Evidence map›Paper›PMID 23199118›Full record

ArticleThe EPMA journal2010

Personalized medicine and comparative effectiveness research in an era of fixed budgets.

Paul M Brown

Abstract read
In one paragraph

Article in The EPMA journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. 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.

Paul M BrownLineberger Comprehensive Cancer Center & Institute of Pharmacogenomics and Individualized Therapies, University of North Carolina, Chapel Hill, Chapel Hill, NC USA ; Department of Health Policy & Management, University of North Carolina, 1101e McGavran Greenberg, Chapel Hill, NC 27599 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For personalized medicine to be widely adopted in clinical practice, stakeholders need evidence of effectiveness, cost effectiveness and financial viability. Comparative effectiveness research (CER) using population based, retrospective data can inform assessments of personalized medicine. The purpose of this paper is to explore the potential and the limitations of CER. While the analytic methods and data used for CER overcome many of the disadvantages of randomized controlled trials, there are significant barriers, including lack of routinely collected genetic information, patient-reported outcomes and information on new and emerging technologies. Recommendations for using CER include augmenting current data with genetic information, promoting the collection of uniform health outcomes, using value of information analysis to guide development of new technologies, and greater use of decision analysis. Finally, in order to address stakeholder concerns regarding short term financial viability, additional emphasis should be devoted to cost analysis of implementation costs and overall financial impact.

Identifiers

PMID23199118
PMCPMC3405343

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.