Statistical Methods for Personalized Medicine team - Institut Curie - U900 - Paris
Who are we ?
The statistical Methods fo Personalized medicine team is an Inserm unit of Institut Curie. The team is part of U900 Cancer and genome : bioinformatics, biostatistics and epidemiology whose responsible is Emmanuel Barillot (https://science.curie.fr/recherche/biologie-interactive-des-tumeurs-immunologie-environnement/c/). The manager of the team is Aurélien Latouche. The main part of team's activities involves patients with cancer.
Topics of interest
- Methods for validating a biomarker predictive of treatment response for censored data. This work follows on from that carried out for a prognostic biomarker (where the treatment decision is not incorporated), for estimating the area under the time-dependent ROC curve for correlated survival data, and for a time-dependent biomarker, e.g. to quantify the discriminatory ability of different measures of circulating tumor cells with regard to the occurrence of a time-to-event.
- Methods for early-phase trials, notably using early biomarkers of treatment activity to identify an optimal dose or vaccine design.
- Meta-analyses of individual data in ovarian and gastric cancer, notably for the use of new measures of treatment effect, for the validation of surrogate endpoints, and for the study of biomarkers.
- Meta-analyses of summarized data on the methodological aspects of cancer trials
- Measures of the efficiency of care for gynecological cancers, with access to the EGB and the "cancer" database of reimbursement data managed by INCa (Institut National du Cancer).
- Chamseddine A, Oba K, Buyse M, Boku N, Bouché O, Satar T, Auperin A, Paoletti X Impact of follow-up on generalized pairwise comparisons for estimating the irinotecan benefit in advanced/metastatic gastric cancer. Contemporary Clinical Trials. 2021
- Mozgunov P, Paoletti X, Jaki T. A benchmark for dose-finding studies with unknown ordering. Biostatistics. 2021
- Paoletti X, Lewsley L-A; Daniele G, et al. Assessment of Progression Free Survival as a Surrogate Endpoint of Overall Survival in First Line Treatment of Ovarian Cancer. JAMA network open (2020)
- Meddis A, Blanche P, Bidard FC, Latouche A. A covariate-specific time-dependent receiver operating characteristic curve for correlated survival data. Stat Med. 2020
- Le Tourneau C, Delord JP, Kotecki N, Borcoman E, Gomez-Roca C, Hescot S, Jungels C, Vincent-Salomon A, Cockenpot V, Eberst L, Molé A, Jdey W, Bono F, Trochon-Joseph V, Toussaint H, Zandanel C, Adamiec O, de Beaumont O, Cassier PA. A Phase 1 dose-escalation study to evaluate safety, pharmacokinetics and pharmacodynamics of AsiDNA, a first-in-class DNA repair inhibitor, administered intravenously in patients with advanced solid tumours. Br J Cancer. 2020
- Meddis A, Latouche A, Zhou B, Michiels S, Fine J. Meta-analysis of clinical trials with competing time-to-event endpoints. Biom J. 2020 May;62(3):712-723.
- Mboup B, Blanche P, Latouche A. On evaluating how well a biomarker can predict treatment response with survival data. Pharm Stat. 2020
INSERM – Institut Curie : U900 Cancer et génome : bioinformatique, biostatistiques et épidémiologie
Team: Méthodes Statistiques pour la médecine personnalisée
35 rue Dailly 92210 St Cloud (team adress)
26 rue d’Ulm 75005 Paris (structure adress)