Research

Packages

Life of the unit

Next seminars

Last publications

Updated

Poor long-term outcome in second kidney transplantation : a delayed event

Auteurs

• Trébern-Launay Katy - INSERM U1064 
  
  
• Foucher Yohann - Maître de Conférences en Biostatistique - HDR  - UFR de médecine - Université de Nantes 
  
  
• Giral Magali - PU-PH  - CHU de Nantes  
  
  
• Legendre C.
  
  
• Kreiss H
  
  
• Kessler M
  
  
• Ladrière M
  
  
• Kamar N
  
  
• Rostaing L
  
  
• Garrigue V
  
  
• Mourad G
  
  
• Morelon E
  
  
• Soulillou Jean-Paul
  
  
• Dantal J
  
  

Description

Nature : Articles dans une revue internationale
Thématique : Biostatistique et Mesures Subjectives en Santé
Rang : Rang A : publication porté par un membre de l'unité, dans le cadre de l'unité
Axe de recherche principal: Modèles pronostiques
Axe de recherche secondaire: Recherche Clinique
Sujet : Données Informatiques VAlidées en Transplantation

Trébern-Launay K, Foucher Y, Giral M, Legendre C, Kreiss H, Kessler M, Ladrière M, Kamar N, Rostaing L, Garrigue V, Mourad G, Morelon E, Soulillou JP, Dantal J (2012) Poor long-term outcome in second kidney transplantation : a delayed event. PLoS One, 7(10): e47915.

Lien

Résumé

BACKGROUND: Old studies reported a worse outcome for second transplant recipient (STR) than for first transplant recipient (FTR) mainly due to non-comparable populations with numbers confounding factors. More recent analysis, based on improved methodology by using multivariate regressions, challenged this generally accepted idea: the poor prognosis for STR is still under debate. METHODOLOGY: To assess the long-term patient-and-graft survival of STR compared to FTR, we performed an observational study based on the French DIVAT prospective cohort between 1996 and 2010 (N = 3103 including 641 STR). All patients were treated with a CNI, an mTOR inhibitor or belatacept in addition to steroids and mycophenolate mofetil for maintenance therapy. Patient-and-graft survival and acute rejection episode (ARE) were analyzed using Cox models adjusted for all potential confounding factors such as pre-transplant anti-HLA immunization. RESULTS: We showed that STR have a higher risk of graft failure than FTR (HR = 2.18, p = 0.0013) but that this excess risk was observed after few years of transplantation. There was no significant difference between STR and FTR in the occurrence of either overall ARE (HR = 1.01, p = 0.9675) or steroid-resistant ARE (HR = 1.27, p = 0.4087). CONCLUSIONS: The risk of graft failure following second transplantation remained consistently higher than that observed in first transplantation after adjusting for confounding factors. The rarely performed time-dependent statistical modeling may explain the heterogeneous conclusions of the literature concerning second transplantation outcomes. In clinical practice, physicians should not consider STR and FTR equally.

Abstract

BACKGROUND: Old studies reported a worse outcome for second transplant recipient (STR) than for first transplant recipient (FTR) mainly due to non-comparable populations with numbers confounding factors. More recent analysis, based on improved methodology by using multivariate regressions, challenged this generally accepted idea: the poor prognosis for STR is still under debate. METHODOLOGY: To assess the long-term patient-and-graft survival of STR compared to FTR, we performed an observational study based on the French DIVAT prospective cohort between 1996 and 2010 (N = 3103 including 641 STR). All patients were treated with a CNI, an mTOR inhibitor or belatacept in addition to steroids and mycophenolate mofetil for maintenance therapy. Patient-and-graft survival and acute rejection episode (ARE) were analyzed using Cox models adjusted for all potential confounding factors such as pre-transplant anti-HLA immunization. RESULTS: We showed that STR have a higher risk of graft failure than FTR (HR = 2.18, p = 0.0013) but that this excess risk was observed after few years of transplantation. There was no significant difference between STR and FTR in the occurrence of either overall ARE (HR = 1.01, p = 0.9675) or steroid-resistant ARE (HR = 1.27, p = 0.4087). CONCLUSIONS: The risk of graft failure following second transplantation remained consistently higher than that observed in first transplantation after adjusting for confounding factors. The rarely performed time-dependent statistical modeling may explain the heterogeneous conclusions of the literature concerning second transplantation outcomes. In clinical practice, physicians should not consider STR and FTR equally.

