Oncostat - Methodology and Clinical Epidemiology for Molecular Oncology

Group leader : 
Stefan Michiels
+ 33 (0)1 42 11 41 44

Bâtiment de médecine moléculaire, Level 0, Room 85


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Oncostat - Methodology and Clinical Epidemiology for Molecular Oncology


Methodology and Clinical Epidemiology for Molecular Oncology

This group is the Oncostat team of the UMR1018/CESP.

The recent revolution in –omics technology and the advent of targeted therapies have increased the interest in molecular biomarkers capable of predicting the diagnostic, the clinical outcome of cancer patients or the response to specific therapies (diagnostic, prognostic and predictive). There are many challenges in the appropriate processing of modern sequencing data and the integration of molecular data in clinical epidemiology. The development of personalised medicine implies the segmentation of common cancers in small groups of tumours with specific abnormalities

Research theme 1 "Clinical Trial Methodology"

A new generation of clinical trial designs requiring repeated biomarker measurements and surrogate clinical endpoints is needed to evaluate treatment effects in trials with limited sample sizes

Research theme 2 "Meta-analysis of treatments and biomarkers"

Large-scale collaborative individual patient data meta-analyses are useful tools to provide high level of evidence on the efficacy and toxicity of anti-cancer therapies in molecularly defined strata.

Research theme 3 "Economic evaluation of treatments and biomarkers"

With the increasing number of therapies available for a specific indication in oncology, methods for network meta-will be developed to compare their effectiveness. Because of the high costs associated with the new tandem diagnostic and therapeutic medicine, economic analyses will be needed to evaluate the strategy associating the biomarkers with the molecularly targeted treatments, which represents a new field of research

Research theme 4 "Molecular cancer epidemiology"

Once a potential biomarker has been identified for the prediction of diagnosis or clinical outcome of patients, evidence-based evaluation implies careful replication in other cohorts. Advances in molecular genetics and in the knowledge of pathology of cancer are re-shaping the traditional methods in clinical and molecular epidemiology research.


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