Evidence map›Paper›PMID 20831293›Full record

ArticlePharmacoEconomics2010

Regulatory benefit-risk assessment and comparative effectiveness research: strangers, bedfellows or strange bedfellows?

Louis P Garrison

Abstract read
PubMed Publisher
In one paragraph

Article in PharmacoEconomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Should benefit-risk assessment have its own drug "label"?Drug, healthcare and patient safety · 2011
    Article
  6. 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.

Louis P GarrisonPharmaceutical Outcomes Research & Policy Program, Department of Pharmacy, University of Washington, Seattle, WA 98195-7630, USA. lgarrisn@u.washington.edu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past 5 years, we have witnessed growing interest in both comparative effectiveness research (CER) and regulatory benefit-risk assessment (BRA). Both deal with benefits and harms, although at different stages of the product lifecycle. There are growing pressures for a more systematic and quantitative approach to regulatory BRA. However, there is also a need for CER - beyond the evidence that can reasonably be generated during pre-launch product development. Important regulatory and policy questions include the following: What would be a level playing field across disease areas and companies? Who should bear the costs of these studies? What role can benefit-risk modelling play? What is the value of research and how is it related to the prevalence of disease? What is the relationship between uncertainty and the value of evidence? We need to recognize the lifecycle nature of evidence generation, moving from the regulatory setting to the real world and affecting potentially hundreds of thousands, or even millions, of patients worldwide. We need to emphasize not only the public goods nature of information embedded in innovations, but also that it is global. Finally, we need to more systematically explore the benefits and costs of gathering further information - the value of research - recognizing that doing this requires a model or methodology, which we have, for systematically appraising our current state of knowledge and what could be gained from further research. All said, it would seem that BRA and CER should be neither strangers nor strange bedfellows, but may need to be coaxed into being bedfellows.

Indexed as

Comparative Effectiveness ResearchCost-Benefit AnalysisEvidence-Based MedicineHumansPolicyRisk Assessment

Identifiers

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.