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1. Structuring and centralizing breast cancer real-world biomarker data from pathology reports through C-LAB artificial intelligence platform

Author

Florent Le Borgne, Camille Garnier, Camille Morisseau, Yanis Navarrete, Yanina Echeverria, Juan Mir, Jaume Calafell, Tanguy Perennec, Olivier Kerdraon, Jean-Sébastien Frenel, Judith Raimbourg, Mario Campone, Maria Fe Paz, and François Bocquet

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Purpose To evaluate the effectiveness of C-LAB ® , an artificial intelligence (AI) platform, in extracting, structuring, and centralizing biomarker data from breast cancer pathology reports within the challenging, heterogeneous dataset of the Institut de Cancérologie de l’Ouest (ICO). Methods C-LAB ® was deployed at the ICO to analyze HER2 and hormonal receptor data from breast cancer pathology reports. During the development phase, 292 anatomic pathology reports were used to design and refine the rule-based extraction algorithm through an iterative process of monitoring and adjustments. After finalizing the algorithm, it was applied to a total of 2323 anatomic pathology reports. To evaluate the platform's accuracy, performance metrics could only be calculated for a subset of these reports that were also available in the structured National Epidemiological Strategy and Medical Economics (ESME) database. Out of the 2323 pathology reports belonging to 487 patients analyzed by C-LAB ® , 666 corresponded to 97 patients present in the ESME database. These reports were used as the gold standard for performance assessment, as ESME provides structured data against which the outputs of the C-LAB ® algorithm could be compared. Results C-LAB ® achieved over 80% agreement with human extractions (precision, recall, and F1-score) in structuring biomarker data from complex, unstructured pathology reports, despite dataset variability and optical character recognition errors. While the ESME database served as a benchmark, its reliance on single manual data entry without secondary review introduces potential inaccuracies, suggesting the observed performance reflects close alignment between human and algorithmic extractions rather than absolute accuracy. C-LAB ® demonstrates significant potential to reduce manual workload, centralize data, and enable scalable, real-time reporting. Conclusion AI technologies like C-LAB ® show significant potential in creating accessible and actionable digital factories from complex pathology data, aiding in the precision management of diseases such as breast cancer diagnostics and treatment.

Published
2025
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2. The role of donor hypertension and angiotensin II in the occurrence of early pancreas allograft thrombosis

Author

Christophe Masset, Julien Branchereau, Fanny Buron, Georges Karam, Maud Rabeyrin, Karine Renaudin, Florent Le Borgne, Lionel Badet, Xavier Matillon, Christophe Legendre, Denis Glotz, Corinne Antoine, Magali Giral, Jacques Dantal, Diego Cantarovich, DIVAT Consortium, Maria Brunet, Rémi Cahen, Ricardo Codas, Sameh Daoud, Valérie Dubois, Coralie Fournie, Arnaud Grégoire, Alice Koenig, Charlène Lévi, Emmanuel Morelon, Claire Pouteil-Noble, Thomas Rimmelé, Olivier Thaunat, Gilles Blancho, Agnès Chapelet, Clément Deltombe, Lucile Figueres, Raphael Gaisne, Claire Garandeau, Caroline Gourraud-Vercel, Maryvonne Hourmant, Clarisse Kerleau, Delphine Kervella, Aurélie Meurette, Simon Ville, Christine Kandell, Anne Moreau, Florent Delbos, Alexandre Walencik, Anne Devis, Lucile Amrouche, Dany Anglicheau, Olivier Aubert, Lynda Bererhi, Alexandre Loupy, Frank Martinez, Arnaud Méjean, Rébecca Sberro-Soussan, Anne Scemla, Marc-Olivier Timsit, Julien Zuber, Gillian Divard, and Carmen Lefaucheur

Subjects
body mass index (BMI), pre-procurement pancreas suitability score, pancreas transplantation, allograft thrombosis, high blood pressure, immunothrombosis, Immunologic diseases. Allergy, RC581-607
Abstract

BackgroundAbout 10–20% of pancreas allografts are still lost in the early postoperative period despite the identification of numerous detrimental risk factors that correlate with graft thrombosis.MethodsWe conducted a multicenter study including 899 pancreas transplant recipients between 2000 and 2018. Early pancreas failure due to complete thrombosis, long-term pancreas, kidney and patient survivals were analyzed and adjusted to donor, recipient and perioperative variables using a multivariate cause-specific Cox model stratified to transplant centers.ResultsPancreas from donors with history of hypertension (6.7%), as well as with high body mass index (BMI), were independently associated with an increased risk of pancreas failure within the first 30 post-operative days (respectively, HR= 2.57, 95% CI from 1.35 to 4.89 and HR= 1.11, 95% CI from 1.04 to 1.19). Interaction term between hypertension and BMI was negative. Donor hypertension also impacted long-term pancreas survival (HR= 1.88, 95% CI from 1.13 to 3.12). However, when pancreas survival was calculated after the postoperative day 30, donor hypertension was no longer a significant risk factor (HR= 1.22, 95% CI from 0.47 to 3.15). A lower pancreas survival was observed in patients receiving a pancreas from a hypertensive donor without RAAS (Renin Angiotensin Aldosterone System) blockers compared to others (50% vs 14%, p < 0.001). Pancreas survival was similar among non-hypertensive donors and hypertensive ones under RAAS blockers.ConclusionDonor hypertension was a significant and independent risk factor of pancreas failure. The well-known pathogenic role of renin-angiotensin-aldosterone system seems to be involved in the genesis of this immediate graft failure.

Published
2024
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3. Antibody-mediated allograft rejection is associated with an increase in peripheral differentiated CD28-CD8+ T cells – Analyses of a cohort of 1032 kidney transplant recipients

Author

Hoa Le Mai, Nicolas Degauque, Sabine Le Bot, Marie Rimbert, Karine Renaudin, Richard Danger, Florent Le Borgne, Clarisse Kerleau, Gaelle Tilly, Anaïs Vivet, Florent Delbos, Alexandre Walencik, Magali Giral, and Sophie Brouard

Subjects
Kidney transplantation, Rejection, Antibody, T lymphocyte, CD8, CD28, Medicine, Medicine (General), R5-920
Abstract

