Evidence map›Paper›PMID 27600079›Full record

ReviewMicroarrays (Basel, Switzerland)2016

Advantages of Array-Based Technologies for Pre-Emptive Pharmacogenomics Testing.

Al Shahandeh, Daniel M Johnstone, Joshua R Atkins, Jean-Marie Sontag, Moones Heidari, Nilofar Daneshi, Elvis Freeman-Acquah, Elizabeth A Milward

Abstract readReview
In one paragraph

Review in Microarrays (Basel, Switzerland), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing.Annual review of genomics and human genetics · 2022
    Review
  6. Article
  7. Article
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

8 authors.

Al ShahandehSchool of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan 2308, Australia. Ali.Shahandeh@uon.edu.au.
Daniel M JohnstoneThe Bosch Institute and Discipline of Physiology, University of Sydney, Sydney 2006, Australia. Daniel.Johnstone@sydney.edu.au.
Joshua R AtkinsSchool of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan 2308, Australia. Joshua.Atkins@uon.edu.au.
Jean-Marie SontagSchool of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan 2308, Australia. Jean-Marie.Sontag@newcastle.edu.au.
Moones HeidariSchool of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan 2308, Australia. Moones.Heidari@uon.edu.au.
Nilofar DaneshiSchool of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan 2308, Australia. Nilofar.Daneshi@uon.edu.au.
Elvis Freeman-AcquahInstitute of Genetics and Cytology, School of Life Sciences, Northeast Normal University, Changchun 130024, China. davfreeman82@yahoo.com.
Elizabeth A MilwardSchool of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan 2308, Australia. Liz.Milward@newcastle.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As recognised by the National Institutes of Health (NIH) Precision Medicine Initiative (PMI), microarray technology currently provides a rapid, inexpensive means of identifying large numbers of known genomic variants or gene transcripts in experimental and clinical settings. However new generation sequencing techniques are now being introduced in many clinical genetic contexts, particularly where novel mutations are involved. While these methods can be valuable for screening a restricted set of genes for known or novel mutations, implementation of whole genome sequencing in clinical practice continues to present challenges. Even very accurate high-throughput methods with small error rates can generate large numbers of false negative or false positive errors due to the high numbers of simultaneous readings. Additional validation is likely to be required for safe use of any such methods in clinical settings. Custom-designed arrays can offer advantages for screening for common, known mutations and, in this context, may currently be better suited for accredited, quality-controlled clinical genetic screening services, as illustrated by their successful application in several large-scale pre-emptive pharmacogenomics programs now underway. Excessive, inappropriate use of next-generation sequencing may waste scarce research funds and other resources. Microarrays presently remain the technology of choice in applications that require fast, cost-effective genome-wide screening of variants of known importance, particularly for large sample sizes. This commentary considers some of the applications where microarrays continue to offer advantages over next-generation sequencing technologies.

Indexed as

microarraynext-generation sequencingpersonalized healthcarepharmacogenomics

Identifiers

PMID27600079
PMCPMC5003488

What OpenQuestion holds

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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.