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An approach to combining parallel and cross-over trials with and without run-in periods using individual patient data
Ingunn F Tvete1, Inge C Olsen, Morten W Fagerland
1Norwegian Computing Center - SAMBA, Oslo, Norway. Ingunn.Fride.Tvete@nr.no
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.
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