Evidence map›Paper›PMID 41210372›Full record

ArticleGenetics in medicine open2025

Evaluation of DNA-poli: Study protocol of a randomized controlled trial to assess a digital platform for family cascade genetic testing and predictive genetic counseling.

Marlies N van Lingen, Janine V Meulenkamp, Marten A Siemelink, Tessa C Beinema, Randy Klaassen, Dirk K J Heylen, J Peter van Tintelen, Lieke M van den Heuvel

Abstract read
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Article in Genetics in medicine open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Marlies N van LingenUniversity Medical Centre Utrecht, Department of Genetics, Utrecht, The Netherlands.
Janine V MeulenkampUniversity Medical Centre Utrecht, Department of Genetics, Utrecht, The Netherlands.
Marten A SiemelinkUniversity Medical Centre Utrecht, Department of Genetics, Utrecht, The Netherlands.
Tessa C BeinemaUniversity of Twente, Department of Human Media Interaction, Enschede, The Netherlands.
Randy KlaassenUniversity of Twente, Department of Human Media Interaction, Enschede, The Netherlands.
Dirk K J HeylenUniversity of Twente, Department of Human Media Interaction, Enschede, The Netherlands.
J Peter van TintelenUniversity Medical Centre Utrecht, Department of Genetics, Utrecht, The Netherlands.
Lieke M van den HeuvelUniversity Medical Centre Utrecht, Department of Genetics, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The current uptake of predictive genetic counseling among at-risk relatives (ARRs) for cardiogenetic diseases is suboptimal, with 40% to 50% of ARRs undergoing testing within 1 to 3 years after disclosure. Digital technologies are increasingly proposed to improve accessibility, efficiency, and uptake of predictive genetic counseling and, if desired, predictive genetic testing. Therefore, DNA-poli was developed: a digital platform providing family communication support and pre- and posttest genetic counseling for ARRs. Here, we describe the study protocol for a randomized controlled trial evaluating DNA-poli in clinical practice. Methods: A noninferiority multicenter randomized controlled trial with parallel group design will be conducted. The intervention group using the DNA-poli platform will be compared with a control group receiving regular counseling. Probands with genetic hypertrophic or dilated cardiomyopathy will be included along with their ARRs and physicians. The primary outcome is the uptake of cardiogenetic counseling 6- and 12-months after result disclosure and stakeholders' experiences. Secondary outcomes are informed decision making in ARRs, empowerment, and satisfaction in all stakeholder groups. In addition, the efficiency of consultations and the genetic care process will be analyzed. Descriptive and inferential statistics will be performed to analyze data. Discussion: This study aims to provide insight into the potential of digitalizing the cascade genetic testing process in cardiogenetics. Demonstrating noninferiority of the DNA-poli pathway compared with standard care could have major implications, suggesting that counseling supported by digital tools is at least equally effective. This may enhance the cascade genetic testing process, uptake, and efficiency while maintaining high quality standards.

Indexed as

CardiomyopathiesDigital counselingDigital healthGenetic carrier screeningGenetic counseling

Identifiers

PMID41210372
PMCPMC12593443

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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.