Trial reportBMC medical research methodology2019
Using joint models to disentangle intervention effect types and baseline confounding: an application within an intervention study in prodromal Alzheimer's disease with Fortasyn Connect.
Trial report in BMC medical research methodology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- 36-month LipiDiDiet multinutrient clinical trial in prodromal Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2021Trial
- Impact of ventilatory and laboratory parameter trajectories on short-term survival in acute respiratory distress syndrome patients: a retrospective study using joint models.European journal of medical research · 2025Article
- Budget impact analysis of the use of Souvenaid in patients with prodromal Alzheimer's Disease in Spain.Alzheimer's research & therapy · 2022Article
- Joint modeling of endpoints can be used to answer various research questions in randomized clinical trials.Journal of clinical epidemiology · 2022Article
- A competing risk joint model for dealing with different types of missing data in an intervention trial in prodromal Alzheimer's disease.Alzheimer's research & therapy · 2021Article
- Economic evaluation of supplementing the diet with Souvenaid in patients with prodromal Alzheimer's disease.Alzheimer's research & therapy · 2020Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany prodromal Alzheimer's disease trials collect two types of data: the time until clinical diagnosis of dementia and longitudinal patient information. These data are often analysed separately, although they are strongly associated. By combining the longitudinal and survival data into a single statistical model, joint models can account for the dependencies between the two types of data.
methodsWe illustrate the major steps in a joint modelling approach, motivated by data from a prodromal Alzheimer's disease study: the LipiDiDiet trial.
resultsBy using joint models we are able to disentangle baseline confounding from the intervention effect and moreover, to investigate the association between longitudinal patient information and the time until clinical dementia diagnosis.
conclusionsJoint models provide a valuable tool in the statistical analysis of clinical studies with longitudinal and survival data, such as in prodromal Alzheimer's disease trials, and have several added values compared to separate analyses.
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