Evidence map›Paper›PMID 34125426›Full record

ArticleMolecular diagnosis & therapy2021

Internal Standardization of the Interpretation and Reporting of Sequence Variants in Hematologic Neoplasms.

Nikita Mehta, Rong He, David S Viswanatha

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Article in Molecular diagnosis & therapy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Nikita MehtaDepartment of Laboratory Medicine and Pathology, Molecular Hematology Laboratory, Mayo Clinic, Rochester, MN, USA. MehtaN5@mskcc.org.ORCID 0000-0003-1465-2934
Rong HeDepartment of Laboratory Medicine and Pathology, Molecular Hematology Laboratory, Mayo Clinic, Rochester, MN, USA.
David S ViswanathaDepartment of Laboratory Medicine and Pathology, Molecular Hematology Laboratory, Mayo Clinic, Rochester, MN, USA. Viswanatha.David@mayo.edu.
Mayo Clinic · USMayo Clinic in Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAccurate classification of somatic genetic alterations detected by next-generation sequencing (NGS) assays is of paramount importance to ensure the provision of high-quality clinical data. Clinical significance of variants can be assessed and tiered based on guidelines from the Association for Molecular Pathology (AMP), the American Society of Clinical Oncology, and the College of American Pathology for the interpretation of somatic sequence variants identified in cancer.

methodsWe sought to develop a formal structured approach for the classification of somatic variants in hematologic neoplasms, to account for both a variant's clinical significance and its ability to drive tumorigenesis, by adapting elements from these existing guidelines. However, we additionally utilized key criteria from the American College of Medical Genetics/AMP standards for variant reporting to focus evaluation into specific categories of evidence and to gauge the effect of a given variant on tumorigenesis.

resultsThe combined approach was applied to the annotation of 87 variants identified by a targeted NGS panel for myeloid neoplasms. In the application of our variant evaluation, we classified 2/87 variants as benign, 6/87 as likely benign, 56/87 as variants of unknown significance (VUS), 13/87 variants as likely pathogenic, and 10/87 variants as pathogenic.

conclusionWell-established oncogenic alterations were accurately classified as pathogenic. Although there is no defined benchmark for the remaining variants, drawing from two existing guidelines enabled the creation of a modified curation process for variant interpretation that emphasizes systematic review of relevant evidence.

Indexed as

Genetic VariationAlgorithmsGuidelines as TopicHematologic NeoplasmsHigh-Throughput Nucleotide SequencingHumansResearch DesignSequence Analysis, DNA

Identifiers

PMID34125426
OpenAlexW3167844968

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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.