A5005448546- Renal Transplantation Outcomes and Treatments
- Statistical Methods and Inference
- Organ Donation and Transplantation
- Health Systems, Economic Evaluations, Quality of Life
- Organ Transplantation Techniques and Outcomes
- Statistical Methods and Bayesian Inference
- Bayesian Methods and Mixture Models
- Advanced Causal Inference Techniques
- Traumatic Brain Injury and Neurovascular Disturbances
- Renal and Vascular Pathologies
- Prostate Cancer Diagnosis and Treatment
- Neurological Complications and Syndromes
- Insurance, Mortality, Demography, Risk Management
- Intracerebral and Subarachnoid Hemorrhage Research
- Neurosurgical Procedures and Complications
- Renal Diseases and Glomerulopathies
- Pregnancy and Medication Impact
- Liver Disease and Transplantation
- Liver Disease Diagnosis and Treatment
- Healthcare Policy and Management
- Blood donation and transfusion practices
- Prostate Cancer Treatment and Research
- Constraint Satisfaction and Optimization
- BRCA gene mutations in cancer
- Genetic Associations and Epidemiology
Nantes Université
2013-2024
Sciences, Philosophie, Histoire
2014-2024
Université de Tours
2017-2024
Inserm
2008-2024
Patient-Centered Outcomes Research Institute
2013-2022
Centre Hospitalier Universitaire de Tours
2018-2021
methodS in Patient-centered outcomes and HEalth ResEarch
2016-2019
Medical University of Vienna
2016
University Hospital Frankfurt
2016
Goethe University Frankfurt
2016
Bioprosthetic heart valves (BHVs) are commonly used to replace severely diseased but their susceptibility structural valve degeneration (SVD) limits use in young patients. We hypothesized that antibodies against immunogenic glycans present on BHVs, particularly the xenoantigens galactose-α1,3-galactose (αGal) and N-glycolylneuraminic acid (Neu5Gc), could mediate deterioration through calcification. established a large longitudinal prospective international cohort of patients (n = 1668, 34 ±...
Missing data and especially dropouts frequently arise in longitudinal data. Maximum likelihood estimates are consistent when missing at random (MAR) but, as this assumption is not checkable, pattern mixture models (PMM) have been developed to deal with informative dropout. More recently, latent class (LCM) proposed a way relax PMM assumptions. The aim of paper compare LCM order tackle dropout study cognitive ageing measured by several psychometric tests. Using multivariate model process,...
Data regarding the incidence and outcome of renal involvement in patients with inflammatory myopathies (IM) remain scarce. We assessed causes acute kidney injury (AKI) chronic disease (CKD) 150 dermatomyositis, polymyositis, antisynthetase syndrome followed 3 French referral centers. Renal occurred 35 (23.3%) patients: AKI 16 (10.7%), CKD 31 (20.7%) patients. The main cause was drug or myoglobinuria-induced tubular necrosis. Male sex, cardiovascular risk factors, cardiac involvement, initial...
From a prospective and multicentric French cohort, we proposed an external validation study for the expanded criteria donor (ECD), based on 4833 kidney recipients transplanted first time between 2000 2014. We estimated subject-specific effect from multivariable Cox model. confirmed 1.75-fold (95% confidence interval [CI] 1.53-2.00, P < .0001) increase in graft failure risk if given patient received ECD compared to with standard (standard [SCD]). Complementarily, population-average using...
In many chronic diseases, the patient's health status is followed up by quantitative markers. The evolution often characterized a 2-phase degradation process, that is, normal phase pathological preceding disease diagnosis. We propose joint multistate model with latent state for modeling of repeated measures marker, time-to-illness and time-to-death. Using data from PAQUID cohort on cognitive aging, we jointly studied decline, dementia risk, death risk. estimated mean scores given age at...
Informing kidney transplant recipients of their prognosis and disease progression is primary importance in a patient-centred vision care. By participating decisions from the outset, may be more adherent to complex medical regimens due enhanced understanding.We proposed include repeated measurements serum creatinine (SCr), addition baseline characteristics, order obtain dynamic predictions graft failure risk that could updated continuously during patient follow-up. Adult French Données...
The objective was to compare classical test theory and Rasch-family models derived from item response for the analysis of longitudinal patient-reported outcomes data with possibly informative intermittent missing items. A simulation study performed in order assess performance Rasch model terms bias, control type I error power time effect. controlled whether were complete or some items missing. Both methods unbiased displayed similar data. When missing, remained higher than theory. better...
Medical researchers are often interested to investigate the relationship between explicative variables and times-to-events such as disease progression or death. Such multiple can be studied using multistate models. For chronic diseases, it may relevant consider semi-Markov models because transition intensities two clinical states more likely depend on time already spent in current state than chronological time. When cause of death for a patient is unavailable not totally attributable...
In the context of chronic diseases, patient's health evolution is often evaluated through study longitudinal markers and major clinical events such as relapses or death. Dynamic predictions types may be useful to improve patients management all along their follow-up. consist that are based on information repeatedly collected over time, measurements a biomarker, can updated soon new becomes available. Several techniques derive dynamic have already been suggested, computation becoming...
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In kidney transplantation, dynamic prediction of patient and graft survival (DynPG) may help to promote therapeutic alliance by delivering personalized evidence-based information about long-term for transplant recipients. The objective the current study is externally validate DynPG.Based on 6 baseline variables, DynPG can be updated with any new serum creatinine measure available during follow-up. From an external validation sample 1637 recipients a functioning at 1-year posttransplantation...
In kidney transplantation, dynamic predictions of graft survival may be obtained from joint modelling longitudinal and data for which a common assumption is that random-effects error terms in the sub-model are Gaussian. However, this too restrictive, e.g. presence outliers, more flexible distributions would required. study, we relax Gaussian by defining robust framework with t-distributed to obtain transplant patients. We take Bayesian paradigm inference sample posterior densities. While...
Purpose. Mortality is often assessed during ICU stay and early after, but rarely at later stage. We studied the long-term mortality of three survivor's populations identified associated risk factors. Materials Methods. From an observational cohort, we 233 severe trauma patients without TBI, 580 with TBI 435 ICH, admitted from January 2013 to February 2021 in 3 ICUs alive 7-days post-ICU discharge. stratified Lasso-penalized Cox survival analyses according these populations. Results....
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 significant literature demonstrating their advantages compared usual survival models. Possible explanations uncommon availability classical statistical software or, when they available, by limitations related multivariable modelling take confounding into consideration. In this paper, we propose a strategy based on propensity scores...