Contact details

Institut de Recherche en Santé 2 22 boulevard Bénoni Goullin 44200 Nantes, France

0253009122 (n° interne : 329122)
Personal Website

Activities / Resume

Research activities:
  • Analysis of longitudinal and survival data;
  • Competing risks models and multistate regressions;
  • Methods in diagnostic and prognostic analysis;
  • Patient-centered stratified medical decision making;
  • Confounders and related methodologies (multivariate modelling or propensity scores).
University diploma:
  • 2013 : Habilitation to supervise research. University of Nantes. Modelisation and prognostic of chronic diseases' evolutions: applications in kidney transplantation.
  • 2007 : PhD in Biostatistics (University of Montpellier). Semi-Markoviens models in the analysis of chronic diseases.
  • KTFS: a score computing at 1-year post-transplantation for evaluating the risk of middle-term graft failure (return to dialysis).
  • DGFS: a pre-transplant score for evaluating the risk of delayed graft function (the need of at least one dialysis post-transplantation).

International publications since 2010 (first or last author):

  • Le Borgne F., Giraudeau B., Quérard A.H., Giral M., Foucher Y. (2015) Comparisons of the performance of different statistical tests for time-to-event analysis with confounding factors: practical illustrations in kidney transplantation. Statistics in Medicine. 30;35(7):1103-16.
  • Gillaizeau F., Dantan E., Giral M., Foucher Y. (2015) A multistate additive relative survivalsemi-Markov model. Statistical Methods in Medical Research: online first.
  • Lorent M., Giral M., Foucher Y. (2014) Net time-dependent ROC curves: a solution for evaluating the accuracy of a marker to predict disease-related mortality. Statistics in Medicine,33(14): 2379-89.
  • Chapal M., Le Borgne F., Legendre C., Kreiss H., Mourad G., Garrigue V., Morelon E.,Buron F., Rostaing L., Kamar N., Kessler M., Ladrière M., Soulillou J.P.,Launay K., Daguin P., Offredo L., Giral M., Foucher Y. (2014) A useful scoring system for the prediction andmanagement of delayed graft function following kidney transplantation fromcadaveric donors. Kidney International, 86(6):1130-9.
  • Dantan E., Combescure C., Lorent M., Ashton-Chess J., Daguin P., Classe J.M., GiralM., Foucher Y. (2014) An original approach was used to better evaluate the capacity of a prognostic marker usingpublished survival curves. Journal of Clinical Epidemiology, 67(4): 441-8.
  • Foucher Y., Akl A., Rousseau V.,Trébern-Launay K., Lorent M., Kessler M., Ladrière M., Legendre C., Kreiss H.,Rostaing L., Kamar N., Mourad G., Garrigue V., Morelon E., Daurès J.P.,Soulillou J.P., Giral M. (2014) An alternative approach to estimate age-related mortality of kidney transplant recipients compared to the general population: results in favor of old-to-old transplantations. Transplant International, 27(2): 219-25.
  • Combescure C., Perneger T., Weber D., Daurès J.P., FoucherY. (2014) Prognostic ROC Curves: A Method for Representing the Overall Discriminative Capacity of Binary Markers with Right-Censored Time-to-Event Endpoints. Epidemiology, 25(1): 103-9.
  • Trebern-Launay K., Giral M., Dantal J., Foucher Y. (2013) Comparison of the risk factors effects between two populations: twoalternative approaches illustrated by the analysis of first and second kidney transplant recipients. BMC Medical Research Methodology, 13: 102.
  • Danger R., Foucher Y. (2012) Time dependent ROC curves for the estimation of true prognostic capacity of microarray data. Statistical Applications in Genetics and Molecular Biology, 11(6)
  • Combescure C., Daurès J.P., Foucher Y. (2012) A literature-based approach to evaluate the predictive capacity of a marker usingtime-dependent summary receiver operating characteristics. Stat Methods Med Res: online first.
  • Foucher Y., Combescure C., Ashton-ChessJ., Giral M. (2012) Prognostic Markers: Data Misinterpretation Often Leads toOveroptimistic Conclusions. Am J Transplant, 12(4): 1060-1.
  • Foucher Y., Giral M., Soulillou J.P.,Daurès J.P. (2012) Cut-off estimation and medical decision making based on acontinuous prognostic factor : the prediction of kidney graft failure. IntJ Biostat, 8(1): 1-13.
  • Foucher Y., Giral M., Soulillou J.P., Daurès J.P. (2010) Time-dependent ROC analysis for a three-class prognosticwith application to kidney transplantation. Statisticsin Medicine, 29(30): 3079-87.
  • Foucher Y., Daguin P., Akl A., KesslerM., Ladrière M., Legendre C., Kreiss H., Kamar N., Rostaing L., Garrigue V.,Bayle F., de Ligny B., Buchler M., Meier C., Soulillou J.P., Giral M. (2010) Aclinical scoring system highly predictive of long-term kidney graft survival.. KidneyInternational, 78(12): 1288-94.
  • Foucher Y., Giral M., Soulillou J.P., Daurès J.P. (2010) A flexible semi-Markov model for interval-censored data andgoodness-of-fit testing. Statistical Methods in Medical Research, 19(2): 127-45.
  • Foucher Y., Giral M., Soulillou J.P., Daurès J.P. (2010) Cut-off estimation and medical decision making based on a continuous prognostic factor: the prediction of kidney graft failure. InternationalJournal of Biostatistics, 8(1).