Evidence map›Paper›PMID 18535933›Full record

ReviewCurrent opinion in molecular therapeutics2008

Challenges to the translation of genomic information into clinical practice and health policy: Utilization, preferences and economic value.

Kathryn A Phillips, Su-Ying Liang, Stephanie Van Bebber, Canpers Research Group

Abstract readReview
In one paragraph

Review in Current opinion in molecular therapeutics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. The economic value of personalized medicine tests: what we know and what we need to know.Genetics in medicine : official journal of the American College of Medical Genetics · 2014
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Paving the Way to Personalized Genomic Medicine: Steps to Successful Implementation.Current pharmacogenomics and personalized medicine · 2009
    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

4 authors.

Kathryn A PhillipsUniversity of California at San Francisco, Department of Clinical Pharmacy, School of Pharmacy, Institute for Health Policy Studies, and UCSF Comprehensive Cancer Center, San Francisco, CA 94143 USA. phillipsk@pharmacy.ucsf.edu
Su-Ying Liang
Stephanie Van Bebber
Canpers Research Group

Funding

Screening for Colorectal Cancer: An Integrated ApproachR01CA101849 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI PHILLIPS, KATHRYN A · 2004 to 2007
$2.4M
NCI NIH HHS R01 CA101849
6 · The paper itself

Abstract

It is important to understand how knowledge of genomics can be translated from research into clinical practice and health policies. This review examines existing evidence on three key factors in the adoption of personalized medicine: utilization, preferences, and economic value, using two cancer examples: HER2/neu antigen testing and trastuzumab (Herceptin) treatment and genetic testing for Lynch syndrome. Our findings highlight areas in which additional research is required to build an evidence base addressing utilization of, preferences for, and the potential costs and benefits of personalized medicine. Major challenges include a lack of linked data, the need for relevant research frameworks and methodologies, and the clinical complexities of genomic-based diagnostics and treatment.

Indexed as

Health PolicyEconomics, MedicalGenomicsHumansMedicineNeoplasms

Identifiers

PMID18535933
PMCPMC2910510

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.