The ultimately desired high statistical significance of results for
clinical applications is initially in conflict with the search for
individually predictive parameter patterns through the collection of large
amounts of multi-parametric information from flow cytometry of
heterogeneous cellular suspensions, bead arrays or DNA and protein
expression arrays. A two phase strategy (L2)
is therefore appropriate (fig.2). The initial pilot phase
study (fig.2 phase 1) is performed at an acceptable minimum of
statistical stringency such as a significance level of P<0.05 or P<0.10.
The majority of uninformative parameters can be eliminated at this stage
by data sieving.
In the second phase (fig.2 phase 2), the remaining discriminatory
parameters for disease course prediction are analysed in statistically
large patient groups (L3). This provides
exact numbers for the reliability of individualized disease course
predictions and eliminates pseudo-informative parameters which have
slipped for random statistical reasons into the group of informative
parameters during the first phase. Informative parameters may
likewise have been lost for random statistical reasons into the group
of non-informative parameters during the initial phase. They my be
recoverable during the later deductive hypothesis and concept forming phase
from the molecular context of the final predictive parameter pattern.