Projet(s) ayant donné lieu à cette publication

DIVAT-SPHERE - Axe 2 : Prédiction/pronostic à long-terme du patient transplanté

Thèse(s) ou stage(s) lié(s) à cette publication

Katy Trébern-Launay : Apport des modèles de survie relative dans la modélisation des patients transplantés rénaux : application à la cohorte DIVAT (soutenue le 24 octobre 2013)

Publications ayant le même axe principal de recherche (Modèles pronostiques)

• Fournier MC, Foucher Y, Blanche P, Legendre C, Girerd S, Ladrière M, Morelon E, Buron F, Rostaing L, Kamar N, Mourad G, Garrigue V, Couvrat-Desvergnes G, Giral M, Dantan E (2019) Dynamic predictions of long-term kidney graft failure: an information tool promoting patient-centred care.. Nephrology Dialysis Transplantation: .
  
  
• Hanson C, Sautenet B, Craig J, Chapman J, Knoll G, Reddy B, Tong A (2019) Informative for Decision-making? The Spectrum and Consistency of Outcomes Following Living Kidney Donation Reported in Trials and Observational Studies. Transplantation, 103(2): 284-90.
  
  
• Tong A, Manns B, Wang A, Hemmelgarn B, Wheeler D, Gill J, Tugwell P, Pecoits-Filho R, Crowe S, Harris T, van Biesen W, Winkelmayer W, Levin A, Thompson A, Perkovic V, Ju A, Gutman T, Bernier-Jean A, Viecelli A, O'Lone E, Shen J, Josephson M, Cho Y, Johnson D, Sautenet B, Tonelli M, Craig J, SONG Implementation Workshop Investigators (2018) Implementing core outcomes in kidney disease: report of the Standardized Outcomes in Nephrology (SONG) implementation workshop. Kidney Int, 94(6): 1053-68.
  
  
• Machet L, Zaragoza J, Finon A, Garnier M, Maillard H, Caille A (2018) Baseline neutrophil-to-lymphocyte ratio in patients with advanced melanoma treated with immune checkpoint inhibitors. Br J Dermatol, 179(1): 224. doi: 10.1111/bjd.16675. Epub 2018 May 8.
  
  
• Dantan E, Foucher Y, Lorent M, Giral M, Tessier P (2018) Optimal threshold estimator of a prognostic marker by maximizing a time-dependent expected utility function for a patient-centered stratified medicine. Statistical Methods in Medical Research, 27(6): 1847-1859.
  
  
• Fournier MC, Dantan E, Blanche P (2018) An R2-curve for evaluating the accuracy of dynamic predictions. Stat Med, 37(7): 1125-1133.
  
  
• Finon A, Zaragoza J, Maillard H, Beneton N, Bens G, Samimi M, Caille A, Machet L (2018) A high neutrophil to lymphocyte ratio prior to BRAF inhibitor treatment is a predictor of poor progression-free survival in patients with metastatic melanoma. Eur J Dermatol, 28(1): 38-43.
  
  
• Desmée S, Mentré F, Veyrat-Follet C, Sebastien B, Guedj J (2017) Nonlinear joint models for individual dynamic prediction of risk of death using Hamiltonian Monte Carlo: application to metastatic prostate cancer. BMC Med Res Methodol, 17(1): 105.
  
  
• Terrier LM, Bauchet L, Rigau V, Amelot A, Zouaoui S, Filipiak I, Caille A, Almairac F, Aubriot-Lorton M, Bergemer-Foucquet A, Bord E, Cornu P, Czorny A, Dam Hieu P, Debono B, Delisle M, Emery E, Farah W, Gauchotte G, Godfraind C, et al. (2017) Natural course and prognosis of anaplastic gangliogliomas: a multicenter retrospective study of 43 cases from the French Brain Tumor Database. Neuro Oncol, 19(5): 678-88.
  
  
• Le Borgne F, Combescure C, Gillaizeau F, Giral M, Chapal M, Giraudeau B, Foucher Y (2017) Standardized and weighted time-dependent ROC curves to evaluate the intrinsic prognostic capacities of a marker by taking into account confounding factors. Statistical Methods in Medical Research: 962280217702416. doi: 10.1177/0962280217702416.
  
