Clinical Trial Emulation by Matching Time-dependent Propensity Scores: The Example of Estimating Impact of Kidney Transplantation
| dc.rights.license | open | en_US |
| dc.contributor.author | LENAIN, Remi | |
| dc.contributor.author | BOUCQUEMONT, Julie | |
| hal.structure.identifier | Bordeaux population health [BPH] | |
| dc.contributor.author | LEFFONDRE, Karen
IDREF: 183599128 | |
| dc.contributor.author | COUCHOUD, Cecile | |
| dc.contributor.author | LASSALLE, Mathilde | |
| dc.contributor.author | HAZZAN, Marc | |
| dc.contributor.author | FOUCHER, Yohann | |
| dc.date.accessioned | 2021-06-29T09:45:10Z | |
| dc.date.available | 2021-06-29T09:45:10Z | |
| dc.date.issued | 2021-03-01 | |
| dc.identifier.issn | 1044-3983 | en_US |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/79320 | |
| dc.description.abstractEn | 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. | |
| dc.language.iso | EN | en_US |
| dc.title.en | Clinical Trial Emulation by Matching Time-dependent Propensity Scores: The Example of Estimating Impact of Kidney Transplantation | |
| dc.type | Article de revue | en_US |
| dc.identifier.doi | 10.1097/ede.0000000000001308 | en_US |
| dc.subject.hal | Sciences du Vivant [q-bio]/Santé publique et épidémiologie | en_US |
| dc.identifier.pubmed | 33284166 | en_US |
| bordeaux.journal | Epidemiology | en_US |
| bordeaux.page | 220-229 | en_US |
| bordeaux.volume | 32 | en_US |
| bordeaux.hal.laboratories | Bordeaux Population Health Research Center (BPH) - UMR 1219 | en_US |
| bordeaux.issue | 2 | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | INSERM | en_US |
| bordeaux.team | BIOSTAT_BPH | en_US |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.inpress | non | en_US |
| hal.identifier | hal-03273513 | |
| hal.version | 1 | |
| hal.date.transferred | 2021-06-29T09:45:14Z | |
| hal.export | true | |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Epidemiology&rft.date=2021-03-01&rft.volume=32&rft.issue=2&rft.spage=220-229&rft.epage=220-229&rft.eissn=1044-3983&rft.issn=1044-3983&rft.au=LENAIN,%20Remi&BOUCQUEMONT,%20Julie&LEFFONDRE,%20Karen&COUCHOUD,%20Cecile&LASSALLE,%20Mathilde&rft.genre=article |
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