Evidence map›Paper›PMID 25126223›Full record

ArticleAmerican health & drug benefits2008

Meta-analysis 101: what you want to know in the era of comparative effectiveness.

J B Jones, Saul Blecker, Nirav R Shah

Abstract read
In one paragraph

Article in American health & drug benefits, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 3 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, 3 syntheses or guidelines pooled it.

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

3 authors.

J B JonesThe Center for Health Research, Geisinger Health System, Danville, PA.
Saul BleckerThe Division of General Internal Medicine, NYU School of Medicine, New York, NY.
Nirav R ShahAssistant Professor of Medicine, NYU School of Medicine, Associate Investigator at the Geisinger Center for Health Research, and Principal of MetaResearch, LLC.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of "comparative effectiveness" research, each of the major stakeholders in healthcare-payors, patients, providers, and government-face a similar challenge. When making a decision about whether a new device, drug, or a diagnostic modality should be considered for use or coverage, what choices are best supported by the evidence? Medical evidence is defined by randomized controlled trials and by observational studies that vary greatly in their design, the accuracy of their analyses, and the relevance of their conclusions and recommendations. Hence, key decision makers increasingly rely on systematic reviews and meta-analyses to facilitate the interpretation and application of research evidence. Knowing how to evaluate meta-analyses and understanding the potential pitfalls of the method are crucial for those involved in designing drug benefits. The authors highlight the process, strengths, and weaknesses of meta-analysis and explain how to judge the value of the results.

Identifiers

PMID25126223
PMCPMC4115319

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.