The aim of this project is to study the different diagnostic, predictive, and prognostic profiles, as well as their interrelationships (clinical, biological, genetic) in children with Acute Myeloid Leukemia (AML). Despite numerous research projects on separate cohorts, the prognosis for pediatric AML has not improved.
The project therefore consists of pooling research data and existing clinical and biological data from healthcare in a health data warehouse to increase its power.
As these diseases are rare and genetic subgroups even rarer, it is crucial to combine all these data sets into a single database to statistically validate our observations.
The ultimate goal of this project is to reduce the relapse rate and improve the survival rate of pediatric AML by identifying rare, uncharacterized patient subgroups at high risk of relapse, for whom clinical characteristics and outcomes will be compared with omics data, Leukemia Stem Cells signatures, and drug responses to establish accurate and in-depth profiles.