Evidence map›Paper›PMID 31896328›Full record

ArticleThe American journal of bioethics : AJOB2020

Misrepresenting "Usual Care" in Research: An Ethical and Scientific Error.

Ruth Macklin, Charles Natanson

Abstract read
In one paragraph

Article in The American journal of bioethics : AJOB, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Modeling current practices in critical care comparative effectiveness research.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2022
    Article
  9. Article
  10. Article
  11. Comparative effectiveness research in critically ill patients: risks associated with mischaracterising usual care.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Ruth MacklinAlbert Einstein College of Medicine.
Charles NatansonNational Institutes of Health.

Funding

Intramural NIH HHS Z99 CL999999
6 · The paper itself

Abstract

Comparative effectiveness studies, referred to here as "usual-care" trials, seek to compare current medical practices for the same medical condition. Such studies are presumed to be safe and involve only minimal risks. However, that presumption may be flawed if the trial design contains "unusual" care, resulting in potential risks to subjects and inaccurately informed consent. Three case studies described here did not rely on clinical evidence to ascertain contemporaneous practice. As a result, the investigators drew inaccurate conclusions, misinformed research participants, and subjects' safety was compromised. Before approving usual-care protocols, IRBs and scientific review committees should evaluate the quality and completeness of information documenting usual-care practices. Guidance from governmental oversight agencies regarding evidence-based documentation of current clinical practice could prevent similar occurrences in future usual-care trials. Accurate information is necessary to ensure that trials comply with government regulations that require minimizing research risks to subjects and accurate informed consent documents.

Indexed as

Clinical Trial Protocols as TopicStandard of CareClinical Trials as TopicEthical ReviewEthics Committees, ResearchHumansInformed ConsentResearch DesignResearch SubjectsScientific Experimental ErrorHuman subjects researchinformed consentIRB (Institutional Review Board)risk/benefit analysis

Identifiers

PMID31896328
PMCPMC10809361

What OpenQuestion holds

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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.