Abstract
Background: Crossover design is very popular for a study of new and developmental drugs. However this design tends to be misused
regardless of whether it is suitable for underlying research questions.
Method: Given that in clinical practice 2x2 cross over is the
most commonly used design, the Hills- Arbitrage approach is suggested to
analyze data. Furthermore, we propose fitting a linear mixed model and
then conducting a likelihood ratio test to yield a single p-value on
data
with multiple time points within each stratum.
Finding: Applying these methods to a real data, we evaluate
effect of glucagon-like peptide 1 (GLP-1) on women with polycystic ovariansyndrome (PCOS). Despite absence of statistically significant results,
this study as the first study to explore direct administration of GLP-1
to
PCOS women is nevertheless clinically meaningful. Not only does it show a
longer washout period is desired, but also it suggests GLP-1 may
have the same positive effect on PCOS as MET does.
Improvement: A larger parallel study is warranted, and clinicians and biostatisticians should collaborate more so that data can be analyzed
appropriately and interpreted from both statistical and clinical points of view.
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