Summary: Background: CD28-CD8+ T cells represent a differentiated CD8+ T cell subset that is found to be increased in various conditions associated with chronic antigenic stimulation such as aging, chronic viral infections, autoimmune diseases, cancers, and allotransplantation. Methods: Using multivariate models, we analyzed a large cohort of 1032 kidney transplant patients in whom 1495 kidney graft biopsies were performed concomitant with a peripheral blood leukocyte phenotyping by flow cytometry. We investigated the association between the level of CD28-CD8+ T cells in the blood and the diagnosis of graft rejection according to the recent Banff classification of renal allograft pathology. Findings: We found that antibody-mediated rejection (ABMR) was associated with a significant increase in the percentage as well as the absolute number of CD28-CD8+ T cells in the peripheral blood of kidney transplant patients at the time of biopsy. The confounder-adjusted mean difference of log percentage and log absolute value between the ABMR group and the normal/subnormal histology group were 0.29 (p=0.0004) and 0.38 (p=0.0004), respectively. Moreover, we showed that CD28-CD8+ T cells from the patients diagnosed with ABMR responded more rigorously to TCR and FcγRIIIA (CD16) engagement compared to their CD28+ counterparts as evidenced by an increase in the expression of IFNγ, TNFα, and CD107a. Interpretation: Collectively, our data suggest that differentiated CD28-CD8+ T cells, with increased frequency, number, and function, may participate in the pathobiology of ABMR. Further studies are warranted to clarify the immunological role of this T cell subset in kidney graft rejection. Funding: Agence nationale de la recherche (France).

Published
2022
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4. G-computation and machine learning for estimating the causal effects of binary exposure statuses on binary outcomes

Author

Florent Le Borgne, Arthur Chatton, Maxime Léger, Rémi Lenain, and Yohann Foucher

Subjects
Medicine, Science
Abstract

Abstract In clinical research, there is a growing interest in the use of propensity score-based methods to estimate causal effects. G-computation is an alternative because of its high statistical power. Machine learning is also increasingly used because of its possible robustness to model misspecification. In this paper, we aimed to propose an approach that combines machine learning and G-computation when both the outcome and the exposure status are binary and is able to deal with small samples. We evaluated the performances of several methods, including penalized logistic regressions, a neural network, a support vector machine, boosted classification and regression trees, and a super learner through simulations. We proposed six different scenarios characterised by various sample sizes, numbers of covariates and relationships between covariates, exposure statuses, and outcomes. We have also illustrated the application of these methods, in which they were used to estimate the efficacy of barbiturates prescribed during the first 24 h of an episode of intracranial hypertension. In the context of GC, for estimating the individual outcome probabilities in two counterfactual worlds, we reported that the super learner tended to outperform the other approaches in terms of both bias and variance, especially for small sample sizes. The support vector machine performed well, but its mean bias was slightly higher than that of the super learner. In the investigated scenarios, G-computation associated with the super learner was a performant method for drawing causal inferences, even from small sample sizes.

Published
2021
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5. G-computation, propensity score-based methods, and targeted maximum likelihood estimator for causal inference with different covariates sets: a comparative simulation study

Author

Arthur Chatton, Florent Le Borgne, Clémence Leyrat, Florence Gillaizeau, Chloé Rousseau, Laetitia Barbin, David Laplaud, Maxime Léger, Bruno Giraudeau, and Yohann Foucher

Subjects
Medicine, Science
Abstract

Abstract Controlling for confounding bias is crucial in causal inference. Distinct methods are currently employed to mitigate the effects of confounding bias. Each requires the introduction of a set of covariates, which remains difficult to choose, especially regarding the different methods. We conduct a simulation study to compare the relative performance results obtained by using four different sets of covariates (those causing the outcome, those causing the treatment allocation, those causing both the outcome and the treatment allocation, and all the covariates) and four methods: g-computation, inverse probability of treatment weighting, full matching and targeted maximum likelihood estimator. Our simulations are in the context of a binary treatment, a binary outcome and baseline confounders. The simulations suggest that considering all the covariates causing the outcome led to the lowest bias and variance, particularly for g-computation. The consideration of all the covariates did not decrease the bias but significantly reduced the power. We apply these methods to two real-world examples that have clinical relevance, thereby illustrating the real-world importance of using these methods. We propose an R package RISCA to encourage the use of g-computation in causal inference.

Published
2020
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6. Impact of Late and Recurrent Acute Graft Pyelonephritis on Long-Term Kidney Graft Outcomes

Author

Margaux Pacaud, Luc Colas, Clarisse Kerleau, Florent Le Borgne, Magali Giral, Sophie Brouard, and Jacques Dantal

Subjects
acute pyelonephritis, kidney allograft, graft failure, patient survival, long-term outcome, Immunologic diseases. Allergy, RC581-607
Abstract

BackgroundWhile Urinary tract infections are the most common infections in kidney transplant recipients, the impact of late acute graft pyelonephritis (AGPN) on graft outcomes remains unknown. Our study was performed to more precisely evaluate the long-term impact of AGPN.MethodsWe included 9052 kidney and combined kidney-pancreas recipients who underwent transplantation between 2008 and 2018 from a French multicenter cohort. The relationships between AGPN and patient and graft survival were analyzed with a time-dependent multivariate Cox model.ResultsThe cumulative incidence of AGPN was 20.9%. A first episode of early AGPN is associated with a non-significant increase in the risk of graft failure (hazard ratio [HR], 1.27; 95% confidence interval [95% CI], 0.90 to 1.79). Though, cumulative number of AGPN episodes (HR = 1.51; 95% CI, 0.89 to 2.57 for two episodes and HR = 2.08; 95% CI, 1.17 to 3.69 for three or more episodes) is associated with an increased risk of graft failure. In contrast, when the first episode of AGPN occurred late (i.e., 6 months post transplantation), the risk of graft failure is significantly increased (HR = 2.25; 95% CI, 1.65 to 3.07), and this risk remains relatively stable with the recurrence of late AGPN episodes. The onset of late AGPN were also associated with a higher risk of patient death. ConclusionThis analysis shows that late AGPN and recurrent AGPN are both risk factors for a poor long-term graft outcome and mortality. Late AGPN should not be considered benign infections in post-transplantation follow-up.

Published
2022
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7. Early use of barbiturates is associated with increased mortality in traumatic brain injury patients from a propensity score-based analysis of a prospective cohort.

