Evidence map›Paper›PMID 31028539›Full record

ArticleVirchows Archiv : an international journal of pathology2019

IQN path ASBL report from the first European cfDNA consensus meeting: expert opinion on the minimal requirements for clinical ctDNA testing.

Zandra C Deans, Rachel Butler, Melanie Cheetham, Elisabeth M C Dequeker, Jennifer A Fairley, Francesca Fenizia, Jacqueline A Hall, Cleo Keppens, Nicola Normanno, Ed Schuuring and 1 more

Abstract readConsensus Statement
In one paragraph

Article in Virchows Archiv : an international journal of pathology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–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

19 citing papers in PubMed.

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  7. Circulating tumor DNA in Hodgkin lymphoma.Annals of hematology · 2022
    Review
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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

11 authors.

Zandra C DeansUK NEQAS for Molecular Genetics, Department of Laboratory Medicine, Royal Infirmary of Edinburgh, Little France Crescent, Edinburgh, EH16 4SA, UK. sandi.deans@ed.ac.uk.ORCID http://orcid.org/0000-0001-9361-6012
Rachel ButlerAll Wales Genetic Laboratory, Institute of Medical Genetics, University Hospital of Wales, Heath Park, Cardiff, CF14 4XW, UK.
Melanie CheethamEuropean Molecular Genetics Quality Network, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester, M13 9WL, UK.
Elisabeth M C DequekerBiomedical Quality Assurance Research Unit, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
Jennifer A FairleyUK NEQAS for Molecular Genetics, Department of Laboratory Medicine, Royal Infirmary of Edinburgh, Little France Crescent, Edinburgh, EH16 4SA, UK.
Francesca FeniziaCell Biology and Biotherapy Unit, Istituto Nazionale Tumori "Fondazione G. Pascale"-IRCCS, Naples, Italy.
Jacqueline A HallInternational Quality Network for Pathology (IQN Path ASBL), 3A Sentier de l'Esperance, 1474, Luxembourg, Luxembourg.
Cleo KeppensBiomedical Quality Assurance Research Unit, Department of Public Health and Primary Care, KU Leuven, Leuven, Belgium.
Nicola NormannoCell Biology and Biotherapy Unit, Istituto Nazionale Tumori "Fondazione G. Pascale"-IRCCS, Naples, Italy.
Ed SchuuringDepartment of Pathology, University of Groningen, University Medical Center of Groningen, Groningen, The Netherlands.
Simon J PattonEuropean Molecular Genetics Quality Network, Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester, M13 9WL, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liquid biopsy testing is a new laboratory-based method that detects tumour mutations in circulating free DNA (cfDNA) derived from minimally invasive blood sampling techniques. Recognising the significance for clinical testing, in 2017, IQN Path provided external quality assessment for liquid biopsy testing. Representatives of those participating laboratories were invited to attend a workshop to discuss the findings and how to achieve quality implementation of cfDNA testing in the clinical setting, the discussion and outcomes of this consensus meeting are described below. Predictive molecular profiling using tumour tissue in order to select cancer patients eligible for targeted therapy is now routine in diagnostic pathology. If insufficient tumour tissue material is available, in some circumstances, recent European Medicines Agency (EMA) guidance recommends mutation testing with plasma cfDNA. Clinical applications of cfDNA include treatment selection based on clinically relevant mutations derived from pre-treatment samples and the detection of resistant mutations upon progression of the disease. In order to identify tumour-related mutations in amongst other nucleic acid material found in plasma samples, highly sensitive laboratory methods are needed. In the workshop, we discussed the variable approaches taken with regard to cfDNA extraction methods, the tests, and considered the impact of false-negative test results. We explored the lack of standardisation of complex testing procedures ranging from plasma collection, transport, processing and storage, cfDNA extraction, and mutation analysis, to interpretation and reporting of results. We will also address the current status of clinical validation and clinical utility, and its use in current diagnosis. This workshop revealed a need for guidelines on with standardised procedures for clinical cfDNA testing and reporting, and a requirement for cfDNA-based external quality assessment programs.

Indexed as

Liquid BiopsyCell-Free Nucleic AcidsCirculating Tumor DNADNA Mutational AnalysisHumansMutationNeoplasmsCell-Free Nucleic AcidsCirculating Tumor DNAcfDNActDNALiquid biopsy testing

Identifiers

PMID31028539
PMCPMC6581928

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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.