Cell Biochemistry Martinsried
represents an inductive approach for the exhaustive information extraction
from large multi-parametric data spaces in view of predictive or
diagnostic goals. Hypothesis driven data collection (fig.1a)
is followed by
(fig.1b) and interpretation (fig.1c) of the resulting
predictive data patterns for
individualized classification of
such as for the pretherapeutic identification of risk patients or for
individualized pretherapeutic risk assessment.
2. Practical Determination of Predictive Data Patterns
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
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.
Predictive Medicine by Cytomics: Potential and Challenges.
J.Biol.Regulators 16:164-167, (2002)
L2. G.Valet, A.Tárnok: Cytomics in predictive medicine. Cytometry 53B:1-3 (2003) (PDF)
L3. G.Valet, R.Repp, H.Link, A.Ehninger, M.Gramatzki and SHG-AML study group: Pretherapeutic identification of high risk acute myeloid leukemia (AML) patients from immunophenotype, cytogenetic and clinical parameters. Cytometry 53B:3-10 (2003) (PDF)
Ln. further readings
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