Titre :

Clinical trial emulation by matching time-dependent propensity scores: the example of estimating impact of kidney transplantation

Auteur(s) :

Lenain, Remi [Auteur]
Service de Néphrologie et Transplantation rénale [CHRU-lille]
MethodS in Patients-centered outcomes and HEalth ResEarch [SPHERE]
Boucquemont, Julie [Auteur]
MethodS in Patients-centered outcomes and HEalth ResEarch [SPHERE]
Leffondre, Karen [Auteur]
Team MORPH3EUS [INSERM U1219 - UB - ISPED]
Couchoud, Cecile [Auteur]
Agence de la biomédecine [Saint-Denis la Plaine]
Lassalle, Mathilde [Auteur]
Agence de la biomédecine [Saint-Denis la Plaine]
Hazzan, Marc [Auteur]
Service de Néphrologie et Transplantation rénale [CHRU-lille]
Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286
Foucher, Yohann [Auteur]
Centre Hospitalier Universitaire de Nantes = Nantes University Hospital [CHU Nantes]
MethodS in Patients-centered outcomes and HEalth ResEarch [SPHERE]

Titre de la revue :

Epidemiology (Cambridge, Mass.)

Nom court de la revue :

Epidemiology

Date de publication :

2020-11-23

ISSN :

1531-5487

Mot(s)-clé(s) :

Dialysis
Time-dependent treatment
Propensity score
Kidney transplantation
Immortal time bias
Causal inference

Discipline(s) HAL :

Sciences du Vivant [q-bio]

Résumé en anglais : [en]

No study to our knowledge has examined the use of observational data to emulate a clinical trial whereby patients at the time of kidney transplant proposal are randomly assigned to an awaiting transplantation or transplantation ...
Lire la suite >No study to our knowledge has examined the use of observational data to emulate a clinical trial whereby patients at the time of kidney transplant proposal are randomly assigned to an awaiting transplantation or transplantation group. The main methodologic issue is definition of the baseline for dialyzed patients assigned to awaiting transplantation, resulting in the inability to use common propensity score-based approaches. We aimed to use time-dependent propensity score to better appraise the benefit of transplantation. We studied 23,231 patients included in the French registry and on a transplant waiting list from 2005 to 2016. The main outcome was time to death. By matching on time-dependent propensity score, we obtained 10,646 pairs of recipients (transplantation group) versus comparable patients remaining on dialysis (awaiting transplantation group). The baseline exposure, that is, pseudo-randomization, was matching time. Median follow-up time was 3.5 years. At 10 years' follow-up, the restricted mean survival time was 8.8 years [95% confidence interval (CI) = 8.7, 8.9] in the transplantation group versus 8.2 years (95% CI = 8.1, 8.3) in the awaiting transplantation group. The corresponding life expectancy gain was 6.8 months (95% CI = 5.5, 8.2), and this corresponded to one prevented death at 10 years for 13 transplantations. Our study has estimated the life expectancy gain due to kidney transplantation. It confirms transplantation as the best treatment for end-stage renal disease. Furthermore, we demonstrated that this simple method should also be considered for estimating marginal effects of time-dependent exposures.Lire moins >

Langue :

Anglais

Audience :

Internationale

Vulgarisation :

Non

Établissement(s) :

CHU Lille
Inserm
Université de Lille

Collections :

• Institut de Recherche Translationnelle sur l'Inflammation (INFINITE) - U1286

Date de dépôt :

2021-07-06T12:50:29Z
2024-01-26T14:50:22Z