Author

Maxime Léger, Denis Frasca, Antoine Roquilly, Philippe Seguin, Raphaël Cinotti, Claire Dahyot-Fizelier, Karim Asehnoune, Florent Le Borgne, Thomas Gaillard, Yohann Foucher, Sigismond Lasocki, and for AtlanRéa group

Subjects
Medicine, Science
Abstract

Barbiturates are proposed as a second/third line treatment for intracranial hypertension in traumatic brain injury (TBI) patients, but the literature remains uncertain regarding their benefit/risk balance. We aimed to evaluate the impact of barbiturates therapy in TBI patients with early intracranial hypertension on the intensive care unit (ICU) survival, the occurrence of ventilator-associated pneumonia (VAP), and the patient's functional status at three months. We used the French AtlanREA prospective cohort of trauma patients. Using a propensity score-based methodology (inverse probability of treatment weighting), we compared patients having received barbiturates within the first 24 hours of admission (barbiturates group) and those who did not (control group). We used cause-specific Cox models for ICU survival and risk of VAP, and logistic regression for the 3-month Glasgow Outcome Scale (GOS) evaluation. Among the 1396 patients with severe trauma, 383 had intracranial hypertension on admission and were analyzed. Among them, 96 (25.1%) received barbiturates. The early use of barbiturates was significantly associated with increased ICU mortality (HR = 1.85, 95%CI 1.03-3.33). However, barbiturates treatment was not significantly associated with VAP (HR = 1.02, 95%CI 0.75-1.41) or 3-month GOS (OR = 1.67, 95%CI 0.84-3.33). Regarding the absence of relevant clinical trials, our results suggest that each early prescription of barbiturates requires a careful assessment of the benefit/risk ratio.

Published
2022
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9. Impact of the Kidney Transplantation Moratorium in France Because of the COVID-19 Pandemic: A Cohort-based Study

Author

Vincent Bonnemains, Florent Le Borgne, Emile Savoye, Camille Legeai, Myriam Pastural, Sahar Bayat-Makoei, Rémi Lenain, Stéphanie Ragot, Karen Leffondré, Cécile Couchoud, Yohann Foucher, MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Nantes Université - UFR des Sciences Pharmaceutiques et Biologiques (Nantes Univ - UFR Pharmacie), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Agence de la biomédecine [Saint-Denis la Plaine], École des Hautes Études en Santé Publique [EHESP] (EHESP), Centre de Recherches sur l'Action Politique en Europe (ARENES), Université de Rennes (UR)-Institut d'Études Politiques [IEP] - Rennes-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Centre National de la Recherche Scientifique (CNRS), Recherche sur les services et le management en santé (RSMS), Université de Rennes (UR)-École des Hautes Études en Santé Publique [EHESP] (EHESP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), CIC - Poitiers, Université de Poitiers-Centre hospitalier universitaire de Poitiers (CHU Poitiers)-Direction Générale de l'Organisation des Soins (DGOS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), This work was supported by a public grant overseen by the French National Research Agency (ANR-20-COV8-0002-01)., and ANR-20-COV8-0002,KiT-COVID,Accès à la liste d'attente active pour une transplantation rénale en cas de rebond de COVID-19: études de simulations pour aider aux futures recommandations(2020)

Subjects
Moratorium, History, Transplantation, Polymers and Plastics, Waiting Lists, COVID-19, COVID-19 pandemic, Kidney, Kidney Transplantation, Industrial and Manufacturing Engineering, Renal Dialysis, Humans, Kidney Failure, Chronic, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, France, Business and International Management, Pandemics
Abstract

International audience; Background: The COVID-19 pandemic has resulted in worldwide kidney transplantation (KT) moratoriums. The impacts of these moratoriums on the life expectancy of KT candidates remain unclear.Methods: We simulated the evolution of several French candidate populations for KT using a multistate semi-Markovian approach and according to moratorium durations ranging from 0 to 24 mo. The transition rates were modeled from the 63 927 French patients who began dialysis or were registered on the waiting list for KT between 2011 and 2019.Results: Among the 8350 patients active on the waiting list at the time of the French KT moratorium decided on March 16, 2020, for 2.5 mo, we predicted 4.0 additional months (confidence interval [CI], 2.8-5.0) on the waiting list and 42 additional deaths (CI, -70 to 150) up to March 16, 2030, compared with the scenario without moratorium. In this population, we reported a significant impact for a 9-mo moratorium duration: 135 attributable deaths (CI, 31-257) up to March 16, 2030. Patients who became active on the list after March 2020 were less impacted; there was a significant impact for an 18-mo moratorium (175 additional deaths [CI, 21-359]) in the 10 862 prevalent end-stage renal disease patients on March 16, 2020 and for a 24-mo moratorium (189 additional deaths [CI, 10-367]) in the 16 355 incident end-stage renal disease patients after this date.Conclusion: The temporary moratorium of KT during a COVID-19 peak represents a sustainable decision to free up hospitals' resources if the moratorium does not exceed a prolonged period.

Published
2022
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10. Observations on improving COVID-19 vaccination responses in kidney transplant recipients: heterologous vaccination and immunosuppression modulation

Author

Christophe Masset, Simon Ville, Claire Garandeau, Florent Le Borgne, Thibaut Letellier, Diego Cantarovich, Aurélie Meurette, Cécile Guillot-Gueguen, Maxime Bentoumi-Loaec, Magali Giral, Jacques Dantal, Gilles Blancho, Service de Néphrologie et Immunologie Clinique [CHU de Nantes], Centre hospitalier universitaire de Nantes (CHU Nantes), Institut de Transplantation et de Recherche en Transplantation [CHU Nantes] (ITERT), Centre de Recherche en Transplantation et Immunologie - Center for Research in Transplantation and Translational Immunology (U1064 Inserm - CR2TI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Nantes Université - UFR de Médecine et des Techniques Médicales (Nantes Univ - UFR MEDECINE), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Nantes Université - UFR des Sciences Pharmaceutiques et Biologiques (Nantes Université - UFR Pharmacie), IDBC/A2com [Pace, France], and Le Bihan, Sylvie

Subjects
[SDV] Life Sciences [q-bio], Immunosuppression Therapy, COVID-19 Vaccines, Nephrology, SARS-CoV-2, [SDV]Life Sciences [q-bio], Vaccination, COVID-19, Humans, Letter to the Editor, Kidney Transplantation, ComputingMilieux_MISCELLANEOUS, Transplant Recipients
Abstract

International audience; No abstract available

Published
2021
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11. Causal inference in case of near-violation of positivity: comparison of methods

Author

Maxime Léger, Arthur Chatton, Florent Le Borgne, Romain Pirracchio, Sigismond Lasocki, and Yohann Foucher

Subjects
Statistics and Probability, General Medicine, Statistics, Probability and Uncertainty
Abstract

In causal studies, the near-violation of the positivity may occur by chance, because of sample-to-sample fluctuation despite the theoretical veracity of the positivity assumption in the population. It may mostly happen when the exposure prevalence is low or when the sample size is small. We aimed to compare the robustness of g-computation (GC), inverse probability weighting (IPW), truncated IPW, targeted maximum likelihood estimation (TMLE), and truncated TMLE in this situation, using simulations and one real application. We also tested different extrapolation situations for the sub-group with a positivity violation. The results illustrated that the near-violation of the positivity impacted all methods. We demonstrated the robustness of GC and TMLE-based methods. Truncation helped in limiting the bias in near-violation situations, but at the cost of bias in normal conditions. The application illustrated the variability of the results between the methods and the importance of choosing the most appropriate one. In conclusion, compared to propensity score-based methods, methods based on outcome regression should be preferred when suspecting near-violation of the positivity assumption.

