Evidence map›Paper›PMID 42702697›Full record

ArticlePharmacoEconomics2026

Value of Knowing the Risk of Developing a Neurodegenerative Disease: A Discrete Choice Experiment.

Patricia G Synnott, Daniel A Ollendorf, Steven M Kymes, Donna L Bernstein, Montserrat Vera-Llonch

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Article in PharmacoEconomics, 2026. 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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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Patricia G SynnottCenter for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts University Medical Center, Boston, MA, USA.
Daniel A OllendorfCenter for the Evaluation of Value and Risk in Health, Institute for Clinical Research and Health Policy Studies, Tufts University Medical Center, Boston, MA, USA.
Steven M KymesIonis Pharmaceuticals, Carlsbad, CA, USA. skymes@ionis.com.
Donna L BernsteinIonis Pharmaceuticals, Carlsbad, CA, USA.
Montserrat Vera-LlonchIonis Pharmaceuticals, Carlsbad, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenetic tests predict an individual's risk of developing neurodegenerative diseases. A portion of the value provided by genetic tests can be attributed to the individual's value of early knowledge of their risk, or the "value of knowing."

methodsWe developed a discrete choice experiment survey and administered it to a nationally representative sample of US adults. Respondents were presented with 8 choice tasks, each with two hypothetical tests and an opt-out option, where tests varied in cost, type, and accuracy. Respondents were randomly assigned to scenarios with varied disease severity, perceived risk, treatment availability, and whom the test was for. We used a generalized multinomial logit model to estimate preferences and willingness to pay (WTP).

resultsThe final sample included 1,034 respondents. The alternative-specific constant implied a baseline model-derived WTP of $2,954 (95% CI: $$2,559, $3,348) for undergoing genetic testing. Estimates were higher when the disease being tested for was fatal, when perceived disease risk was high, and when considering testing for a child. Conversely, preferences were lower for low-severity diseases and when considering testing for oneself. In exploratory subgroup analyses, respondents with genetic testing experience, those who had children, and those who had cared for someone with a neurodegenerative disease reported a higher marginal WTP. DISCUSSION: Our study suggests that individuals place a premium on knowing their risk of developing a neurodegenerative disease. These findings provide preference evidence that may inform coverage deliberations for genetic tests for neurodegenerative disease when considered alongside other decision criteria.

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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.