Evidence map›Paper›PMID 28166795›Full record

ArticleBMC medical ethics2017

Ethical framework for the detection, management and communication of incidental findings in imaging studies, building on an interview study of researchers' practices and perspectives.

Eline M Bunnik, Lisa van Bodegom, Wim Pinxten, Inez D de Beaufort, Meike W Vernooij

Abstract read
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Article in BMC medical ethics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Returning Incidental Research Findings FromArthritis care & research · 2024
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. The Impact of Incidental Findings Detected During Brain Imaging on Research Participants of the Rotterdam Study: An Interview Study.Cambridge quarterly of healthcare ethics : CQ : the international journal of healthcare ethics committees · 2020
    Article
  12. Predictive Analytics and the Return of "Research" Information to Participants.Applied Human Factors and Ergonomics Conference · 2020
    Article
  13. Article
  14. 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

5 authors.

Eline M BunnikDepartment of Medical Ethics and Philosophy of Medicine, Erasmus MC, University Medical Centre Rotterdam, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands. e.bunnik@erasmusmc.nl.
Lisa van BodegomDepartment of Medical Ethics and Philosophy of Medicine, Erasmus MC, University Medical Centre Rotterdam, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands.
Wim PinxtenDepartment of Morphology, Hasselt University, Agoralaan Gebouw D, BE 3590, Diepenbeek, Belgium.
Inez D de BeaufortDepartment of Medical Ethics and Philosophy of Medicine, Erasmus MC, University Medical Centre Rotterdam, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands.
Meike W VernooijDepartment of Epidemiology, Erasmus MC, University Medical Centre Rotterdam, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs thousands of healthy research participants are being included in small and large imaging studies, it is essential that dilemmas raised by the detection of incidental findings are adequately handled. Current ethical guidance indicates that pathways for dealing with incidental findings should be in place, but does not specify what such pathways should look like. Building on an interview study of researchers' practices and perspectives, we identified key considerations for the set-up of pathways for the detection, management and communication of incidental findings in imaging research.

methodsWe conducted an interview study with a purposive sample of researchers (n = 20) at research facilities across the Netherlands. Based on a qualitative analysis of these interviews and on existing guidelines found in the literature, we developed a prototype ethical framework, which was critically assessed and fine-tuned during a two-day international expert meeting with bioethicists and representatives from large population-based imaging studies from the United Kingdom, Germany, Sweden and Belgium (n = 14).

resultsPractices and policies for the handling of incidental findings vary strongly across the Netherlands, ranging from no review of research scans and limited feedback to research participants, to routine review of scans and the arrangement of clinical follow-up. Respondents felt that researchers do not have a duty to actively look for incidental findings, but they do have a duty to act on findings, when detected. The principle of reciprocity featured prominently in our interviews and expert meeting.

conclusionWe present an ethical framework that may guide researchers and research ethics committees in the design and/or evaluation of appropriate pathways for the handling of incidental findings in imaging studies. The framework consists of seven steps: anticipation of findings, information provision and informed consent, scan acquisition, review of scans, consultation on detected abnormalities, communication of the finding, and further clinical management and follow-up of the research participant. Each of these steps represents a key decision to be made by researchers, which should be justified not only with reference to costs and/or logistical considerations, but also with reference to researchers' moral obligations and the principle of reciprocity.

Indexed as

Diagnostic ImagingIncidental FindingsMoral ObligationsBiomedical ResearchDisclosureEthics, ResearchEuropeHumansResearch PersonnelEthical frameworkImaging studiesIncidental findingsInterview studyPopulation imagingPrinciple of reciprocityResearch ethics

Identifiers

PMID28166795
PMCPMC5294804

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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.