Trial treatment length optimization with an emphasis on disease progression studies.

Abstract:

:Optimal design has been used in the past mainly to optimize sampling schedules for clinical trials. Optimization on design variables other than sampling times has been published in the literature only once before. This study shows, as an example, optimization on the length of treatment periods to obtain reliable estimates of drug effects on longterm disease progression studies. Disease progression studies are high in cost, effort, and time; therefore, optimization of treatment length is highly recommended to avoid failure or loss of information. Results are provided for different drug effects (eg, protective and symptomatic) and for different lengths of studies and sampling schedules. The merits of extending the total study length versus inclusion of more samples per participants are investigated. The authors demonstrate that if no observations are taken during the washout period, a trial can lose up to 40% of its efficiency. Furthermore, when optimization of treatment length is performed using multiple possible drug effect models simultaneously, these studies show high power in discriminating between different drug effect models.

journal_name

J Clin Pharmacol

authors

Hennig S,Nyberg J,Hooker AC,Karlsson MO

doi

10.1177/0091270008329560

subject

Has Abstract

pub_date

2009-03-01 00:00:00

pages

323-35

issue

3

eissn

0091-2700

issn

1552-4604

pii

49/3/323

journal_volume

49

pub_type

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