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Méthodologie de l’évaluation des biomarqueurs prédictifs quantitatifs et de la détermination d’un seuil pour leur utilisation en médecine personnalisée

Abstract : In France, the cancer research is a major public health issue. The number of new cancer cases nearly doubled between 1980 and 2012. The heterogeneity of the tumor characteristics, for a given cancer, presents a great challenge in the research of new effective treatments. In this context, much hope is placed in the research of predictive (or treatment selection) biomarkers that reflect the patients’ characteristics in order to guide treatment choice. For example, in the metastatic colorectal cancer setting, it is admitted that the addition of cetuximab (an anti-EGFR) to classical chemotherapy (the FOLFOX4), only improve the outcome of patients with KRAS wild-type tumors. In that context, the KRAS gene is a binary treatment selection marker, but plenty of biomarkers result from some quantifications or dosage measurements. The first aim of this thesis is to quantify the global treatment selection ability of a biomarker. After a review of the existing litterature, a method based on an extension of ROC curves is proposed and compared to existing methods. Its main advantage is that it is non-parametric, and that it does not depend on the mean risk of event in each treatment arm. In a second time, when a quantitative treatment selection biomarker is assessed, there is a need to estimate a marker thereshold value above which one treatment is preferred, and below which the other treatment is recommended. An approach that relies on the definition of a utility function is proposed in order to take into account both efficacy and toxicity of treatments when estimating the optimal threshold. A Bayesian method for the estimation of the optimal threshold is proposed
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Submitted on : Tuesday, November 26, 2019 - 5:23:07 PM
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Yoann Blangero. Méthodologie de l’évaluation des biomarqueurs prédictifs quantitatifs et de la détermination d’un seuil pour leur utilisation en médecine personnalisée. Bio-Informatique, Biologie Systémique [q-bio.QM]. Université de Lyon, 2019. Français. ⟨NNT : 2019LYSE1125⟩. ⟨tel-02381703⟩

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