Evidence map›Paper›PMID 26374681›Full record

ArticleClinical trials (London, England)2015

The ethics and regulatory landscape of including vulnerable populations in pragmatic clinical trials.

Mary Jane Welch, Rachel Lally, Jennifer E Miller, Stephanie Pittman, Lynda Brodsky, Arthur L Caplan, Gina Uhlenbrauck, Darcy M Louzao, James H Fischer, Benjamin Wilfond

Abstract read
In one paragraph

Article in Clinical trials (London, England), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 4 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

41 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Applications of Blockchain in the Medical Field: Narrative Review.Journal of medical Internet research · 2021
    Pooled it
  5. Trial
  6. Article
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  12. Review
  13. Article
  14. Article
  15. Establishing a Pregnancy Lyme Disease Biobank.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  16. IRBs and the Protection-Inclusion Dilemma: Finding a Balance.The American journal of bioethics : AJOB · 2023
    Article
  17. Article
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  19. Article
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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

10 authors.

Mary Jane WelchHuman Subjects' Protection, College of Nursing, Rush University Medical Center, Chicago, IL, USA Mary_Jane_Welch@rush.edu.
Rachel LallyColumbia University Medical Center, New York, NY, USA.
Jennifer E MillerKenan Institute for Ethics, Duke University, Durham, NC, USA Edmond J. Safra Center for Ethics, Harvard University, Cambridge, MA, USA Division of Medical Ethics, NYU Langone Medical Center, New York, NY, USA.
Stephanie PittmanHuman Subjects' Protection, Rush University Medical Center, Chicago, IL, USA.
Lynda BrodskyCook County Health & Hospitals System, Chicago, IL, USA.
Arthur L CaplanDivision of Medical Ethics, NYU Langone Medical Center, New York, NY, USA.
Gina UhlenbrauckDuke Clinical Research Institute, Duke University, Durham, NC, USA.
Darcy M LouzaoDuke Clinical Research Institute, Duke University, Durham, NC, USA.
James H FischerUniversity of Illinois at Chicago, Chicago, IL, USA.
Benjamin WilfondTreuman Katz Center for Pediatric Bioethics, Seattle Children's Hospital, Seattle, WA, USA Division of Bioethics, Department of Pediatrics, University of Washington School of Medicine, Seattle, WA, USA.

Funding

Health Care Systems Research Collaboratory SupplementU54AT007748 · NCCIH · DUKE UNIVERSITY · PI CURTIS, LESLEY H, HERNANDEZ, ADRIAN · 2012 to 2017
$15.1M
NCCIH NIH HHS U54 AT007748
6 · The paper itself

Abstract

Policies have been developed to protect vulnerable populations in clinical research, including the US federal research regulations (45 Code of Federal Regulations 46 Subparts B, C, and D). These policies generally recognize vulnerable populations to include pregnant women, fetuses, neonates, children, prisoners, persons with physical handicaps or mental disabilities, and disadvantaged persons. The aim has been to protect these populations from harm, often by creating regulatory and ethical checks that may limit their participation in many clinical trials. The recent increase in pragmatic clinical trials raises at least two questions about this approach. First, is exclusion itself a harm to vulnerable populations, as these groups may be denied access to understanding how health interventions work for them in clinical settings? Second, are groups considered vulnerable in traditional clinical trials also vulnerable in pragmatic clinical trials? We argue first that excluding vulnerable subjects from participation in pragmatic clinical trials can be harmful by preventing acquisition of data to meaningfully inform clinical decision-making in the future. Second, we argue that protections for vulnerable subjects in traditional clinical trial settings may not be translatable, feasible, or even ethical to apply in pragmatic clinical trials. We conclude by offering specific recommendations for appropriately protecting vulnerable research subjects in pragmatic clinical trials, focusing on pregnant women, fetuses, neonates, children, prisoners, persons with physical handicaps or mental disabilities, and disadvantaged persons.

Indexed as

Biomedical ResearchChildChild, PreschoolClinical Trials as TopicFemaleFetusHumansInfantInfant, NewbornInformed ConsentMalePersons with DisabilitiesPregnancyPrisonersResearch SubjectsVulnerable Populationscluster randomized trialspragmatic clinical trialsregulationresearch ethicsresearch with childrenresearch with disadvantaged populationsresearch with persons with diminished capacityresearch with pregnant womenresearch with prisonersVulnerable subjects

Identifiers

PMID26374681
PMCPMC4662375

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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.