ArticleJournal of pharmacokinetics and pharmacodynamics2014
Continuous-time Markov modelling of flexible-dose depression trials.
Article in Journal of pharmacokinetics and pharmacodynamics, 2014. 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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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.
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5 authors.
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Abstract
The aim of this paper is to provide a systematic methodology for modelling longitudinal data to be used in contexts of limited or even absent knowledge of the physiological mechanism underlying the disease time course. Adopting a system-theoretic paradigm, a population response model is developed where the clinical endpoint is described as a function of the patient's health state. In particular, a continuous-time stochastic approach is proposed where the clinical score and its time-derivative summarize the patient's health state affected by a random term accounting for exogenous unpredictable factors. The proposed approach is validated on experimental data from the placebo and drug arms of a Phase II depression trial. Since some subjects in the trial may undergo changes in their treatment dose due to the flexible dosing scheme, dose escalations are modelled as instantaneous perturbations on the state. In its simplest form--an integrated Wiener process--was able to correctly capture the individual responses in both treatment arms. However, a better description of inter-individual variability was obtained by means of a stable Markovian model. Parameter estimation has been carried out according to the empirical Bayes method.
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