Published
2021

12. Early use of barbiturates is associated with increased mortality in traumatic brain injury patients from a propensity score-based analysis of a prospective cohort

Author

Maxime, Léger, Denis, Frasca, Antoine, Roquilly, Philippe, Seguin, Raphaël, Cinotti, Claire, Dahyot-Fizelier, Karim, Asehnoune, Florent, Le Borgne, Thomas, Gaillard, Yohann, Foucher, Sigismond, Lasocki, Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Nantes Université - UFR des Sciences Pharmaceutiques et Biologiques (Nantes Université - UFR Pharmacie), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Centre hospitalier universitaire de Poitiers (CHU Poitiers), Centre hospitalier universitaire de Nantes (CHU Nantes), CHU Pontchaillou [Rennes], Pharmacologie des anti-infectieux et antibiorésistance (PHAR2), Université de Poitiers-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Poitiers - Faculté de Médecine et de Pharmacie, Université de Poitiers, IDBC/A2com [Pace, France], and Chauzy, Alexia

Subjects
[SDV] Life Sciences [q-bio], [SDV.SP] Life Sciences [q-bio]/Pharmaceutical sciences, Multidisciplinary, [SDV]Life Sciences [q-bio], Barbiturates, Brain Injuries, Traumatic, Humans, Pneumonia, Ventilator-Associated, Glasgow Coma Scale, Prospective Studies, [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences, Intracranial Hypertension, Propensity Score
Abstract

International audience; Barbiturates are proposed as a second/third line treatment for intracranial hypertension in traumatic brain injury (TBI) patients, but the literature remains uncertain regarding their benefit/risk balance. We aimed to evaluate the impact of barbiturates therapy in TBI patients with early intracranial hypertension on the intensive care unit (ICU) survival, the occurrence of ventilator-associated pneumonia (VAP), and the patient’s functional status at three months. We used the French AtlanREA prospective cohort of trauma patients. Using a propensity score-based methodology (inverse probability of treatment weighting), we compared patients having received barbiturates within the first 24 hours of admission (barbiturates group) and those who did not (control group). We used cause-specific Cox models for ICU survival and risk of VAP, and logistic regression for the 3-month Glasgow Outcome Scale (GOS) evaluation. Among the 1396 patients with severe trauma, 383 had intracranial hypertension on admission and were analyzed. Among them, 96 (25.1%) received barbiturates. The early use of barbiturates was significantly associated with increased ICU mortality (HR = 1.85, 95%CI 1.03–3.33). However, barbiturates treatment was not significantly associated with VAP (HR = 1.02, 95%CI 0.75–1.41) or 3-month GOS (OR = 1.67, 95%CI 0.84–3.33). Regarding the absence of relevant clinical trials, our results suggest that each early prescription of barbiturates requires a careful assessment of the benefit/risk ratio.

Published
2020
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13. Covariates adjustment questioned conclusions of predictive analyses: an illustration with the Kidney Donor Risk Index

Author

Etienne Dantan, Yohann Foucher, Magali Giral, Florent Le Borgne, Anne-Hélène Querard, Angelina Dion, MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Université de Nantes (UN)-Université de Nantes (UN), IDBC/A2com [Pace, France], Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Institut de transplantation urologie-néphrologie (ITUN), Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), Réseau CENTAURE, CHD Vendée - Hôpital Les Oudairies [La Roche sur Yon], Centre hospitalier universitaire de Nantes (CHU Nantes), Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Centre Hospitalier Départemental - Hôpital de La Roche-sur-Yon (CHD Vendée), and Dantan, Etienne

Subjects
Adult, Male, medicine.medical_specialty, Graft failure, Epidemiology, Risk Assessment, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Risk index, Mean Survival Time, Internal medicine, Covariate, medicine, Humans, 030212 general & internal medicine, Registries, Kidney transplantation, ComputingMilieux_MISCELLANEOUS, Aged, Kidney, [STAT.ME] Statistics [stat]/Methodology [stat.ME], business.industry, Graft Survival, Reproducibility of Results, Middle Aged, medicine.disease, Kidney Transplantation, Confidence interval, Tissue Donors, medicine.anatomical_structure, ROC Curve, Graft survival, Female, France, business, [STAT.ME]Statistics [stat]/Methodology [stat.ME], 030217 neurology & neurosurgery
Abstract

Objectives We aimed to illustrate that considering covariates can lead to meaningful interpretation of the discriminative capacities of a prognostic marker. For this, we evaluated the ability of the Kidney Donor Risk Index (KDRI) to discriminate kidney graft failure risk. Study design and setting From 4114 French patients, we estimated the adjusted area under the time-dependent ROC curve by standardizing the marker and weighting the observations. By weighting the contributions, we also studied the impact of KDRI-based transplantations on the patient and graft survival. Results The covariate-adjusted AUC varied from 55% (95% confidence interval [CI]: 51–60%) for a prognostic up to 1 year post-transplantation to 56% (95% CI: 52–59%) up to 7 years. The Restricted Mean Survival Time (RMST) was 6.44 years for high-quality graft recipients (95% CI: 6.30–6.56) and would have been 6.31 years (95% CI: 6.13–6.46) if they had medium-quality transplants. The RMST was 5.10 years for low-quality graft recipients (95% CI: 4.90–5.31) and would have been 5.52 years (95% CI: 5.17–5.83) if they had medium-quality transplants. Conclusion We demonstrated that the KDRI discriminative capacities were mainly explained by the recipient characteristics. We also showed that counterfactual estimations, often used in causal studies, are also interesting in predictive studies, especially regarding the new available methods.

