Evidence map›Paper›PMID 24872353›Full record

SynthesisStatistical methods in medical research2015

Meta-analysis of the technical performance of an imaging procedure: guidelines and statistical methodology.

Erich P Huang, Xiao-Feng Wang, Kingshuk Roy Choudhury, Lisa M McShane, Mithat Gönen, Jingjing Ye, Andrew J Buckler, Paul E Kinahan, Anthony P Reeves, Edward F Jackson and 3 more

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Statistical methods in medical research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 2 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

25 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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  13. Article
  14. MRI biomarkers in neuro-oncology.Nature reviews. Neurology · 2021
    Review
  15. Review
  16. Review
  17. NCTN Assessment on Current Applications of Radiomics in Oncology.International journal of radiation oncology, biology, physics · 2019
    Review
  18. Review
  19. Magnetic resonance imaging biomarkers for chronic kidney disease: a position paper from the European Cooperation in Science and Technology Action PARENCHIMA.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 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

13 authors.

Erich P HuangDivision of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA erich.huang@nih.gov.
Xiao-Feng WangDepartment of Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH, USA.
Kingshuk Roy ChoudhuryDepartment of Biostatistics and Bioinformatics/Department of Radiology, Duke University Medical School, Durham, NC, USA.
Lisa M McShaneDivision of Cancer Treatment and Diagnosis, National Cancer Institute, NIH, Bethesda, MD, USA.
Mithat GönenDepartment of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Jingjing YeDivision of Biostatistics, Center of Devices and Radiological Health, Food and Drug Administration, Silver Spring, MD, USA.
Andrew J BucklerElucid Biomedical Imaging Inc., Wenham, MA, USA.
Paul E KinahanDepartment of Radiology, University of Washington, Seattle, WA, USA.
Anthony P ReevesSchool of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA.
Edward F JacksonDepartment of Medical Physics, University of Wisconsin, Madison, WI, USA.
Alexander R GuimaraesMassachusetts General Hospital, Boston, MA, USA.
Gudrun ZahlmannF. Hoffmann-La Roche, Ltd., Basel, Switzerland.
Meta-Analysis Working Group

Funding

Advanced PET/CT Imaging for Improving Clinical TrialsU01CA148131 · NCI · UNIVERSITY OF WASHINGTON · PI KINAHAN, PAUL E., LINDEN, HANNAH M · 2010 to 2019
$6.0M
NCI NIH HHS U01 CA148131NIBIB NIH HHS HHSN268201000050C
6 · The paper itself

Abstract

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test-retest repeatability data for illustrative purposes.

Indexed as

BiomarkersDiagnostic ImagingGuidelines as TopicMeta-Analysis as TopicResearch DesignStatistics as TopicHumansReproducibility of ResultsBiomarkersimaging biomarkersmeta-analysismeta-regressionquantitative imagingrepeatabilityreproducibilitysystematic reviewtechnical performance

Identifiers

PMID24872353
PMCPMC5226954

What OpenQuestion holds

Textmetadata
LicenceTDM
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.