Sereng
☆

USA,
2022-05-12 17:22
(14 d 02:21 ago)

Posting: # 22976
Views: 186

## Sample Size Estimate in BE Studies [Power / Sample Size]

Dear colleagues, in BE studies that must be conducted as parallel group design (e.g., depot formulations with sampling for 2 to 3 months), (i) is the sample size generally the same when compared to crossover design studies? and (ii) how do you estimate sample size when the known CV of the reference drug is excessive and much higher (e.g., double or triple) than the estimated CV of the Test drug? Regards

Biostatistically Challenged CEO
ElMaestro
★★★

Denmark,
2022-05-13 02:02
(13 d 17:41 ago)

@ Sereng
Posting: # 22984
Views: 166

## Sample Size Estimate in BE Studies

Hi Sereng,

(i) The sample size for a parallel trial will generally be somewhat higher. This is because the between-subject variance is most often higher than the within-subject variance (anomalies exist, but they have to do with the estimation methods). When you do a parallel trial, the (residual) variance estimate incorporates both the withins and betweens, and both are positive quantities.

(ii) This is not always straightforward. If you have CVs from data on the log scale (yes, on the log scale) for the two treatments then you can convert them to useful variances. Variances can handily be pooled (weighted according to sample size in the two groups). Most often you just aim for balance between groups, so the average of the two variances serves well. Your resulting variance estimate can now be plugged into the software of your choice along with a guess for the match, like 95% similarity of Cmax or AUCt.
Your software may prefer CVs as argument and it may even accept a vector of variances or CVs as argument, so you don't need to pool.
To convert between CV and variance, use CV = sqrt(exp(Variance)-1)

But you really need to start out with CVs based on data on the log scale.

Pass or fail!
ElMaestro
Sereng
☆

USA,
2022-05-18 05:58
(8 d 13:45 ago)

@ ElMaestro
Posting: # 22998
Views: 98

## Sample Size Estimate in BE Studies

Many thanks!

Biostatistically Challenged CEO