Self-advocacy is associated with lower likelihood of living donor kidney transplantation

Am J Surg. 2021 Jul;222(1):36-41. doi: 10.1016/j.amjsurg.2020.12.035. Epub 2020 Dec 24.

Abstract

Background: The Living Donor Navigator (LDN) Program pairs kidney transplant candidates (TC) with a friend or family member for advocacy training to help identify donors and achieve living donor kidney transplantation (LDKT). However, some TCs participate alone as self-advocates.

Methods: In this retrospective cohort study of TCs in the LDN program (04/2017-06/2019), we evaluated the likelihood of LDKT using Cox proportional hazards regression and rate of donor screenings using ordered events conditional models by advocate type.

Results: Self-advocates (25/127) had lower likelihood of LDKT compared to patients with an advocate (adjusted hazard ratio (aHR): 0.22, 95% confidence interval (CI): 0.03-1.66, p = 0.14). After LDN enrollment, rate of donor screenings increased 2.5-fold for self-advocates (aHR: 2.48, 95%CI: 1.26-4.90, p = 0.009) and 3.4-fold for TCs with an advocate (aHR: 3.39, 95%CI: 2.20-5.24, p < 0.0001).

Conclusions: Advocacy training was beneficial for self-advocates, but having an independent advocate may increase the likelihood of LDKT.

Keywords: Advocacy; Disparities in LDKT; Living donor kidney transplantation (LDKT); Navigator program; Transplantation.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Black or African American / statistics & numerical data
  • Donor Selection / standards
  • Donor Selection / statistics & numerical data*
  • Female
  • Health Services Accessibility / standards
  • Health Services Accessibility / statistics & numerical data
  • Healthcare Disparities / statistics & numerical data*
  • Humans
  • Kidney Failure, Chronic / surgery*
  • Kidney Transplantation / standards
  • Kidney Transplantation / statistics & numerical data*
  • Living Donors / statistics & numerical data
  • Male
  • Marital Status / statistics & numerical data
  • Middle Aged
  • Patient Advocacy / statistics & numerical data*
  • Retrospective Studies
  • Sex Factors
  • White People / statistics & numerical data