Rémi Lenain1,2, Julie Boucquemont1, Karen Leffondré3, Cécile Couchoud4, Mathilde Lassalle4, Marc Hazzan2, Yohann Foucher1,5. 1. From the INSERM UMR 1246 -SPHERE, Nantes University, Tours University, Nantes, France. 2. Nephrology Department, Lille University Hospital, Lille, France. 3. University of Bordeaux, ISPED, INSERM, Bordeaux Population Health Research Center, UMR1219, Bordeaux, France. 4. REIN Registry, Agence de la Biomedecine, Saint-Denis La Plaine, France. 5. Nantes University Hospital, Nantes, France.
Abstract
BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.
BACKGROUND: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.
Authors: Alexander Kainz; Michael Kammer; Roman Reindl-Schwaighofer; Susanne Strohmaier; Vojtěch Petr; Ondrej Viklicky; Daniel Abramowicz; Marcel Naik; Gert Mayer; Rainer Oberbauer Journal: Clin J Am Soc Nephrol Date: 2021-12-29 Impact factor: 8.237