Evidence map›Paper›PMID 31550176›Full record

ReviewJCO clinical cancer informatics2019

Operationalization of Next-Generation Sequencing and Decision Support for Precision Oncology.

Jia Zeng, Amber Johnson, Md Abu Shufean, Michael Kahle, Dong Yang, Scott E Woodman, Thuy Vu, Shhyam Moorthy, Vijaykumar Holla, Funda Meric-Bernstam

Abstract readReview
In one paragraph

Review in JCO clinical cancer informatics, 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.

  1. Article
  2. Article
  3. Article
  4. Sex-dependent Prognosis of Patients with Advanced Soft Tissue Sarcoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Cancers · 2021
    Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. 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

10 authors.

Jia ZengThe University of Texas MD Anderson Cancer Center, Houston, TX.
Amber JohnsonThe University of Texas MD Anderson Cancer Center, Houston, TX.
Md Abu ShufeanThe University of Texas MD Anderson Cancer Center, Houston, TX.
Michael KahleThe University of Texas MD Anderson Cancer Center, Houston, TX.
Dong YangThe University of Texas MD Anderson Cancer Center, Houston, TX.
Scott E WoodmanThe University of Texas MD Anderson Cancer Center, Houston, TX.
Thuy VuThe University of Texas MD Anderson Cancer Center, Houston, TX.
Shhyam MoorthyThe University of Texas MD Anderson Cancer Center, Houston, TX.
Vijaykumar HollaThe University of Texas MD Anderson Cancer Center, Houston, TX.
Funda Meric-BernstamThe University of Texas MD Anderson Cancer Center, Houston, TX.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Fabien Delerue · 1985 to 2026
$290.8M
Center for Clinical and Translational Sciences (CCTS)UL1TR000371 · NCATS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI MCPHERSON, DAVID D · 2012 to 2016
$13.4M
NCATS NIH HHS UL1 TR000371NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

Genomic testing has become a part of routine oncology care and plays critical roles in diagnosis, prognostic assessment, and treatment selection. Thus, in parallel, the variety of genomic testing providers and sequencing platforms has grown exponentially. Selection of the best-fit panel for each case can be daunting, with many factors to consider. Among them is whether alteration interpretation and therapy/clinical trial matching are included and/or sufficient. In this article, we review some common commercially available sequencing platforms for the genes and types of alterations tested, samples needed, and reporting content provided. We review publicly available resources for a do-it-yourself approach to alteration interpretation when it is not provided or when supplemental research is needed, along with resources to identify genomically matched treatment options that are approved and/or investigational. However, with both commercially provided interpretation and publicly available resources, there are still caveats and limitations that can stem from insufficient or ambiguous nomenclature as well as from the presentation of information. Use cases in which clinical decision making was affected are discussed. After treatment options are identified, it is important to assess the level of evidence for use within the patient's tumor type and molecular profile. However, numerous level-of-evidence scales have been published in recent years, so we provide a publicly available tool to facilitate interoperability. The level of evidence, along with other factors, such as allelic frequency and copy number, can be used to prioritize treatment options when multiple are identified.

Indexed as

Decision Support Systems, ClinicalHigh-Throughput Nucleotide SequencingMedical OncologyPrecision MedicineClinical Decision-MakingDisease ManagementHealth PrioritiesHumansPractice Patterns, Physicians'

Identifiers

PMID31550176
PMCPMC6874004

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.