Trial reportPharmaceutical research2011
Modeling sleep data for a new drug in development using markov mixed-effects models.
Trial report in Pharmaceutical research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 16 citations in OpenAlex.
- Multinomial logistic estimation of Markov-chain models for modeling sleep architecture in primary insomnia patients.Journal of pharmacokinetics and pharmacodynamics · 2010Trial
- Mathematical modeling of sleep state dynamics in a rodent model of shift work.Neurobiology of sleep and circadian rhythms · 2018Article
- Quantifying sleep architecture dynamics and individual differences using big data and Bayesian networks.PloS one · 2018Article
- Optimal clinical trial design based on a dichotomous Markov-chain mixed-effect sleep model.Journal of pharmacokinetics and pharmacodynamics · 2014Article
- Semi-mechanistic modelling of the analgesic effect of gabapentin in the formalin-induced rat model of experimental pain.Pharmaceutical research · 2014Article
- Pharmacodynamic models for discrete data.Clinical pharmacokinetics · 2012Review
- A hidden Markov model to assess drug-induced sleep fragmentation in the telemetered rat.Journal of pharmacokinetics and pharmacodynamics · 2011Article
- Multinomial logistic functions in markov chain models of sleep architecture: internal and external validation and covariate analysis.The AAPS journal · 2011Article
- The impact of misspecification of residual error or correlation structure on the type I error rate for covariate inclusion.Journal of pharmacokinetics and pharmacodynamics · 2009Article
- Relationship between zolpidem concentrations and sleep parameters in pediatric burn patients.Journal of burn care & research : official publication of the American Burn AssociationArticle
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 at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeTo characterize the time-course of sleep in insomnia patients as well as placebo and concentration-effect relationships of two hypnotic compounds, PD 0200390 and zolpidem, using an accelerated model-building strategy based on mixed-effects Markov models.
methodsData were obtained in a phase II study with the drugs. Sleep stages were recorded during eight hours of sleep for two nights per treatment for the five treatments. First-order Markov models were developed for one transition at a time in a sequential manner; first a baseline model, followed by placebo and lastly the drug models. To accelerate the process, predefined models were selected based on a priori knowledge of sleep, including inter-subject and inter-occasion variability.
resultsBaseline sleep was described using piece-wise linear models, depending on time of night and duration of sleep stage. Placebo affected light sleep stages; drugs also affected slow-wave sleep. Administering PD 0200390 30 min earlier than standard dosing was shown through simulations to reduce latency to persistent sleep by 40%.
conclusionThe proposed accelerated model-building strategy resulted in a model well describing sleep patterns of insomnia patients with and without treatments.
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Registered trials
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.