  
• Le Borgne F, Giraudeau B, Querard AH, Giral M, Foucher Y (2016) Comparisons of the performance of different statistical tests for time-to-event analysis with confounding factors: practical illustrations in kidney transplantation. Stat Med, 35(7): 1103-16.
  
  
• Querard AH, Foucher Y, Combescure C, Dantan E, Larmet D, Lorent M, Pouteau LM, Giral M, Gillaizeau F (2016) Comparison of survival outcomes between Expanded Criteria Donors and Standard Criteria Donors kidney transplant recipients: a systematic review and meta-analysis. Transplant International, 29(4): 403-15.
  
  
• Fournier MC, Foucher Y, Blanche P, Buron F, Giral M, Dantan E (2016) A joint model for longitudinal and time-to-event data to better assess the specific role of donor and recipient factors on long-term kidney transplantation outcomes. European Journal of Epidemiology, 31(5): 469-79.
  
  
• Zaragoza J, Caille A, Beneton N, Bens G, Christiann F, Maillard H, Machet L (2016) High neutrophil to lymphocyte ratio measured before starting ipilimumab treatment is associated with reduced overall survival in patients with melanoma. Br J Dermatol, 174(1): 146-51.
  
  
• Le Fur A, Fournier MC, Gillaizeau F, Masson D, Giral M, Cariou B, Cantarovich D, Dantal J (2015) Vitamin D deficiency is an independent risk factor for PTDM after kidney transplantation.. Transplant international: .
  
  
• Chapal M, Foucher Y, Marquette C, Néau K, Papuchon E, Daguin P, Morelon E, Mourad G, Castillo J, Ladrière M, Legendre C, Giral M (2015) PREventing Delayed Graft Function by Driving Immunosuppressive InduCtion Treatment (PREDICT-DGF): study protocol for a randomized controlled trial. Trials, 16(1): 282.
  
  
• Gillaizeau F, Dantan E, Giral M, Foucher Y (2015) A multistate additive relative survival semi-Markov model. Statistical Methods in Medical Research, 26(4): 1700-1711.
  
  
• Foucher Y, Meurette A, Daguin P, Bonnaud-Antignac A, Hardouin JB, Néau K, Papuchon E, Guaboriau S, Legendre C, Morelon E, Tessier P, Giral M (2015) A Personalized Follow-up of Kidney Transplant Recipients by Using Video Conferencing based on a 1-year scoring system predictive of long term graft failure (TELEGRAFT study): Protocol for a Randomized Controlled Trial. BMC Nephrology, 16(1): 6.
  
  
• Senage T, Le Tourneau T, Foucher Y, Pattier S, Michel M, Mugniot A, Perigaud C, Carton F, Al Habash O, Baron O, Roussel J (2014) Early Structural Valve Deterioration of Mitroflow aortic bioprosthesis : mode, incidence and impact on outcome in a large cohort of patients. Circulation, 130(23): 2012-20.
  
  
• 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 JP, Launay K, Daguin P, Offredo L, Giral M, Foucher Y (2014) A useful scoring system for the prediction and management of delayed graft function following kidney transplantation from cadaveric donors. Kidney International, 86(6): 1130-9.
  
  
• Debout A, Foucher Y, Trébern-Launay K, Legendre C, Kreiss H, Mourad G, Garrigue V, Morelon E, Buron F, Rostaing L, Kamar N, Kessler M, Ladrière M, Poignas A, Blidi A, Soulillou JP, Giral M, Dantan E (2014) Each additional hour of Cold Ischemia Time significantly increases the risk of graft failure and mortality after renal transplantation. Kidney International, 87: 343-9.
  
  
• Yap M, Boeffard F, Clave E, Pallier A, Danger R, Giral M, Dantal J, Foucher Y, Guillot-Gueguen C, Toubert A, Soulillou JP, Degauque N (2014) Expansion of Highly Differentiated Cytotoxic Terminally Differentiated Effector Memory CD8+ T Cells in a Subset of Clinically Stable Kidney Transplant Recipients: A Potential Marker for Late Graft Dysfunction. J Am Soc Nephrol, 25(8): 1856-68.
  
  
• Combescure C, Foucher Y, Jackson D (2014) Meta-analysis of single-arm survival studies: a distribution-free approach for estimating summary survival curves with random effects. Statistics in Medicine, 33(15): 2521-37.
  
