IT'S ABOUT TIME: A TARGET TRIAL EMULATION OF PREEMPTIVE VERSUS NON-PREEMPTIVE KIDNEY TRANSPLANTATION IN A U.S. NATIONAL COHORT

 

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https://storage.unitedwebnetwork.com/files/1288/17f2d005dd509b3dcf47d201539315f2.pdf
IT'S ABOUT TIME: A TARGET TRIAL EMULATION OF PREEMPTIVE VERSUS NON-PREEMPTIVE KIDNEY TRANSPLANTATION IN A U.S. NATIONAL COHORT

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Ian
Tatt-Liew
Ian Tatt-Liew iantatt.liew@uhn.ca Singapore General Hospital Department of Renal Medicine Singapore Singapore *
Sang Joseph Kim joseph.kim@uhn.ca University Health Network Nephrology Toronto Canada -
Christie Rampersad christie.rampersad@uhn.ca University Health Network Nephrology Toronto Canada -
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Preemptive kidney transplantation is widely promoted as the optimal treatment for kidney failure. Proposed benefits include avoiding dialysis-related morbidity and improving survival. However, prior studies are limited by lead-time, selection, and confounding biases. We emulated a target trial to estimate the causal effect of preemptive vs. non-preemptive transplantation on mortality and graft outcomes in a large national cohort.

We designed the study following target trial principles aligned with the TARGET statement. Eligible participants were first kidney-alone transplant recipients in the U.S. Scientific Registry of Transplant Recipients (SRTR) preemptively wait-listed from 2005 to 2015 and transplanted before November 2023. Treatment strategies were (1) preemptive transplantation (before starting chronic dialysis) and (2) non-preemptive transplantation.

 

Time-zero was defined as the date eGFR first reached ≤20 mL/min/1.73 m², representing biologic eligibility for transplant. Follow-up continued until death, graft loss, or administrative censoring. The primary outcome was all-cause mortality; secondary outcomes were all-cause graft failure (ACGF) and delayed graft function (DGF: dialysis ≤7 days or <25% creatinine decline ≤24 h post-transplant).

 

A logistic regression model estimated each recipient’s probability of preemptive transplant using demographic, clinical, socioeconomic, donor, year, and centre variables. Stabilized truncated weights achieved covariate balance (standardized mean differences < 0.10). We estimated the as-treated effect using inverse probability of treatment weighting (IPTW) and left-truncated Cox proportional hazards models for mortality and ACGF, with patients entering the risk set at transplant to address selection bias and align follow-up from a shared time-zero, mitigating lead-time bias. DGF was analyzed with a weighted logistic regression model. Sensitivity analyses adjusted for donor variables and clustering by centre and year; subgroups analyses were performed by donor type, donor age, and recipient age.

Among 32,770 recipients (15,894 [48.5%] preemptive; 265,369 person-years), crude analyses suggested a survival benefit of preemptive transplantation (HR 0.75 [95% CI 0.71, 0.79]) that attenuated after left truncation (HR 0.88 [0.84, 0.92]) or IPTW (0.95 [0.90, 1.00]) and disappeared in the final model (HR 1.01 [0.96, 1.07]). Results were consistent across donor type, age, and sensitivity analyses. Preemptive transplantation modestly lowered ACGF risk (HR 0.95 [0.91, 1.00]) and reduced DGF (OR 0.68 [0.64, 0.71]), particularly among deceased donor kidney transplants (OR 0.56 [0.52, 0.59]) and older recipients, with a signal toward greater benefit for transplants from older donors.

In this target trial emulation, preemptive kidney transplantation conferred no long-term patient or all-cause graft survival advantage after correction for lead-time, selection, and confounding biases. Although preemptive transplantation reduced DGF – especially among deceased-donor kidneys and older recipients – these short-term gains did not yield lasting survival benefit. Our findings provide greater support for allocation policies prioritizing clinical urgency over preemptive status.

Kewords