Population Disease Progress Models for the Time Course of HAMD Score in Depressed Patients Receiving Placebo in Anti-Depressant Clinical Trials
Nick Holford, Jianguo Li, Lisa Benincosa, Mattias Birath
Division of Pharmacology and Clinical Pharmacology, University of Auckland, New Zealand Pfizer Global Research & Development, Groton CT, USA, University of Uppsala, Sweden
Introduction: The time course of depression in humans is well known to be cyclical with episodes of depression and typically spontaneous remission. Despite the definition of a specific cyclical syndrome, seasonal affective disorder, there is almost no quantitative description of the pattern of depression within an episode and from episode to episode in patients with clinical depression. The largest collections of data in individuals arise in the setting of clinical trials of anti-depressants but these trials are typically short (approx. 6 weeks) and span barely half of a typical episode of depression. We have developed a model to describe multiple episodes of depression and applied it to Hamilton Depression scale (HAMD) observations from placebo treated patients in clinical trials of two different drugs.
Model: An empirical, linked cosine model has been developed to describe multiple episodes of depression. It is capable of describing cyclical depressive episodes with flexibility both within the episode and across episodes within each individual. An episode starts at the least depressed state e.g. lowest HAMD score. The episode is split into 3 sections; onset, depression, and recovery. Each section is characterized by amplitude and length. Variability between episodes is accounted for by a random effects model for the 6 parameters which describe each episode. Variability between subjects is described by additional random effects on these same parameters. An inverse Bateman function was also used to describe short term changes during a clinical trial.
Computation: Model building and parameter estimation was performed using NONMEM Version V release 1.1. Estimation used the first order conditional method with 3 significant figures for convergence. The Compaq Visual Fortran compiler version 6.6 was used to compile NONMEM. NM-TRAN codes were expressed in extended format for use with Wings for NONMEM version 301 (http://wfn.sourceforge.net).
Results: Both inverse Bateman and a limited linked cosine model described the short term HAMD data equally well. The models allowed a description of the rate of recovery and exposed the largely unrecognized onset of the next episode of depression towards the end of the trial observation period. The inverse Bateman model is numerically more stable and may be of more practical use for describing the short term time course of disease progression. Longer observation periods are required to fully characterize the time course of depression over multiple episodes. Both models have the ability to distinguish different drug effects affecting rate and magnitude of treatment response in clinical depression.