Impact of integrating clinical and genetic information.
To assess the relevance of molecular markers it is required to combine clinical and genetic information. For reliable assessment of parameters relevant to diagnostics and therapy large patient collectives must be characterized both with respect to phenotype and genotype. Matching of genetic data like gene expression profiles, molecular genetics and cytogenetics with clinical data like follow-up, morphological findings and diagnoses involves integration of complex databases. In the context of a nationwide leukemia research network in Germany we designed an integrated database covering both genetic and clinical data of patients. The system contains follow-up data and relevant laboratory modalities, i. e. cytomorphology, cytogenetics, molecular genetics, FISH, immunophenotyping and gene expression profiling. So far 13,541 cases from 7,746 patients treated by 1,225 physicians are documented. The data structure consists of up to 888 variables per case. From our experience, integration of clinical and genetic information requires significant efforts - including data protection issues -, but is feasible and improves data quality leading to faster and more reliable research results for the benefit of the patients.
Dugas
Martin
M
Department of Medical Informatics, Biometrics and Epidemiology (IBE), University of Munich, Marchioninistr. 15, D-81377 Munich, Germany. dug@ibe.med.uni-muenchen.de
Schoch
Claudia
C
Schnittger
Susanne
S
Kohlmann
Alexander
A
Kern
Wolfgang
W
Haferlach
Torsten
T
Uberla
Karl
K
D003199:Computer Systems; D020869:Gene Expression Profiling; D005819:Genetic Markers; D006801:Humans; D016130:Immunophenotyping; D017404:In Situ Hybridization, Fluorescence; D007938:Leukemia / Q000235:genetics* / Q000473:pathology*; D018511:Systems Integration
D005819:Genetic Markers