ArticlePharmacoEconomics2015
Reduce mortality risk above all else: a discrete-choice experiment in acute coronary syndrome patients.
Article in PharmacoEconomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Preferences of People Living with HIV for Long-Acting Antiretroviral Treatment in Germany: Evidence from a Discrete Choice Experiment.The patient · 2023Pooled it
- Discrete Choice Experiments in Health Economics: Past, Present and Future.PharmacoEconomics · 2019Pooled it
- Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments.Health economics · 2019Trial
- Optimizing presentation formats for SF-6Dv2 health status valuation: a qualitative study using cognitive interviews.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025Article
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- Preferences of Patients With Chronic Kidney Disease for Invasive Versus Conservative Treatment of Acute Coronary Syndrome: A Discrete Choice Experiment.Journal of the American Heart Association · 2023Article
- Patient Preferences of Low-Dose Aspirin for Cardiovascular Disease and Colorectal Cancer Prevention in Italy: A Latent Class Analysis.The patient · 2021Article
- Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveCardiovascular disease is the main cause of death in Germany and other industrialized countries. However, until now, little has been known about how people with acute coronary syndrome (ACS) value aspects of their medical treatment. The objective of this study was to evaluate patients' preferences regarding different antiplatelet medication options following an ACS.
methodAfter identification of patient-relevant treatment attributes (a literature review and qualitative interviews), a discrete-choice experiment (DCE) including five patient-relevant attributes was conducted. The DCE used a forced-choice approach in which no "opt out" was present, as no treatment is not an option after ACS. The attribute and level combinations were created using a fractional-factorial NGene design with priors. Data analysis was performed using a random-effects logit model. An additional generalized linear latent and mixed models (GLLAMM) analysis was performed to evaluate subgroup differences.
resultsACS patients (N = 683) participated in computer-assisted personal interviews. Preference analysis showed a clear dominance of the attribute "mortality risk" (coefficient: 0.803). Ranked second was "side effect: dyspnea" (coefficient: 0.550) followed by "risk of a new myocardial infarction" (coefficient: 0.464) and "side effect: bleeding" (coefficient: 0.400). "Frequency of intake" was less important (coefficient: 0.025). Within the 3-class GLLAMM, the variables "marital status" (p = 0.008), "highest level of education" (p = 0.003), and "body-mass index" (according to World Health Organization cluster; p = 0.014) showed a significant impact on the estimated class probabilities.
conclusionOur study found "mortality risk" to be of the highest value for patients. Patient-centered care and decision making requires consideration of patient preferences; moreover, the information on preferences can be used to develop effective therapies after an ACS. The data generated will enable healthcare decision makers and stakeholders to understand patient preferences to promote patients' benefit.
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