Bioequivalence and Bioavailability Forum

Hello,

A multiplicative model is commonly admitted for PK parameters, which justifies that any statistical analysis is performed after log-transformation.

In one study (not a BE ) we have to analyze, one patient has all concentrations < LLOQ after one treatment.
As this was not really expected, this case was specifically planned neither in the study protocol nor in the SAP. The SAP however specified that concentrations < LLOQ should be set to zero, which then resulted in C_max and AUC_last = 0.

Nothing weird has been noticed on the clinical or laboratory side, and other patients also show a very low concentrations profile (but with at least one or two concentrations > LLOQ).
It therefore makes sense trying to keep these Cmax and AUC = 0 in the outcome of the statistical analysis, but of course, this information is being lost by the log-transformation: log(0)= .

Different workarounds are possible:

1. Analyzing the data in the original scale without log-transformation
   
2. Imputing C_max and AUC_last by something positive. For C_max, one can think using LLOQ or LLOQ/2, but what for AUC_last? Moreover, the results of the statistical analysis then become quite dependent of the selected imputation rule.
   
3. Applying a log(Param+d)- instead of a log(Param)-transformation, where d is a very small positive number. But again the statistical outcome is very dependent of the value chosen for d.
   

As it is the second time I face such a special case over the last few months, I would be very interested in having expert advices on the best (or less worse) practice to deal with it?

Many thanks in advance for sharing your thoughts!