Bioequivalence and Bioavailability Forum

Dear Martin!

❝ Full analysis data set (intent-to-treat): subjects that were randomized and received at least one study treatment.

Full ACK.

❝ Per-protocol analyses data set: subjects that were randomized, met all inclusion criteria, were dosed according to the protocol, received both treatments with measurements at all assessment time points with both study drugs, etc.

IMHO only almost.
I disagree with:

❝ […] met all inclusion criteria, […]

In the ‘real world’ sometimes a subject was included although an exclusion criterion should have prevented this. A ‘classical example’ is a violation of limits set for the Body Mass Index. Due to rounding sometimes a subject finished the study and the violation becomes only evident during QAU data clearing. In such a case I would handle it according to ICH E6 (Section 10.2 Protocol Deviations), and keep the subject in the evaluation.

❝ […] measurements at all assessment time points with both study drugs […]

You’re suggesting to exclude a subject if one sample vial is broken?

❝ based on these example definitions, handling of missing values is applicable for the full analyses dataset only.

Why?

❝ for PK analyses, both data sets are analyzed and the results for the full analyses data set is the more important as pointed out by the ICH E9 guideline (i.e. primary analysis).

Disagree. See NfG on BA/BE (Section 3.8 Reporting of results):

‘All results should be clearly presented and should include data from subjects who eventually dropped-out. Drop-out and withdrawal of subjects should be fully documented and accounted for.’

At least by means of an ANOVA it’s simply not possible to run a BE analysis of the full data set in a conventional 2×2 cross-over if the second period is missing. Of course PK parameters have to be calculated as far as possible and presented. A nice example is the case where a subject drops out let’s say in the middle of the elimination phase of the second period. In such a case it would be possible to base the assessment of C_max on the data set of n subjects and of AUC of n-1 subjects in order to maintain maximum power.

❝ for safety analyses, only the full analysis data set is used.

100% ACK.