Published
2020
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14. G-computation and doubly robust standardisation for continuous-time data: a comparison with inverse probability weighting

Author

Arthur Chatton, Yohann Foucher, Florent Le Borgne, and Clemence Leyrat

Subjects
Statistics and Probability, FOS: Computer and information sciences, Models, Statistical, Epidemiology, Computer science, Inverse probability weighting, Estimator, Context (language use), Time data, Reference Standards, Doubly robust, Methodology (stat.ME), Specification, Health Information Management, Causal inference, 62P10, G computation, Computer Simulation, Algorithm, Statistics - Methodology, Probability
Abstract

In time-to-event settings, g-computation and doubly robust estimators are based on discrete-time data. However, many biological processes are evolving continuously over time. In this paper, we extend the g-computation and the doubly robust standardisation procedures to a continuous-time context. We compare their performance to the well-known inverse-probability-weighting (IPW) estimator for the estimation of the hazard ratio and restricted mean survival times difference, using a simulation study. Under a correct model specification, all methods are unbiased, but g-computation and the doubly robust standardisation are more efficient than inverse probability weighting. We also analyse two real-world datasets to illustrate the practical implementation of these approaches. We have updated the R package RISCA to facilitate the use of these methods and their dissemination., Accepted for publication in Statistical Methods in Medical Research, 16 pages, including 4 figures and 2 tables

Published
2020

15. G-computation, propensity score-based methods, and targeted maximum likelihood estimator for causal inference with different covariates sets: a comparative simulation study

Author

Florence Gillaizeau, Clemence Leyrat, Chloé Rousseau, Laetitia Barbin, Florent Le Borgne, Yohann Foucher, Arthur Chatton, David Laplaud, Bruno Giraudeau, Maxime Léger, Jonchère, Laurent, Recherche en Informatique et en Statistique pour l'Analyse de Cohortes - - RISCA2016 - ANR-16-LCV1-0003 - LABCOM - VALID, MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Université de Nantes (UN)-Université de Nantes (UN), London School of Hygiene and Tropical Medicine (LSHTM), Centre d'Investigation Clinique [Rennes] (CIC), Université de Rennes (UR)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d’Investigation Clinique de Nantes (CIC Nantes), Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre hospitalier universitaire de Nantes (CHU Nantes), Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Centre Hospitalier Universitaire d'Angers (CHU Angers), PRES Université Nantes Angers Le Mans (UNAM), ANR-16-LCV1-0003-01, Agence Nationale de la Recherche, ANR-16-LCV1-0003,RISCA,Recherche en Informatique et en Statistique pour l'Analyse de Cohortes(2016), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-Institut National de la Santé et de la Recherche Médicale (INSERM), and Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques

Subjects
Matching (statistics), Computer science, Epidemiology, Science, Context (language use), 01 natural sciences, Article, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Statistics, Covariate, 030212 general & internal medicine, 0101 mathematics, Multidisciplinary, [STAT.ME] Statistics [stat]/Methodology [stat.ME], Confounding, Variance (accounting), Outcome (probability), Risk factors, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Causal inference, Propensity score matching, Medicine, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [STAT.ME]Statistics [stat]/Methodology [stat.ME]
Abstract

Controlling for confounding bias is crucial in causal inference. Distinct methods are currently employed to mitigate the effects of confounding bias. Each requires the introduction of a set of covariates, which remains difficult to choose, especially regarding the different methods. We conduct a simulation study to compare the relative performance results obtained by using four different sets of covariates (those causing the outcome, those causing the treatment allocation, those causing both the outcome and the treatment allocation, and all the covariates) and four methods: g-computation, inverse probability of treatment weighting, full matching and targeted maximum likelihood estimator. Our simulations are in the context of a binary treatment, a binary outcome and baseline confounders. The simulations suggest that considering all the covariates causing the outcome led to the lowest bias and variance, particularly for g-computation. The consideration of all the covariates did not decrease the bias but significantly reduced the power. We apply these methods to two real-world examples that have clinical relevance, thereby illustrating the real-world importance of using these methods. We propose an R package RISCA to encourage the use of g-computation in causal inference.

Published
2020
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16. Lack of impact of pre-emptive deceased-donor kidney transplantation on graft outcomes: a propensity score-based study

Author

Magali Giral, Marc Ladrière, Sophie Girerd, Christophe Legendre, Laetitia Albano, Fanny Buron, Denis Glotz, Valérie Garrigue, Florent Le Borgne, Emmanuel Morelon, Carmen Lefaucheur, Yohann Foucher, Georges Mourad, Elisabeth Cassuto, MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Université de Nantes (UN)-Université de Nantes (UN), Centre hospitalier universitaire de Nantes (CHU Nantes), IDBC/A2com [Pace, France], Réseau CENTAURE, Département de Néphrologie [CHU Necker], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Hospices Civils de Lyon (HCL), Service de Néphrologie [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), Service de transplantation rénale [CHRU Nancy], Centre Hospitalier Universitaire de Nancy (CHU Nancy), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Cellules Souches, Plasticité Cellulaire, Médecine Régénératrice et Immunothérapies (IRMB), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Ecotaxie, microenvironnement et développement lymphocytaire (EMily (UMR_S_1160 / U1160)), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hopital Saint-Louis [AP-HP] (AP-HP), Hôpital Pasteur [Nice] (CHU), Centre d’Investigation Clinique de Nantes (CIC Nantes), Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre hospitalier universitaire de Nantes (CHU Nantes), Immunoregulation And Immunointervention in Transplantation and Autoimmunity (Team 4 - U1064 Inserm - CRTI), Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Le Bihan, Sylvie, Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Kidney Transplant Center [CHU Necker], CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Université Paris Descartes - Paris 5 (UPD5), Department of Nephrology, Transplantation and Clinic Immunology [Hospices civils de Lyon], Hospices Civils de Lyon (HCL)-Hôpital Edouard Herriot [CHU - HCL], Service de Néphrologie, Dialyse et Transplantation (Hôpital Lapeyronie [Montpellier] CHU), Hôpital Lapeyronie [Montpellier] (CHU), Paris Translational Research Center for Organ Transplantation & Department of Nephrology and Transplantation, Université Paris Diderot - Paris 7 (UPD7)-Hopital Saint-Louis [AP-HP] (AP-HP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Service de néphrologie et transplantation rénale [Nice], and Université Paris Descartes - Paris 5 (UPD5)-Sorbonne Université (SU)-CHU Necker - Enfants Malades [AP-HP]

Subjects
Male, medicine.medical_specialty, Time Factors, Waiting Lists, medicine.medical_treatment, 030232 urology & nephrology, 030204 cardiovascular system & hematology, patient and graft survival, [SDV.MHEP.UN]Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology, 03 medical and health sciences, 0302 clinical medicine, Renal Dialysis, Risk Factors, Internal medicine, medicine, Humans, Renal replacement therapy, Prospective Studies, causal inference, Propensity Score, Dialysis, Kidney transplantation, Transplantation, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, business.industry, Graft Survival, pre-emptive kidney transplantation, Middle Aged, medicine.disease, Kidney Transplantation, [SDV.MHEP.UN] Life Sciences [q-bio]/Human health and pathology/Urology and Nephrology, Tissue Donors, 3. Good health, Treatment Outcome, Nephrology, Cohort, Propensity score matching, Kidney Failure, Chronic, dialysis, Observational study, Female, observational study, Hemodialysis, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Follow-Up Studies
Abstract

