Evidence map›Paper›PMID 31489595›Full record

ArticlePharmacoEconomics2020

Demand for Precision Medicine: A Discrete-Choice Experiment and External Validation Study.

Dean A Regier, David L Veenstra, Anirban Basu, Josh J Carlson

Abstract read
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In one paragraph

Article in PharmacoEconomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 5 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

22 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Article
  7. Article
  8. Review
  9. How is Value Defined in Molecular Testing in Cancer? A Scoping Review.Applied health economics and health policy · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Economics and Precision Medicine.Handbook of experimental pharmacology · 2023
    Article
  14. Article
  15. Article
  16. Article
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  18. Article
  19. Article
  20. 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 · 2021
    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

4 authors.

Dean A RegierCancer Control Research - Canadian Centre for Applied Research in Cancer Control (ARCC), BC Cancer, 675 West 10th Avenue, Vancouver, British Columbia, V5Z 1L3, Canada. dregier@bccrc.ca.ORCID 0000-0001-8876-0511
David L VeenstraThe Comparative Health Outcomes, Policy and Economics (CHOICE) Institute, Department of Pharmacy, University of Washington, Seattle, Washington, USA.
Anirban BasuThe Comparative Health Outcomes, Policy and Economics (CHOICE) Institute, Department of Pharmacy, University of Washington, Seattle, Washington, USA.
Josh J CarlsonThe Comparative Health Outcomes, Policy and Economics (CHOICE) Institute, Department of Pharmacy, University of Washington, Seattle, Washington, USA.

Funding

NIH HHS 1U01AG047109
6 · The paper itself

Abstract

backgroundA limited evidence base and lack of clear clinical guidelines challenge healthcare systems' adoption of precision medicine. The effect of these conditions on demand is not understood.

objectiveThis research estimated the public's preferences and demand for precision medicine outcomes.

methodsA discrete-choice experiment survey was conducted with an online sample of the US public who had recent healthcare experience. Statistical analysis was undertaken using an error components mixed logit model. The responsiveness of demand in the context of a changing evidence base was estimated through the price elasticity of demand. External validation was examined using real-world demand for the 21-gene recurrence score assay for breast cancer.

resultsIn total, 1124 (of 1849) individuals completed the web-based survey. The most important outcomes were survival gains with statistical uncertainty, cost of testing, and medical expert agreement on changing care based on test results. The value ($US, year 2017 values) for a test where most (vs. few) experts agreed to changing treatment based on test results was $US1100 (95% confidence interval [CI] 916-1286). Respondents were willing to pay $US265 (95% CI 46-486) for a test that could result in greater certainty around life-expectancy gains. The predicted demand of the assay was 9% in 2005 and 66% in 2014, compared with real-world uptake of 7% and 71% (root-mean-square prediction error 0.11). Demand was sensitive to price (1% increase in price resulted in > 1% change in demand) when first introduced and insensitive to price (1% increase in price resulted in < 0.1% change in demand) as the evidence base became established.

conclusionsEvidence of external validity was found. Demand was weak and responsive to price in the near term because of uncertainty and an immature evidence base. Clear communication of precision medicine outcomes and uncertainty is crucial in allowing healthcare to align with individual preferences.

Indexed as

Choice BehaviorModels, TheoreticalUncertaintyAdolescentAdultFemaleHumansMaleMiddle AgedPatient PreferencePharmacogenomic TestingPrecision MedicineSurveys and QuestionnairesUnited StatesYoung Adult

Identifiers

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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.