Evidence map›Paper›PMID 32005225›Full record

ArticleBMC medical ethics2020

Why genomics researchers are sometimes morally required to hunt for secondary findings.

Julian J Koplin, Julian Savulescu, Danya F Vears

Abstract read
In one paragraph

Article in BMC medical ethics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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.

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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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

3 authors.

Julian J KoplinBiomedical Ethics Research Group, Murdoch Children's Research Institute, Melbourne, Australia. koplinj@unimelb.edu.au.ORCID 0000-0002-2752-7334
Julian SavulescuBiomedical Ethics Research Group, Murdoch Children's Research Institute, Melbourne, Australia.
Danya F VearsBiomedical Ethics Research Group, Murdoch Children's Research Institute, Melbourne, Australia.

Funding

Wellcome Trust 104848Wellcome Trust 104848/Z/14/ZWellcome Trust 203132/Z/16/Z
6 · The paper itself

Abstract

backgroundGenomic research can reveal 'unsolicited' or 'incidental' findings that are of potential health or reproductive significance to participants. It is widely thought that researchers have a moral obligation, grounded in the duty of easy rescue, to return certain kinds of unsolicited findings to research participants. It is less widely thought that researchers have a moral obligation to actively look for health-related findings (for example, by conducting additional analyses to search for findings outside the scope of the research question). MAIN TEXT: This paper examines whether there is a moral obligation, grounded in the duty of easy rescue, to actively hunt for genomic secondary findings. We begin by showing how the duty to disclose individual research findings can be grounded in the duty of easy rescue. Next, we describe a parallel moral duty, also grounded in the duty of easy rescue, to actively hunt for such information. We then consider six possible objections to our argument, each of which we find unsuccessful. Some of these objections provide reason to limit the scope of the duty to look for secondary findings, but none provide reason to reject this duty outright.

conclusionsWe argue that under a certain range of circumstances, researchers are morally required to hunt for these kinds of secondary findings. Although these circumstances may not currently obtain, genomic researchers will likely acquire an obligation to hunt for secondary findings as the field of genomics continues to evolve.

Indexed as

Moral ObligationsConflict, PsychologicalDisclosureEthics, ResearchGenetic ResearchGenome, HumanHumansIncidental FindingsResearcher-Subject RelationsResearch PersonnelSocial ResponsibilityDuty to rescueGenomicsIncidental findingsResearch ethicsSecondary findings

Identifiers

PMID32005225
PMCPMC6995186

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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.