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Clin Trials. 2012 Apr;9(2):164-75. doi: 10.1177/1740774511430714. Epub 2012 Feb 1.

An approach to combining parallel and cross-over trials with and without run-in periods using individual patient data.

Author information

1
Norwegian Computing Center - SAMBA, Oslo, Norway. Ingunn.Fride.Tvete@nr.no

Abstract

BACKGROUND:

In active run-in trials, where patients may be excluded after a run-in period based on their response to the treatment, it is implicitly assumed that patients have individual treatment effects. If individual patient data are available, active run-in trials can be modelled using patient-specific random effects. With more than one trial on the same medication available, one can obtain a more precise overall treatment effect estimate.

METHODS:

We present a model for joint analysis of a two-sequence, four-period cross-over trial (AABB/BBAA) and a three-sequence, two-period active run-in trial (AB/AA/A), where the aim is to investigate the effect of a new treatment for patients with pain due to osteoarthritis.

RESULTS:

Our approach enables us to separately estimate the direct treatment effect for all patients, for the patients excluded after the active run-in trial prior to randomisation, and for the patients who completed the active run-in trial. A similar model approach can be used to analyse other types of run-in trials, but this depends on the data and type of other trials available.

LIMITATIONS:

We assume equality of the various carry-over effects over time.

CONCLUSIONS:

The proposed approach is flexible and can be modified to handle other designs. Our results should be encouraging for those responsible for planning cost-efficient clinical development programmes.

PMID:
22297620
DOI:
10.1177/1740774511430714
[Indexed for MEDLINE]

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