scholarly journals Racial Disparities in Eligibility for Preemptive Waitlisting for Kidney Transplantation and Modification of eGFR Thresholds to Equalize Waitlist Time

2021 ◽  
Vol 32 (3) ◽  
pp. 677-685 ◽  
Author(s):  
Elaine Ku ◽  
Charles E. McCulloch ◽  
Deborah B. Adey ◽  
Libo Li ◽  
Kirsten L. Johansen

BackgroundPatients may accrue wait time for kidney transplantation when their eGFR is ≤20 ml/min. However, Black patients have faster progression of their kidney disease compared with White patients, which may lead to disparities in accruable time on the kidney transplant waitlist before dialysis initiation.MethodsWe compared differences in accruable wait time and transplant preparation by CKD-EPI estimating equations in Chronic Renal Insufficiency Cohort participants, on the basis of estimates of kidney function by creatinine (eGFRcr), cystatin C (eGFRcys), or both (eGFRcr-cys). We used Weibull accelerated failure time models to determine the association between race (non-Hispanic Black or non-Hispanic White) and time to ESKD from an eGFR of ≤20 ml/min per 1.73 m2. We then estimated how much higher the eGFR threshold for waitlisting would be required to achieve equity in accruable preemptive wait time for the two groups.ResultsBy eGFRcr, 444 CRIC participants were eligible for waitlist registration, but the potential time between eGFR ≤20 ml/min per 1.73 m2 and ESKD was 32% shorter for Blacks versus Whites. By eGFRcys, 435 participants were eligible, and Blacks had 35% shorter potential wait time compared with Whites. By the eGFRcr-cys equation, 461 participants were eligible, and Blacks had a 31% shorter potential wait time than Whites. We estimated that registering Blacks on the waitlist as early as an eGFR of 24–25 ml/min per 1.73 m2 might improve racial equity in accruable wait time before ESKD onset.ConclusionsPolicies allowing for waitlist registration at higher GFR levels for Black patients compared with White patients could theoretically attenuate disparities in accruable wait time and improve racial equity in transplant access.

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Moumita Chatterjee ◽  
Sugata Sen Roy

AbstractIn this article, we model alternately occurring recurrent events and study the effects of covariates on each of the survival times. This is done through the accelerated failure time models, where we use lagged event times to capture the dependence over both the cycles and the two events. However, since the errors of the two regression models are likely to be correlated, we assume a bivariate error distribution. Since most event time distributions do not readily extend to bivariate forms, we take recourse to copula functions to build up the bivariate distributions from the marginals. The model parameters are then estimated using the maximum likelihood method and the properties of the estimators studied. A data on respiratory disease is used to illustrate the technique. A simulation study is also conducted to check for consistency.


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