Evidence map›Paper›PMID 38916649›Full record

SynthesisApplied health economics and health policy2025

Public Preferences for Genetic and Genomic Risk-Informed Chronic Disease Screening and Early Detection: A Systematic Review of Discrete Choice Experiments.

Amber Salisbury, Joshua Ciardi, Richard Norman, Amelia K Smit, Anne E Cust, Cynthia Low, Michael Caruana, Louisa Gordon, Karen Canfell, Julia Steinberg and 1 more

Abstract readSystematic Review
In one paragraph

Synthesis in Applied health economics and health policy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

11 authors.

Amber SalisburyThe Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia. amber.salisbury@sydney.edu.au.ORCID 0000-0003-1557-5918
Joshua CiardiSydney School of Public Health, The University of Sydney, Sydney, NSW, Australia.ORCID 0009-0001-6431-6915
Richard NormanCurtin University, Perth, WA, Australia.ORCID 0000-0002-3112-3893
Amelia K SmitThe Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia.ORCID 0000-0001-5712-220X
Anne E CustThe Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia.ORCID 0000-0002-5331-6370
Cynthia LowLived Experience Expert, Adelaide, SA, Australia.ORCID 0000-0003-4297-1967
Michael CaruanaThe Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia.ORCID 0000-0002-5439-6552
Louisa GordonQIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.ORCID 0000-0002-3159-4249
Karen CanfellThe Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia.ORCID 0000-0002-6443-6618
Julia SteinbergThe Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia.ORCID 0000-0002-0585-2312
Alison PearceThe Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia.ORCID 0000-0002-5690-9542

Funding

Medical Research Future Fund 2007708
6 · The paper itself

Abstract

purposeGenetic and genomic testing can provide valuable information on individuals' risk of chronic diseases, presenting an opportunity for risk-tailored disease screening to improve early detection and health outcomes. The acceptability, uptake and effectiveness of such programmes is dependent on public preferences for the programme features. This study aims to conduct a systematic review of discrete choice experiments assessing preferences for genetic/genomic risk-tailored chronic disease screening.

methodsPubMed, Embase, EconLit and Cochrane Library were searched in October 2023 for discrete choice experiment studies assessing preferences for genetic or genomic risk-tailored chronic disease screening. Eligible studies were double screened, extracted and synthesised through descriptive statistics and content analysis of themes. Bias was assessed using an existing quality checklist.

resultsTwelve studies were included. Most studies focused on cancer screening (n = 10) and explored preferences for testing of rare, high-risk variants (n = 10), largely within a targeted population (e.g. subgroups with family history of disease). Two studies explored preferences for the use of polygenic risk scores (PRS) at a population level. Twenty-six programme attributes were identified, with most significantly impacting preferences. Survival, test accuracy and screening impact were most frequently reported as most important. Depending on the clinical context and programme attributes and levels, estimated uptake of hypothetical programmes varied from no participation to almost full participation (97%).

conclusionThe uptake of potential programmes would strongly depend on specific programme features and the disease context. In particular, careful communication of potential survival benefits and likely genetic/genomic test accuracy might encourage uptake of genetic and genomic risk-tailored disease screening programmes. As the majority of the literature focused on high-risk variants and cancer screening, further research is required to understand preferences specific to PRS testing at a population level and targeted genomic testing for different disease contexts.

Indexed as

Choice BehaviorGenetic TestingPublic OpinionChronic DiseaseEarly Detection of CancerEarly DiagnosisGenetic Predisposition to DiseaseGenomicsHumansRisk Assessment

Identifiers

PMID38916649
PMCPMC12053130

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.