Evidence map›Paper›PMID 22818218›Full record

ArticleBMC medical genomics2012

Patient-controlled encrypted genomic data: an approach to advance clinical genomics.

Yannis J Trakadis

Abstract read
In one paragraph

Article in BMC medical genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Is there a duty to recontact in light of new genetic technologies? A systematic review of the literature.Genetics in medicine : official journal of the American College of Medical Genetics · 2015
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Self-guided management of exome and whole-genome sequencing results: changing the results return model.Genetics in medicine : official journal of the American College of Medical Genetics · 2013
    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

1 author.

Yannis J TrakadisDepartment of Medical Genetics, Montreal Children's Hospital-McGill University Health Centre, 2300 Tupper, Montreal, QC, Canada. john.trakadis@mail.mcgill.ca

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe revolution in DNA sequencing technologies over the past decade has made it feasible to sequence an individual's whole genome at a relatively low cost. The potential value of the information generated by genomic technologies for medicine and society is enormous. However, in order for exome sequencing, and eventually whole genome sequencing, to be implemented clinically, a number of major challenges need to be overcome. For instance, obtaining meaningful informed-consent, managing incidental findings and the great volume of data generated (including multiple findings with uncertain clinical significance), re-interpreting the genomic data and providing additional counselling to patients as genetic knowledge evolves are issues that need to be addressed. It appears that medical genetics is shifting from the present "phenotype-first" medical model to a "data-first" model which leads to multiple complexities. DISCUSSION: This manuscript discusses the different challenges associated with integrating genomic technologies into clinical practice and describes a "phenotype-first" approach, namely, "Individualized Mutation-weighed Phenotype Search", and its benefits. The proposed approach allows for a more efficient prioritization of the genes to be tested in a clinical lab based on both the patient's phenotype and his/her entire genomic data. It simplifies "informed-consent" for clinical use of genomic technologies and helps to protect the patient's autonomy and privacy. Overall, this approach could potentially render widespread use of genomic technologies, in the immediate future, practical, ethical and clinically useful. SUMMARY: The "Individualized Mutation-weighed Phenotype Search" approach allows for an incremental integration of genomic technologies into clinical practice. It ensures that we do not over-medicalize genomic data but, rather, continue our current medical model which is based on serving the patient's concerns. Service should not be solely driven by technology but rather by the medical needs and the extent to which a technology can be safely and effectively utilized.

Indexed as

Computer SecurityPatientsData MiningDiseaseGenomicsHumansMutationPhenotype

Identifiers

PMID22818218
PMCPMC3439266

What OpenQuestion holds

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LicenceCC BY
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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.