Evidence map›Paper›PMID 28270221›Full record

ArticleTrials2017

Marketing trials, marketing tricks - how to spot them and how to stop them.

Alastair Matheson

Abstract readLetterComment
In one paragraph

Article in Trials, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Alastair Matheson, Toronto, Canada. amatheson@outlook.com.ORCID 0000-0003-0462-2379

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLast this year in this journal, Barbour and colleagues reported a study of "marketing trials" in leading medical journals (Trials 2016;17:31). In this commentary I discuss their research, describe new analyses of the study cohort and consider measures to address marketing within academic medical literature. DISCUSSION: Barbour et al. sought to identify a subgroup of "marketing trials" within leading medical journals, but in reality, nearly all industry-financed trials serve marketing functions, and many exhibit marketing-related features, including biases, in their framing, methodology or reporting. I conducted new analyses of the cohort of Barbour et al., showing that most trials funded exclusively by drug manufacturers had direct involvement of the manufacturer in design, analysis and reporting, and features supportive of product seeding. However, these commercial enterprises were without exception presented to journal readers as academic-led projects, using attributional spin, which should itself be considered an important form of marketing bias. Barbour et al. correctly conclude that commercial bias in industry clinical trials articles often requires expertise to recognize, and in many cases cannot be identified from the published journal report. Several potential remedies are discussed, including independent clinical research, data sharing, improved reporting guidance, improved tools for assessing research quality, reforms to article attribution, submission checklists and new editorial standards.

conclusionMedicine's journals have a responsibility to uphold rigorous scientific and reporting standards, require ready trials data access and ensure the commercial dimensions of research are brought prominently to their readers' attention. Failure to meet these responsibilities constitutes an enduring threat to the integrity of biomedical literature.

Indexed as

Information DisseminationMarketingBiasResearch DesignResearch ReportAuthorshipBiasChecklistDisclosureGuidelinesMarketingMarketing trialPharmaceutical industryResearch integritySeeding trialTransparency

Identifiers

PMID28270221
PMCPMC5341186

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.