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The aim of the study is to create new tools for improving management of patients with hematological malignancies by combining extensive clinical data from patients newly diagnosed with hematological malignancies and innovative laboratory analyses made on available tissue samples in regional biobanks from these patients.
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Firstly, clinical information is collected on all hematological malignancies diagnosed in our hospital district area retrospectively between the years 2000 and 2019. Clinical outcomes, laboratory results, clinically relevant diagnoses, characteristics defining clinical stage and established prognostic parameters are gathered.
Simultaneously a tissue microarray (TMA) of diagnostic samples is compiled using representative annotated tissue areas. This TMA is used in combination with additional control material to identify prognostic and predictive biomarkers.
A combined microarray dataset of hematological malignancies (Hemap) is utilized to point out genes of possible drug targets, disease specific markers, prognostic markers, or predictive markers.
The clinical datasets and Hemap dataset is ultimately utilized to gain knowledge, new tools for prognostication and diagnostics, and targets for treatment. Artificial intelligence -assisted differential diagnostics will be tested.
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Data sourced from clinicaltrials.gov
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