  
• 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.
  
  
• Dantan E, Combescure C, Lorent M, Ashton-Chess J, Daguin P, Classe JM, Giral M, Foucher Y (2014) An original approach was used to better evaluate the capacity of a prognostic marker using published survival curves. Journal of Clinical Epidemiology, 67(4): 441-8.
  
  
• Gillaizeau F, Giral M, Dantan E, Dragun D, Soulillou JP, Foucher Y (2014) Multi-state analysis of kidney transplant recipients outcome: a semi-Markov model for studying the role of pre-transplant sensitization against Angiotensin II Type 1 receptor. Journal de la Société Française de Statistique , 155(1): 117-133.
  
  
• 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 JP, Soulillou JP, 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 JP, Foucher Y (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.
  
  
• Giral M, Foucher Y, Dufay A, Duong Van Huyen J, Renaudin K, Moreau A, Philippe A, Hegner B, Dechend R, Brouard S, Cesbron A, Castagnet S, Devys A, Soulillou JP, Dragun D (2013) Pretransplant Sensitization Against Angiotensin II Type 1 Receptor Is a Risk Factor for Acute Rejection and Graft Loss. American Journal of Transplantation, 13(10): 2567-76.
  
  
• Trébern-Launay K, Giral M, Dantal J, Foucher Y (2013) Comparison of the risk factors effects between two populations: two alternative approaches illustrated by the analysis of first and second kidney transplant recipients. BMC Medical Research Methodology, 13: 102.
  
  
• Foucher Y (2013) Modélisation et pronostic de l'évolution de pathologies chroniques : Applications en transplantation renale. , 193.
  
  
• 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): Article 1.
  
  
• Combescure C, Daurès JP, Foucher Y (2012) A literature-based approach to evaluate the predictive capacity of a marker using time-dependent summary receiver operating characteristics. Stat Methods Med Res: online first.
  
  
• Foucher Y, Combescure C, Ashton-Chess J, Giral M (2012) Prognostic Markers: Data Misinterpretation Often Leads to Overoptimistic Conclusions. Am J Transplant, 12(4): 1060-1.
  
  
• Foucher Y, Giral M, Soulillou JP, Daurès JP (2012) Cut-off estimation and medical decision making based on a continuous prognostic factor : the prediction of kidney graft failure. Int J Biostat, 8(1): 1–13.
  
  
• Degauque N, Boeffard F, Foucher Y, Ballet C, Brouard S, Soulillou JP (2011) The Blood of Healthy Individuals Exhibits CD8 T Cells with a Highly Altered TCR Vb Repertoire but with an Unmodified Phenotype. PLoS One, 6(6): e21240.
  
  
• Brouard S, Le Bars A, Dufay A, Gosselin M, Foucher Y, Guillet M, Cesbron A, Thervet E, Legendre C, Dugast E, Pallier A, Guillot-Gueguen C, Lagoutte L, Evanno G, Giral M, Soulillou JP (2011) Identification of a gene expression profile associated with operational tolerance among a selected group of stable kidney transplant patients. Transplantation International, 24(6): 536-547.
  
  
• Foucher Y, Giral M, Soulillou JP, Daurès JP (2010) Time-dependent ROC analysis for a three-class prognostic with application to kidney transplantation. Statistics in Medicine, 29(30): 3079-87.
  
  
• Foucher Y, Daguin P, Akl A, Kessler M, Ladrière M, Legendre C, Kreiss H, Kamar N, Rostaing L, Garrigue V, Bayle F, de Ligny B, Buchler M, Meier C, Soulillou JP, Giral M (2010) A clinical scoring system highly predictive of long-term kidney graft survival.. Kidney International, 78(12): 1288-94.
  
  
• Foucher Y, Giral M, Soulillou JP, Daurès JP (2010) A flexible semi-Markov model for interval-censored data and goodness-of-fit testing. Statistical Methods in Medical Research, 19(2): 127-45.
  
  
• Ladrière M, Foucher Y, Legendre C, Kamar N, Garrigue V, Morelon E, Kressler M, Soulillou JP, Giral M (2010) The Western Europe Cohort Of Kidney Transplanted Recipients - The DIVAT Network. In Clinical Transplants (J. Michael Cecka and Paul I. Terasaki): Terasaki Foundation Laboratory.
  