International audience; BACKGROUND: A significant number of studies have compared graft outcomes between patients with Pre-emptive Kidney Transplantation (PreKT) and patients on Dialysis before their Kidney Transplantation (DiaKT). These studies have suffered from the limitation that the DiaKT group is composed of all the dialysed patients, including those placed on a waiting list at the time of their first dialysis session. This seriously questions the comparability of these patients with those placed on the waiting list a long time before the need for renal replacement therapy. The aim of this study was to precisely evaluate the causal effect of PreKT from deceased donors.METHODS: Data were extracted from the multicentric French DIVAT (Données Informatisées et VAlidées en Transplantation) cohort. The DiaKT group was composed of patients placed on the waiting list with an initial intention of pre-emptive transplantation. Cause-specific Cox models with propensity scores (inverse probability weighting) were used to study the patient and graft outcomes.RESULTS: Among the 1138 included patients, 554 patients were in the PreKT group. The outcomes of the PreKT group were similar compared with the DiaKT group. In particular, the life expectancy with a functioning graft was 8.51 years [95% confidence interval (CI) 8.20-8.81] for the PreKT recipients versus 8.49 years (95% CI 8.15-8.84) for the DiaKT recipients.CONCLUSIONS: Our results challenge the utility of PreKTs from deceased donors, especially with regard to the consequential increase in the waiting list.

Published
2019
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17. Inverse probability weighting to control confounding in an illness-death model for interval-censored data

Author

Yohann Foucher, Etienne Dantan, Bruno Giraudeau, Florence Gillaizeau, Thomas Senage, Florent Le Borgne, Thierry Le Tourneau, Raphaël Porcher, Karen Leffondré, Jean-Christian Roussel, Biostatistique, Pharmacoépidémiologie et Mesures Subjectives en Santé, PRES Université Nantes Angers Le Mans (UNAM), Institut de transplantation urologie-néphrologie (ITUN), Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier de l'Université de Montréal (CHUM), Université de Montréal (UdeM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA), Centre d’Investigation Clinique [Tours] CIC 1415 (CIC ), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Hôpital Bretonneau-Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM), MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC), CIC Tours, Hôpital Bretonneau-Université de Tours-Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Institut National de la Santé et de la Recherche Médicale (INSERM), Biostatistique, Recherche Clinique et Mesures Subjectives en Santé, Université de Nantes (UN), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Hôpital Bretonneau-Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, and Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Statistics and Probability, Biometry, Epidemiology, Computer science, [SDV]Life Sciences [q-bio], Population, Interval (mathematics), 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, multistate, 0302 clinical medicine, Risk Factors, Statistics, Humans, Computer Simulation, 030212 general & internal medicine, confounding factors, 0101 mathematics, Mortality, education, Survival analysis, propensity score, Probability, education.field_of_study, Inverse probability weighting, Multivariable calculus, Confounding, Confounding Factors, Epidemiologic, Survival Analysis, Markov Chains, Heart Valve Prosthesis, Propensity score matching, Chronic Disease, Disease Progression, Regression Analysis, Biostatistics, semi-Markov, inverse probability weighting
Abstract

International audience; Multistate models with interval-censored data, such as the illness-death model, are still not used to any considerable extent in medical research regardless of the significant literature demonstrating their advantages compared to usual survival models. Possible explanations are their uncommon availability in classical statistical software or, when they are available, by the limitations related to multivariable modelling to take confounding into consideration. In this paper, we propose a strategy based on propensity scores that allows population causal effects to be estimated: the inverse probability weighting in the illness semi-Markov model with interval-censored data. Using simulated data, we validated the performances of the proposed approach. We also illustrated the usefulness of the method by an application aiming to evaluate the relationship between the inadequate size of an aortic bioprosthesis and its degeneration or/and patient death. We have updated the R package multistate to facilitate the future use of this method.

Published
2018
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18. Is pre-transplant sensitization against angiotensin II type 1 receptor still a risk factor of graft and patient outcome in kidney transplantation in the anti-HLA Luminex era? A retrospective study

Author

Florent Le Borgne, Magali Giral, Yohann Foucher, Marie Rimbert, Daniel Anglicheau, Clement Deltombe, Emmanuel Morelon, Florence Gillaizeau, Pierrick Guerif, Stéphanie Malard-Castagnet, Katy Trébern-Launay, Institut de transplantation urologie-néphrologie (ITUN), Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), MethodS in Patients-centered outcomes and HEalth ResEarch (SPHERE), Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Biostatistique, Recherche Clinique et Mesures Subjectives en Santé, Université de Nantes (UN), LabEx TRANSPLANTEX [CHU de Nantes], Thematic Research and Care Network RTRS 'Centaure' [Strasbourg], Université de Strasbourg (UNISTRA), Département de transplantation rénale [Hôpital Necker], CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Département de transplantation et d'immunologie clinique [Hôpital Edouard Herriot, HCL], Hôpital Edouard Herriot [CHU - HCL], Hospices Civils de Lyon (HCL)-Hospices Civils de Lyon (HCL), Centre d'Immuno-Monitorage Nantes Atlantique [CHU Nantes] (Plate-forme CIMNA - SFR Santé), Centre hospitalier universitaire de Nantes (CHU Nantes), CIC biothérapies CBT 0503 [Nantes], Hôtel-Dieu de Nantes-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre hospitalier universitaire de Nantes (CHU Nantes), Etablissement Français du Sang [Nantes], One lambda., Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, and Le Bihan, Sylvie

Subjects
Adult, Graft Rejection, Male, medicine.medical_specialty, 030232 urology & nephrology, 030230 surgery, Gastroenterology, acute rejection, Receptor, Angiotensin, Type 1, Angiotensin type 1 receptor antibodies, 03 medical and health sciences, 0302 clinical medicine, HLA Antigens, Internal medicine, medicine, Humans, Risk factor, graft outcome, Kidney transplantation, Aged, Retrospective Studies, Transplantation, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, business.industry, Proportional hazards model, Retrospective cohort study, Middle Aged, medicine.disease, Kidney Transplantation, Angiotensin II, Tacrolimus, 3. Good health, Surgery, Cohort, Female, Kidney Diseases, business, pretransplant, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

