Evidence map›Paper›PMID 25880439›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2016

A classification system for clinical relevance of somatic variants identified in molecular profiling of cancer.

Mahadeo A Sukhai, Kenneth J Craddock, Mariam Thomas, Aaron R Hansen, Tong Zhang, Lillian Siu, Philippe Bedard, Tracy L Stockley, Suzanne Kamel-Reid

Open access · bronzeAbstract readEvaluation Study
PubMed Publisher
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
47citing papers in PubMed, 2 pooled it
5.0field-weighted citation impact, top 4% 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

47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 97 citations in OpenAlex.

  1. Guideline
  2. Molecular Biomarkers for the Evaluation of Colorectal Cancer.American journal of clinical pathology · 2017
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  14. Practice guidelines forJournal of medical genetics · 2022
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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

9 authors at 2 institutions in 1 country.

Mahadeo A SukhaiLaboratory Medicine Program, Advanced Molecular Diagnostics Laboratory, Department of Pathology, University Health Network, Toronto, Ontario, Canada.ORCID http://orcid.org/0000-0002-9122-2519
Kenneth J CraddockLaboratory Medicine Program, Advanced Molecular Diagnostics Laboratory, Department of Pathology, University Health Network, Toronto, Ontario, Canada.
Mariam ThomasLaboratory Medicine Program, Advanced Molecular Diagnostics Laboratory, Department of Pathology, University Health Network, Toronto, Ontario, Canada.
Aaron R HansenDivision of Medical Oncology, Princess Margaret Cancer Centre, The University Health Network, Toronto, Ontario, Canada.
Tong ZhangLaboratory Medicine Program, Advanced Molecular Diagnostics Laboratory, Department of Pathology, University Health Network, Toronto, Ontario, Canada.
Lillian SiuDivision of Medical Oncology, Princess Margaret Cancer Centre, The University Health Network, Toronto, Ontario, Canada.
Philippe BedardDivision of Medical Oncology, Princess Margaret Cancer Centre, The University Health Network, Toronto, Ontario, Canada.
Tracy L StockleyLaboratory Medicine Program, Advanced Molecular Diagnostics Laboratory, Department of Pathology, University Health Network, Toronto, Ontario, Canada.
Suzanne Kamel-ReidLaboratory Medicine Program, Advanced Molecular Diagnostics Laboratory, Department of Pathology, University Health Network, Toronto, Ontario, Canada.
Princess Margaret Cancer Centre · CAUniversity Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeInterpretation systems for clinical laboratory reporting of genetic variants for inherited conditions have been widely published. By contrast, there are no existing systems for interpretation and classification of somatic variants found from molecular testing of cancer.

methodsWe designed an assessment protocol and classification system for somatic variants identified through next-generation sequencing molecular profiling of tumor-derived samples and applied these to a pilot dataset of somatic variants found by next-generation sequencing profiling of 158 tumor samples derived from advanced cancer patients examined at the Princess Margaret Cancer Centre.

resultsWe present a classification system to interpret the significance of genetic variants in molecular analysis of cancer, including the following key factors: (i) known or predicted pathogenicity of the variant; (ii) primary site and tumor histology in which the variant is found; (iii) recurrence of the variant; and (iv) evidence of clinical actionability. We used these factors to develop a five-category somatic variant classification for simplified reporting of variant interpretations to treating oncologists.

conclusionOur somatic variant classification can be of practical value to other clinical molecular laboratories performing cancer genetic profiling by promoting consistent reporting of somatic variants and permitting harmonization of variant data among laboratories and clinical studies.

Indexed as

Genetic TestingGenetic VariationBreast NeoplasmsCohort StudiesColorectal NeoplasmsGenetic TechniquesHumansNeoplasmsPilot Projects

Identifiers

PMID25880439
OpenAlexW2070727336

What OpenQuestion holds

Textmetadata
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.