Trial reportEuropean journal of human genetics : EJHG2018
Patient preferences for massively parallel sequencing genetic testing of colorectal cancer risk: a discrete choice experiment.
Trial report in European journal of human genetics : EJHG, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 8 of them syntheses that pooled 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.
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.
Who cites it
20 citing papers in PubMed, 8 syntheses or guidelines pooled it.
- Public Preferences for Emerging Cancer Screening Modalities: A Systematic Review of Discrete Choice Experiments.The patient · 2026Pooled it
- The Evolving Landscape of Discrete Choice Experiments in Health Economics: A Systematic Review.PharmacoEconomics · 2025Pooled it
- The Cost Effectiveness of Genomic Medicine in Cancer Control: A Systematic Literature Review.Applied health economics and health policy · 2025Pooled it
- Public Preferences for Genetic and Genomic Risk-Informed Chronic Disease Screening and Early Detection: A Systematic Review of Discrete Choice Experiments.Applied health economics and health policy · 2025Pooled it
- Approaches to Incorporation of Preferences into Health Economic Models of Genomic Medicine: A Critical Interpretive Synthesis and Conceptual Framework.Applied health economics and health policy · 2025Pooled it
- Preferences for Genetic Testing to Predict the Risk of Developing Hereditary Cancer: A Systematic Review of Discrete Choice Experiments.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Pooled it
- Demographic Characteristics Associated With Perceptions of Personal Utility in Genetic and Genomic Testing: A Systematic Review.JAMA network open · 2023Pooled it
- A Systematic Review of Discrete Choice Experiments and Conjoint Analysis on Genetic Testing.The patient · 2022Pooled it
- A WeChat-Based Decision Aid Intervention to Promote Informed Decision-Making for Family Members Regarding the Genetic Testing of Patients With Colorectal Cancer: Randomized Controlled Trial.Journal of medical Internet research · 2025Trial
- Societal Preferences, Values and Priorities for Genomic Testing for Atrial Fibrillation: Evidence from Two Discrete Choice Experiments.The patient · 2026Article
- Public perceptions of genetic sequencing in China: barriers and drivers of adoption.European journal of human genetics : EJHG · 2026Article
- Advancing the science of qualitative patient preference assessment using large language models.PLOS digital health · 2026Article
- How is Value Defined in Molecular Testing in Cancer? A Scoping Review.Applied health economics and health policy · 2025Article
- Article
- Implementing Screening, Brief Intervention and Referral Intervention for Health Promotion and Disease Prevention in Hospital Settings in Alberta: A Pilot Study.International journal of public health · 2023Article
- Continuing the sequence? Towards an economic evaluation of whole genome sequencing for the diagnosis of rare diseases in Scotland.Journal of community genetics · 2022Article
- Genomic Testing for Relapsed and Refractory Lymphoid Cancers: Understanding Patient Values.The patient · 2021Article
- The value of genomic sequencing in complex pediatric neurological disorders: a discrete choice experiment.Genetics in medicine : official journal of the American College of Medical Genetics · 2021Article
- Payer Preferences and Willingness to Pay for Genomic Precision Medicine: A Discrete Choice Experiment.Journal of managed care & specialty pharmacy · 2020Article
- Preferences for Sun Protection With a Self-Monitoring App: Protocol of a Discrete Choice Experiment Study.JMIR research protocols · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
This study enumerated patients' preference-based personal utility and willingness-to-pay for massively parallel sequencing (MPS) genetic testing of colorectal cancer (CRC) risk. Our setting was the New Exome Technology in (NEXT) Medicine Study, a randomized control trial of usual care genetic testing vs. exome sequencing. Using a discrete choice experiment (DCE), we elicited patient preferences for information on genetic causes of CRC. We estimated personal utility for the following four attributes: proportion of individuals with a genetic cause of CRC who receive a diagnosis, number of tests used, wait time for results, and cost. A total of 122 patients completed our DCE (66% response rate). On average, patients preferred genetic tests identifying more individuals with a diagnosis and involving a shorter wait time. Assuming MPS identifies more individuals with a Mendelian form of CRC risk, involves fewer tests, and results in a shorter wait than traditional diagnostic testing, average willingness-to-pay (WTP) for MPS ranged from US$400 (95% CI: $300, $500) to US$1541 (95% CI: $1224, $1859). These results indicate that patients value information on genetic causes of CRC and replacing traditional diagnostic testing with MPS testing will increase patients' utility. Future research exploring the costs and benefits of MPS for CRC risk is warranted.
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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.