International audience; We aimed to assess the correlation of anti-angiotensin II type 1 receptor antibodies (anti-AT1R-Abs) before transplantation on a multicentric cohort of kidney transplant recipients (2008-2012), under tacrolimus and mycophenolate mofetil (MMF), screened by Luminex technology for anti-HLA immunization. Anti-AT1R antibody levels were measured by ELISA in pretransplantation sera of 940 kidney recipients from three French centers of the DIVAT cohort. Multivariable Cox models estimated the association between pretransplant anti-angiotensin II type 1 receptor antibodies and time to acute rejection episodes (ARE) or time to graft failure. Within our cohort, 387 patients (41.2%) had pretransplant AT1R-Abs higher than 10 U/ml and only 8% (72/970) greater than 17 U/ml. The cumulative probability of clinically relevant (cr)-ARE was 22.5% at 1 year post-trans-plantation [95% CI (19.9-25.4%)]. The cumulative probability of graft failure and patient death were 10.6% [95% CI (8.4-13.3%)] and 5.7% [95% CI (4.0-8.1%)] at 3 years post-transplantation, respectively. Multivariate Cox models indicated that pretransplant anti-AT1R antibody levels higher than 10 U/ml were not significantly independently associated with higher risks of acute rejection episodes [HR = 1.04, 95% CI (0.80-1.35)] nor with risk of graft failure [HR = 0.86, 95% CI (0.56-1.33)]. Our study did not confirm an association between pretransplant anti-AT1R antibody levels and kidney transplant outcomes.

Published
2017
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19. Standardized and weighted time-dependent receiver operating characteristic curves to evaluate the intrinsic prognostic capacities of a marker by taking into account confounding factors

Author

Florence Gillaizeau, Christophe Combescure, Magali Giral, Marion Chapal, Yohann Foucher, Florent Le Borgne, Bruno Giraudeau, Le Bihan, Sylvie, Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), and Université de Nantes (UN)-Université de Nantes (UN)

Subjects
Statistics and Probability, Epidemiology, Computer science, 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Health Information Management, Statistics, 030212 general & internal medicine, confounding factors, receiver operating characteristic curve, 0101 mathematics, propensity score, Event (probability theory), [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Receiver operating characteristic, business.industry, Inverse probability weighting, Confounding, Pattern recognition, Confounding Factors, Epidemiologic, Prognosis, Kidney Transplantation, ROC Curve, Creatinine, Prognostic capacities, Propensity score matching, Artificial intelligence, Primary Graft Dysfunction, time-to-event data, business, Algorithms, Biomarkers, inverse probability weighting, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

International audience; Time-dependent receiver operating characteristic curves allow to evaluate the capacity of a marker to discriminate between subjects who experience the event up to a given prognostic time from those who are free of this event. In this article, we propose an inverse probability weighting estimator of a standardized and weighted time-dependent receiver operating characteristic curve. This estimator provides a measure of the prognostic capacities by taking into account potential confounding factors. We illustrate the robustness of the estimator by a simulation-based study and its usefulness by two applications in kidney transplantation.

Published
2017
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20. Comparisons of the performance of different statistical tests for time-to-event analysis with confounding factors: practical illustrations in kidney transplantation

Author

Anne Héléne Querard, Bruno Giraudeau, Yohann Foucher, Magali Giral, Florent Le Borgne, Le Bihan, Sylvie, Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Biostatistique, Pharmacoépidémiologie et Mesures Subjectives en Santé, PRES Université Nantes Angers Le Mans (UNAM), Institut de transplantation urologie-néphrologie (ITUN), Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), IDBC/A2com [Pace, France], Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d’Investigation Clinique [Tours] CIC 1415 (CIC ), Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Hôpital Bretonneau-Université de Tours (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Francois Rabelais [Tours], PRES Centre-Val de Loire Université, Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Service de Néphrologie, dialyse, transplantation [CHD Vendée] (Site de La Roche sur Yon), Centre Hospitalier Départemental - Hôpital de La Roche-sur-Yon (CHD Vendée), Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA), Centre Hospitalier Départemental Vendée, Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC), CIC Tours, Hôpital Bretonneau-Université de Tours-Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Régional Universitaire de Tours (CHRU TOURS), and Centre Hospitalier Régional Universitaire de Tours (CHRU Tours)-Hôpital Bretonneau-Université de Tours-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Statistics and Probability, Time Factors, Epidemiology, adjusted Kaplan-Meier estimator, Biostatistics, Wald test, 01 natural sciences, 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Statistics, Econometrics, Humans, Medicine, Computer Simulation, 030212 general & internal medicine, 0101 mathematics, propensity score, Proportional Hazards Models, Statistical hypothesis testing, Models, Statistical, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Proportional hazards model, business.industry, Inverse probability weighting, Confounding, Confounding Factors, Epidemiologic, Kidney Transplantation, simulation study, Tissue Donors, survival data, Propensity score matching, adjusted log-rank test, Observational study, business, inverse probability weighting, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Type I and type II errors
Abstract

International audience; Confounding factors are commonly encountered in observational studies. Several confounder-adjusted tests to compare survival between differently exposed subjects were proposed. However, only few studies have compared their performances regarding type I error rates, and no study exists evaluating their type II error rates. In this paper, we performed a comparative simulation study based on two different applications in kidney transplantation research. Our results showed that the propensity score-based inverse probability weighting (IPW) log-rank test proposed by Xie and Liu (2005) can be recommended as a first descriptive approach as it provides adjusted survival curves and has acceptable type I and II error rates. Even better performance was observed for the Wald test of the parameter corresponding to the exposure variable in a multivariable-adjusted Cox model. This last result is of primary interest regarding the exponentially increasing use of propensity score-based methods in the literature.

Published
2016
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21. A useful scoring system for the prediction and management of delayed graft function following kidney transplantation from cadaveric donors

