performed.

resultsIn the base-case analysis, the model yielded a total cost of $185,597 and an effectiveness of 2.347 QALYs for CE-MR/CT and $187,601 and 2.337 QALYs for CE-CT respectively. With a net monetary benefit (NMB) of $49,133, CE-MR/CT is shown to be dominant over CE-CT with a NMB of $46,117. Deterministic and probabilistic survival analysis showed model robustness for varying input parameters.

conclusionBased on our results, combined CE-MR/CT can be regarded as a cost-effective imaging strategy for the staging of pancreatic cancer. KEY POINTS: • Additional MRI of the liver for initial staging of pancreatic cancer results in lower total costs and higher effectiveness. • The economic model showed high robustness for varying input parameters.

Indexed as

Magnetic Resonance ImagingPancreatic NeoplasmsCost-Benefit AnalysisHumansQuality-Adjusted Life YearsTomography, X-Ray ComputedCancer stagingCost-effectivenessMagnetic resonance imagingMultidetector computed tomographyPancreatic neoplasms

Identifiers

PMID34837511
PMCPMC8921086
OpenAlexW3217548781

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.