Socioeconomic status and kidney transplant outcomes in a universal healthcare system: a population-based cohort study
Naylor KL, Knoll GA, Shariff SZ, McArthur E, Garg AX, van Walraven C, Austin PC, McCallum MK, Quinn RR, Tan VS, Kim SJ. Transplantation. 2019; 103(5):1024-35. Epub 2018 Sep 21.
Background — Conflicting evidence exists regarding the relationship between socioeconomic status (SES) and outcomes following kidney transplantation.
Methods — We conducted a population-based cohort study in a publicly funded healthcare system using linked administrative healthcare databases from Ontario, Canada to assess the relationship between SES and total graft failure (ie, return to chronic dialysis, preemptive retransplantation, or death) in individuals who received their first kidney transplant between 2004 and 2014. Secondary outcomes included death-censored graft failure, death with a functioning graft, all-cause mortality and all-cause hospitalization (post hoc outcome).
Results — Four thousand four hundred-fourteen kidney transplant recipients were included (median age, 53 years; 36.5% female) and the median (25th, 75th percentile) follow-up was 4.3 (2.1-7.1) years. In an unadjusted Cox proportional hazards model, each CAD$10,000 increase in neighborhood median income was associated with an 8% decline in the rate of total graft failure (hazard ratio [HR], 0.92; [95% confidence interval [CI], 0.87-0.97). After adjusting for recipient, donor and transplant characteristics, SES was not significantly associated with total or death-censored graft failure. However, each $10 000 increase in neighborhood median income remained associated with a decline in the rate of death with a functioning graft (adjusted (a)HR, 0.91; 95% CI, 0.83-0.98), all-cause mortality (aHR, 0.92; 95% CI, 0.86-0.99), and all-cause hospitalization (aHR, 0.95; 95% CI, 0.92-0.98).
Conclusions — In conclusion, in a universal healthcare system, SES may not adversely influence graft health but SES gradients may negatively impact other kidney transplant outcomes and could be used to identify patients at increased risk of death or hospitalization.