Evidence map›Paper›PMID 24588254›Full record

ReviewClinical genetics2014

Biobanks and personalized medicine.

J E Olson, S J Bielinski, E Ryu, E M Winkler, P Y Takahashi, J Pathak, J R Cerhan

Abstract readReview
In one paragraph

Review in Clinical genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Establishing a Pregnancy Lyme Disease Biobank.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Dynamic Biobanking for Advancing Breast Cancer Research.Journal of personalized medicine · 2023
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Biobanking in health care: evolution and future directions.Journal of translational medicine · 2019
    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

7 authors.

J E OlsonDepartment of Health Sciences Research, Rochester, MN, USA.
S J Bielinski
E Ryu
E M Winkler
P Y Takahashi
J Pathak
J R Cerhan

Funding

National Infrastructure for Standardized and Portable EHR Phenotyping AlgorithmsR01GM105688 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI LUO, YUAN, PATHAK, JYOTISHMAN · 2013 to 2020
$5.7M
Informatics Tools for Pharmacogenomic Discovery using Practice-based DataR01GM103859 · NIGMS · VANDERBILT UNIVERSITY MEDICAL CENTER · PI DENNY, JOSHUA C., PATHAK, JYOTISHMAN · 2014 to 2017
$2.4M
NIGMS NIH HHS R01 GM103859NIGMS NIH HHS R01 GM105688
6 · The paper itself

Abstract

We provide a mini-review of how biobanks can support clinical genetics in the era of personalized medicine. We discuss types of biobanks, including disease specific and general biobanks not focused on one disease. We present considerations in setting up a biobank, including consenting and governance, biospecimens, risk factor and related data, informatics, and linkage to electronic health records for phenotyping. We also discuss the uses of biobanks and ongoing considerations, including genotype-driven recruitment, investigations of gene-environment associations, and the re-use of data generated from studies. Finally, we present a brief discussion of some of the unresolved issues, such as return of research results and sustaining biobanks over time. In summary, carefully designed biobanks can provide critical research and infrastructure support for clinical genetics in the era of personalized medicine.

Indexed as

Biological Specimen BanksComputational BiologyDatabases, GeneticGenetics, MedicalGenotypeHumansPrecision Medicinebiobankingbiobanksbiorepositorypersonalized medicine

Identifiers

PMID24588254
PMCPMC4898781

What OpenQuestion holds

Textmetadata
LicenceTDM
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.