  
• Foucher Y, Daguin P, Kessler M, Ladrière M, Legendre C, Kreiss H, Durand D, Mourad G, Garrigue V, Soulillou JP, Giral M (2008) How well do pre- and peritransplant variables predict the long-term results of kidney transplantation?. In Clinical Transplants - Chapter 10 (J. Michael Cecka and Paul I. Terasaki): Terasaki Foundation Laboratory.
  
  
• Foucher Y, Daguin P, Kessler M, Laveyssiere L, Legendre C, Kreiss H, Durand D, Layrolle P, Mourad G, Garrigue V, Daurès JP, Soulillou JP, Giral M (2008) How to evaluate the long-term prognostic capacity of pre-graft variables in transplantation?. Clinical Transplant: 113-8.
  
  
• Foucher Y, Giral M, Soulillou JP, Daurès JP (2007) A semi-Markov model for multistate and interval-censored data with multiple terminal events. Application in renal transplantatio. Statistics in Medicine, 26(30): 5381-93.
  
  
• Castelli C, Combescure C, Foucher Y, Daurès JP (2007) Cost-effectiveness analysis in colo-rectal cancer using a semi-Markov model. Statistics in Medicine, 26(30): 5557-71.
  
  
• Foucher Y (2007) Modèles semi-Markoviens : Application à l'analyse de l'évolution de pathologies chroniques. Thèse de doctorat de l'Université Montpellier 1, 184.
  
  
• Mathieu E, Foucher Y, Dellamonica P, Daurès JP (2007) A Parametric and Non Homogeneous Semi-Markov Process for HIV control. Methodology and Computing in Applied Probability, 9(3): 389-97.
  
  
• Foucher Y, Saint-Pierre P, Puglièse P, Daurès JP (2006) A Semi-Markov Frailty Model for Multistate Survival Data : Illustration on HIV Disease. Far East Journal of Theoretical Statistics, 19: 185-201.
  
  
• Foucher Y, Mathieu E, Saint-Pierre P, Durand JF, Daurès JP (2005) A semi-Markov model based on Generalized Weibull distribution with an illustration for HIV disease. Biometrical Journal, 47(6): 825-33.
  
  
• Giral M, NGuyen JM, Karam G, Kessler M, Hurault de Ligny B, Buchler M, Bayle F, Meyer C, Foucher Y, Martin ML, Daguin P, Soulillou JP (2005) Impact of graft mass in the clinical outcome of kidney transplants. Journal of the American Society of Nephrology, 16: 261-268.
  
  

Publications liées à l'axe principal de recherche (Modèles pronostiques)

• Chapal M, Néel M, Le Borgne F, Meffray E, Carceles O, Hourmant M, Giral M, Foucher Y, Moreau A, Fakhouri F (2013) Increased soluble flt-1 correlates with delayed graft function and early loss of peritubular capillaries in the kidney graft. Transplantation, 96(8): 739-44.
  
  
• Cantarovich D, Hodemon-Corne B, Trébern-Launay K, Giral M, Foucher Y, Dantan E (2013) Early steroid withdrawal compared with steroid avoidance correlates with graft failure among kidney transplant recipients with an history of diabetes. Transplantation Procedings, 45(4): 1497-502.
  
  
• Danger R, Paul C, Giral M, Foucher Y, Degauque N, Pallier A, Durand M, Castagnet S, Duong Van Huyen J, Delahousse M, Renaudin K, Soulillou JP, Brouard S (2013) Expression of miR-142-5p in peripheral blood mononuclear cells from renal transplant patients with chronic antibody-mediated rejection. PLoS One, 8(4): e60702.
  
  
• Thibaud A, Foucher Y, Danger R, Migone T, Pallier A, Castelli C, Castagnet S, Devys A, Cesbron A, Giral M, Soulillou JP, Brouard S (2012) BAFF and BAFF-R levels are associated with risk of long-term kidney graft dysfunction and development of donor-specific antibodies. Am J Transplant, 12(10): 2754-62.
  
  
• Racapé M, Duong Van Huyen J, Danger R, Giral M, Bleicher F, Foucher Y, Pallier A, Pilet P, Tafelmeyer P, Ashton-Chess J, Dugast E, Pettre S, Charreau B, Soulillou JP, Brouard S (2011) The involvement of SMILE/TMTC3 in endoplasmic reticulum stress response. PLoS One, 6(5): e19321.