ArticleTrials2017
Marketing trials, marketing tricks - how to spot them and how to stop them.
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.
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.
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.
Who cites it
5 citing papers in PubMed.
- Article
- Are Corporations Re-Defining Illness and Health? The Diabetes Epidemic, Goal Numbers, and Blockbuster Drugs.Journal of bioethical inquiry · 2021Review
- Do we really know how many clinical trials are conducted ethically? Why research ethics committee review practices need to be strengthened and initial steps we could take to strengthen them.Journal of medical ethics · 2021Review
- Rescuing Informed Consent: How the new "Key Information" and "Reasonable Person" Provisions in the Revised U.S. Common Rule open the door to long Overdue Informed Consent Disclosure Improvements and why we need to walk Through that door.Science and engineering ethics · 2020Article
- Relationships among commercial practices and author conflicts of interest in biomedical publishing.PloS one · 2020Article
Corrections and comments
- Comment on
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
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
Identifiers
What OpenQuestion holds
Registered trials
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.