Author

Georges Mourad, Fanny Buron, Lionel Rostaing, Florent Le Borgne, Michèle Kessler, Magali Giral, Valérie Garrigue, Christophe Legendre, Emmanuel Morelon, Pascal Daguin, Katy Launay, Jean-Paul Soulillou, Henri Kreis, Marion Chapal, Yohann Foucher, Lucile Offredo, Marc Ladrière, Nassim Kamar, Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Réseau CENTAURE [Nantes], Université de Nantes (UN)-Institut de Transplantation et de Recherche en Transplantation (ITUN - Institut Transplantation Urologie Néphroplogie*)-Centre hospitalier universitaire de Nantes (CHU Nantes), Institut de transplantation urologie-néphrologie (ITUN), Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), LabEx TRANSPLANTEX [CHU de Nantes], Biostatistique, Pharmacoépidémiologie et Mesures Subjectives en Santé, PRES Université Nantes Angers Le Mans (UNAM), Service Néphrologie et transplantation rénale Adultes [CHU Necker], CHU Necker - Enfants Malades [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Université Paris Descartes - Paris 5 (UPD5), Université Sorbonne Paris Cité (USPC), Service de Néphrologie, Dialyse et Transplantation (Hôpital Lapeyronie [Montpellier] CHU), Hôpital Lapeyronie [Montpellier] (CHU), Service de Néphrologie [Lyon], Hospices Civils de Lyon (HCL)-Centre Hospitalier Lyon Sud [CHU - HCL] (CHLS), Hospices Civils de Lyon (HCL), Département de Néphrologie et Transplantation d'organes, Hôpital de Rangueil, CHU Toulouse [Toulouse]-CHU Toulouse [Toulouse], Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées, Service de transplantation rénale [CHRU Nancy], Centre Hospitalier Universitaire de Nancy (CHU Nancy), Roche Laboratory., ANR-11-JSV1-0008,CSM (Composite Surrogate Marker),Construction d'un marqueur composite de substitution de la survie à long terme : application à la transplantation rénale(2011), Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes)-Institut de Transplantation et de Recherche en Transplantation (ITUN - Institut Transplantation Urologie Néphroplogie*), Département de Néphrologie et Transplantation d'organes [CHU Toulouse], Pôle Urologie - Néphrologie - Dialyse - Transplantations - Brûlés - Chirurgie plastique - Explorations fonctionnelles et physiologiques [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Le Bihan, Sylvie, and Jeunes Chercheuses et Jeunes Chercheurs - Construction d'un marqueur composite de substitution de la survie à long terme : application à la transplantation rénale - - CSM (Composite Surrogate Marker)2011 - ANR-11-JSV1-0008 - JCJC - VALID

Subjects
Male, 030232 urology & nephrology, 030230 surgery, Body Mass Index, Cohort Studies, chemistry.chemical_compound, 0302 clinical medicine, risk factors, Prospective Studies, Young adult, Child, Prospective cohort study, Kidney transplantation, Aged, 80 and over, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Cold Ischemia, Age Factors, Induction Chemotherapy, Middle Aged, Mobile Applications, Tissue Donors, 3. Good health, Nephrology, statistics, Area Under Curve, Child, Preschool, Creatinine, Predictive value of tests, Female, Smartphone, Immunosuppressive Agents, Cohort study, Adult, medicine.medical_specialty, Adolescent, kidney transplantation, Decision Support Techniques, Young Adult, 03 medical and health sciences, delayed graft function, Predictive Value of Tests, Cadaver, medicine, Humans, Aged, Antilymphocyte Serum, business.industry, transplant outcomes, Infant, medicine.disease, Surgery, Transplantation, ROC Curve, chemistry, business, Complication, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

International audience; Delayed graft function (DGF) is a common complication in kidney transplantation and is known to be correlated with short-and long-term graft outcomes. Here we explored the possibility of developing a simple tool that could predict with good confidence the occurrence of DGF and could be helpful in current clinical practice. We built a score, tentatively called DGFS, from a French multicenter and prospective cohort of 1844 adult recipients of deceased donor kidneys collected since 2007, and computerized in the Données Informatisées et VAlidées en Transplantation databank. Only five explicative variables (cold ischemia time, donor age, donor serum creatinine, recipient body mass index, and induction therapy) contributed significantly to the DGF prediction. These were associated with a good predictive capacity (area under the ROC curve at 0.73). The DGFS calculation is facilitated by an application available on smartphones, tablets, or computers at www.divat.fr/en/online-calculators/ dgfs. The DGFS should allow the simple classification of patients according to their DGF risk at the time of transplantation, and thus allow tailored-specific management or therapeutic strategies.

Published
2014
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22. Increased soluble Flt-1 correlates with delayed graft function and early loss of peritubular capillaries in the kidney graft

Author

Anne Moreau, Fadi Fakhouri, Maryvonne Hourmant, Emanuelle Meffray, Florent Le Borgne, Yohann Foucher, Marion Chapal, Mélanie Néel, Odette Carceles, Magalie Giral, Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Institut de transplantation urologie-néphrologie (ITUN), Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), Biostatistique, Recherche Clinique et Mesures Subjectives en Santé, Université de Nantes (UN), Département de Pathologie [CHU Nantes], Centre hospitalier universitaire de Nantes (CHU Nantes), An ATIP-AVENIR funding from INSERM., and Le Bihan, Sylvie

Subjects
Adult, Male, medicine.medical_specialty, Vascular repair, 030232 urology & nephrology, Urology, Endothelial repair, Delayed Graft Function, Peritubular capillaries, Monocytes, 03 medical and health sciences, 0302 clinical medicine, Postoperative Complications, Risk Factors, medicine, Living Donors, Humans, Prospective Studies, Risk factor, Tyrosine, 030304 developmental biology, Aged, 0303 health sciences, Transplantation, Kidney, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Vascular Endothelial Growth Factor Receptor-1, business.industry, Ischemia-reperfusion, Plasma levels, Anatomy, Middle Aged, VEGF, Kidney Transplantation, Capillaries, medicine.anatomical_structure, Kidney Tubules, Solubility, Reperfusion Injury, embryonic structures, Female, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

International audience; Background. Ischemia-reperfusion induces tubular and endothelial damage in the renal graft and leads to delayed graft function (DGF) and to an early loss of peritubular capillaries (PTC). Few, if any, clinical studies have assessed the impact of proangiogenic and antiangiogenic factors on endothelial repair during renal transplantation (RT)Yrelated ischemia-reperfusion. Methods. We prospectively assessed the kinetics of the antiangiogenic factor soluble Fms-like tyrosine kinase-1 (sFlt-1) in 136 consecutive RT patients and analyzed sFlt-1 impact on DGF and PTC loss.Results. sFlt-1 plasma levels increased by twofold to threefold throughout the first week after RT. This increase was more marked in recipients of grafts from deceased donors compared with living donors. Patients with DGF had higher sFlt-1 levels at all time points during the first 7 days after RT and a higher peak sFlt-1 compared with those without DGF. In multivariate analysis, a peak plasma sFlt-1 of 250 pg/mL or higher was associated with 2.5-fold increase in the risk of DGF (P=0.04). Similarly, patients with a peak plasma sFlt-1 of 250 pg/mL or higher had a more pronounced early decrease in PTC compared with those with a peak sFlt-1 less than 250 pg/mL.Conclusions. sFlt-1 is a new nonimmunologic independent risk factor for DGF and PTC loss. Its inhibition may help improve the outcome of RT.

Published
2013
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